Publications

Chandna, PK; Mondal, S (2020). Analyzing multi-year rice-fallow dynamics in Odisha using multi-temporal Landsat-8 OLI and Sentinel-1 Data. GISCIENCE & REMOTE SENSING, 57(4), 431-449.

Abstract
Sustainable intensification of existing cropland is one of the most viable options for meeting the escalating food demands of the ever-increasing population in the world. Accurate geospatial data about the potential single-crop (rice-fallows) areas is vital for policymakers to target the agro-technologies for enhancing crop productivity and intensification. Therefore, the study aimed to evaluate and understand the dynamics of rice-fallows in the Odisha state of India, using SAR (Sentinel-1) and Optical (Landsat OLI) datasets. This study utilized a decision-tree approach and Principal component analysis (PCA) for the segmentation and separation of different vegetation classes. The estimated overall accuracy of extracted rice-fallow maps was in the range of 84 to 85 percent. The study identified about 2.2, 2.0 and 2.1mha of Rice-Fallows in the years 2015-16, 2016-17, and 2017-18, respectively. The combined analysis (all three years) of rice-fallow maps identified about 1.34mha of permanent rice-fallows, whereas the remaining 0.6-0.8mha area was under the current-fallow category. About 50% of the total permanent rice-fallows were detected in the rainfed areas of Mayurbhanj, Bhadrak, Bolangir, Sundargarh, Keonjhar, Baleswar, Nawarangpur and Bargarh districts. The study also illustrated the time-series profiles of SMAP (soil moisture) datasets for the ten agroclimatic zones of the Odisha, which can be utilized (along with rice-fallow maps) for the selection of crop and cultivars (e.g. short or medium duration pulses or oilseeds) to target the rice fallows. The approach utilized in the current study can be scaled up in similar areas of South and South-east Asia and Africa to identify single-crop areas for targeting improved technologies for enhanced crop productivity and intensification.

DOI:
10.1080/15481603.2020.1731074

ISSN:
1548-1603