TY - GEN
T1 - A REVIEW of LAND CHANGE MODELLING TECHNIQUES USING REMOTE SENSING and GIS
AU - Dahy, Basam
AU - Issa, Salem
AU - Saleous, Nazmi
N1 - Publisher Copyright:
© ACRS 2021.All right reserved.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - change detection
KW - LULC
KW - time-series
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M3 - Conference contribution
AN - SCOPUS:85127413886
T3 - 42nd Asian Conference on Remote Sensing, ACRS 2021
BT - 42nd Asian Conference on Remote Sensing, ACRS 2021
PB - Asian Association on Remote Sensing
T2 - 42nd Asian Conference on Remote Sensing, ACRS 2021
Y2 - 22 November 2021 through 26 November 2021
ER -