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DOI10.1088/1748-9326/aa5a2f
Using spatial statistics to identify emerging hot spots of forest loss
Harris, Nancy L.1; Goldman, Elizabeth1; Gabris, Christopher2; Nordling, Jon2; Minnemeyer, Susan1; Ansari, Stephen2; Lippmann, Michael2; Bennett, Lauren3; Raad, Mansour3; Hansen, Matthew4; Potapov, Peter4
发表日期2017
ISSN2397-334X
卷号12期号:2
英文摘要

A s sources of data for global forest monitoring grow larger, more complex and numerous, data analysis and interpretation become critical bottlenecks for effectively using them to inform land use policy discussions. Here in this paper, we present a method that combines big data analytical tools with Emerging Hot Spot Analysis (ArcGIS) to identify statistically significant spatiotemporal trends of forest loss in Brazil, Indonesia and the Democratic Republic of Congo (DRC) between 2000 and 2014. Results indicate that while the overall rate of forest loss in Brazil declined over the 14-year time period, spatiotemporal patterns of loss shifted, with forest loss significantly diminishing within the Amazonian states of Mato Grosso and Rondonia and intensifying within the cerrado biome. In Indonesia, forest loss intensified in Riau province in Sumatra and in Sukamara and West Kotawaringin regencies in Central Kalimantan. Substantial portions of West Kalimantan became new and statistically significant hot spots of forest loss in the years 2013 and 2014. Similarly, vast areas of DRC emerged as significant new hot spots of forest loss, with intensified loss radiating out from city centers such as Beni and Kisangani. While our results focus on identifying significant trends at the national scale, we also demonstrate the scalability of our approach to smaller or larger regions depending on the area of interest and specific research question involved. When combined with other contextual information, these statistical data models can help isolate the most significant clusters of loss occurring over dynamic forest landscapes and provide more coherent guidance for the allocation of resources for forest monitoring and enforcement efforts.


英文关键词deforestation;spatial statistics;Brazil;Democratic Republic of Congo;Indonesia
语种英语
WOS记录号WOS:000410375200001
来源期刊ENVIRONMENTAL RESEARCH LETTERS
来源机构世界资源研究所
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/56097
作者单位1.World Resources Inst, 10 G St NE,Suite 800, Washington, DC 20002 USA;
2.Blue Raster, 2200 Wilson Blvd,Suite 400, Arlington, VA 22201 USA;
3.Esri, 380 New York St, Redlands, CA 92373 USA;
4.Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
推荐引用方式
GB/T 7714
Harris, Nancy L.,Goldman, Elizabeth,Gabris, Christopher,et al. Using spatial statistics to identify emerging hot spots of forest loss[J]. 世界资源研究所,2017,12(2).
APA Harris, Nancy L..,Goldman, Elizabeth.,Gabris, Christopher.,Nordling, Jon.,Minnemeyer, Susan.,...&Potapov, Peter.(2017).Using spatial statistics to identify emerging hot spots of forest loss.ENVIRONMENTAL RESEARCH LETTERS,12(2).
MLA Harris, Nancy L.,et al."Using spatial statistics to identify emerging hot spots of forest loss".ENVIRONMENTAL RESEARCH LETTERS 12.2(2017).
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