Discrimination Plot Wise Area Estimation of Seasonal Crops

In the present study a semi-automated process model, named as ‘Accelerated Plot Based Crop Discrimination’ (APCD), has been developed for identifying and discriminating seasonal crops as well as estimating their plot level coverage area using very high resolution satellite image as this type of information plays a vital role in any agricultural policy making. The overall accuracy calculated is 89.10% with Kappa coefficient being 0.87. The plot wise crop coverage area estimated from the process model is also very closely matching with area obtained from detailed GPS survey data. To cross check the discrimination achieved from WV 2 multispectral data, hyperspectral measurements of the same crops are also collected by the field spectroradiometer and the statistical indices calculated from it shows similar spectral pattern as well as good co-relation (R2 > .90) with the same indices generated from the image. Findings of this study suggest that (1) plot level crop discrimination is achievable through pixel based approaches, (2) best discrimination can be achieved from NIR 1, NIR 2, Red Edge and Green bands combinations of WV 2 and (3) crop wise coverage area can be correctly estimated through the application of Raster Statistics for Vector (RSV) operation.

Discrimination Plot Wise Area Estimation of Seasonal Crops

Authors: Kakali Das, Pratyay Das Sarma and Saradindu Sengupta

Keywords : Crop discrimination, band indices, FCC, ISODATA, Co-Occurrence, J-M distance, liner regression, area estimation, Raster Statistics for Vector.

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