{"title":"基于遥感和Gis技术的农业土地流失的多时相检测,shananderman,伊朗","authors":"Fatemeh Rahimi-Ajdadi, M. Khani","doi":"10.2478/ata-2022-0011","DOIUrl":null,"url":null,"abstract":"Abstract Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on agricultural land changes for the period of 1990–2020 at Shanderman, Iran, employed Landsat 5 TM, and Landsat 8 OLI/TIRS images. A supervised maximum likelihood classification technique was utilized for the purposes of satellite data classification to four classes: agricultural land, forest, grassland, and built-up area. Results of land change modeller showed that, during the last three decades, agricultural land, grassland and forest decreased by 42.81%, 35.50%, and 4.05%, respectively, while built-up area increased by 361.23%. Most of the losses in agriculture areas occurred in 1990–2011 (44.64%). The predominant losses in 2011–2020 belonged to the forestland (12.47%), making them approx. 3.44 times higher than in 1990–2011. The results highlight the need for serious attention to the deforestation phenomenon, which leads to the conversion of forest into agricultural and built-up areas.","PeriodicalId":43089,"journal":{"name":"Acta Technologica Agriculturae","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-Temporal Detection of Agricultural Land Losses Using Remote Sensing and Gis Techniques, Shanderman, Iran\",\"authors\":\"Fatemeh Rahimi-Ajdadi, M. Khani\",\"doi\":\"10.2478/ata-2022-0011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on agricultural land changes for the period of 1990–2020 at Shanderman, Iran, employed Landsat 5 TM, and Landsat 8 OLI/TIRS images. A supervised maximum likelihood classification technique was utilized for the purposes of satellite data classification to four classes: agricultural land, forest, grassland, and built-up area. Results of land change modeller showed that, during the last three decades, agricultural land, grassland and forest decreased by 42.81%, 35.50%, and 4.05%, respectively, while built-up area increased by 361.23%. Most of the losses in agriculture areas occurred in 1990–2011 (44.64%). The predominant losses in 2011–2020 belonged to the forestland (12.47%), making them approx. 3.44 times higher than in 1990–2011. The results highlight the need for serious attention to the deforestation phenomenon, which leads to the conversion of forest into agricultural and built-up areas.\",\"PeriodicalId\":43089,\"journal\":{\"name\":\"Acta Technologica Agriculturae\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Technologica Agriculturae\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/ata-2022-0011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AGRICULTURE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Technologica Agriculturae","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ata-2022-0011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
Multi-Temporal Detection of Agricultural Land Losses Using Remote Sensing and Gis Techniques, Shanderman, Iran
Abstract Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on agricultural land changes for the period of 1990–2020 at Shanderman, Iran, employed Landsat 5 TM, and Landsat 8 OLI/TIRS images. A supervised maximum likelihood classification technique was utilized for the purposes of satellite data classification to four classes: agricultural land, forest, grassland, and built-up area. Results of land change modeller showed that, during the last three decades, agricultural land, grassland and forest decreased by 42.81%, 35.50%, and 4.05%, respectively, while built-up area increased by 361.23%. Most of the losses in agriculture areas occurred in 1990–2011 (44.64%). The predominant losses in 2011–2020 belonged to the forestland (12.47%), making them approx. 3.44 times higher than in 1990–2011. The results highlight the need for serious attention to the deforestation phenomenon, which leads to the conversion of forest into agricultural and built-up areas.
期刊介绍:
Acta Technologica Agriculturae is an international scientific double-blind peer reviewed journal focused on agricultural engineering. The journal is multidisciplinary and publishes original research and review papers in engineering, agricultural and biological sciences, and materials science. Aims and Scope Areas of interest include but are not limited to: agricultural and biosystems engineering; machines and mechanization of agricultural production; information and electrical technologies; agro-product and food processing engineering; physical, chemical and biological changes in the soil caused by tillage and field traffic, soil working machinery and terramechanics; renewable energy sources and bioenergy; rural buildings; related issues from applied physics and chemistry, ecology, economy and energy.