Spatio-temporal classification and prediction of land use and land cover change for the Vembanad Lake system, Kerala: a machine learning approach.

Parthasarathy Kulithalai Shiyam Sundar,Paresh Chandra Deka

doi:10.1007/s11356-021-17257-0

Abstract

Land use and land cover (LULC) change has become a critical issue for decision planners and conservationists due to inappropriate growth and its effect on natural ecosystems. As a result, the goal of this study is to identify the LULC for the Vembanad Lake system (VLS), Kerala, in the short term, i.e., within a decade, utilizing three standard machine learning approaches, random forest (RF), classification and regression trees (CART), and support vector machines (SVM), on the Google Earth Engine (GEE) platform. When comparing the three techniques, SVM performed poor at an average accuracy of around 82.5%, CART being the next at accuracy of 87.5%, and the RF model being good at the average of 89.5%. The RF outperformed the SVM and CART in almost identical spectral classes such as barren land and built-up areas. As a result, RF-classified LULC is considered to predict the spatio-temporal distribution of LULC transition analysis for 2035 and 2050. The study was conducted in Idrisi TerrSet software using the cellular automata (CA)-Markov chain analysis. The model's efficiency is evaluated by comparing the projected 2019 image to the actual 2019 classified image. The efficiency was good with more than 94.5% accuracy for the classes except for barren land, which might have resulted from the recent natural calamities and the accelerated anthropogenic activity in the area.

Highlights

The natural and anthropogenic activities worldwide influence the land cover, resulting in modifying its landscapes and the subsequent dynamics of natural processes (Silva et al 2020).Monitoring and assessing urban growth aid in the planning and utilization of natural resources for the foreseeable future
For providing a better region of interest (ROI), 15-35 pixels in each sample were selected
Since the study area was seriously impacted by the Kerala floods in 2018 and 2019, this study will help society understand the changes in the land use and land cover (LULC) due to anthropogenic and flood-related factors

Summary

Introduction

The natural and anthropogenic activities worldwide influence the land cover, resulting in modifying its landscapes and the subsequent dynamics of natural processes (Silva et al 2020).Monitoring and assessing urban growth aid in the planning and utilization of natural resources for the foreseeable future. Anthropogenic processes have altered almost half of the Earth's land surfaces (Tayyebi and Pijanowski 2014). These changes are called land use and land cover (LULC). Over the last few decades, economic prosperity and population growth have resulted in unplanned urbanization and industrialization to meet livelihood and job needs. These enormous increases in need boosted the demand for critical infrastructures such as water supplies, sewage services, and recreational activities. The complex interaction of the factors like policy management, human needs, environment, culture, and economics results in changing LULC

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