A REVIEW of LAND CHANGE MODELLING TECHNIQUES USING REMOTE SENSING and GIS

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Land Use and/or Land Cover Change (LULCC) is characterized as dynamic, widespread, and accelerating process. Due to the significance of such changes, modeling changes in land cover is a high priority area for research thus, monitoring and analyzing LULCC has become one of the most critical studied issues. In effect, maps and datasets which quantify biophysical variables, including LULC, are essential for understanding and modeling complex interactions and impacts between the natural and human environments, from regional to global scales. Furthermore, multi-temporal analyses of LULC provide important insights into long-term trends which serve to identify drivers and determinants of change and prediction of future changes. Remote sensing (RS) is continuously providing valuable data for the earth's surface since 1972, while the power of the Geographic Information System (GIS) in modeling the change provides the suitable platform for handling the digital spatial data necessary for characterizing and predicting these changes and associated impacts. This review deals with the most frequent, up to date methods for modelling the LULCC such as data types, pre-processing of RS data and time-series imagery, and analysing the LULCC using conventional as well as the most developed and cutting-edge algorithms and techniques. The generic flow of the LULCC modeling, challenges, and limitations faced by the researchers over the past five decades were presented and discussed. Indeed, in regions where there is a lack of sufficiently detailed cartographic information, land change modelling using geospatial technologies can be pivotal in providing a basis for planning, management, and conservation initiatives.

Original languageEnglish
Title of host publication42nd Asian Conference on Remote Sensing, ACRS 2021
PublisherAsian Association on Remote Sensing
ISBN (Electronic)9781713843818
Publication statusPublished - 2021
Event42nd Asian Conference on Remote Sensing, ACRS 2021 - Can Tho, Viet Nam
Duration: Nov 22 2021Nov 26 2021

Publication series

Name42nd Asian Conference on Remote Sensing, ACRS 2021

Conference

Conference42nd Asian Conference on Remote Sensing, ACRS 2021
Country/TerritoryViet Nam
CityCan Tho
Period11/22/2111/26/21

Keywords

  • LULC
  • change detection
  • time-series

ASJC Scopus subject areas

  • Information Systems

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