Analysis of vegetation dynamics using remote sensing and GIS: a case study of Madhya Pradesh, India
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ORIGINAL ARTICLE
Analysis of vegetation dynamics using remote sensing and GIS: a case study of Madhya Pradesh, India Shashank Dhar1 · Suresh Goswami1 · Jyoti Sarup1 · Shafique Matin2 Received: 20 June 2020 / Accepted: 6 October 2020 © Springer Nature Switzerland AG 2020
Abstract This paper is aimed to study the correct growth cycle of two staple foods (i.e., wheat and rice), of Madhya Pradesh state of India through an approach of vegetation dynamics which focuses on analysing various parameters, such as rainfall, soil temperature, soil moisture, and crop growth trend over time using temporal data based on regression analysis to generate crop maps. This paper analyses various stages of growth for two major staple crops in Madhya Pradesh (M.P.) region. Wheat and rice farming in M.P. is facing issues related to climate change, drought, fertilizer application, low selling prices, and other. Nature of growth and effect of various parameters like rainfall, temperature, was studied and a proper graph analysis was done for a better understanding of plant growth, and generation of various phenological maps. In multiple regression analysis, R2 value of 0.24 and 0.45 was found highest for HH and VV polarization for wheat and rice, respectively. This means that multi-linear regression for HH and VV explains 24% and 45% for wheat and rice, respectively. Analysis and simulation of crop phenology was done by using the trend analysis approach with the help of the various graphs values that explains the different stages of crop growth and the effect of changing temperature and rainfall over the growth of the crops, Use of ArcGIS 10.5 software simplifies the study process and helped in developing a better understanding. Keywords Dielectric constant · Phenological maps · Time-series graph · Vegetation dynamics
Introduction In the world full of challenges, growing demands for food and technological developments it becomes a necessity to use state-of-the-art modern developments in the field of agriculture for real-time access to the field data so that instant and accurate decisions can be made to maximize our yield at a minimum cost and effort. Crop phenology application requires relatively high temporal resolution of remote sensing data, as well as high spatial resolution (Inoue and Sakaiya 2013). Microwave remote sensing has great potential in agricultural application due to its unique target interaction as well as all-weather capability. Vegetation dynamics reflect net effects of many factors including * Shashank Dhar [email protected] 1
Department of Civil Engineering, Centre for GIS and Remote Sensing, Maulana Azad National Institute of Technology, Bhopal, M.P., India
TEAGASC, The Agriculture and Food Development Authority, Dublin, Ireland
2
climate, abiotic landscape, biotic interactions, and distortion history. To map regional plant suitability, a phenological model is required to estimate growing time from seed to maturity. The products of wheat are mainly consumed by the urban population and by the
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