MONITORING AND PREDICTING LAND USE-LAND COVER (LULC) CHANGES WITHIN AND AROUND KRAU WILDLIFE RESERVE (KWR) PROTECTED AREA IN MALAYSIA USING MULTI-TEMPORAL LANDSAT DATA

Q4 Social Sciences
J. Gambo, H. Shafri, N. S. N. Shaharum, F. A. Z. Abidin, Mohd Faid Abdul Rahman
{"title":"MONITORING AND PREDICTING LAND USE-LAND COVER (LULC) CHANGES WITHIN AND AROUND KRAU WILDLIFE RESERVE (KWR) PROTECTED AREA IN MALAYSIA USING MULTI-TEMPORAL LANDSAT DATA","authors":"J. Gambo, H. Shafri, N. S. N. Shaharum, F. A. Z. Abidin, Mohd Faid Abdul Rahman","doi":"10.14710/GEOPLANNING.5.1.17-34","DOIUrl":null,"url":null,"abstract":"Natural and anthropogenic activities surrounding a Protected Area (PA) may cause its natural area to change in terms of Land Use-Land Cover (LULC). Thus, there is need of environmental change monitoring within and around PA because of its significant values to ecosystem at conservation scales. Effects and influences of local community within and around PA turn into the major problems for natural resource and conservations management as well as environmental impact assessment. Ascertaining the complex interface in relations to changes and its driving factors over period of time within and around PA is significant in order to predict future LULC changes, build alternative scenarios and serve as tools for decision making.  The main objective of this work was to evaluate temporal change detection and prediction of LULC as well as the trends of changes from 1989 to 2016 within and around Krau Wildlife Reserve (KWR).  The cloud issues were mitigated by producing cloud free image and object-based image analysis (OBIA) was adopted after a comparison with pixel-based analysis for overall accuracy and kappa statistics. The comparison of classified maps had produced a satisfactory results of overall accuracies of 91%, 86% and 90% for 1989, 2004 and 2016 respectively. The natural/dense forest between periods of 1989-2016 was decreased whereas built-up and agricultural/sparse forest were increased. The simulation model of Land Change Modeler (LCM) was utilized with digital elevation model (DEM) and past LULC maps to project future LULC pattern using Markov chain. The predicted map trend showed an increase of dense forest converted to agricultural/sparse forest in the north-western, and urban/built-up in east-southern part of KWR. The study is important for the conservation of habitat species and monitoring the current status of the KWR","PeriodicalId":30789,"journal":{"name":"Geoplanning Journal of Geomatics and Planning","volume":"5 1","pages":"17-34"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.14710/GEOPLANNING.5.1.17-34","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoplanning Journal of Geomatics and Planning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/GEOPLANNING.5.1.17-34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 17

Abstract

Natural and anthropogenic activities surrounding a Protected Area (PA) may cause its natural area to change in terms of Land Use-Land Cover (LULC). Thus, there is need of environmental change monitoring within and around PA because of its significant values to ecosystem at conservation scales. Effects and influences of local community within and around PA turn into the major problems for natural resource and conservations management as well as environmental impact assessment. Ascertaining the complex interface in relations to changes and its driving factors over period of time within and around PA is significant in order to predict future LULC changes, build alternative scenarios and serve as tools for decision making.  The main objective of this work was to evaluate temporal change detection and prediction of LULC as well as the trends of changes from 1989 to 2016 within and around Krau Wildlife Reserve (KWR).  The cloud issues were mitigated by producing cloud free image and object-based image analysis (OBIA) was adopted after a comparison with pixel-based analysis for overall accuracy and kappa statistics. The comparison of classified maps had produced a satisfactory results of overall accuracies of 91%, 86% and 90% for 1989, 2004 and 2016 respectively. The natural/dense forest between periods of 1989-2016 was decreased whereas built-up and agricultural/sparse forest were increased. The simulation model of Land Change Modeler (LCM) was utilized with digital elevation model (DEM) and past LULC maps to project future LULC pattern using Markov chain. The predicted map trend showed an increase of dense forest converted to agricultural/sparse forest in the north-western, and urban/built-up in east-southern part of KWR. The study is important for the conservation of habitat species and monitoring the current status of the KWR
利用多时相陆地卫星数据监测和预测马来西亚克劳野生动物保护区及其周围的土地利用-土地覆盖(lulc)变化
保护区(PA)周围的自然和人为活动可能会导致其自然面积在土地利用-土地覆盖方面发生变化。因此,由于PA在保护范围内对生态系统具有重要价值,因此需要对其内部和周围的环境变化进行监测。PA内部和周围的当地社区的影响和影响已成为自然资源和自然保护管理以及环境影响评估的主要问题。为了预测未来的LULC变化、构建替代方案并作为决策工具,确定PA内部及其周围一段时间内与变化及其驱动因素相关的复杂界面具有重要意义。这项工作的主要目的是评估LULC的时间变化检测和预测,以及1989年至2016年克劳野生动物保护区(KWR)内部和周围的变化趋势。通过生成无云图像缓解了云问题,在与基于像素的分析进行总体准确性和kappa统计比较后,采用了基于对象的图像分析(OBIA)。1989年、2004年和2016年,分类地图的比较产生了令人满意的结果,总体准确率分别为91%、86%和90%。1989-2016年期间,天然林/密林减少,而建成林和农业林/疏林增加。土地变化建模器(LCM)的模拟模型与数字高程模型(DEM)和过去的LULC地图一起使用马尔可夫链来预测未来的LULC模式。预测的地图趋势显示,KWR西北部的茂密森林转化为农业/稀疏森林,东南部的城市/建成区增加。这项研究对于保护栖息地物种和监测KWR的现状具有重要意义
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
Geoplanning Journal of Geomatics and Planning
Geoplanning Journal of Geomatics and Planning Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.00
自引率
0.00%
发文量
5
审稿时长
4 weeks
×
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