An approach to estimate the instability, growth rate and decomposition analysis of mango crop productivity through Landsat-8 satellite images

Abstract

One of the primary fruit crops in Uttar Pradesh (UP) State is the mango (Mangifera Indica L.), and its production, as well as mango-growing areas, has considerably increased over time. Precise and appropriate information about mango crop area and output can be used by other stakeholders and governments to adapt their profitable policies. The primary issue is that some areas’ lower growth rates for the mango fruit crop may be due to the reason that improved varieties are not being adopted as widely and more advanced management methods are not used. In this paper, mango crop area, production, and productivity are estimated for two regions in the Indian state of UP that produce mangoes viz., Lucknow and Meerut by using Landsat-8 images from 2013-14 to 2020-21. By using a knowledge-based decision tree classifier (DTC), satellite images from both districts are classified for mango crop region identification and acreage estimation. Additionally, the estimated mango crop areas are used to determine the compound growth rates (CGR), decomposition analysis, and coefficient of variance (CV). A thorough analysis reveals that Meerut district had the greatest levels of instability in the mango fruit crop area, at 6.39%, and growth rate, at 2.59. A decomposition analysis reveals that the largest contributor to rising mango output in both districts is the area dedicated to growing mangoes. Therefore, it is found that increasing the production and area of the mango crop will improve yields in both districts. The government and policymakers may find this research helpful in their planning to expand mango crop areas.