Assessment of the spatio-temporal dynamics of shifting cultivation is important to understand the opportunities for land restoration. The past studies on shifting cultivation mapping of North-East (NE) India lack systematic assessment techniques. We have developed a decision tree-based multi-step threshold (DTMT) method for consistent and long-term mapping of shifting cultivation using Landsat data from 1975 to 2018. Widely used vegetation indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio (NBR) and its relative difference NBR (RdNBR) were integrated with the suitable thresholds in the classification, which yielded overall accuracy above 85%. A significant decrease in total shifting cultivation area was observed with an overall reduction of 75% from 1975–1976 to 2017–2018. The methodology presented in this study is reproducible with minimal inputs and can be useful to map similar changes by optimizing the index threshold values to accommodate relative differences for other landscapes. Furthermore, the crop-suitability maps generated by incorporating climate and soil factors prioritizes suitable land use of shifting cultivation plots. The Google Earth Engine (GEE) platform was employed for automatic mapping of the shifting cultivation areas at desired time intervals for facilitating seamless dissemination of the map products. Besides the novel DTMT method, the shifting cultivation and crop-suitability maps generated in this study, can aid in sustainable land management.

The COVID-19 lock/slow down affected humanity and livelihood, while it showed some positive effects on the environment with improvement in air quality indicators. Though many studies published after COVID-19 first phase lockdown observed reduction in pollutants over India, no studies yet compared the air quality indicators over the two lock/slow down windows during 2020-21. This study reports results of rapid assessment of seven air quality indicators such as Nitrogen dioxide (NO₂), Sulphur dioxide (SO₂), Formaldehyde (HCHO), Methane (CH₄), Carbon monoxide (CO), Aerosol (Ultraviolet Aerosol Index, UVAI), and Ozone (O₃) for the past three years on monthly time scale using TROPOMI (Tropospheric Monitoring Instrument) data on GEE (Google Earth Engine) platform over India, with focus on the Gangetic plain, an air pollution hotspot. Significant reduction in NO₂, SO₂, HCHO and Absorbing Aerosol Index (AAI) was observed during March-May 2020 as compared to the same period in 2019, while the levels of NO₂, SO₂, HCHO and CO increased significantly in 2021 compared to March-May 2020. This suggests that COVID-19 lock/slow down in 2020 played a significant role in improving air quality indicators, while the relaxation in 2021 has led to detoriation, compared to 2020. The pyrogenic (forest fire and slash and burn agriculture) and agricultural (wet crop) sources were identified to contaminate the expression of slow/lock down effects on air quality indicators such as HCHO, CO and CH₄ over India.