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Remote sensing –Beyond images Mexico 14-15 December 2013 The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
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AGRICULTURAL STATISTICS OF ROOTS AND TUBERS
PERCY ZOROGASTÚA C. ROBERTO QUIROZMICHAEL POTTSSTEFFEN SCHULZ
INTRODUCTION
Potato crop has a production of more than 314000 MT/Y and is the fourth crop of importance in the world. Sweet potato production reaches more than 110000 MT/year and occupies the seventh place in the world.
In recent years, CIP has introduced several clones of orange flesh sweet potato in Africa, as a strategy to solve the severe vitamin A deficiency affecting the human population. This introduction requires precise information on cropping area to assess the potential dissemination of the new germplasm and their beneficiaries, both in the spatial and time scales. This knowledge is necessary for estimating the production, marketable volumes, per capita consumption, required inputs and to orient research.
Potato is acquiring more importance in Ethiopia due to frequent adverse factors that cause famine problems. Information about the area and zones where potato is grown and production volumes are necessary, in order to provide agricultural inputs for increasing productivity
There are reasons to believe that the statistics of FAO in Africa do not have a relation to the actual cultivated area. This reasonable doubt is based on the fact that crop statistics related to small producers, are obtained through field sampling and survey techniques that have some limitations.
CIP’s Production Systems and the Environment Sub-Program is developing and validating methodologies based on a) Spectroradiometry and the use of high-resolution remote sensing images that provides reliable, accurate, and dynamic information for estimating cropping areas and b) Detection of recently dehaulmed potato areas
ActualWhat is?How much is there ? Where do we have ?What is the current status?
PotentialHow much more it could produce?Where else it could be?
Key questions:
Agricultural statistics can be determined under two criteria: one through the use of a List frame in which a list of production units that can be registered each one through a census or only taken some samples of them, and through the Area frame in which area of land cover & land use is determined.
We have used the Area frame criteria, with the estimation of the cropping area derived from remote sensing products and field data, classifying high resolution satellite data and counting pixels. We utilized high resolution Spot images for building the agricultural statistics for the districts of Kumi (sweetpotato) in Uganda and Jeldu (potato) in Ethiopia
B RG NEAR IR MID INFRARED
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Wavelength in nanometers
% R
eflec
tanc
e
water
Green vegetation
Dry vegetation
Soil
Generic spectral signatures
Source: National Technical University of Athens
IMAGE ANALYSIS
Kumi
Statistics of Sweetpotato in Kumi district, UGANDA
Kumi climatic diagram
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CROPS REFLECTANCES
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Maize Bare Soil Millet Sweet potato Cassava Banana
Classified SPOT Image of the Kumi district, May 2006
Classified SPOT Image of the Kumi district, October 2006
Ground Truth Category 1 2 3 4 5 6 7Classificati
on
1 Forest/Mango 92.9 0 0 0.6 0 0 02 Water bodies 0 100 0 0 0 0 03 Clouds 0 0 100 0 0 0 0
4 Sweetpotato 5.9 0 0 93.1 0 0 0
5 Grassland 0.6 0 0 0 100 17.4 06 Other crops 0.6 0 0 6.4 0 82.5 07 Bare soil 0 0 0 0 0 0 100
Total 100 100 100 100 100 100 100
Confusion Matrix of Land Cover & Land Use of Kumi (%)
Area covered by different land use and plant cover categories, May and October 2006
44620 ha of sweetpotato
Area planted in Kumi for Sweet potato
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1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2,003
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Ha.
Source: Uganda Bureau of Statistics
The area projected to 2006according to official statistical records, compared with our results was 63 % of the total surface covered by sweetpotato
Jeldu
Addis Ababa
Potato in the Jeldu district, West Shewa region – Ethiopia
Source: Google Earth
Source: Gildemacher et al, 2009
Image SPOT 5 XS 10/11/2012
Source: Spot Image-Astrium
Land Cover & Land Use Dec. 2012 in Jeldu, West Shewa – Ethiopia
Source: CIP, based on: XS SPOT image
Category Area (Ha) % Forest/Shrubs 34635.9 26.4Grassland/Weeds/Bare soil 16880.5 12.9Wheat 26284.1 20.0Barley 14886.4 11.3Teff 6210.6 4.7Potato 10663.6 8.1Urban Area / Infraestructure 4098.6 3.1Other crops 13503.0 10.3ND 4078.0 3.1Total 131240.7 100.0
Ground truth/Classification
Potato Grassland Forest Wheat Teff Barley
Urban area/Infrastr.
Potato 93.5 0 0 0 0 0 11.3Grassland/Weeds/Bare soil/Fallow 6.3 78.6 0 0 0 0 7.2Forest 0.0 0 100 0 0 0 0Wheat 0.0 0 0 70.8 0 1 0Teff 0.0 21.4 0 0 0 0 0Barley 0.2 0 0 29.2 2 99 0Urban area/ Infrastructure 0.0 0 0 0 0 1 81.4Total 100.0 100 100 100 0 100 100
Confusion Matrix of Land Cover & Land Use of Jeldu District
The radiometric evaluation and processing of the SPOT scenes of the district of Kumi in Uganda have made it possible to determine that the sweet potato foliage has a distinct spectral pattern defined by a low reflectance in the visible range of the spectrum and a high reflectance in the near infrared range.
This spectral pattern makes it possible to identify the sweet potato crop with a high degree of certainty, which allows defining with precision the cultivated area and the spatial distribution of the crop through the utilization of high-resolution SPOT images.
Conclusions
The results suggest that the traditional statistics of sweet potato was underestimated by about 37 % of total area.
Jeldu district in Ethiopia has 131240.7 ha, where we determined 10386.4 ha with potato (7.9 %) as to December of 2012. Jeldu is dominated by cereals cropping which occupy 36% of the total area. Forest area and scrubland occupy the 26.4% of the total. Grasses, weeds and bare soils occupy 13% of total. Urban area and infrastructure cover the 3.1% and 13.4% of total area were covered by other crops
