Land Use Change Monitoring and Modelling using GIS and Remote Sensing Data for Watershed Scale in Thailand

P. Chaikaew
{"title":"Land Use Change Monitoring and Modelling using GIS and Remote Sensing Data for Watershed Scale in Thailand","authors":"P. Chaikaew","doi":"10.5772/INTECHOPEN.79167","DOIUrl":null,"url":null,"abstract":"Landsat 7 Enhanced Thematic Mapper (ETM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images obtained in 1991, 2005 and 2014 with maps, and field survey data were used to classify land use and land cover (LULC) changes over 23 years and predict soil erosion risk locations in the Khlong Kui watershed (73,700 ha), Prachuap Khiri Khan province, Thailand. Classified images together with soil features, slope and rainfall data were used to identify potential risk areas of soil erosion. Based on field check data, the overall classification accuracy was accessed from random samples that resulted as 80% for 1991, 83% for 2005 and 86% for 2014. The study discovered that rice field and rangeland increased by 1.12 and 2.81%, respectively, deciduous forest, and on the other hand, it decreased by 8.28%. GIS analysis identified the potential risk areas of soil erosion as 46,431 ha (0.63%) at very high risk.","PeriodicalId":270958,"journal":{"name":"Land Use - Assessing the Past, Envisioning the Future","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Land Use - Assessing the Past, Envisioning the Future","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5772/INTECHOPEN.79167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Landsat 7 Enhanced Thematic Mapper (ETM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images obtained in 1991, 2005 and 2014 with maps, and field survey data were used to classify land use and land cover (LULC) changes over 23 years and predict soil erosion risk locations in the Khlong Kui watershed (73,700 ha), Prachuap Khiri Khan province, Thailand. Classified images together with soil features, slope and rainfall data were used to identify potential risk areas of soil erosion. Based on field check data, the overall classification accuracy was accessed from random samples that resulted as 80% for 1991, 83% for 2005 and 86% for 2014. The study discovered that rice field and rangeland increased by 1.12 and 2.81%, respectively, deciduous forest, and on the other hand, it decreased by 8.28%. GIS analysis identified the potential risk areas of soil erosion as 46,431 ha (0.63%) at very high risk.
基于GIS和遥感数据的泰国流域土地利用变化监测与建模
利用1991年、2005年和2014年获得的Landsat 7增强型专题成像仪(ETM)、Landsat 8操作土地成像仪(OLI)和热红外传感器(TIRS)图像与地图以及野外调查数据,对泰国Prachuap Khiri Khan省Khlong Kui流域(73,700公顷)23年来的土地利用和土地覆盖(LULC)变化进行了分类,并预测了土壤侵蚀风险位置。分类图像与土壤特征、坡度和降雨数据一起用于识别土壤侵蚀的潜在风险区域。根据现场检查数据,从随机样本中获得总体分类精度,1991年为80%,2005年为83%,2014年为86%。研究发现,稻田和草地面积分别增加了1.12%和2.81%,落叶林面积则减少了8.28%。地理信息系统分析确定土壤侵蚀的潜在风险区域为46,431公顷(0.63%),风险非常高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信