Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.jag.2016.07.019 |
Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland | |
Ng, Wai-Tim1; Meroni, Michele2; Immitzer, Markus1; Boeck, Sebastian1; Leonardi, Ugo3; Rembold, Felix2; Gadain, Hussein3; Atzberger, Clement1 | |
通讯作者 | Ng, Wai-Tim |
来源期刊 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
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ISSN | 0303-2434 |
出版年 | 2016 |
卷号 | 53页码:76-89 |
英文摘要 | Prosopis spp. is a fast and aggressive invader threatening many arid and semi-arid areas globally. The species is native to the American dry zones and was introduced in Somaliland for dune stabilization and fuel wood production in the 1970’s and 1980’s. Its deep rooting system is capable of tapping into the groundwater table thereby reducing its reliance on infrequent rainfalls and near-surface water. The competitive advantage of Prosopis is further fuelled by the hybridization of the many introduced subspecies that made the plant capable of adapting to the new environment and replacing endemic species. This study aimed to test the mapping accuracy achievable with Landsat 8 data acquired during the wet and the dry seasons within a Random Forest (RF) classifier, using both pixel- and object-based approaches. Maps are produced for the Hargeisa area (Somaliland), where reference data was collected during the dry season of 2015. Results were assessed through a 10-fold cross-validation procedure. In our study, the highest overall accuracy (74%) was achieved when applying a pixel-based classification using a combination of the wet and dry season Earth observation data. Object-based mapping were less reliable due to the limitations in spatial resolution of the Landsat data (15-30 m) and problems in finding an appropriate segmentation scale. (C) 2016 Elsevier B.V. All rights reserved. |
英文关键词 | Prosopis spp. Invasive species Random forest classifier OBIA |
类型 | Article |
语种 | 英语 |
国家 | Austria ; Italy ; Kenya |
收录类别 | SCI-E |
WOS记录号 | WOS:000384788300007 |
WOS关键词 | COVER CLASSIFICATION ACCURACY ; TIME-SERIES ; MEAN-SHIFT ; MESQUITE ; SATELLITE ; JULIFLORA ; CROP ; SEGMENTATION ; GLANDULOSA ; SPACE |
WOS类目 | Remote Sensing |
WOS研究方向 | Remote Sensing |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/193678 |
作者单位 | 1.Univ Nat Resources & Life Sci, Vienna BOKU, Inst Surveying Remote Sensing & Land Informat IVF, Peter Jordan Str 82, A-1190 Vienna, Austria; 2.Joint Res Ctr European Commiss, MARS Unit, Via Fermi 2749,TP-266, I-21027 Ispra, VA, Italy; 3.Food & Agr Org United Nations, Somalia Water & Land Informat Management FAO SWAL, POB 30470-00100, Nairobi, Kenya |
推荐引用方式 GB/T 7714 | Ng, Wai-Tim,Meroni, Michele,Immitzer, Markus,et al. Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland[J],2016,53:76-89. |
APA | Ng, Wai-Tim.,Meroni, Michele.,Immitzer, Markus.,Boeck, Sebastian.,Leonardi, Ugo.,...&Atzberger, Clement.(2016).Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,53,76-89. |
MLA | Ng, Wai-Tim,et al."Mapping Prosopis spp. with Landsat 8 data in arid environments: Evaluating effectiveness of different methods and temporal imagery selection for Hargeisa, Somaliland".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 53(2016):76-89. |
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