Land and Forest Accounts (Action 1) Final Report Statistics...Environment Statistics and Accounts – Land and fore st accounts (Action 1) and Material Flow accounts and NAMEA Waste

Environment Statistics and Accounts – Land and fore st accounts (Action 1)

and Material Flow accounts and NAMEA Waste (Action 2)

Agreement number: 71401.2005.001-2005.295

Land and Forest Accounts (Action 1)

Final Report

Compiled by

Pál Bóday – Hungarian Central Statistical Office

Lajos Kaposi – Hungarian Central Statistical Office

Péter Kottek – State Forest Service

Gergely Maucha – Institute of Geodesy, Cartography and Remote Sensing

András Pluzsik – State Forest Service

András Rónai – State Forest Service

Gábor Valkó – Hungarian Central Statistical Office

Budapest, February 2007

Final report – Land and Forest Accounts 2


Contents

Preface ....................................................................................................................................... 5

A. Forest Accounts ................................................................................................................ 7

1. Preface.................................................................................................................................... 8

2. Data Sources........................................................................................................................... 9

2.1 State Forest Service.......................................................................................................... 9

2.1.1 Hungarian Forest Inventory .................................................................................... 10

2.1.2 Yearly data collection on forestations and final cutting.......................................... 12

2.1.3 Yearly data collection on primary forest products .................................................. 12

2.1.4 ICP Forest................................................................................................................ 12

2.2 Hungarian Central Statistical Office .............................................................................. 13

2.2.1 Inputs of producers of agricultural and forestry products .......................................13

2.2.2 Statistical survey on agricultural and forestry services........................................... 13

2.2.3 Statistical survey on land use .................................................................................. 14

2.2.4 Annual Institutional Labour Statistical Survey ....................................................... 14

2.2.5 Labour Force Survey............................................................................................... 14

2.2.6 Input-Output Tables ................................................................................................ 15

2.3 Other sources.................................................................................................................. 17

2.3.1 National Land Fund................................................................................................. 17

2.3.2 Hungarian Energy Office ........................................................................................ 17

3. Definitions............................................................................................................................ 18

4. Methodology ........................................................................................................................ 22

5. Follow up.............................................................................................................................. 26

B. Land Accounts................................................................................................................ 61

1 The short history of land use in Hungary......................................................................... 63

2 Available data sources on land cover............................................................................... 65

2.1 Direct data sources ................................................................................................... 65

2.1.1 CORINE Land Cover ....................................................................................... 65

2.1.2 LUCAS............................................................................................................. 66

2.1.3 Comparison of direct land cover databases...................................................... 66

2.2 Complementary data sources ................................................................................... 67

2.2.1 Land use statistics by HCSO............................................................................ 67

2.2.2 Agricultural Plot Identification System (APIR) database by Agricultural and Rural Development Agency (ARDA) .............................................................. 67

2.2.3 Forest area by State Forest Service (SFS)........................................................ 68

2.2.4 Road and railway network................................................................................ 68


2.2.5 Inland waters by Ministry of Agriculture and Rural Development ................. 68

3 Land cover of Hungary, 2000 .......................................................................................... 69

4 Ecosystems (EA.3. in SEEA 2000) in the year 2000....................................................... 72

5 Land use by industry and households .............................................................................. 74

6 Land cover change ........................................................................................................... 76

7 Methodological notes ....................................................................................................... 80

Annexes.................................................................................................................................... 83


Preface The sub-project Land and forest accounts (Action 1) is part of the project Environmental statistics and accounts. The project was financially funded by Eurostat for the time period of January-December 2006. Experts of the Hungarian Central Statistical Office, the State Forest Service and the Institute of Geodesy, Cartography and Remote Sensing participated in the project. The main objective of the project Land and Forest Accounts (Action 1) was the compilation of the land accounts and forest accounts for Hungary according to the EU requirements. This report summarises the work done in the two fields of environmental accounts. This project has been the first attempt in Hungary to elaborate methodology and to compile data for both land and forest accounts. As a result of this project the set of accounts has been developed for both areas. All data and the necessary methodological remarks are presented in this report. The report consists of two parts:

• Part A. Forest accounts • Part B. Land accounts



A. Forest Accounts


1. Preface

The first estimation of IEEAF was made in close collaboration between the Hungarian State

Forest Service (SFS) and the Hungarian Central Statistical Office (HCSO).

In the first implementation of IEEAF, tables were filled in for the years 2000 and 2005. The

reasons for choosing these years were that the year 2000 was a benchmark year for both SFS

and HCSO and 2005 is the last year when all data are available.

The main task during the project was to explore data sources, define methodologies and

definitions. The results of these activities are a set of table that is presented in this report.

During the implementation of the IEEAF, data and methodology of the pilot EAF have been

used.

State Forest Service has data on physical units, wooded land and on prices, as well. Mainly

these data were used.

During the valuation process, additional data sources have been used. In case of monetary

tables, information of SFS had been supplemented by other statistical data. Data of national

supply and use tables were utilised. Besides, several additional data sources have been used

for the compilation of EAF tables since data on secondary activities, inputs, income etc.

require other data that are not related to forest.


2. Data Sources

Main institutions for data sources were the State Forest Service and the Hungarian Central

Statistical Office.

2.1 State Forest Service

The SFS is a governmental (budgetary) organization working under direct control of the

Ministry of Agriculture and Rural Development. The sphere of activities of SFS covers the

total area of the country. The SFS consists of ten directorates and the headquarters.

The main tasks of SFS cover the following fields:

• Forest inventory on the forested area of the country (The forest inventory is carried out on one tenth of the total forested area annually.);

• Preparation of district forest plans to be approved by the Minister of Agriculture and Rural Development and to constitute the base of the obligatory forest management plans related to the activities of forest managers;

• Base and thematic mapping, including the interpretation of aerial photos, GPS and geodesic measurements;

• Management of the National Forest Stand Database, updated annually and providing information services;

• Supervision of forest management, including the following: o Approval of annual operational plans; o Control of forest management practices (silvicultural and felling activities); o Management of the forestry related financial means and subsidisation system;

• Forest health monitoring according to manual of ICP Forests (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests launched and operating under the Convention on Long-Range Transboundary Air Pollution of UNECE); SFS is the National Focal Centre;

• Collection of data and data processing for statistics on forestry and primary forest industry;

• Development of application software and GIS application; • Cooperation with international organization (among others FAO, UN-ECE, OECD,

EUROSTAT, etc.); • Providing information on the actualities and development of forest resources to

governmental organizations and to the public; • Providing information to – primarily private – forest owners (professional

publications, technical expertise), who often have no professional (forestry related) background;

• As a new assignment due to EU membership, the tasks related to the EU subsidized forestation of agricultural lands;


• The SFS completes the above listed tasks sector-neutrally as far as the legal status of forests is concerned (irrespectively of the ownership forms of forests) in harmony with the Act on Forests.

2.1.1 Hungarian Forest Inventory

District Forest Planning

Forest Inventory is made in the framework of District Forest Planning including site survey

and mapping. Considering that District Forest Plans are made for a 10 years period of time,

one tenth of the total forest area is inventoried each year, which amounts roughly to 180

thousand hectares/year in Hungary. The inventory system principally is a full scope survey.

Samplings (aimed at volume, soil, species, sizes, etc. using very conventional methods) are

always made within the sub-compartment. The number of districts is more than 170 and the

size of districts ranged approx. from 3000 to 24000 ha.

Sampling method

In the stand-wise system each and every stand/sub-compartment is inventoried. In matured

stands the sampling is mostly done with the strip-cruise system within the compartment, but

the sampling method and the reliability is determined by the age and quality of the stands too.

In premature stands the growing stock is calculated with the help of yield tables, therefore

much less dense network of sampling is required in these sub-compartments. All these means

that although the inventory covers the whole country, no systematic sampling is used. The

sampling can rather be considered as a random one from the inventories point of view,

because the areas to be inventoried are determined by the management plans running out of

their validity.

Aerial photos are also used within the process of compilation of Forest Inventory. The aims of

the use of aerial photos are the followings:

• mapping,

• delineation of the border of forested area,

• estimation of forest area,

• change of forest,

• support the daily working plan.

Data collected

There are four groups of parameters:


Compartment data

- Owner

- Municipality

- Compartment ID

- Cadastral ID

- Responsible forest administration

- Actual forest area

- Primary forest function

- Restrictions (if any)

- Goal of wood production

- Game feeding potential

- Size of forest block

- Date of last management action

Site data

- Topography: Elevation, Exposition, Slope declination

- Climate

- Hydrology

- Genetic soil type, soil texture and depth of fertile layer

- Potential/Optimal stand type with its estimated mean increment

- Canopy class

- Shrub cover

Stand data

- Stand component

- Tree-species, Age, Origin

- Proportion by area, Type of mixing

- DBH

- Height

- Stem quality

- Volume

- Basal area

- Current increment

- Method of volume measurement

- Dominant damage type, Intensity

Management data by tree-species


- Rotation age

- Drain/removal

- Intensity (m3/ha to be harvested)

- Type of felling (cleaning, thinning, selective cutting, etc)

- Reforestation

- Method

- Tree-species composition

2.1.2 Yearly data collection on forestations and final cutting

In addition to the inventories made in 10 years rotation, more detailed data are collected

yearly in every stand where there is forestation or final cutting. Making a description about

these stands is included in the official act called “technical acceptance”. The granting of

subsidies is based on the data collected in stands of forestations.

2.1.3 Yearly data collection on primary forest products

Data collections on forest and wood based products are also carried out by SFS on a yearly

basis. Information on processing of wood by species is collected both for forest and wood

based products. Data on stocks, production, domestic trade, export and prices are also

available.

2.1.4 ICP Forest

In addition to the full-stand inventory, some data are collected according to the ICP Forest

sampling protocol, in the transnational 16*16 km grid as well as in the national 4*4 km grid.

Data about health condition, defoliation, discoloration and game damage are collected on a

yearly basis. In every two years, data about increment are collected.


2.2 Hungarian Central Statistical Office

2.2.1 Inputs of producers of agricultural and forestry products

Main variables

Value of inputs used in crop production (e.g. seeds, fertilizers, pesticides), inputs used in

animal husbandry (e.g. feedingstuffs, veterinary products), general expenses (e.g. energy,

maintenance, services, labour costs)

Frequency

Annual (calendar year)

Main characteristics of the survey method

Full-scope observation is applied for agricultural enterprises, sample survey for private

holdings and households. Data are collected by enumerators on private farms and by mail

from enterprises.

Sample

8.000 agricultural enterprises / 65.000 private farms

Response rate

In case of agricultural enterprises 80-85% / private farms 95%

Estimation of missing data

Imputation by the data of the previous survey

2.2.2 Statistical survey on agricultural and forestry services

Main variables

Agricultural enterprises:

Quantity in physical terms (e.g. hectare, working hours, piece, etc.) and Value excluding VAT

(in 1000HUF) of services provided (e.g. ploughing, cultivation of the soil, planting, plant

protection, irrigating /watering/, sowing, harvesting, preparing plants for market, drying,

fixation, storage, fertilizing, manuring, cleaning of hutches, provision of accommodation for

livestock, artificial insemination)

Private farms:

Quantity in working days and Value excluding VAT (in 1000HUF) of services provided (crop

production, animal husbandry, forestry)


Frequency


2.2.3 Statistical survey on land use

Main variables

Data on land use by land use categories, data on land commerce, area under cover, use of

arable land, sawn area by species.

Frequency


Main characteristics of the survey method

Full-scope observation is applied for agricultural enterprises, sample survey for private

holdings and households. Data were collected by enumerators on private farms and by mail

from enterprises.

2.2.4 Annual Institutional Labour Statistical Survey

Annual full scope data collection is carried out on corporations employing more than 20

persons, and all budgetary and social security institutions irrespective of the number of

employees; whereas surveys are carried out on a representative basis on non-profit institutions

and corporations employing 5-19 persons.

2.2.5 Labour Force Survey

The Labour Force Survey (LFS) is a household survey which provides quarterly information

on non-institutional population aged 15–74. The aim of the survey is to observe the

employment and unemployment according to the international statistical recommendation

based on the concepts and definitions recommended by the ILO independently from the

existing national labour regulations or their changes.


2.2.6 Input-Output Tables

The construction of the input-output tables is based upon the commodity flow system. The

application of the commodity flow system means the compilation of many interdependent

commodity balances which account for the sources by commodities at disposal (domestic +

imports) and the uses. In establishing the balance between the sources and uses, the changes

performed on certain groups of products mutually impact each other. The balances cover all

supplies and uses of goods and services appearing in the economy.

The supply table shows the supply of goods and services at basic prices, row-wise by groups

of goods and services, column-wise broken down into the domestic output and imports. The

domestic output is given even in the details of industries classified to branches.

The use table shows the use of goods and services at purchasers’ prices, row-wise by groups

of goods and services, column-wise by aims of use, i.e. as intermediate consumption (detailed

by industries classified to branches), final consumption expenditure of the households, the

government and the non-profit institutions serving households, gross fixed capital formation,

changes in inventories and exports.

Furthermore, the table contains the gross value added broken down by branches.

Balancing methods in the commodity flow system

Identity by industry:

Output by industry = Input by industry, i.e.

Output = Intermediate consumption + Value added

for each industry;

Identity by product:

Total supply by product = Total use by product, i.e.

Output + Imports = Intermediate consumption + Final consumption expenditure

+ Gross fixed capital formation + Changes in inventories + Exports

for each product.

The most important data sources of the supply table:

• the PRODCOM survey (statistics of industrial products),

• agricultural production data from the Economic Accounts for Agriculture (EAA) and the

commodity balances,

• the data of questionnaires of the structural business statistics survey,

• data of the annual survey of the construction,


• data of the following activities: post and telecommunication, tourist accommodations and

services, computer and related services, research and development services, cultural activity,

sewage and refuse disposal services, repair services,

• output of the government sector broken down by functional tasks in details,

• output of the financial corporations sector,

• output of the sector of the non-profit institutions serving households,

• estimation of the output of the household sector,

• data of imports from external trade statistics database by CN code of product and by

importer classified to branches, imports of services from the balance of payments by titles and

broken down by estimation into commodities,

• the use of administrative data sources as control.

The most important data sources of the use table:

• material input statistics on the structure of the intermediate consumption,

• the structure of the expenditure of government institutions from the budgetary reports,

• data collection of branch statistics related to the intermediate consumption structure of the

agricultural activity,

• experts’ estimation for the cost structure of the financial corporations,

• estimation for the cost structure of the own-account construction of dwellings and the own-

account dwelling services by owner-occupiers,

• the energy consumption data from the energy balance,

• household consumption in detailed groups of commodities (household final consumption

expenditure, the agricultural production for own final use, social transfers in kind, the balance

of tourism expenditure),

• collective consumption at detailed level,

• data of the investment statistics and other items of the gross capital formation, the own-

account capital formation data broken down by estimation into commodities,

• data of the inventory statistics broken down into own produced inventory, purchased goods

and materials,

• data of exports from external trade statistic database, export of services from the balance of

payment,

• data of the value added components (compensation of employees, other taxes on production,

other subsidies on production, gross operating surplus).


2.3 Other sources

2.3.1 National Land Fund

The aim of establishing a National Land Fund was to realise the rational management of land

property belonging to the Hungarian State, to assist in the realisation of estate political

directives, and also to support the development of a modern property structure based on

family farms.

The NLF created the reason for the existence of land as credit security with the provision of

security of mortgage credits.

The valuation system „TÉR”, created by the National Land Fund, is a many-sided, flexible

system adjusted to the Hungarian conditions. This evaluation system can determine the value

of land in a reliable way. NLF built further controls into the process with the co-operation of

independent revisers providing real determination of land value.

NLF has a separate simplified method for the valuation of forests. The valuation takes place

in two phases, the valuation of forest land and the valuation of standing timber.

2.3.2 Hungarian Energy Office

Data on consumption of fuel wood is available from Hungarian Energy Office. The Office is a

national, public administration body with independent powers and competence, acting under

the Government’s control and the supervision of the Minister of Economy and Transport.


3. Definitions

The terms and definitions of the UN-ECE/FAO TBFRA-2000 are the bases for the IEEAF

tables; this is why a comparison of the definitions of SFS and TBFRA2000 was made.

Only relevant definitions were compared. Terms TBFRA2000 Definitions Comments

Above-stump woody biomass

The mass of the woody part (stem, bark, branches, twigs) of trees, alive or dead, shrubs and bushes, excluding stumps and roots.

Shrubs and bushes are not included. No estimation of the biomass of the non-tree vegetation.

Annual fellings Average annual standing volume of all trees, living or dead, measured overbark to a minimum diameter of 0 cm (d.b.h.) that are felled during the given reference period, including the volume of trees or parts of trees that are not removed from the forest, other wooded land or other felling site. Includes: silvicultural and pre-commercial thinnings and cleanings left in the forest; and natural losses that are recovered (harvested).

No difference

Annual removals Average annual of those fellings that are removed from the forest, other wooded land or other felling site during the given reference period. Includes: Removals during the given reference period of trees felled during an earlier period and removal of trees killed or damaged by natural causes (natural losses), e.g. fire, windblow, insects and diseases.

Not exactly differentiated from fellings. Usually substituted by fellings. (Only rough estimation is available for the amount of biomass felled but remained in the forest.)

Broadleaved All trees classified botanically as Angiospermae They are sometimes referred to as "non-coniferous" or "hardwoods".

No difference

Coniferous All trees classified botanically as Gymnospermae They are sometimes referred to as "softwoods".

No difference

Defoliation classes

The extent of visually assessed defoliation of trees, as developed by the International Co-operative Programme (ICP Forests) of the Executive Committee for the Convention on Long-range Transboundary Air Pollution in Europe. Damage classes are from 0 to 4, as follows: Class Needle/Leaf loss Degree of defoliation 0 up to and including 10% none 1 > 10 to 25 % slight (warning stage) 2 > 25 to 60 % moderate 3 > 60 to < 100 % severe 4 100% dead */ For methods of assessment and other concepts, see ICP documentation.

No difference


Forest Land with tree crown cover (or equivalent stocking level) of more than 10 percent and area of more than 0.5 ha. The trees should be able to reach a minimum height of 5 m at maturity in situ. May consist either of closed forest formations where trees of various storeys and undergrowth cover a high proportion of the ground; or of open forest formations with a continuous vegetation cover in which tree crown cover exceeds 10 percent. Young natural stands and all plantations established for forestry purposes which have yet to reach a crown density of 10 percent or tree height of 5m are included under forest, as are areas normally forming part of the forest area which are temporarily unstocked as a result of human intervention or natural causes but which are expected to revert to forest. Includes: Forest nurseries and seed orchards that constitute an integral part of the forest; forest roads, cleared tracts, firebreaks and other small open areas within the forest; forest in national parks, nature reserves and other protected areas such as those of special environmental, scientific, historical, cultural or spiritual interest; windbreaks and shelterbelts of trees with an area of more than 0.5 ha and a width of more than 20 m. Rubberwood plantations and cork oak stands are included. Excludes: Land predominantly used for agricultural practices.

Minimum area 0.15 ha tree crown cover more than 30 percent (Not adjustable, but expected to cause negligible effect) In Hungary, all forest resources area statistics, except that of primary forest functions, relate to stocked and temporarily unstocked (i.e. under regeneration) forests. The unstocked areas constituting integral parts of the forest according to the TBFRA 2000 definition are registered separately. These areas were added to the area of forests by proportionally distributing them between the different forest categories: Area XTBFRA = Area X National + Unstocked TBFRA *Area X National / Total Area Nationa*100

Forest available for wood supply

Forest where any legal, economic, or specific environmental restrictions do not have a significant impact on the supply of wood. Includes: areas where, although there are no such restrictions, harvesting is not taking place, for example areas included in long-term utilization plans or intentions.

“Forest available” and “not available for wood supply” categories are not used in the national forestry statistics. National categories are: “Forest with production primary function” and “Forest with non-production primary function”. In order to bridge this gap “Forest not available for wood supply” was computed from inventory raw data as described below: For conservation/protection reasons = area of forest reserves and strictly protected areas For economic reasons = Hunting reserves, seed orchards, steep slopes, forests with indefinite rotation period. “Forest available for wood supply” is of course an inverted value. Based on this grouping area and volume, data were calculated from the raw data. See also Forest, and Other wooded land

Forest not available for wood supply

Forest where legal, economic or specific environmental restrictions prevent any significant supply of wood. Includes: (a) Forest with legal restrictions or restrictions resulting from other political decisions, which totally exclude or severely limit wood supply, inter alia for reasons of environmental or biodiversity conservation, e.g. protection forest, national parks, nature reserves and other protected areas, such as those of special environmental, scientific, historical, cultural or spiritual interest; (b) Forest where physical productivity or wood quality is too low or harvesting and transport costs are too high to warrant wood harvesting, apart from occasional cuttings for autoconsumption.

See FAWS

Gross annual increment

Average annual volume of increment over the reference period of all trees, measured to a minimum diameter breast height (d.b.h.) of 0 centimetres (cm). Includes: The increment on trees which have been felled or die during the reference period.

No difference

Growing stock The living tree component of the standing volume. No difference

Land area Total area, excluding inland water. No difference

Managed forest/other wooded land

Forest and other wooded land which is managed in accordance with a formal or an informal plan applied regularly over a sufficiently long period (five years or more). The management operations include the tasks to be accomplished in individual forest stands (e.g. compartments) during the given period.

No difference

Mixed forest/other wooded land

Forest/other wooded land on which neither coniferous, nor broadleaved, nor palms, bamboos, etc account for more than 75 percent of the tree crown area.

No difference


Natural colonization of non-forest land

The colonization of non-forest land with forest trees through stages of natural succession without human intervention. Natural colonization may frequently occur after other (nonforest) land has been abandoned or withdrawn from its former utilization, e.g. farming or pasturing.

No difference in definition (but hardly detectable).

Natural conversion other wooded land

The conversion of other wooded land to forest as a result of natural processes. The process may occur without intentional intervention by man, but may be aided by human interventions such as the withdrawal of animal grazing from the land allowing tree regeneration to succeed, soil scarification, or actions to protect the area from fire, overcutting, etc.

Other wooded land is not a typical category in the Hungarian vegetation. Not definied. See OWL.

Natural losses Average annual losses to the growing stock during the given reference period, measured to a minimum diameter of 0 cm (d.b.h.), due to mortality from causes other than cutting by man, e.g. natural mortality, diseases, insect attacks, fire, windthrow or other physical damage.

No difference

Natural regeneration

Re-establishment of a forest stand by natural means, i.e. by natural seeding or vegetative regeneration. It may be assisted by human intervention, e.g. by scarification or fencing to protect against wildlife damage or domestic animal grazing.

No difference

Natural regeneration enhanced by planting

Natural regeneration which has been combined with artificial planting or seeding, either to ensure satisfactory restocking with the naturally regenerated species or to increase species diversity.

No difference

Net annual increment

Average annual volume over the given reference period of gross increment less that of natural losses on all trees to a minimum diameter of 0 cm (d.b.h.).

No difference

Other land Land not classified as forest or other wooded land as they are defined in this enquiry.

No difference

Other wooded land

Land either with a tree crown cover (or equivalent stocking level) of 5-10 percent of trees able to reach a height of at maturity in situ; or a crown cover (or equivalent stocking level) of more than 10 percent of trees not able to reach height of 5 m at maturity in situ (e.g. dwarf or stunted trees) and shrub or bush cover. Excludes: Areas having the tree, shrub or bush cover specified above but of less than 0.5 ha and width of 20 which are classed under "other land" ; Land predominantly used for agricultural practices.

Area is insignificant. There is an area about 4,000 ha (i.e. 0.22 per cent) recorded as forest in the national statistics, which would fall into the category of other wooded land regarding the 0.5 ha area limit of the TBFRA definitions. Given the fact that there is no reliable information on land cover available from those areas, which fall outside the sphere of competence of the forestry administration, adjustment was not carried out here, and these areas are displayed as forest in this enquiry. The above value is considered in the likely range values where possible.

Plantation (s) Forest stands established by planting or/and seeding in process of afforestation or reforestation. They are either: - of introduced species (all planted stands), or - intensively managed stands of indigenous species which meet all the following criteria: one or two species plantation, even age class, regular spacing. Excludes: Stands which were established as plantations which have been without intensive management for significant period of time. These should be considered seminatural.

Includes the total area of genetically improved poplar stands, plus area of stands where regular spacing was applied to enchance wood production

Planting and seeding

The act of establishing a forest stand (e.g. plantation) or reestablishing a forest stand by artificial means, either planting of seedlings or by scattering seed. The material used may be of indigenous or introduced origin. Planting and seeding may take place on forest, other wooded land other land.

No difference

Predominantly broadleaved

Forest/other wooded land on which more than 75 percent the tree crown cover consists of broadleaved species.

No difference

Predominantly coniferous

Forest/other wooded land on which more than 75 percent the tree crown cover consists of coniferous species.

No difference


Reference period The year or years during which the national forest inventory or other method of collection of the data reported in forest resources assessment was carried out.

SFS uses 10 year rotation of tracts. Each year 1/10 of tracts are measured.

Regeneration Re-establishment of a forest stand by natural or artificial means following the removal of the previous stand by felling or as a result of natural causes, e.g. fire or storm.

No difference

Semi-natural forest/other wooded land

Forest/other wooded land which is neither "forest/other wooded land undisturbed by man" nor "plantation" defined separately.

No difference

Shrubs and bushes

Woody perennial plants, generally of more than 0.5 m less than 5 m height, and often without a definite stem crown.

No difference

Standing volume Volume of standing trees, living or dead, above-stump measured overbark to top (0 cm). Includes all trees with diameter over 0 cm (d.b.h.) Includes: Tops of stems, large branches; dead trees lying the ground which can still be used for fibre or fuel. Excludes: Small branches, twigs and foliage.

In case of conifers, includes small branches and twigs, even foliage.

Stumps and roots Parts of the whole tree volume, which exclude the volume the above-stump woody biomass. The height of the stump taken to be that at which the tree would be cut under normal felling practices in that country or region. Excludes: Small roots.

No difference

Total area Total area of country, including area of inland water bodies. Excludes: offshore territorial waters.

No difference

Tree A woody perennial with a single main stem or, in the case coppice, with several stems, having a more or less definite crown. Includes: Bamboos, palms and other woody plants meeting the above criterion.

No difference

Trees outside the forest

Trees on land other than forest or other wooded land. Includes: Trees on land that meets the definitions of forest and of other wooded land except that the area is less than 0.5 ha and the width is less than 20 m; scattered trees in permanent meadows and pastures; permanent tree crops such as fruit tree orchards and coconut palm plantations; trees in parks and gardens, around buildings, in hedgerows and in lines along streets, roads, railways, rivers, streams and canals; trees in shelterbelts and windbreaks of less than 20 m in width and 0.5 ha in area.

No difference

Woody biomass The mass of the woody parts (wood, bark, branches, twigs, stumps and roots) of trees, alive and dead, shrubs and bushes, measured to a minimum diameter of 0 mm (d.b.h.). Includes: Above-stump woody biomass, and stumps and roots. Excludes: Foliage.

Shrubs and bushes are not included. No estimation of the biomass of the non-tree vegetation.


4. Methodology

Table 1a

Data on opening/closing area and afforestation/deforestation are available from the database

of SFS.

Data on changes in use/status

Transform from FAWS to FNAWS or vice versa. The area of forest was studied by the

breakdown of municipalities. The area of forest and FAWS were examined.

1 if FAWS area has not changed, no changes in use/status has to be recorded

2 if the change of FAWS area and forest area is the same, no changes in use/status has to be

recorded

3 if forest are is stable and FAWS area has changed, changes in use/status has to be recorded

4 if both areas have changed, no exact information is available to determine weather

transform from FAWS to FNAWS (or vice versa) or other changes have to be recorded.

Since data on other changes calculated as residual of other items, data for further breakdown

were not available.

Table 1b

Data on forest land price are calculated by the method of National Land Fund.

National Land Fund has a simplified valuation method on forests. Value of forests is

measured by valuing the land and standing timber separately.

Average forestland price by species was defined by NLF. Forestland price was calculated

using the average price of land by species weighted by the area of relevant species.

Since the valuation method does not take into consideration the inflation, land price was

deflated by agricultural land price index.

Data of Table 1a have been multiplied by this deflated average land price.


Table 2a

Data on changes in volume were available from the inventory database of SFS. Data on

changes on use/status were available only on areas not on volumes since the calculation

process of transformation from FAWS to FNAWS (see Table 1a) was based on the area of

forests and no other information was available on these forests.

Table 2b

Data of Table 2a were multiplied by the average stumpage price.

Calculation of stumpage price was done according to the method NLF for valuation of

standing timber. Average standing timber price was available from NLF by species and age

groups and stock data in the same breakdown was available from SFS.

Table 2c

Data for defoliation were available according to the methodology of ICP forest. National

sample gives better results than international one since survey grid is 4x4 km instead of 16x16

km, data on forest health conditions are surveyed on a yearly basis.

Table 3a

Data of table 3a were derived mainly from other tables:

Natural growth = gross increment (see Table 2b)

Wood in the rough = total removals (see Table 2b)

Forestry and logging related services (see Table 3c)

Output for own final use is estimated for the use of fuel wood

Meat, fur, skin from hunting and trapping output of game (according to EAA)

Other products = production of charcoal

Table 3c

Output data derived from table 5b.

Non-forestry (inseparable) secondary activities is calculated for the process of sawn logs

For the calculation of data on intermediate consumption data collections of HCSO on

expenditures, services and land-use were applied.


Data on fixed capital consumption calculated by perpetual inventory method (PIM). PIM is a

Data on other taxes and subsidies derived from financial accounts of national accounts.

Data on GFCF derived from investment statistics data.

Labour input and compensation of employees data has been calculated on the basis of AIL

and LFS data (see data sources)

Table 4a

Use of products: production + initial stock – final stock – export + import

Content of the table is in connection with the traditional forestry statistics data on production

and trade derived from joint forest sector questionnaires. In case of stocks and other products,

data collection on production, stock and sales of forestry and wood products of SFS were used

as data source.

For the estimation of breakdown of the use of products by different industries and purposes

(final consumption, capital formation), their values (see Table 5b) were used.

Capital formation of standing timber: value of changes in inventories (Closing stock-opening

stock) was used (Table 2b).

Final consumption of Fuel wood: Data on consumed fuel wood were available from “Energy

Centre” in tons. Conversion factor for fuel wood was also available from definitions of Joint

Forest Sector Questionnaire 2006.

For waste products no data are available.

Table 4b

Supply of products: production + initial stock – final stock

The same data sources were used as for Table 4a.


Table 5a, Table 5b

For the valuation of natural data of Table 4a – 4b, prices were calculated from international

trade and domestic trade information. For each categories and transactions, specific prices

were calculated.

For estimation of non forest or related products and industries, data of supply and use tables

(SUT) were used. Since SUT is not available for 2005, for both years (i.e. 2000 and 2005) the

2000 SUT was used.

Also SUT data were used for the estimation for items such as consumption and capital

formation; taxes less subsidies and trade/transport margins; and income data.

Table F1 and F2

For determining carbon balance, data on volume of forest were used by species. Their density

values were defined and the ratio of carbon fraction of dry wood was estimated.

Only data on FAWS were available.


5. Follow up

We plan to develop the methodology of estimation for certain items. In our further work, a

detailed methodology of the revised table sets including crosslinks between the tables would

be of much use.


Annex – Tables of IEEAF for 2000 and 2005


61 Final report – Land and Forest Accounts

B. Land Accounts



1 The short history of land use in Hungary

The population of Hungary, similarly to the population of Europe, significantly increased in

the second half of the 19th century. Food was produced on an expanded agricultural area

gained by river regulation. The production was driven by the rising demand. At the beginning

of the 20th century, the share of agricultural land area was one of the highest in Europe. The

cereal surplus was exported. The whole agricultural land area was kept in production;

peasants used even the ruderal grassland for grazing cattle. After the Second World War,

there was a huge demand for Hungarian food surplus in the Soviet markets; food was a

strategic product that time.

Figure 1 Land area by land-use categories

0%

20%

40%

60%

80%

100%

1950 1960 1970 1980 1990 2000

Forest

Reed and fish-pond

Uncultivated land areaa)

Grassland

Garden, orchard and vineyard

Arable land

a)The uncultivated land area is a mixed category of land cover. It contains waterbodies, built-in areas, the natural land area and the majority of uncultivated agricultural land area.

In the last decades, the size of agricultural land area has decreased continuously, while the

forest area and the uncultivated land area have increased. In the latter case, the increase in the

year 2000 can be explained by the fact that the non- utilised land area was reclassified

according to its actual land use (former agricultural land area, mainly arable land) by the

Agricultural Census of 2000.

Between 1960 and 1980, the share of arable land area decreased from 57% to 51%, while the

crop production on arable land became more and more intensive. On the contrary, an

increasing share of grassland area became unused from the 1970’s.


Large-scale cattle farming became widespread in that period. It was based on fodder crops produced on arable land, mostly maize silage and alfalfa hay. The cattle stock of small farms decreased drastically and became insignificant by these days. Posterior drop of cattle farming accelerated the recession of the use of grassland. The cattle stock decreased to its four-fifths in the 1980’, and half of it disappeared in the 1990’s. During the last two decades, there was altogether a 60% decrease. The average agricultural grassland area per one notional livestock unit (grazing animals) was 0.9 hectares in 1950 while 4.0 hectares in 2000. Less and less agricultural grassland is used for producing fodder; these areas are becoming important for soil and nature conservation purposes instead.

After the accession to the EU, Hungary is perpetually having difficulties with the surplus of

cereals because of the collapse of the former Soviet market. As a consequence of the

agricultural subsidies, the ratio of the arable land remained the same; but according to the

future utilization plans, a significant part of the arable land could be used to produce energy

(energy crops, biofuel production from rapeseed and sunflower seed, bioethanol production

from cereals).

“Based on the agricultural potential of the country, approximately 7-8 million tons of biomass may be used for energy purposes. The current level of biomass production in Hungary is very low compared to the production potential. There is a steady demand for renewable energy resources providing the possibility of export expansion. At present, Hungary cannot meet the Community requirements on the usage of renewable energy. The national processing capacity of the renewable energy sources is minimal. This is accompanied by the low level of energy efficiency. Presently in Hungary, the ratio of biofuels within the total amount of fuels used is 0.4%, which is one tenth of the relevant ratio in the EU. Only 8-10% of all biomass produced is used for energy purposes. The production of bio-energy could provide a solution for the overproduction on two sides. On the production side, the plantation of fast growing species decreases the land used for cereal production, while on the market side, the use of cereals for bio-ethanol production decreases the surplus that was produced.” (New Hungary Rural Development Strategic Plan, 2007-2013)


2 Available data sources on land cover

2.1 Direct data sources

Land cover data are available from two different sources: satellite images and air photos

analysed with visual and geographical information (GIS) methods on one side and local

photographs identified with GPS on the other. The first data source is related to EU’s

CORINE (Coordination of Information on the Environment) Land Cover (CLC) project,

while the LUCAS (Land Use/Cover Area Frame Statistical Survey) project run by

EUROSTAT represents the second one.

Besides the databases that are representative on EU-level, detailed databases suitable for national purposes were created in many countries including Hungary.

2.1.1 CORINE Land Cover

The scale 1:100.000 EU-level CORINE Land Cover (minimum mapping unit 25 ha, minimum

width of linear features 100 m) map (CLC100) has been updated and enhanced with satellite

images taken in 1998-99 in order to deriveCLC50. The CLC50 database (scale 1:50.000,

minimum mapping unit 4 ha, 1 ha for lakes, minimum width of linear features 50 m)

significantly improved the reliability of the database and its suitability for national purposes.

In Hungary, the CLC projects were executed by the Institute of Geodesy, Cartography and

Remote Sensing (FÖMI).

Minimum mapping unit means that land cover patches smaller than 4 ha (1 ha for lakes) are not identified during the mapping. Linear infrastructure and landmarks narrower than 50 m are not delineated either.

Scale 1:100.000 CLC2000, which was created using also the results of the CLC50 is more

reliable than the first CLC100 created in the early 1990s. However, the most reliable results

usable for the land accounts still come from the CLC50, because these data are more detailed

than those of the other surveys. (The land cover categories of CLC50 can be found in Annex

1.)


2.1.2 LUCAS

The original 18x18 km grid of the EU frame was ameliorated to a 9x9 km grid in the national

level LUCAS survey in 2002. This way, the number of segments in the grid [so called

Primary Sampling Units (PSU)] quadrupled. (See Annex 2 for the land cover categories of

LUCAS.) The original EU sampling consists of 2 stages: Primary Sampling Units (PSUs) that are cells of an 18x18 km regular grid and Secondary Sampling Units (SSUs) that are 10 points regularly distributed (in a rectangle of 1500x600 m) around the centre of each PSU. The SSUs reflect the 0,9km2 surface of the segments reliably while they give only rough information on the cells of 81km2. We can obtain usable information only on the 7 main land cover categories and on some subcategories like cereals.

2.1.3 Comparison of direct land cover databases

The reliability of CLC and LUCAS data is not satisfactory in many aspects due to their

limited details. The representation of the surveys is summarised in the following chart:

Table 1 Comparison of land cover databases

CORINE Land Cover (CLC)

CLC50 CLC2000

LUCAS2002

Method of database production

Mapping, based on satellite images

Area frame sampling in 9x9 km grid (PSU), 10 sampling

points in each elements (SSU)

Time consistency 1998-1999 2000-2001 2002

Observation unit 4 ha (200x200m), water

1 ha (100x100m) 25 ha (500x500m) 7 m2

Linear accuracy 50 m 100 m Number of polygons > 174 000 > 24 000 Number of classes 79 27 ( of 44) 50 Number of level 1. 5 5 7 Geometric accuracy To a maxima 20 m To a maxima 100 m

Thematic accuracy >90% >85% Cv% of level 1. generally

2-6%

The use of other (administrative and statistical) data sources was necessary to improve the

reliability of the data on land cover.


2.2 Complementary data sources

2.2.1 Land use statistics by HCSO

Besides the direct databases of land cover, the land use statistics of the Hungarian Central

Statistical Office (HCSO) are the basic sources of data on productive land area (meaning land

used for agricultural and forestry production). Land use statistics describe the factual

utilisation of productive land area. The categories sometimes differ from the land cover

categories. As an example, abandoned arable land is classified by land use statistics in the

category “uncultivated land area”, while in CLC it is considered to be arable land for 3 years,

then pasture for another 4 years and afterwards natural grassland or transitional

woodland/shrub.

„Of all arable land in the country, died-out plantations, waste land and fallow land accounted for 143,000 ha in 2005.” (New Hungary Rural Development Programme)” HCSO collects data from land users. These data are refined by expert estimations in co-operation with county offices of the Ministry of Agriculture and Rural Development and other agricultural experts. Detailed specification by cultivation provides information for comprehensive analyses of land cover and for direct control of land cover databases.

2.2.2 Agricultural Plot Identification System (APIR) database by Agricultural and Rural Development Agency (ARDA)

Land use statistics of HCSO can be compared to the APIR database of ARDA (detailed data

of those who apply for area-based subsidy) for further refinement. It is a basic financial

interest of agricultural land users to be registered in APIR in order to be entitled for Single

Area Payment Scheme subsidies. Farmers cultivating area smaller then 1.0 hectare are not

entitled to apply for subsidies except if they cultivate at least 0.3 hectare of orchard or

vineyard. According to the data of General Agricultural Census of the year 2000, 7% of

productive area belongs to farms under these thresholds. There are other, more important

reasons for not requiring subsidies e.g. lack of cultivation. For these reasons, area registered

in APIR can be estimated to be 80-85% of the utilised agricultural area.

In CLC and LUCAS surveys – differing from APIR – small forest areas surrounded by agricultural areas, roads, uncultivated, usually wooded and bushy low-lying areas or areas lying on steep slopes attached to the agricultural areas are not delineated. For this reason, these surveys report larger agricultural area than the factual territory. On the


contrary, the area in the APIR database is smaller than the real territory because of the reasons mentioned above.

2.2.3 Forest area by State Forest Service (SFS)

State Forest Service registers areas larger than 1500 m2 with wood and shrub cover that are

involved in forest management planning. These areas include the so called “territories with

wood cover” which exclude clear-cuts, shrub vegetation and areas to be recovered by

afforestation.

2.2.4 Road and railway network

The majority of road and railway network is a linear establishment that is narrower than 50

meter therefore it is not registered in CLC 50. Data on state and municipality road network

(length, average width, area) are registered by Hungarian Roads Management Company. Data

on the railway network are available in the HCSO.

2.2.5 Inland waters by Ministry of Agriculture and Rural Development

The area of inland waters is bigger in the statistics of the Ministry of Agriculture and Rural

Development than in CLC50. CLC50 does not identify the water areas that are narrower than

50 meter.


3 Land cover of Hungary, 2000

The results of various land cover databases (CLC50, CLC2000 and LUCAS 2002)

significantly differ from each other. The main reason for this is that their production

methodology (scale, minimum mapping unit, classification etc.) was different. The effect of

time difference is negligible compared to that of the methodology. Eurostat proposes the CLC

classification as a possible solution for the demonstration of land cover. The CLC50 is the

most detailed and the most reliable CLC survey.

The ecosystem-approach (it takes into consideration the degree of human intervention) CLC

categories are more suitable for the purpose of presenting land cover than the OECD grouping

(land use approach). The differences between the CLC and the OECD classifications are

presented in Table 2 with the data of CLC50.

Table 2

Land cover of Hungary by CLC50

Original data Data regrouped by OECDa) Name

1000 ha Distribution,

% 1000 ha

Distribution, %

Artificial surfaces 554.1 6.0 488.7 5.3 Agricultural areas 5846.7 62.9 6458.7 69.4 Forests and semi-natural areas 2577.6 27.7 2031.0 21.8 Wetlands 127.5 1.4 127.5 1.4 Inland waters 195.2 2.1 195.2 2.1

Total 9301.1 100.0 9301.1 100.0 a) Agricultural units within settlements (from artificial surface class) and natural grassland (from semi-natural area class) regrouped to agricultural areas.

In CLC 50, there are 395.6 thousand hectares of heterogeneous agricultural area (together with 67.1 thousand hectares of garden that was reclassified from the built-up areas) within the CLC category 24. In category 24, the area of natural vegetation is probably some 50-100 thousand hectares, while the area of real agricultural area (mostly arable land or grassland) must be 230-280 thousand hectares. CLC database does not allow the differentiation between these two categories.

Table 3 contains the distribution of land cover by different data sources and those data that are

the most reliable for the compilation of land accounts. (The basic data for the calculation of

the distribution in Table 3 is available in Annex 3.)


Land cover, 2000 Table 3

CLC50 a)

CLC2000 LU-CAS 2002

HCSO, 2000

Other data

sources Approved, 2000 CLC

co-de

Name

Distribution, % Area,

1000 ha

11 Urban fabric 3.9 b) 4.5 3.1 291.3

12 Industrial, commercial abd transport units 1.4 0.7 1.8 c 1.8 163.4

13 Mine, dump and construction sites 0.2 0.1 0.2 20.7

14 Artificial non-agricultural vegetated areas 0.4 0.4 0.4 40.2

1. Artificial surfaces 6.0 5.7 5.6 14.4 d) 6.9 e) 5.5 515.7

21 Arable land 52.7 53.3 47.6 48.4 43.8 f) 48.4 4

499.8 22 Permanent crops 2.3 2.2 2.8 2.2 1.6 f) 2.2 201.3 23 Pastures 4.3 7.1 14.7 11.3 7.0 f) 7.7 713.9 g)

24 Heterogeneous agricultural areas 3.5 5.2 .. 1.1 4.3 395.6 b)

2. Agricultural areas 62.9 67.8 65.1 62.9 62.5 5

810.6 312 Coniferous forest 1.7 1.1 1.7 2.2 h) 2.2 203.4

311 Broad-leaved forest 16.7 15.9 17.6 15.6 1

452.9

313 Mixed forest 0.9 1.7 1.2 0.9 80.3

31 Forests 19.3 18.7 20.5 19.0 18.7 h) 18.7 1

736.5 321 Natural grassland 5.9 2.4 6.4 593.5 324 Transitional woodland/shrub 2.4 2.4 3.2 294.1

32 Shrub and/or herbaceous vegetation association 8.3 4.8 4.7 9.5 887.6

33 Open spaces with little or no vegetation 0.1 0.0 0.2 0.1 9.7

3 Forests and semi-natural areas 27.7 23.5 25.3 19.0 28.3

2 633.8

411 Inland marshes 1.2 1.0 1.2 116.2 412 Peat bogs 0.1 0.1 0.1 11.3

4. Wetlands 1.4 1.1 reed: 0.6 1.4 127.5 511 Water courses 0.7 0.5 0.8 76.7

Fish-pond 0.3 0.0 0.3 0.3 32.0

Other water-bodies 1.1 0.0 1.1 104.8

512 Water bodies 1.4 1.4 1.5 136.8

5. Inland waters 2.1 1.9 3.9 3.0 3.7 i) 2.3 213.5

TOTAL 100.0 100.0 100.0 100.0 100.0 100.0 9

301.1

a) CLC50 corrected with a par of category 24 FÖMI. b) From CLC50 112 to 24: garden of private farmers: 67100 ha (HCSO). c) Hungarian Roads Management Company+calc. d) Uncultivated land area, without water bodies. e) Inner city from census, 1990. f) Data by ARDA. g) Data by ARDA+10%. h) SFS: forests covered by trees (over 1500 m2), 1736,5 thousand ha. i)MARD. Inland waters with wetlands.

accepted data accepted data with correction


The land cover statistics are not suitable for direct use by the land use statistics of HCSO

however they can be a basis for correction of land use statistics. It can be assumed that the

area of grassland utilised by agriculture registered in the land use statistics is overestimated;

contrary to the uncultivated area, which is assumed to be underestimated. The majority of

other woodland and semi-natural areas can be classified to the uncultivated area.


4 Ecosystems (EA.3. in SEEA 2000) in the year 2000

According to the available data on land cover presented in Table 3, the land area can also be

described by ecosystems. The ecosystems are classified according to role of the man-driven

development and maintenance.

Figure 2

Land cover by ecosystems, 2000

EA312. Agricultural

58 106 km2 (62.5%)

EA313. Forest and other semi-natural

20 403 km2 (21.9%)

EA314. Semi-natural grassland

5 935 km2 (6.4%)

EA32.a Wetland: 1 275 km2 (1.4%)

EA311. Urban

5 157 km2 (5.5%)

EA32.b Inland water

2 135 km2 (2.3%)

97.7 percent of the country’s area is mainland while 2.3 percent is covered with water (lake,

river, artificial reservoir). Contrary to this distribution, 96.3 percent of the total area is

covered with terrestrial ecosystem, while aquatic ecosystem can be found on 3.7 percent of

the area. The latter also contains the wetlands (inland marshes and peat bogs) while it is

considered to be mainland. The enhancement of the low proportion of aquatic ecosystems can

be an important goal: they can be used as a buffer in case of flood, they can serve as a water

reservoir for irrigation purposes in case of drought and they can also be a tool of increasing

biodiversity.

“Within the framework of the agri-environmental programmes, which serve the sustainable use of agricultural land, special emphasis will be given to special farming methods that are connected to water management programmes, or to those that serve the protection of water-basin or linked to the climate change.” (New Hungarian Rural Development Strategic Plan, 2007-2013)

The share of agricultural ecosystems (EA 312) is so high that it is matched only by a few

European countries. The favourable natural conditions allow that a great proportion of land


area is used for agricultural production. In the last 15-20 years, Hungary had to face the

continuous problem of cereal surplus. In order to avoid the surplus, the agricultural production

will probably be given up on the less favourable areas and new utilisation methods (e.g.

production of energy crops) will spread.

“Afforestation of agricultural areas less capable of competitive production, preservation of the environmental state of forests and the support of traditional forest management play a significant role in agriculture.” (New Hungarian Rural Development Strategic Plan, 2007-2013)

28.3 percent of the country’s area is covered by forests and other semi-natural ecosystems and

semi-natural grasslands. Out of these, the area of forest ecosystems is 18.7 percent while that

of transitional woodland and shrubs (clear-cuts, growing forest, other woodland and shrub,

areas previously used for agricultural production) is 3.2 percent.

5.5 percent of the total area is urban ecosystem: mostly houses and buildings, road and

railway systems and other infrastructure.


5 Land use by industry and households

Detailed information on land area use is not available therefore estimations are necessary.

96.6 percent of the total area can be classified by its users (98.3 percent of the terrestrial and

60.1 percent of the aquatic ecosystems). These data do not necessarily refer to the real

utilisation. After the change of land use, it takes years that the land cover actually changes due

to the vegetation succession processes (e.g. forestation or recovery of semi-natural ecosystems

on the uncultivated area).

The utilisation of built-up areas is not complete, which is mainly due to the abandoned houses

and agricultural buildings. Houses, service buildings and courtyards, small green areas and

kitchen gardens belonging to the houses take 56 percent of built-up areas. 27 percent of built-

up area is used by transportation and other public services (commerce, tourism, health care,

education, etc.). The remaining 18 percent belongs to the manufacturing sector.

The private farms and enterprises classified in the agricultural, forestry and fishery sector use

82 percent of the agricultural area, forest and other semi-natural area. Besides, these areas are

used by almost all economic sectors. The most important uses are the protected natural areas

(national parks, nature conservation areas, and landscape protection regions), which occupy

the majority of natural grasslands. (The use for nature conservation is classified to public

administration belonging to services.)


Table 4

Land use by industries and households, 2000

EA.2 Land and surface water

Industries (ISIC) and households

EA 21 Land

under-lying building

and structures

EA 22 Agricul-

tural land

EA 23 Wooded

land

EA 251 Semi-natural

grassland

EA 24 Major water-bodies

Total

1000 hectares Agriculture, hunting, forestry, fishing (A+B) 58.1 5 393.6 1 447.1 100.0 110.0 7 108.8 Mining quarrying ( C ) 9.5 5.0 5.0 5.0 24.5 Manufacturing, electricity (D+E) 21.9 5.0 5.0 20.0 51.9 Construction (F) 3.5 5.0 0.0 8.5 Transport, storage, communication (I) 54.5 10.0 20.0 10.0 94.5 Other services (G+H+J+K+L+M+N+O+P) 82.6 341.9 461.3 420.5 60.0 1 366.3 Private households 277.5 30.0 50.0 357.5

Sub-total 507.6 5 790.5 1 988.4 520.5 205.0 9 012.0 No direct use 8.1 20.1 51.9 73.0 136.0 289.1

Total 515.7 5 810.6 2 040.3 593.5 341.0 9 301.1 Distribution, % Agriculture, hunting, forestry, fishing (A+B) 11.3 92.8 70.9 16.8 32.3 76.4 Mining quarrying ( C ) 1.8 0.1 0.2 0.0 1.5 0.3 Manufacturing, electricity (D+E) 4.2 0.1 0.2 0.0 5.9 0.6 Construction (F) 0.7 0.1 0.0 0.0 0.0 0.1 Transport, storage, communication (I) 10.6 0.2 1.0 0.0 2.9 1.0 Other services (G+H+J+K+L+M+N+O+P) 16.0 5.9 22.6 70.9 17.6 14.7 Private households 53.8 0.5 2.5 0.0 0.0 3.8

Sub-total 98.4 99.7 97.5 87.7 60.1 96.9 No direct use 1.6 0.3 2.5 12.3 39.9 3.1

Total 100.0 100.0 100.0 100.0 100.0 100.0

40 percent of the aquatic ecosystems cannot be linked to users. 32 percent of the area is used

for the purposes of agriculture, forestry and fishery (fishing, reed production and hunting)

while 18 percent is used for sports, recreation, health care and nature conservation.


6 Land cover change

The state of land cover in the year 2000 can be described comparing different data sources,

however only the CLC2000 project gives information on the changes over time. FÖMI

detected and mapped the changes in land cover between 1990 and 2000 in the frame of this

project. (The basic data of the CLC changes can be found in Annex 4.) Changes were

identified in 416.6 thousand hectares, which corresponds to 4.5 percent of the total area of the

country. For 85 percent of this area the changes meant changes within a main category so the

main category did not change for these cases.

34.5 percent of the total changes identified in CLC was detected within the agricultural area

(EA312) and 50.8 percent within the forest and other semi-natural area. As an effect of the

changes, the area of arable land and heterogeneous agricultural areas increased by 23

thousand hectares within the agricultural area because of conversion of pastures and the

cutting of plantations. The reason for the increase of forest area by 55 thousand hectares is the

growing up of new forests (conversion from transitional woodland and shrub).

Table 5 Most important changes within the main categories, 1990-2000

Entry Exit Net change

Name 1000 ha

distri-bution,

%

1000 ha

distri-bution,

%

1000 ha

in % of 1990

Total change 416.6 100.0 416.6 100.0 - - Of this: Arable land 77.7 18.7 58.5 14.0 19.2 0.4 Permanent crops 9.3 2.2 18.2 4.4 -8.9 -4.2 Agricultural grassland 49.9 12.0 64.0 15.4 -14.1 -1.9 Heterogeneous agricultural land 6.7 1.6 3.0 0.7 3.7 0.9 Agricultural land 143.7 34.5 143.7 34.5 - - Forest 133.4 32.0 78.2 18.8 55.2 3.3 Transitional woodland/shrub 78.0 18.7 133.2 32.0 -55.2 -16.9 Sparsely vegetated areas 0.0 0.0 0.0

Forest and other semi-natural areas 211.4 50.7 211.4 50.7 - -

Taking into account the changes among ecosystem categories, the area of arable land

decreased by 7 thousand hectares (mostly because of afforestation and partly because of urban

sprawl). The forest area increased by 63 thousand hectares (the 8 thousand hectares surplus

came from the afforestation of former agricultural area).


CLC detected only small changes of the main ecosystem categories even during one decade

however the typical processes of longer terms are reflected in the results.

The area of the terrestrial ecosystems slightly decreased, while the area of aquatic ecosystems

(mostly the area of lakes) showed a small increase. The urban sprawl occurred at the expense

of agricultural area because on the border of the expanded settlements usually agricultural

area can be found (green-field investments). For the agricultural area, change of the

cultivation method was more important. Afforestation and spontaneous natural regeneration

resulted in the increase of forests and other semi natural areas (the areas of transitional

woodland and shrub increased the most). Table 6

Land-cover change matrix, 1990–2000 (hectares)

EA.3 Land-cover, 2000

EA3. Land-cover, 1990 EA.311.

Urban

EA.312 Agri-

cultural

EA:313 Forests and other semi-

natural

EA.314 Grass-land

EA.31 Terrest-rial eco-systems

EA.32a Wetland

EA.32b Inland water

EA.32 Aquatic

eco-systems

Total, initial

year=1990

De-crease

EA.311. Urban 707 1 582 618 0 2 907 0 124 124 3 031 2 324 EA.312 Agricultural 9 573 143 725 35 302 1 335 189 935 1 145 2 530 3 675 193 610 49 885 EA:313 Forests and other semi-natural 691 813 211 479 572 213 555 18 243 261 213 816 2 337 EA.314 Grassland 10 2 139 527 0 2 676 822 167 989 3 665 3 665 EA.31 Terrestrial ecosystems 10 981 148 259 247 926 1 907 409 073 1 985 3 064 5 049 414 122 5 049

EA.32a Wetland 35 88 46 0 169 0 1 565 1 565 1 734 1 734 EA.32b Inland water 24 216 101 0 341 354 0 354 695 695 EA.32 Aquatic ecosystems 59 304 147 0 510 354 1 565 1 919 2 429 510

Total (final year) 11 040 148 563 248 073 1 907 409 583 2 339 4 629 6 968 416 551 5 559

Increase 10 333 4 838 36 594 1 907 510 2 339 4 629 5 049 5 559 Change account

Initial stock, 1990 507 702 5 855 638 2 006 004 595 305 8 964 649 125 355 211 106 336 461 9 301 110 Final stock, 2000 515 712 5 810 589 2 040 259 593 549 8 960 109 125 959 215 041 341 000 9 301 109 Total changes (Increase +Decrease) 12 657 54 723 38 931 5 572 5 559 4 073 5 324 5 559 11 118 Net changes (Increase -Decrease) 8 009 -45 047 34 257 -1 758 -4 539 605 3 934 4 539

The reason for the changes is usually the deliberate decision of the man e.g. building,

changing in cultivation method, afforestation and developing artificial water surfaces.

However, the area of forests and other semi natural areas increased also because of natural

processes. On non-cultivated areas first natural herbaceous vegetation grew up followed by

the spread of transitional woodland and shrub areas.

The land cover accounts allow the analysis of the changes that occurred in the 1990s. From

the 2000 land cover database by ecosystems, the proportion of unchanged areas since 1990

can be calculated. 99.4 percent of the area of terrestrial ecosystems and 98.0 percent of the

area of aquatic ecosystems did not change in the ten-year period. Within the terrestrial


ecosystems, 99.9 percent of the opening stocks of agricultural ecosystems was left unchanged,

while 98.0 percent of urban, forests and other semi-natural areas did not show any change at

that period. The size of artificial surfaces changed because of the recultivation of mines and

dumps and the decreasing area of construction sites. The reason for the change of forests and

other semi-natural areas must have been the starting of agricultural production and partly

building on these areas.

The processes of this decade can also be demonstrated by the share of gross and net changes.

The decrease of the area of terrestrial ecosystems and the increase of the area of aquatic

ecosystems can also be noticed in this way.

Of the terrestrial ecosystems, the area of forests and other semi-natural areas and the artificial

surfaces increased, while the area of agricultural ecosystems and semi-natural grassland

decreased. Table 7

Land-cover types of changes in stock and land cover account for Hungary, 1990-2000

Name EA311 Urban

(CLC1)

EA312 Agricul-

tural (CLC2)

EA313 Forests

and other semi-

natural (CLC3.1

+324+3.3)

EA314 Grass-land

(CLC321)

EA31 Terrestrial

eco-systems

EA32a Wetland (CLC4)

EA32b Inland water

(CLC5)

EA32 Aquatic

eco-systems

Total

Hectares Initial stock, 1990 507 702 5 855 638 2 006 004 595 305 8 964 649 125 355 211 106 336 461 9 301 110 Development 10 333 -9 573 -692 -10 59 -35 -24 -59 0 Agricultural intensification -1 582 4 837 -2 723 -231 301 -88 -216 -304 -3 Woodland creation/rotation -146 -8 380 8 533 -6 1 0 0 0 1 Semi-natural creation/rotation -472 -29 403 29 380 -1 342 -1 837 2 292 -455 1 837 0 Water body creation -124 -2 530 -243 -167 -3 064 -1 565 4 630 3 065 1 Final stock, 2000 515 712 5 810 589 2 040 259 593 549 8 960 109 125 959 215 041 341 000 9 301 109 Change account Reductions, 1990-2000 -2 324 -49 886 -3 658 -1756 -56 701 -1 688 -695 -2 383 -59 084 Additions, 1990-2000 10 333 4 837 37 913 52 160 2 292 4 630 6 922 59 082 Total changes (Increase +Decrease) 12 657 54 723 41 571 1756 108 861 3 980 5 325 9 305 118 166 Net change, 1990-2000 8 009 -45 049 34 255 -1 756 -4 541 604 3 935 4 539 -2

Percent Stock un-changed since 1990, in %, by final stock 98.0 99.9 98.1 100.0 99.4 98.2 97.8 98.0 99.4 Total change in %, by final stock 2.5 0.9 2.0 0.3 1.2 3.2 2.5 2.7 1.3 Net change in %, by final stock 1.6 -0.8 1.7 -0.3 -0.1 0.5 1.8 1.3 0.0


In the future, the increasing share of water, forests and other semi-natural ecosystems is

expected in line with the aims of sustainable development.

As a further task in the compilation of land accounts, a detailed breakdown of natural

resources (introducing biotopes and biodiversity) can be carried out. Our future tasks include

the use of LUCAS 2006 survey data and the development of the inventory of land value.


7 Methodological notes

Differences caused by rounding

The area of Hungary is 93 011 km2 according to the CLC50 survey, which serves as a base

for the land cover 2000 data. There is a 19 km2 difference between this land cover figure and

the data taken from the database of the HCSO because of the rounding at the land cover

categories (altogether 79 categories).

The 2 ha difference between the 1990 and 2000 figures in Table 7 is also caused by rounding.

This table describes the types of land cover changes. The data of land cover 2000 (according to Annex 3)

Following the recommendation of EUROSTAT, the ecosystem-approach land cover statistics

is based on the CLC survey. Data of the CLC survey had to be corrected significantly in

several land cover categories for reasons mentioned in paragraph 2.1.1. Data of the CLC50

based on 1998-1999 satellite images seemed to be more reliable than data of the less detailed

CLC2000 based on 2000-2001 satellite images. The divergence caused by time difference was

negligible compared to the divergence due to reduction of detail. The determination of the

territory of individual level-1 groups was made as follows: Artificial surfaces:

Proper details by the CLC50, with the following corrections:

Decrease of territory:

Transfer of the 67.1 thousands ha garden area of private farmers from artificial surfaces

into heterogeneous agricultural areas.

Increase of territory:

The road network area is 38.4 thousand ha according to the Hungarian Roads

Management Company.

The rail network area is 6.4 thousand ha. (Calculated on the basis of Table 26.7. of the

Statistical Yearbook of Hungary, 2003.)

Agricultural area: HCSO data are reliable with the following corrections:

Arable land: HCSO data are reliable.

Orchard and vineyard: HCSO data are reliable.


Agricultural grassland : Using ARDA data (+10% addition) is more reliable, than the

HCSO data. (The description in paragraph 2.2.2. is the ground for the additional

estimation.)

Heterogeneous agricultural area: modified data of CLC50 can be used. These data

contain the mixed use by annual crops, agricultural grassland and permanent crops besides

the garden area of the private farmers, altogether 395.6 thousand ha. (101.6 thousand ha of

garden area falls into this category according to land use statistics of the HCSO) Agricultural area: altogether 5 810.6 thousand ha, which is 99.4% of the figure in

CLC50, and 99.3% of the data in the HCSO land use statistics. (Within this, the

agricultural grassland territory was decreased by 337 thousand ha (32%), on the other

hand, the mixed agricultural land area was increased by 294 thousand ha (390%).)

Forests and semi-natural area: Data of the SFS and the CLC 50 can be used according to the following:

Forests: The “Forests covered by trees” data of the SFS can be used. This figure is 1736.5

thousand ha, and includes the forest areas larger than 1500 m2 without the clear-cuts,

afforestation area, shrubby vegetation. These data are distributed to broad-leaved forest

and coniferous forest. (forest area is 1769.6 thousand ha according to the HCSO land

statistics data, which contains the clear-cuts.)

Necessary correction: the mixed forest (80.3 thousand ha) is a separate category in

CLC50 (considered to be a mixture of broad-leaved and coniferous forest). The broad-

leaved and coniferous forest categories had to be reduced in order to use the mixed forest

category.

Other woodland and semi-natural area: CLC50 can be used.This category includes the

following types of land cover: semi-natural grassland (with or without trees and shrubs),

transitional woodland and shrub, clear-cuts, spontaneously wooded agricultural areas,

open spaces with little or no vegetation.

Necessary correction: we increased the area of this category from 770.2 thousand ha

(CLC50 figure) to 887.6 thousand ha so that the data covers the whole area left of

Hungary. 40% of the 117.4 thousand ha increase is classified as semi-natural grassland

while 60% of that is classified as transitional woodland and shrub.

Semi-natural grassland: it is a separate ecosystem category; the area was taken out of the

category other wooded and semi-natural area. Wetlands:

Data of CLC50 can be used.

Inland waters: Data of MARD can be used (the CLC50 survey does not contain the water surfaces

narrower than 50 m).


Land cover changes between 1990 and 2000

The CLC data on changes can be used because it can be matched to the uncultivated land area

data of the MARD.

According to CLC-Change database, the agricultural area decreased by 45.0 thousand ha

between 1990 and 2000. According to MARD data, it decreased by 41.6 thousand ha (due

to lack in the time series between 1991 and 1993 data are partly calculated). The 8-percent

difference between the two data sources justify the use of CLC data, especially as the

MARD data is not detailed enough and refers to the land use, which is different from land

cover.


Annexes Annex 1

CORINE Land Cover nomenclature

Level 1 Level2 Level3

1.1.1 Continuous urban fabric1.1.2 Discontinuous urban fabric1.2.1 Industrial or commercial units1.2.2 Road and rail network and associated land1.2.3 Port areas1.2.4 Airports1.3.1 Mineral extraction sites1.3.2 Dump sites1.3.3 Construction sites1.4.1 Green urban areas1.4.2 Sport and leisure facilities

2.1.1 Non-irrigated arable land2.1.2 Permanently irrigated land2.1.3 Rice fields2.2.1 Vineyards2.2.2 Fruit trees and berry plantations2.2.3 Olive groves

2.3 Pastures 2.3.1 Pastures2.4.1 Annual crops associated with permanent crops2.4.2 Complex cultivation patterns2.4.3 Land principally occupied by agriculture, with significant areas of natural vegetation

2.4.4 Agro-forestry areas

3.1.1 Broad-leaved forest3.1.2 Coniferous forest3.1.3 Mixed forest3.2.1 Natural grasslands3.2.2 Moors and heathland3.2.3 Sclerophyllous vegetation3.2.4 Transitional woodland/shrub3.3.1 Beaches, dunes and sand plains3.3.2 Bare rocks3.3.3 Sparsely vegetated areas3.3.4 Burnt areas3.3.5 Glaciers and perpetual snow

4.1.1 Inland marshes4.1.2 Peat bogs4.2.1 Salt marshes4.2.2 Salines4.2.3 Intertidal flats

5.1.1 Water courses5.1.2 Water bodies5.2.1 Coastal lagoons5.2.2 Estuaries5.2.3 Sea and ocean

4.2 Coastal wetlands

5.1 Inland waters

5.2 Marine waters

3.1 Forests

3.2 Shrub and/or herbaceous vegetation association

3.3 Open spaces with little or no vegetation

4.1 Inland wetlands4. WETLANDS

5. WATER BODIES

1.1 Urban fabric

1.2 Industrial, commercial and transport units

1.3 Mine, dump and construction sites

1.4 Artificial non-agricultural vegetated areas

2.1 Arable land

2.2 Permanent crops

2.4 Heterogeneous agricultural areas

1. ARTIFICIAL SURFACES

2. AGRICULTURAL AREAS

3. FORSTS AND SEMI-NATURAL AREAS


Annex 2 LUCAS Land Cover codification

CODE Meaning CODE Meaning

A11 Buildings with one to three floors B71 Apple fruit

A12 Buildings with more than three floors

B72 Pear fruit

A13 Greenhouses B73 Cherry fruit

A21 Non built-up area features B74 Nuts trees

A22 Non built-up linear features B75 Other fruit trees and berries

B11 Common wheat B76 Oranges

B12 Durum wheat B77 Other citrus fruit

B13 Barley B81 Olive groves

B14 Rye B82 Vineyards

B15 Oats B83 Nurseries

B16 Maize B84 Permanent industrial crops

B17 Rice C11 Broadleaved forest

B18 Other cereals C12 Coniferous forest

B21 Potatoes C13 Mixed forest

B22 Sugar beet C21 Other broadleaved wooded area

B23 Other root crops C22 Other coniferous wooded land

B31 Sunflower C23 Other mixed wooded land

B32 Rape seeds C30 Poplars, eucalyptus

B33 Soya D01 Shrubland with sparse tree cover

B34 Cotton D02 Shrubland without tree cover

B35 Other fibre and oleaginous crops E01 Permanent grassland with sparse tree/shrub cover

B36 Tobacco E02 Permanent grassland without tree/shrub cover

B37 Other non-permanent industrial crops

F00 Bare land

B41 Dry pulses G01 Inland water bodies

B42 Tomatoes G02 Inland running water

B43 Other fresh vegetables G03 Coastal water bodies

B44 Floriculture and ornamental plants G04 Wetland

B50 Temporary, artificial pastures G05 Glaciers, permanent snow


ANNEX 3 LAND-COVER

CLC CLC-50a) CLC-2000 LUCAS 2002 HCSO, 2000 Other sources Approved, 2000

code name Area, ha % Area, ha % Area, ha % Area, 1000 ha

% Area, ha, 1000 ha

Data source

Area, ha %

111 Continuous urban fabric 3 493 0.0 3 181 0.0 3 493 0.0

112 Discontinuous urban fabric 354 904 3.8 414 209 4.5 287 804 b) 3.1

11 Urban fabric 358 397 3.9 417 391 4.5 291 297 3.1

121 Industrial or commercial units 108 926 1.2 49 675 0.5 108 926 1.2

122 Road and rail network and associated land 16 103 0.2 4 788 0.1 44.8 HRM+calc. 44 800 0.5

123 Port areas 595 0.0 385 0.0 595 0.0

124 Airports 9 097 0.1 6 090 0.1 9 097 0.1

12 Industrial, commercial and transport units 134 721 1.4 60 938 0.7 163 418 1.8

13 Mine, dump and construction sites 20 748 0.2 13 299 0.1 20 748 0.2

14 Artificial non-agricultural vegetated areas 40 249 0.4 37 237 0.4 40 249 0.4

1. Artificial surfaces 554 115 6.0 528 866 5.7 522 320 5.6 1 338.5 c) 14.4 640.3 Censusd) 515 712 5.5

21 Arable land 4 905 377 52.7 4 960 950 53.3 4 425 269 47.6 4 499.8 48.4 4 071 619 ARDA 4 499 800 48.4

22 Permanent crops 211 319 2.3 202 661 2.2 261 328 2.8 201.3 2.2 147 304 ARDA 201 300 2.2

23 Pastures 401 537 4.3 662 234 7.1 1 371 924 14.7 1 051.2 11.3 649 006 ARDA 713 900 e) 7.7

24 Heterogeneous agricultural areas 328 489 3.5 482 883 5.2 .. 101.6 1.1 395 589 b) 4.3

2. Agricultural areas 5 846 722 62.9 6 308 729 67.8 6 058 521 65.1 5 853.9 62.9 5 810 589 62.5

312 Coniferous forest 162 138 1.7 100 381 1.1 160 015 1.7 243.5 SFSf) 203 374 2.2 311 Broad-leaved forest 1 555 435 16.7 1 482 003 15.9 1 634 164 17.6 1 452 873 15.6

313 Mixed forest 80 253 0.9 156 722 1.7 109 982 1.2 80 253 0.9

31 Forests 1 797 826 19.3 1 739 107 18.7 1 904 161 20.5 1 769.6 19.0 1736.5 SFSf) 1 736 500 18.7

321 Natural grassland 546 557 5.9 223 949 2.4 593 549 6.4

324 Transitional woodland/shrub 223 608 2.4 220 787 2.4 294 097 3.2

32 Shrub and/or herbaceous vegetation association 770 165 8.3 444 736 4.8 436 893 4.7 887 646 9.5

33 Open spaces with little or no vegetation 9 563 0.1 2 314 0.0 17 220 0.2 9 662 0.1

3. Forests and semi-natural areas 2 577 554 27.7 2 186 156 23.5 2 358 274 25.3 1 769.6 19.0 2 633 808 28.3

411 Inland marshes 116 183 1.2 91 841 1.0 116 183 1.2

412 Peat bogs 11 311 0.1 12 413 0.1 11 311 0.1

4. Wetlands 127 494 1.4 104 254 1.1 60.0 g) 0.6 127 494 1.4

511 Water courses 61 897 0.7 46 835 0.5 76 738 0.8

Fish-pond 28 563 0.3 0.0 32.0 0.3 32 000 0.3

Other water-bodies 104 768 1.1 0.0 104 768 1.1

512 Water bodies 133 331 1.4 126 271 1.4 136 768 1.5

5. Inland waters 195 228 2.1 173 106 1.9 363 885 3.9 281.0 3.0 341.0 MARD h) 213 506 2.3

TOTAL 9 301 113 100.0 9 301 111 100.0 9 303 000 100.0 9 303.0 100.0 9 301 109 100.0

a) CLC50 corrected division with a section of 24. categorie by FÖMI. b) From CLC50 112 to 24: garden of private farmers: 67 100 ha (HCSO). c) Uncultivated land area, without water bodies. d) Inner city from census, 1990. e) Data by ARDA+10%. f) SFS: forests covered trees (over 1500 m2), 1 736.5 thousand ha. g) Reed h) MARD: Inland waters with wetlands.

accepted data accepted data with correction


ANNEX 4

CLC CHANGE, HA

code00

code90 111 112 11 121 122 123 124 12 131 132 133 13 141 142 14 1 211 213 21 221 222 22 231 242 243 24 2 111 0 0 0 0 0 0 0 0 0 112 0 0 0 0 0 0 0 0 0

11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 121 0 0 0 0 0 0 0 0 0 122 0 0 0 0 0 0 0 0 0 123 0 0 0 0 0 0 0 0 0 124 0 0 0 0 0 0 0 0 0

12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 131 0 0 114 114 57 57 172 50 50 106 106 538 10 10 704 132 0 35 35 0 0 35 23 23 44 44 495 0 562 133 191 191 121 121 6 6 34 83 118 435 0 0 316 0 316

13 0 191 191 156 0 0 0 156 0 120 0 120 34 141 175 641 73 0 73 150 0 150 1 349 10 0 10 1 582 141 20 20 10 10 17 17 18 18 65 0 0 0 0 142 0 0 0 0 0 0 0 0 0

14 0 20 20 10 0 0 0 10 0 0 17 17 0 18 18 65 0 0 0 0 0 0 0 0 0 0 0 1 0 211 211 166 0 0 0 166 0 120 17 137 34 159 193 707 73 0 73 150 0 150 1 349 10 0 10 1 582

211 900 900 1 290 1 163 51 2 503 1 201 395 842 2 438 428 428 6 269 10 10 2 293 5 943 8 236 43 393 3 314 685 3 999 55 639 213 0 0 0 0 0 2 777 2 777 0 76 0 2 853

21 0 900 900 1 290 1 163 0 51 2 503 1 201 395 842 2 438 0 428 428 6 269 2 777 10 2 787 2 293 5 943 8 236 43 469 3 314 685 3 999 58 492 221 41 41 13 13 37 7 44 18 18 116 6 303 6 303 543 543 3 043 505 210 715 10 603 222 0 67 69 136 62 62 0 198 5 915 5 915 35 35 882 780 16 796 7 628

22 0 41 41 67 82 0 0 149 37 0 69 106 0 18 18 314 12 218 0 12 218 35 543 578 3 925 1 286 225 1 511 18 232 231 137 137 600 20 7 627 503 304 426 1 232 32 121 153 2 149 62 509 62 509 128 328 456 781 268 1 049 64 015 242 337 337 137 52 189 7 102 109 12 28 40 674 211 211 13 20 33 1 370 158 158 1 772 243 0 17 17 40 10 28 77 72 72 167 13 13 20 20 1 162 20 20 1 216

24 0 337 337 154 52 0 0 206 47 10 129 186 12 100 112 841 224 0 224 33 20 53 2 532 20 158 178 2 988 2 0 1 415 1 415 2 110 1 317 0 58 3 486 1 787 709 1 466 3 962 43 667 710 9 573 77 728 10 77 738 2 490 6 834 9 324 49 926 5 401 1 337 6 738 143 725

311 0 60 55 115 146 16 162 29 29 307 121 121 17 17 118 5 83 89 344 312 0 8 8 20 9 29 0 37 6 6 0 8 0 14 313 0 22 22 30 30 0 51 5 5 0 0 5

31 0 0 0 68 77 0 0 145 196 16 9 221 0 29 29 395 132 0 132 0 17 17 126 5 83 89 364 321 0 0 10 10 0 10 2 125 2 125 0 15 15 2 139 324 22 22 77 26 103 117 16 29 161 11 11 297 191 191 15 45 60 162 13 13 427 331 0 0 0 0 0 0 0 23 0 23 333 0 0 0 0 0 0 0 0 0

33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 23 31+324+33 0 22 22 145 103 0 0 248 313 32 38 382 0 40 40 691 324 0 324 15 62 77 311 5 96 102 813 411 0 0 0 27 27 27 0 0 88 0 88 412 0 0 8 8 0 8 0 0 0 0

41 0 0 0 0 0 0 0 0 0 0 8 8 0 27 27 35 0 0 0 0 0 0 88 0 0 0 88 511 0 0 6 6 19 19 24 0 0 48 0 48 512 0 0 0 0 0 69 69 0 86 12 12 168

51 0 0 0 0 0 0 0 0 0 0 6 6 0 19 19 24 69 0 69 0 0 0 134 0 12 12 216 Total 0 1 647 1 647 2 421 1 420 0 58 3 899 2 110 861 1 534 4 505 77 912 989 11 041 80 319 10 80 329 2 655 6 896 9 551 51 808 5 430 1 446 6 876 148 565

The rows refer to the 1990 categories while the columns refer to the 2000 categories. For example there is a 114 hectare area that had the code 131 (mine) in 1990 while its code in 2000 is 132 (dump).

ANNEX 4 (continue)

CLC CHANGE, HA

code00

code90 311 312 313 31 321 324 331 333 33 31+324+33 411 412 41 511 512 51 Total 111 0 0 0 0 0 0 112 0 0 0 0 0 0

11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 121 0 9 0 9 0 0 9 122 0 0 0 0 0 0 123 0 0 0 0 0 0 124 0 0 0 0 0 0

12 0 0 0 0 0 9 0 0 0 9 0 0 0 0 0 0 9 131 91 26 117 266 0 384 0 76 76 1 335 132 15 5 8 28 140 0 168 0 0 765 133 0 57 0 57 0 49 49 856

13 106 31 8 146 0 463 0 0 0 609 0 0 0 49 76 124 2 956 141 0 0 0 0 0 65 142 0 0 0 0 0 0

14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 65 1 106 31 8 146 0 472 0 0 0 618 0 0 0 49 76 124 3 031

211 6 125 121 45 6 292 1 105 13 563 0 19 855 135 135 1 485 1 485 84 488 213 0 99 0 0 0 0 2 952

21 6 125 121 45 6 292 1 204 13 563 0 0 0 19 855 135 0 135 0 1 485 1 485 87 439 221 330 330 131 2 174 0 2 504 0 0 13 355 222 124 30 154 861 0 1 015 0 0 8 841

22 454 30 0 484 131 3 035 0 0 0 3 519 0 0 0 0 0 0 22 195 231 637 58 17 712 8 106 0 8 818 963 963 976 976 76 920 242 174 17 190 578 0 769 0 0 3 215 243 588 47 67 702 1 640 0 2 342 47 47 69 69 3 841

24 762 47 84 892 0 2 219 0 0 0 3 111 47 0 47 0 69 69 7 056 2 7 978 256 146 8 380 1 335 26 922 0 0 0 35 302 1 145 0 1 145 0 2 530 2 530 193 611

311 12 12 65 060 0 65 073 18 18 17 17 65 758 312 40 42 82 5 559 0 5 642 0 0 5 692 313 45 53 98 7 390 0 7 488 0 0 7 545

31 85 53 54 192 0 78 010 0 0 0 78 202 18 0 18 0 17 17 78 995 321 6 6 514 6 6 527 822 822 167 167 3 665 324 112 860 9 497 10 899 133 256 455 0 133 256 0 226 226 134 660 331 0 21 0 21 0 0 44 333 0 117 0 0 0 0 117

33 0 0 0 0 117 21 0 0 0 21 0 0 0 0 0 0 161 31+324+33 112 945 9 550 10 953 133 448 572 78 031 0 0 0 211 479 18 0 18 0 243 243 213 817 411 0 46 0 46 0 1 498 1 498 1 659 412 0 0 0 0 67 67 75

41 0 0 0 0 0 46 0 0 0 46 0 0 0 0 1 565 1 565 1 734 511 0 101 0 101 0 0 174 512 0 0 0 354 354 0 522

51 0 0 0 0 0 101 0 0 0 101 354 0 354 0 0 0 696 Total 121 036 9 837 11 108 141 980 1 907 106 087 0 6 6 248 073 2 338 0 2 338 49 4 581 4 630 416 553

The rows refer to the 1990 categories while the columns refer to the 2000 categories. For example there is a 114 hectare area that had the code 131 (mine) in 1990 while its code in 2000 is 132 (dump).

Documents

Land and Forest Accounts (Action 1) Final Report Statistics...Environment Statistics and Accounts – Land and fore st accounts (Action 1) and Material Flow accounts and NAMEA Waste