globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2012.11.007
Scopus记录号: 2-s2.0-84880317463
论文题名:
Mapping the distribution of the main host for plague in a complex landscape in kazakhstan: An object-based approach using SPOT-5 XS, landsat 7 ETM+, SRTM and multiple random forests
作者: Wilschut L; I; , Addink E; A; , Heesterbeek J; A; P; , Dubyanskiy V; M; , Davis S; A; , Laudisoit A; , Begon M; , Burdelov L; A; , Atshabar B; B; , de Jong S; M
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2013
卷: 23, 期:1
起始页码: 81
结束页码: 94
语种: 英语
英文关键词: Desert environment ; Great gerbil ; Landscape epidemiology ; Object-based image analysis ; Stratification ; Vector-borne disease ; Yersinia pestis ; Zoonosis
Scopus关键词: complexity ; desert ; disease ; epidemiology ; forest cover ; image analysis ; Landsat thematic mapper ; landscape ; mapping ; Shuttle Radar Topography Mission ; spatial distribution ; SPOT ; vegetation cover ; Kazakhstan
英文摘要: Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil,the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery.In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape. The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eightlandscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derivedstandard deviation in elevation. In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit. Burrows were successfully classified in all landscape units. In the 'steppe on floodplain' areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the 'floodplain' areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively. In this study, an innovative stratification method using high- and medium resolution imagery was applied inorder to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague. © 2012 Elsevier B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79843
Appears in Collections:气候变化事实与影响

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作者单位: Utrecht University, Department of Physical Geography, Heidelberglaan 2, PO Box 80115, 3508 TC Utrecht, Netherlands; Utrecht University, Faculty of Veterinary Medicine, Yalelaan 7, 3584 CL Utrecht, Netherlands; Stavropol Plague Control Research Institute, Sovetskaya 13-15, Stavropol 355035, Russian Federation; Anti-Plague Institute, M. Aikimbayev's Kazakh Science Centre for Quarantine and Zoonotic Diseases, 14 Kapalskaya Street, Almaty 050074, Kazakhstan; RMIT University, School of Mathematical and Geospatial Sciences, Melbourne, VIC 3000, Australia; University of Liverpool, Institute of Integrative Biology, Crown Street, Liverpool, United Kingdom; University of Antwerp, Department of Biology, Groenenborgerlaan 171, B-2020 Antwerpen, Belgium

Recommended Citation:
Wilschut L,I,, Addink E,et al. Mapping the distribution of the main host for plague in a complex landscape in kazakhstan: An object-based approach using SPOT-5 XS, landsat 7 ETM+, SRTM and multiple random forests[J]. International Journal of Applied Earth Observation and Geoinformation,2013-01-01,23(1)
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