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FASAL (R&D): FORECASTING AGRICULTURAL OUTPUT USING
SPACE, AGRO-METEOROLOGY & LAND BASED OBSERVATIONS

Objectives

• Techniques development for Cotton, Sugarcane and Sorghum crop
discrimination

• To be carried out for Cotton, Sugarcane and kharif sorghum, crop discrimination

• Area and production forecast using multi-temporal AWiFS& RISAT data
• Involving field validation techniques with crop cutting experiments and condition

assessment
Data Used

• In-season multi-temporal AWiFS, LISS-III, LISS-IV and RISAT data
• Near real time Ground Truth information

Methodology

For estimation of sugarcane acreage, early growth stage from March to May will
be detected using multi-date AWiFS data. Few synchronous AWiFS data will be taken in

sample locations to precisely know the signature extension from high to low resolution

data in case of sugarcane fields which are widely spaced during early growth stage. The
signature of ratoon and freshly planted fields at different stages of growth will be mapped

and will be compared with GT data to know their variability at signature levels. GT will be
collected in May and digital analysis will be carried out in May-June.

Multi-date AWiFS data classification using ISODATA clustering technique will be
followed. A stratified sampling scheme using digital approach with the current classified

data will be implemented. This will help in increasing the accuracy of sample segment
location and their stratification, thus improving the coefficient of variation.

Multi-date data of July to November period will be used for cotton analysis.

Methodology consists of registration of multi-date dataset, generation of NDVI images,
development of master temporal profiles and thereby discrimination of cotton from other

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