Abstract
Abstract. Under Pradhan Mantri Fasal Bima Yojana (PMFBY), a large number of Crop Cutting Experiments (CCEs) were conducted by Odisha State for Kharif Rice in the year 2016 and 2017. The present study was carried out to examine the quality of the performed CCEs using statistical methods and Remote Sensing (RS) technique. Total 24389 and 34725 CCEs were conducted. After removing outliers, 22083 and 26848 CCE points were analyzed for the year 2016 and 2017, respectively. Multi-date RISAT-1 (2016) and Sentinel-1A (2017) satellite data were used for generating the Kharif Rice crop mask, which was used to get NDVI and NDWI values for Rice pixels, from MODIS VI products. The values of these indices were divided into four strata from highest A, followed by B, C, and D (Lowest Value) based on the range (minimum and maximum) of values. The CCE based yield data were then divided into four yield strata of equal proportion. Yield and RS (NDVI+NDWI) based strata were combined to examine whether the CCE Points having high yield fall under good NDVI zone or vice versa. The results showed that there was strong match between CCE strata and the vegetation index strata in both the years. Therefore, it could be be concluded that RS based indices have the capability to assess the quality/accuracy of CCEs. Furthermore, the large variety of information available with CCEs such that crop variety, crop condition, water sources, stress conditions etc., can be used as input parameters to train any model to predict better results.
Highlights
Agriculture plays avital role in India’s economy, as a principal mean of livelihood and farmers are the backbone of agriculture sector
The stratification of vegetation index was compared with that of Crop Cutting Experiments (CCEs) yield. It is clear from the comparison (Table 5) that 27% CCE points of remote sensing stratum has been matched accurately with corresponding yield stratum. 41% falls in 1 category difference, 21% CCEs in 2 category difference and 11% under 3 category differences matching level
From this study it can be concluded that Remote sensing technology may considered as suitable tool to identify the outliers in large series of CCEs
Summary
Agriculture plays avital role in India’s economy, as a principal mean of livelihood and farmers are the backbone of agriculture sector. Estimation of yield of different crops is one of the important activities under taken by the government and many other organizations since it plays a major role in policy making, agricultural planning, to monitor the progress of the sector and provide insurance to the sector. The crop yield estimation, in India, is carried out on the on the basis sample survey approach, through large number of scientifically designed crop cutting experiments (CCE) (CSO, 2007). Rice production in India is an important part of the national economy. Since 2010, production as well as yield of rice has increased significantly. Rice yield estimation plays a vital role Indian Agriculture sector
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