%0 Journal Article
%T Investigating the effectiveness of Random Tree Algorithm (RTC), Maximum Likelihood (MLC) and Support Vector Machine (SVM) models in detecting the changes in the water area of Lake Neor and the effect of these changes on the surface temperature
%J Hydrogeomorphology
%I University of Tabriz
%Z 2383-3254
%D 2023
%\ 11/26/2023
%V
%N
%P -
%! Investigating the effectiveness of Random Tree Algorithm (RTC), Maximum Likelihood (MLC) and Support Vector Machine (SVM) models in detecting the changes in the water area of Lake Neor and the effect of these changes on the surface temperature
%K random Tree
%K Maximum likelihood
%K Support Vector Machine
%K LST
%K Neor lake
%R 10.22034/hyd.2023.58342.1706
%X Changes in land cover and land use due to human activities have left adverse effects on the environment. The eastern regions of Ardabil province are a clear example of this phenomenon. The purpose of this research is to analyze spatial and temporal changes in land cover and land use and its effects on the temperature of the surface of the earth in Lake Neor. To estimate land use and land cover, random forest models (RTC), maximum likelihood model (MLC) and support vector machine (SVM) were used and the efficiency of each was estimated by the Kappa coefficient and it was observed that the SVM model has the highest Kappa coefficient (0.87) Bands 6, 5 and 10 of Landsat 8 were also used to extract the LST index, and it was observed that the western part of the lake faced an increase in the temperature of the earth's surface. During the time period of 2002, 2013 and 2022, significant changes were observed in the water area of Neor Lake and its nearby vegetation. Barren lands had the largest extent in all studied periods. Vegetation has increased by 1.04 square kilometers based on SVM model. The surface area of the lake was estimated as 3.19 square kilometers based on the MLC model in 2002. The area of the water zone in the MLC model has decreased by 1.56 square kilometers between 2002 and 2022, and this decrease is 0.67 and 0.69 square kilometers for the RTC and SVM models, respectively.
%U