Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city)

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Naseri Rad Soheila; NAGHAVI HAMED; SOOSANI JAVAD; nouredini ahmad reza; Vafaei Sasan

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Journal: JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY Year:2021 | Volume:22 | Issue:11 (102) Page(s): 121-133

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Title

Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city)

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Keywords

Remote sensingQ2

Markov chainQ1

ModelingQ2

Land useQ2

Land coverQ1

Abstract

Background and Objective: Assessing and estimating the high-accuracy transmission potential is an important step in the process of Land use and Land cover changes Modeling and predicting. The aim of this study is to investigate the transmission potential of Land use and Land cover changes using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods. Method: The Land use and Land cover maps for a 30-year period (1985-2015) were prepared using Landsat 5 and 8 satellite imagery. Land use and Land cover transmission potential Modeling was done using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods and effective variables in the process of change. The accuracy of the results obtained from the models was determined by comparing with ground reality map for mentioned year. Findings: The Kappa coefficient of Similarity Weighted Instance based Learning, Logistic regression and Geomod were 0. 84, 0. 76 and 0. 67, respectively. The investigating predicted maps for 2030 prepared by Similarity Weighted Instance based Learning and Markov chain showed that the area of residential areas, gardens and agricultural lands is increasing and the area of bare land, forests, pastures and water resources will have a decrease trend. Discussion and Conclusion: Finally, the results indicate a relatively high accuracy of three methods in estimating the transmission potential for Land use and Land cover changes, but according to the kappa coefficients, the accuracy of Similarity Weighted Instance based Learning method more than the other two methods.

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APA: Copy

Naseri Rad, Soheila, NAGHAVI, HAMED, SOOSANI, JAVAD, nouredini, ahmad reza, & Vafaei, Sasan. (2021). Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city). JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 22(11 (102) ), 121-133. SID. https://sid.ir/paper/409124/en

Vancouver: Copy

Naseri Rad Soheila, NAGHAVI HAMED, SOOSANI JAVAD, nouredini ahmad reza, Vafaei Sasan. Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city). JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY[Internet]. 2021;22(11 (102) ):121-133. Available from: https://sid.ir/paper/409124/en

IEEE: Copy

Soheila Naseri Rad, HAMED NAGHAVI, JAVAD SOOSANI, ahmad reza nouredini, and Sasan Vafaei, “Investigating the transmission potential of land use and land cover using Similarity Weighted Instance based Learning, Logistic regression and Geomod methods (Case study: Bastam basin, Selseleh city),” JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, vol. 22, no. 11 (102) , pp. 121–133, 2021, [Online]. Available: https://sid.ir/paper/409124/en

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