"Yield Prediction Dataset for Pearl Millet (Bajra) in Rajasthan with Remote Sensing and Environment Data"

"Nowadays, researchers across various domains suffer from insufficient data availability for conducting thorough investigations. Also, the existing data has already been extensively examined and leveraged in previous studies, limiting its potential for generating novel insights. Considering this scenario, an idea of developing a dataset containing data from multiple sources is implemented. This dataset provides a comprehensive and composite information for Peral Millet (Bajra) Yield Prediction in Rajasthan region of India that consists of four types of data from four distinct sources. The first type of data is Bajra yield statistics, taken from Area and Production Statistics, Ministry of Agriculture and Farmers Welfare from 2013 to 2023. The subsequent data is Remote sensing data; Multispectral satellite images are collected from Landsat 8 and Landsat 9 (Collection 2 Level 2 Surface Reflectance Data), for the period of 2013 to 2023 from USGS Earth Explorer. This data has the spatial and temporal resolution of 30m and 16 days; respectively. Images are pre-processed for atmospherically correction, cloud-masking, mosaicking and clipping as per district boundaries. Seven Vegetation Indices (VI\u2019s), namely NDVI, EVI, NDWI, SAVI, GNDVI, CVI and GCI are extracted through red, green, blue, NIR and SWIR spectral bands. Next is climate data having the variables collected from IMD-Pune (Climate Research & Services, Pune) and India-WRIS (Ministry of Jal Shakti, Department of Water Resources, RD & GR, Government of India). The last type of data is Soil data, collected from India-WRIS (Ministry of Jal Shakti, Department of Water Resources, RD & GR, Government of India). This consolidated dataset offers an in-depth analysis of ground data, remote sensing data, climate data and soil data for Bajra cultivation during the Kharif season in Rajasthan, India."