Estimating Agricultural Crop Types and Fallow Lands Using Multi Temporal Sentinel-2A Imageries

Abstract

Meeting the food and nutritional demands of ever growing human population will cause immense pressure on agricultural lands and natural resource bases across the world. This challenge can be met only by proper land and water management, which consists of crucial components like understanding cropping systems and crop fallow dynamics for sustainable intensification. In this work, a methodology was developed for crop and crop fallow land estimation using multi-temporal, high spatial resolution Sentinel-2A data in a test site of Odisha state, in India, comprising of two districts i.e., Bhadrak and Jajpur. Customized codes were written to find temporal variation pattern of NDVI values for each pixel in the study area. Observing the variation of NDVI over time, we have attempted to estimate crop life cycle duration and their type with rigorous field inputs. The cropland and fallow land intensification maps showed 10-different cropping pattern with classification accuracy of 83.33%, and kappa coefficient of 0.81. We observed that (1) kharif is the major crop in the study area, while rabi mainly grows in areas where external fresh water sources are available (2) a large portion of the area remains fallow for most part of the year as mapped from Sentinel 2A data. There is scope to utilise the fallow lands for multi-cropping with appropriate land and water management, through the government policy prescriptions. With Sentinel-2B sensor now on board, the temporal resolution of satellite-2 (2A and 2B combined) could improve leading to improved classification and upgradation of the algorithm followed here.