Operational Agriculture Monitoring System Using Remote Sensing

Maryam Adel Saharkhiz

Outline

Introduction on Using Remote Sensing in

Agriculture

Application of RS in Vegetation

Application of RS in Soil

Application of RS in Forest

Application of RS in Land Cover

Introduction on Using Remote Sensing in Agriculture

Agricultural applications of Remote Sensing

(Land Cover)

LandCover of CANADA

(Forestry)

Laser data from a forest

(Soil)

A mineral map derived from AVIRIS data

(Vegetation)

Color-IR image from

the ASTER sensor

shows "green vegetation"

Vegetation

Crop area estimation Crop growth monitoring Crop yield prediction

Crop Monitoring

Damage Assessment

Crop Condition Assessment

Crop Type Identification and Mapping

Crop Type Identification and Mapping Background

forecasting grain supplies (yield prediction),

collecting crop production statistics,

facilitating crop rotation records,

mapping soil productivity,

identification of factors influencing crop stress,

assessment of crop damage due to storms and drought,

monitoring farming activity.

Why Remote sensing?

providing a synoptic view

provide structure information about the health of the vegetation

Different spectral reflection in various field and situation like:

phenology (growth)stage type, crop health,

Radar is sensitive to the structure, alignment, and moisture content of the crop

Data Requirements

Multitemporal imagery (frequent repeat imaging throughout the growing season)

Multisensor data: (VIR, RADAR)

High Resolution Data

Ancillary Data

Crop Monitoring

Crop area estimation Crop growth monitoring Crop yield prediction

Crop Monitoring & Damage Assessment

Satellite image distribution for early rice monitoring

Satellite image distribution for single cropping and late rice monitoring

Rice area estimateUsing remote sensing

Crop area estimate

Methodology of the crop area estimation

key words:

.National scale: valid for the whole country, for central government

.Sampling system: stratified sampling method, remote sensing for each sample unit

.Extrapolation Model:to derive area estimate at national scale

. Change detection:estimate is based on the analysis of change observed on satellite image

.Ground survey: validation and substitute for remote sensing

Satellite image distribution for winter wheat monitoringWinter wheat area estimate Using remote sensing

Crop area estimate

Crop area estimateChange between 2 years on the satellite image

2005年

2006年

MethodologyNormalized Differential Vegetation Index (NDVI)

will be used as the indicator of crop growth. At present, the crop growth monitoring is carried

out using the difference of NDVI between this two year of the same time

The differences are graded into different classes which reflect the change in same place in two years.

MODIS, NOAA and FY are mainly used in the crop growth condition monitoring.

Crop Growth Monitoring

Crop Growth Monitoring

Once every 15 days

Growth condition of winter wheat

Growth condition of corn

Crop Yield Estimation & Prediction

At present, using several methods to estimate yield at one time is a practical and effective way. The methods include agricultural climate model, remote sensing model, crop growth model, etc. Of course, other ancillary information is essential to get accurate yield results such as crop growth information, soil moisture information and other ground survey data.

Background

Why remote sensing?

With the development of satellites, remote sensing images provide access to spatial information at global scale; of features and phenomena on earth on an almost real-time basis. They have the potential not only in identifying crop classes but also of estimating crop yield they can identify and provide information on spatial variability and permit more efficiency in field scouting. Remote sensing could therefore be used for crop growth monitoring and yield estimation.

Crop Damage Monitoring & Assessment

Background

moisture deficiencies, insects, fungal and weed infestations must be detected early enough to provide an opportunity for the farmer to mitigate.

Why remote sensing?

Infrared wavelengths crop can detect vigor as well as crop stress and crop damage RS gives required spatial overview of the land

RS can aid in identifying crops affected by conditions that are too dry or wet, affected by insect, weed or fungal infestations or weather related damage.

Images can be obtained throughout the growing season to not only detect problems, but also to monitor the success of the treatment.

Crop Disaster Monitoring

Drought Monitoring (2006.8 Sichuan and Chongqing)

Flood Monitoring)

Field Network Monitoring

In order to improve the accuracy and reliability of remote sensing monitoring system, national field monitoring network need to be assigned systematically in the agricultural region of Malaysia.

Soil moisture, crop growth data, yield data will be measured in the field.

This information coming from the field monitoring network counties can provide support and validation for the remote sensing monitoring system.

An Example of Distribution of Regional Centers in China

Distribution of the Regional Centers

Distribution of the Field Monitoring Counties

Example of Distribution of Field Monitoring Counties in china

Extension of monitoring system

The first one is the extension of monitoring objects, ie, the oil crop and sugar crop should be monitored based on the monitoring of five main crops and the background investigation of crop planting acreage need to be carried out based on the inter-annual change monitoring;

the second one is the extension of monitoring region, ie, the global main agricultural region need to be monitored based on the domestic monitoring.

Improvement of system The agricultural remote sensing monitoring

system is composed of national center, regional sub-center and field monitoring counties.

In the near future, the operational system will develop further, the structure harmonization and quality control will be strengthened and run ability of operational system will be upgraded comprehensively.

Thanks for your kind attention