Regional-scale management maps for forested areas of the Southeastern United States and the US Pacific Northwest

被引:17
|
作者
Marsik, Matthew [1 ,2 ,3 ]
Staub, Caroline G. [4 ]
Kleindl, William J. [5 ]
Hall, Jaclyn M. [3 ]
Fu, Chiung-Shiuan [6 ,7 ]
Yang, Di [6 ,7 ]
Stevens, Forrest R. [8 ]
Binford, Michael W. [6 ,7 ,9 ]
机构
[1] Univ Florida, Integrated Data Repository Clin & Translat Sci In, Gainesville, FL 32610 USA
[2] Univ Florida, UF Hlth, Gainesville, FL 32610 USA
[3] Univ Florida Hlth, Decis Suppor Serv, Gainesville, FL 32610 USA
[4] Univ Florida, Inst Food & Agr Sci, Int Programs, Gainesville, FL 32610 USA
[5] Montana State Univ, Dept Land Resources & Environm Sci, Bozeman, MT 59717 USA
[6] Univ Florida, Dept Geog, Gainesville, FL 32611 USA
[7] Univ Florida, Land Use & Environm Change Inst, Gainesville, FL 32611 USA
[8] Univ Louisville, Dept Geog & Geosci, Louisville, KY 40292 USA
[9] Natl Sci Fdn, Alexandria, VA 22314 USA
基金
美国国家科学基金会;
关键词
CLASSIFICATION; CLIMATE; FIRE;
D O I
10.1038/sdata.2018.165
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Forests in the United States are managed by multiple public and private entities making harmonization of available data and subsequent mapping of management challenging. We mapped four important types of forest management, production, ecological, passive, and preservation, at 250-meter spatial resolution in the Southeastern (SEUS) and Pacific Northwest (PNW) USA. Both ecologically and socio-economically dynamic regions, the SEUS and PNW forests represent, respectively, 22.0% and 10.4% of forests in the coterminous US. We built a random forest classifier using seasonal time-series analysis of 16 years of MODIS 16-day composite Enhanced Vegetation Index, and ancillary data containing forest ownership, roads, US Forest Service wilderness and forestry areas, proportion conifer and proportion riparian. The map accuracies for SEUS are 89% (10-fold cross-validation) and 67% (external validation) and PNW are 91% and 70% respectively with the same validation. The now publicly available forest management maps, probability surfaces for each management class and uncertainty layer for each region can be viewed and analysed in commercial and open-source GIS and remote sensing software.
引用
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页数:13
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