Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Exploring NDVI Variation across Seasons in Parbhani, Maharashtra: A Remote Sensing Perspective

Version 1 : Received: 8 January 2024 / Approved: 15 January 2024 / Online: 15 January 2024 (13:39:00 CET)

How to cite: Dhavan, K.; Jagtap, M.; Shinde, G.; Palve, M.; Hivre, A. Exploring NDVI Variation across Seasons in Parbhani, Maharashtra: A Remote Sensing Perspective. Preprints 2024, 2024011128. https://doi.org/10.20944/preprints202401.1128.v1 Dhavan, K.; Jagtap, M.; Shinde, G.; Palve, M.; Hivre, A. Exploring NDVI Variation across Seasons in Parbhani, Maharashtra: A Remote Sensing Perspective. Preprints 2024, 2024011128. https://doi.org/10.20944/preprints202401.1128.v1

Abstract

The proposed research study explore the decision tool for cropwise variability of NDVI using RS techniques and GIS tool as a crucial indicators for monitoring vegetation status.A small case study for Parbhani district of Maharashtra, India was conducted using Landsat-9 satellite images of the Rabi season in the year 2022-23 were processed using ArcGIS 10.7 software to derive the NDVI values. During the analysis, the maximum NDVI in the study area was recorded at 0.5857 on February 03, 2023, while the minimum was observed as -0.1018 on February 19, 2023. For specific crops, the average NDVI ranged from 0.1183 to 0.3189 for wheat, 0.1679 to 0.2891 for jowar, and 0.1163 to 0.3367 for gram. The mean NDVI values for wheat, jowar, and gram crops during the Rabi season of 2022-23 were 0.218, 0.219, and 0.217, respectively.Furthermore, the average NDVI values exhibited an increasing from the initial stage to the mid-crop growth stage, followed by a decrease during the end-season stage for wheat, jowar, and gram crops. Interestingly, the mean NDVI values of major Rabi crops, wheat, jowar, and gram for the year 2022-23, is approximately similar to the mean NDVI values observed for of year 2022-23.

Keywords

Temporal variation; Vegetation Index; NDVI; Landsat 9

Subject

Environmental and Earth Sciences, Remote Sensing

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