Exploring the Impact of Various Spectral Indices on Land Cover Change Detection Using Change Vector Analysis: A Case Study of Crete Island, Greece

Christos Polykretis,Manolis Grillakis,Dimitrios Alexakis

doi:10.3390/rs12020319

Abstract

The main objective of this study was to explore the impact of various spectral indices on the performance of change vector analysis (CVA) for detecting the land cover changes on the island of Crete, Greece, between the last two decades (1999–2009 and 2009–2019). A set of such indices, namely, normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), albedo, bare soil index (BSI), tasseled cap greenness (TCG), and tasseled cap brightness (TCB), representing both the vegetation and soil conditions of the study area, were estimated on Landsat satellite images captured in 1999, 2009, and 2019. Change vector analysis was then applied for five different index combinations resulting to the relative change outputs. The evaluation of these outputs was performed towards detailed land cover maps produced by supervised classification of the aforementioned images. The results from the two examined periods revealed that the five index combinations provided promising performance results in terms of kappa index (with a range of 0.60–0.69) and overall accuracy (with a range of 0.86–0.96). Moreover, among the different combinations, the use of NDVI and albedo were found to provide superior results against the other combinations.

Highlights

Land cover plays a significant role in the terrestrial ecosystem biodiversity, water resources, climate system, and socio-economic sectors
The changes of land cover occurred in a region may have serious environmental and socio-economic impacts
The findings revealed that the selected technique, and land cover change detection, can be affected by the “nature” of indices

Summary

Introduction

Land cover plays a significant role in the terrestrial ecosystem biodiversity, water resources, climate system, and socio-economic sectors. The term “land cover” originally referred to the distribution and type of vegetation (e.g., cropland, forests) that covered a land’s surface [1]. Nowadays, it is considered to describe the general biophysical state of the surface providing information about other aspects of the land such as soils and water [1]. Changes in land cover caused by several natural and anthropogenic forces and represented by relative biophysical changes to the land surface have noticeable impacts on the quality of environmental and ecological systems. Land cover changes can constitute the main indicators of environmental/ecological change at different spatial and temporal scales. The detection and evaluation of these spatio-temporal changes has become a major priority for researchers and policy makers around the world over the last few decades [2]

Objectives

Methods

Results

Discussion

Conclusion