DOI: 10.1016/j.jag.2014.04.011
Scopus记录号: 2-s2.0-84904765099
论文题名: Alerts of forest disturbance from MODIS imagery
作者: Hammer D ; , Kraft R ; , Wheeler D
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 33, 期: 1 起始页码: 1
结束页码: 9
语种: 英语
英文关键词: Cloud computing
; Deforestation
; MODIS
; Parallel processing
; Time series
Scopus关键词: accuracy assessment
; analytical method
; data processing
; deforestation
; forest cover
; humid environment
; image resolution
; MODIS
; pixel
; time series
; Brazil
; Para [Brazil]
英文摘要: This paper reports the methodology and computational strategy for a forest cover disturbance alertingsystem. Analytical techniques from time series econometrics are applied to imagery from the Moder-ate Resolution Imaging Spectroradiometer (MODIS) sensor to detect temporal instability in vegetationindices. The characteristics from each MODIS pixel's spectral history are extracted and compared againsthistorical data on forest cover loss to develop a geographically localized classification rule that can beapplied across the humid tropical biome. The final output is a probability of forest disturbance for each500 m pixel that is updated every 16 days. The primary objective is to provide high-confidence alerts offorest disturbance, while minimizing false positives. We find that the alerts serve this purpose exceed-ingly well in Pará, Brazil, with high probability alerts garnering a user accuracy of 98 percent over thetraining period and 93 percent after the training period (2000-2005) when compared against the PRODESdeforestation data set, which is used to assess spatial accuracy. Implemented in Clojure and Java on theHadoop distributed data processing platform, the algorithm is a fast, automated, and open source systemfor detecting forest disturbance. It is intended to be used in conjunction with higher-resolution imageryand data products that cannot be updated as quickly as MODIS-based data products. By highlightinghotspots of change, the algorithm and associated output can focus high-resolution data acquisition andaid in efforts to enforce local forest conservation efforts. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79735
Appears in Collections: 气候变化事实与影响
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作者单位: World Resources Institute, United States
Recommended Citation:
Hammer D,, Kraft R,, Wheeler D. Alerts of forest disturbance from MODIS imagery[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,33(1)