Content area

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.

Details

Title
Analysis of vegetation dynamics using remote sensing and GIS: a case study of Madhya Pradesh, India
Author
Dhar Shashank 1 ; Goswami Suresh 1 ; Sarup Jyoti 1 ; Matin Shafique 2 

 Maulana Azad National Institute of Technology, Department of Civil Engineering, Centre for GIS and Remote Sensing, Bhopal, India (GRID:grid.419487.7) (ISNI:0000 0000 9191 860X) 
 TEAGASC, The Agriculture and Food Development Authority, Dublin, Ireland (GRID:grid.6435.4) (ISNI:0000 0001 1512 9569) 
Pages
1039-1051
Publication year
2021
Publication date
Jun 2021
Publisher
Springer Nature B.V.
ISSN
23636203
e-ISSN
23636211
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2517674538
Copyright
© Springer Nature Switzerland AG 2020.