Farm-Level Yield mapping for precision crop management by linking remote sensing inputs and a crop simulation model

Abstract

A study aimed at generating wheat yield maps of farmer’s fields by using remote sensing (RS) inputs was undertaken during the rabi season of 1998-99 in six villages of Alipur Block of Delhi State. RS derived leaf area index (LAI) were linked to wheat simulation model WTGROWS by adopting a strategy christened “Modified Corrective Approach”. This essentially uses an empirical relation of grain yield and LAI, which was derived from WTGROWS simulation model by running model for a combination of input resources, management practices and soil types occurring in the area. This biometric relationship was applied to all the wheat fields of the study area for which the LAI was derived from single acquisition of IRS LISS-III data (Jan 27, 99). The LAI-NDVI relation adopted was logarithmic in nature (R2=0.83) and was based on ground measurements of LAI in farmer’s fields in the same area. A comparison of predicted grain yield by the modified corrective approach and actual observed yield for the 22 farmer’s fields showed high correlation coefficient of 0.8 and a root mean square error (RMSE) of 597 kg ha-1 which was 17% of the observed mean yield. Thus linking of RS information and crop simulation model provides an alternative for mapping and forecasting crop yield under highly variable cropping environment of Indian farms, which is a pre-requisite for implementing Precision Crop Management (PCM).