Drought Monitoring & Changes in the Vegetation Cover of Aurangabad Region, Maharashtra Over Last Two Decades: A Comparative Study of Remote Sensing Indices VCI and SVI Using Time Series MODIS Data Product MOD13Q6

DOI

10.2991/978-94-6463-136-4_24How to use a DOI?

Keywords

multispectral; vegetation condition index; standard vegetation index

Abstract

Aurangabad district is part of Marathwada region of Maharashtra, India. The region suffers with frequent drought occurrences resulting in substantial crop yield losses. The times series analysis of the satellite imagery is helpful in monitoring the short term and long-term changes and understand the reasons for recurrent drought occurrences. In this study we analyze time series multispectral data products obtained from MODIS the spectroradiometer on board Terra. The dataset of MOD13Q6 (2001–2020) 250 m for the Aurangabad region is investigated using remote sensing indices VCI and SVI. The statistical tools and techniques were implemented to understand if there is any drought recurrence pattern over the years and then time series regression analysis of both the VCI and SVI indices were done to find out which remote sensing index gives better results. After comparing the results of two indices it is confirmed that though both indices gave same results for some statistical tests. The Generalized Linear Regression analysis performance of SVI is better and can be used for predicting the vegetation condition to some extent. Although the accuracy of such prediction is low because of the unpredictability of the climatic variables and the changing dynamics of the land use due to urbanization and human induced factors. This study was also useful in understanding the limitations of Satellite imagery and vegetation indices.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Rashmi Nitwane
AU  - Vaishali Bhagile
AU  - Ratnadeep Deshmukh
PY  - 2023
DA  - 2023/05/01
TI  - Drought Monitoring & Changes in the Vegetation Cover of Aurangabad Region, Maharashtra Over Last Two Decades: A Comparative Study of Remote Sensing Indices VCI and SVI Using Time Series MODIS Data Product MOD13Q6
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 260
EP  - 275
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_24
DO  - 10.2991/978-94-6463-136-4_24
ID  - Nitwane2023
ER  -