DOI: 10.1016/j.foreco.2016.06.027
Scopus记录号: 2-s2.0-84979706664
论文题名: Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach
作者: Norman S.P. ; Koch F.H. ; Hargrove W.W.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2016
卷: 380 起始页码: 346
结束页码: 358
语种: 英语
英文关键词: Big data
; Drought impacts
; Drought indices
; Forests
; Monitoring
; Remote sensing
Scopus关键词: Data mining
; Drought
; Forestry
; Meteorology
; Moisture
; Monitoring
; Remote sensing
; Temperature measurement
; Vegetation
; Base-line conditions
; Drought indices
; Forests
; Integrated data mining
; Meteorological index
; Moisture conditions
; Remote sensing approaches
; Remotely sensed data
; Big data
; air temperature
; baseline conditions
; climate effect
; data mining
; drought
; environmental disturbance
; environmental monitoring
; environmental stress
; forest management
; integrated approach
; precipitation (climatology)
; remote sensing
英文摘要: Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broad-scale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other datasets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts. © 2016 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64720
Appears in Collections: 影响、适应和脆弱性
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作者单位: USDA Forest Service Southern Research Station, Eastern Forest Environmental Threat Assessment Center, 200 WT Weaver Blvd., Asheville, NC, United States; USDA Forest Service Southern Research Station, Eastern Forest Environmental Threat Assessment Center, 3041 E. Cornwallis Rd., Research Triangle ParkNC, United States
Recommended Citation:
Norman S.P.,Koch F.H.,Hargrove W.W.. Review of broad-scale drought monitoring of forests: Toward an integrated data mining approach[J]. Forest Ecology and Management,2016-01-01,380