Estimation of agricultural burned affected area using NDVI and dNBR satellite-based empirical models

Abstract

One of the major crucial issues that need worldwide attention is open stubble burning, which imposes a variety of adverse impacts on nature and human society, destroying the world's biodiversity. Many earth observation satellites render information to monitor and assess agricultural burning activities. In this study, different remotely sensed data (Sentinel-2A, VIIRS) has been employed to estimate the quantitative measurements of agricultural burned areas of the Purba Bardhaman district from October–December 2018. The multi-temporal image differencing techniques and indices (NDVI, NBR, and dNBR) and VIIRS active fires data (VNP14IMGT) have been utilized to spot agricultural burned areas. In the case of the NDVI technique, a prominent area, 184.82 km2 of agricultural burned area (7.85% of the total agriculture), was observed. The highest (23.04 km2) burned area was observed in the Bhatar block, located in the middle part of the district, and the lowest (0.11 km2) burned area was observed in the Purbasthali-II block, which is located in the eastern part of the district. On the other hand, the dNBR technique revealed that the agricultural burned areas enwrap 8.18% of the total agricultural area, which is 192.45 km2. As per the earlier NDVI technique, the highest agricultural burned areas (24.82 km2) were observed in the Bhatar block, and the lowest (0.13 km2) burn area occurred in the Purbashthali-II block. In both cases, it is observed that agricultural residue burning is high in the western part of the Satgachia block and the adjacent areas of the Bhatar block, which is in the middle part of Purba Bardhaman. The agricultural burned area was extracted using different spectral separability analyses, and the performance of dNBR was the most effective in spectral discrimination of burned and unburned surfaces. This study manifested that agricultural residue burning started in the central part of Purba Bardhaman. Later it spread all over the district due to the trend of early harvesting rice crops in this region. The performance of different indices for mapping the burned areas was evaluated and compared, revealing a strong correlation (R2) = 0.98. To estimate the campaign's effectiveness against the dangerous practice and plan the control of the menace, regular monitoring of crop stubble burning using satellite data is required.