基于卫星影像的土地覆被分类与森林变化分析——以伊朗扎格罗斯山Dehdez地区为例

A. Torahi, S. C. Rai
{"title":"基于卫星影像的土地覆被分类与森林变化分析——以伊朗扎格罗斯山Dehdez地区为例","authors":"A. Torahi, S. C. Rai","doi":"10.4236/jgis.2011.31001","DOIUrl":null,"url":null,"abstract":"The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in mountainous areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) and ASTER data in Zagros mountains of Iran for 1990, 1998, and 2006.Land-use/cover mapping is achieved through interpreta-tion of Landsat TM satellite images of 1990, 1998 and TERRA-ASTER image of 2006 using ENVI 4.3. Based on the Anderson land-use/cover classification system, the land-use and land-covers are classified as forest land, rangeland, water bodies, agricultural land and residential land. The unsupervised image classifi-cation method carried out prior to field visit, in order to determine strata for ground truth. Fieldwork carried out to collect data for training and validating land-use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land-use/cover class. The land-use/cover maps of 1990, 1998 and 2006 were produced by using supervised image classification technique based on the Maxi-mum Likelihood Classifier (MLC) and 132 training samples. Error matrices as cross-tabulations of the mapped class vs. the reference class were used to assess classification accuracy. Overall accuracy, user’s and producer’s accuracies, and the Kappa statistic were then derived from the error matrices. A multi-date post-classification comparison change detection algorithm was used to determine changes in land cover in three intervals, 1990–1998, 1998–2006 and 1990–2006. To evaluate the change maps for the 1990 to 2006 interval, we randomly sampled the areas that classified as change and no-change and determined whether they were correctly classified. The maps showed that between 1990 and 2006 the amount of forest land de-creased from 67% to 38.5% of the total area, while rangelands, agriculture, settlement and surface water in-creased from 30.8% to 45%, 1.2% to 7.0%, 0.3% to 7.5% and 0.6% to 1.8%, respectively. The area was dominated by 35.9%, 28.9% and 29.3% dense forest, 42.2%, 46.4% and 43.2% open forest and 21.9%, 24.8% and 27.5% degraded forest in 1990, 1998 and 2006, respectively. During 16 years span period (1990-2006) about 10170.3 ha, 2963.4 ha, 351.7 ha and 3039.2 ha of forest lands were converted to range-land, agriculture, water body and settlement. The overall five-class classification accuracies averaged 78.6% for the three years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, reached to 80.1%. The results quantify the land cover change patterns in the Zagrous highlands and demonstrate the potential of multitemporal Landsat and ASTER data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.","PeriodicalId":93313,"journal":{"name":"Journal of geographic information system","volume":"10 1","pages":"1-11"},"PeriodicalIF":0.0000,"publicationDate":"2011-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"59","resultStr":"{\"title\":\"Land Cover Classification and Forest Change Analysis, Using Satellite Imagery-A Case Study in Dehdez Area of Zagros Mountain in Iran\",\"authors\":\"A. Torahi, S. C. Rai\",\"doi\":\"10.4236/jgis.2011.31001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in mountainous areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) and ASTER data in Zagros mountains of Iran for 1990, 1998, and 2006.Land-use/cover mapping is achieved through interpreta-tion of Landsat TM satellite images of 1990, 1998 and TERRA-ASTER image of 2006 using ENVI 4.3. Based on the Anderson land-use/cover classification system, the land-use and land-covers are classified as forest land, rangeland, water bodies, agricultural land and residential land. The unsupervised image classifi-cation method carried out prior to field visit, in order to determine strata for ground truth. Fieldwork carried out to collect data for training and validating land-use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land-use/cover class. The land-use/cover maps of 1990, 1998 and 2006 were produced by using supervised image classification technique based on the Maxi-mum Likelihood Classifier (MLC) and 132 training samples. Error matrices as cross-tabulations of the mapped class vs. the reference class were used to assess classification accuracy. Overall accuracy, user’s and producer’s accuracies, and the Kappa statistic were then derived from the error matrices. A multi-date post-classification comparison change detection algorithm was used to determine changes in land cover in three intervals, 1990–1998, 1998–2006 and 1990–2006. To evaluate the change maps for the 1990 to 2006 interval, we randomly sampled the areas that classified as change and no-change and determined whether they were correctly classified. The maps showed that between 1990 and 2006 the amount of forest land de-creased from 67% to 38.5% of the total area, while rangelands, agriculture, settlement and surface water in-creased from 30.8% to 45%, 1.2% to 7.0%, 0.3% to 7.5% and 0.6% to 1.8%, respectively. The area was dominated by 35.9%, 28.9% and 29.3% dense forest, 42.2%, 46.4% and 43.2% open forest and 21.9%, 24.8% and 27.5% degraded forest in 1990, 1998 and 2006, respectively. During 16 years span period (1990-2006) about 10170.3 ha, 2963.4 ha, 351.7 ha and 3039.2 ha of forest lands were converted to range-land, agriculture, water body and settlement. The overall five-class classification accuracies averaged 78.6% for the three years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, reached to 80.1%. The results quantify the land cover change patterns in the Zagrous highlands and demonstrate the potential of multitemporal Landsat and ASTER data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.\",\"PeriodicalId\":93313,\"journal\":{\"name\":\"Journal of geographic information system\",\"volume\":\"10 1\",\"pages\":\"1-11\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"59\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of geographic information system\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4236/jgis.2011.31001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of geographic information system","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/jgis.2011.31001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 59

摘要

准确和及时地提供描述土地资源的性质和范围及其随时间变化的信息的重要性正在增加,特别是在山区。我们开发了一种方法,利用1990年、1998年和2006年伊朗Zagros山区的多时相Landsat Thematic Mapper (TM)和ASTER数据绘制和监测土地覆盖变化。土地利用/覆盖制图是通过使用ENVI 4.3对1990年、1998年的Landsat TM卫星图像和2006年的TERRA-ASTER图像进行解译而实现的。基于Anderson土地利用/覆被分类系统,将土地利用/覆被分为林地、牧场、水体、农用地和居住用地。在实地考察之前进行无监督图像分类方法,以确定地层的地面真相。开展实地工作,收集数据,用于培训和验证2006年卫星图像的土地利用/覆盖解译,以及定性描述每个土地利用/覆盖类别的特征。采用基于最大似然分类器(MLC)和132个训练样本的监督图像分类技术,生成了1990年、1998年和2006年的土地利用/覆盖地图。错误矩阵作为映射类与参考类的交叉表用于评估分类准确性。然后从误差矩阵中得出总体精度、用户和生产者的精度以及Kappa统计量。采用多数据分类后对比变化检测算法确定了1990—1998年、1998—2006年和1990—2006年三个区间的土地覆盖变化。为了评估1990 - 2006年期间的变化图,我们随机抽取了被分类为变化和无变化的区域,并确定它们的分类是否正确。地图显示,1990年至2006年间,林地面积从占总面积的67%减少到38.5%,而牧场、农田、居民点和地表水面积分别从30.8%增加到45%、1.2%增加到7.0%、0.3%增加到7.5%和0.6%增加到1.8%。1990年、1998年和2006年,密林占35.9%、28.9%和29.3%,开阔林占42.2%、46.4%和43.2%,退化林占21.9%、24.8%和27.5%。在16年间(1990-2006),分别有10170.3 ha、2963.4 ha、351.7 ha和3039.2 ha林地被转化为牧地、农业、水体和聚落。总体五类分类准确率在三年内平均为78.6%。利用分类后变化检测方法生成的土地覆被变化图的总体精度达到80.1%。结果量化了扎格鲁高原的土地覆盖变化模式,并展示了多时相Landsat和ASTER数据的潜力,可以提供一种准确、经济的方法来绘制和分析土地覆盖随时间的变化,可作为土地管理和政策决策的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Land Cover Classification and Forest Change Analysis, Using Satellite Imagery-A Case Study in Dehdez Area of Zagros Mountain in Iran
The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in mountainous areas. We have developed a methodology to map and monitor land cover change using multitemporal Landsat Thematic Mapper (TM) and ASTER data in Zagros mountains of Iran for 1990, 1998, and 2006.Land-use/cover mapping is achieved through interpreta-tion of Landsat TM satellite images of 1990, 1998 and TERRA-ASTER image of 2006 using ENVI 4.3. Based on the Anderson land-use/cover classification system, the land-use and land-covers are classified as forest land, rangeland, water bodies, agricultural land and residential land. The unsupervised image classifi-cation method carried out prior to field visit, in order to determine strata for ground truth. Fieldwork carried out to collect data for training and validating land-use/cover interpretation from satellite image of 2006, and for qualitative description of the characteristics of each land-use/cover class. The land-use/cover maps of 1990, 1998 and 2006 were produced by using supervised image classification technique based on the Maxi-mum Likelihood Classifier (MLC) and 132 training samples. Error matrices as cross-tabulations of the mapped class vs. the reference class were used to assess classification accuracy. Overall accuracy, user’s and producer’s accuracies, and the Kappa statistic were then derived from the error matrices. A multi-date post-classification comparison change detection algorithm was used to determine changes in land cover in three intervals, 1990–1998, 1998–2006 and 1990–2006. To evaluate the change maps for the 1990 to 2006 interval, we randomly sampled the areas that classified as change and no-change and determined whether they were correctly classified. The maps showed that between 1990 and 2006 the amount of forest land de-creased from 67% to 38.5% of the total area, while rangelands, agriculture, settlement and surface water in-creased from 30.8% to 45%, 1.2% to 7.0%, 0.3% to 7.5% and 0.6% to 1.8%, respectively. The area was dominated by 35.9%, 28.9% and 29.3% dense forest, 42.2%, 46.4% and 43.2% open forest and 21.9%, 24.8% and 27.5% degraded forest in 1990, 1998 and 2006, respectively. During 16 years span period (1990-2006) about 10170.3 ha, 2963.4 ha, 351.7 ha and 3039.2 ha of forest lands were converted to range-land, agriculture, water body and settlement. The overall five-class classification accuracies averaged 78.6% for the three years. The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, reached to 80.1%. The results quantify the land cover change patterns in the Zagrous highlands and demonstrate the potential of multitemporal Landsat and ASTER data to provide an accurate, economical means to map and analyze changes in land cover over time that can be used as inputs to land management and policy decisions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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