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| Formato: | Artículo científico |
| Lenguaje: | en |
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Universidad Nacional Autónoma de México
2022
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| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=56582396008 https://www.redalyc.org/journal/565/56582396008/ https://www.redalyc.org/journal/565/56582396008/html/ https://www.redalyc.org/journal/565/56582396008/56582396008.epub https://www.redalyc.org/journal/565/56582396008/movil |
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| _version_ | 1866811774261526528 |
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| author | Noredin Rostami |
| author_facet | Noredin Rostami |
| contents | Spatial and temporal changes of land uses and its relationshipwith surface temperature in western Iran Noredin Rostami Hassan Fathizad Biología split fuzzy ARTMAP window algorithm Landsat satellite kappa coefficient A split-window algorithm has been used in the Ilam dam watershed to determine the relationship between land surface temperature (LST) and types of land use. Landsat satellite images of the TM sensor for 1990, 1995, 2000, 2005 and 2010 and Landsat 8 (OLI Sensor) for 2015 and 2018 are used. After geometric and radiometric corrections of satellite images, land use maps are extracted by using the fuzzy ARTMAP method. An accuracy assessment showed that the highest value of the kappa coefficient was 94% with a total accuracy of 0.95 for 2015, and the lowest kappa coefficient value was 87% with a total accuracy of 0.9 for 1990. The high values of these coefficients indicate the acceptable accuracy of using Landsat’s remote sensing data for land use detection. The most important land use change is related to dense forest and sparse forest land uses, with decreases of 20.07 and 17.04%, respectively. The minimum LST measures in 1990, 2010, and 2018 in dense forest are 21.27, 30.55 and 33.82 ºC, respectively. The maximum LSTs for the sparse forest land use in 1990 and 2010 are 52.48 and 56.09, and 56.10 ºC for the dense forest land use in 2018. As a result, the average LST in agricultural lands was lower than in sparse forest and rangeland;, which is mainly due to the high moisture content and the greater evapotranspiration rate. Land use/land cover variations from 1990 to 2018 show that all land uses have experienced an increase in LST. 2022 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56582396008 https://www.redalyc.org/journal/565/56582396008/ https://www.redalyc.org/journal/565/56582396008/html/ https://www.redalyc.org/journal/565/56582396008/56582396008.epub https://www.redalyc.org/journal/565/56582396008/movil 10.20937/ATM.52985 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.4 Vol.35 |
| format | Artículo científico |
| id | redalyc_56582396008 |
| language | en |
| publishDate | 2022 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Spatial and temporal changes of land uses and its relationshipwith surface temperature in western Iran Noredin Rostami Biología split fuzzy ARTMAP window algorithm Landsat satellite kappa coefficient Spatial and temporal changes of land uses and its relationshipwith surface temperature in western Iran Noredin Rostami Hassan Fathizad Biología split fuzzy ARTMAP window algorithm Landsat satellite kappa coefficient A split-window algorithm has been used in the Ilam dam watershed to determine the relationship between land surface temperature (LST) and types of land use. Landsat satellite images of the TM sensor for 1990, 1995, 2000, 2005 and 2010 and Landsat 8 (OLI Sensor) for 2015 and 2018 are used. After geometric and radiometric corrections of satellite images, land use maps are extracted by using the fuzzy ARTMAP method. An accuracy assessment showed that the highest value of the kappa coefficient was 94% with a total accuracy of 0.95 for 2015, and the lowest kappa coefficient value was 87% with a total accuracy of 0.9 for 1990. The high values of these coefficients indicate the acceptable accuracy of using Landsat’s remote sensing data for land use detection. The most important land use change is related to dense forest and sparse forest land uses, with decreases of 20.07 and 17.04%, respectively. The minimum LST measures in 1990, 2010, and 2018 in dense forest are 21.27, 30.55 and 33.82 ºC, respectively. The maximum LSTs for the sparse forest land use in 1990 and 2010 are 52.48 and 56.09, and 56.10 ºC for the dense forest land use in 2018. As a result, the average LST in agricultural lands was lower than in sparse forest and rangeland;, which is mainly due to the high moisture content and the greater evapotranspiration rate. Land use/land cover variations from 1990 to 2018 show that all land uses have experienced an increase in LST. 2022 artículo científico 0187-6236 https://www.redalyc.org/articulo.oa?id=56582396008 https://www.redalyc.org/journal/565/56582396008/ https://www.redalyc.org/journal/565/56582396008/html/ https://www.redalyc.org/journal/565/56582396008/56582396008.epub https://www.redalyc.org/journal/565/56582396008/movil 10.20937/ATM.52985 en http://www.redalyc.org/revista.oa?id=565 Atmósfera application/pdf Universidad Nacional Autónoma de México Atmósfera (México) Num.4 Vol.35 |
| title | Spatial and temporal changes of land uses and its relationshipwith surface temperature in western Iran |
| topic | Biología split fuzzy ARTMAP window algorithm Landsat satellite kappa coefficient |
| url | https://www.redalyc.org/articulo.oa?id=56582396008 https://www.redalyc.org/journal/565/56582396008/ https://www.redalyc.org/journal/565/56582396008/html/ https://www.redalyc.org/journal/565/56582396008/56582396008.epub https://www.redalyc.org/journal/565/56582396008/movil |