Plot-level datasets for groundtruthing and satellite detection of tillage operations, Punjab (India)

The intensive, irrigated rice-wheat systems of the northwestern Indo-Gangetic Plains (NW IGP) are associated with the widespread burning of excess rice residue that cannot be otherwise disposed-off within the limited turn-around time. The second-generation direct seeders (SGDS) for wheat sowing, such as Happy Seeder, facilitate sowing under heavy stubble conditions, and thereby avoid the need for residue burning. The objective of the study is to test the causal relationship between Happy Seeder diffusion and reduction in residue burning and, ultimately, reduction in air pollution in the NW IGP. We draw on data from remote sensing, a systematic review of literature, existing primary datasets, and new surveys among farm-households, service providers, and village elders. The estimated reduction in air pollution due to the technology diffusion will then be converted to savings in human health costs. As part of this study, we aim to study the village characteristics and do groundtruthing for remote sensing of plots where SGDS has adopted. The plot level datasets were constructed twice (for 2021 and 2022 Rabi seasons) for identifying tillage types and residue burning through remote sensing. These datasets were not from the same set of farmers, and the plot selection was not random.