Geo-informatics and Remote Sensing Applications for Village-level Crop Inventory in Gujarat State, India

ABSTRACT The study on Remote Sensing (RS) based Crop Acreage Estimation at Village-level was taken up in two villages of Anand and Mehsana districts of Gujarat state. The major objective of this study was to attempt village-level crop inventory during two crop seasons of Kharif (monsoon season) and Rabi (winter season) using single-date Indian Remote Sensing (IRS) LISS-III and LISS-IV digital data of maximum vegetative growth stage of major crops during each season. The methodology adopted for village-level crop inventory consisted of: a) geo-referencing of satellite data, b) rectification of cadastral maps, c) Ground data collection, d) supervised Maximum Likelihood (MXL) Classification of the RS data and e) accuracy assessment. The results indicate that crop discrimination at field-level is possible using both LISS-III and LISS-IV digital with accuracy ranging from 70 to 75 per cent depending upon plot size. However, higher level of misclassification was observed in case of small plot sizes, which may be due to the effect of high proportion of boundary (mix) pixels. In most of the field crops, a large amount of heterogeneity was found due to sowing date differences and varying management practices resulting in different vigour conditions. The criteria of majority pixels was adopted for plot-level crop identification and mapping. As expected it was observed that the accuracy with LISS-IV data was better in comparison to LISS-III sensor since plot sizes are very small in the study area. The satellite data of proper bio-window of the crops was also not available due to various reasons, therefore, it was observed that, for better crop discrimination and achieving higher accuracy, satellite data of proper bio-window is very important. This study brings out the potentials and limitations