A new satellite-based methodology for continental-scale disturbance detection.
Identifieur interne : 003C56 ( Main/Exploration ); précédent : 003C55; suivant : 003C57A new satellite-based methodology for continental-scale disturbance detection.
Auteurs : David J. Mildrexler [États-Unis] ; Maosheng Zhao ; Faith Ann Heinsch ; Steven W. RunningSource :
- Ecological applications : a publication of the Ecological Society of America [ 1051-0761 ] ; 2007.
Descripteurs français
- KwdFr :
- MESH :
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- MESH :
- geographic : United States.
- Algorithms, Climate, Conservation of Natural Resources, Ecosystem, Uncertainty.
Abstract
The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance.
DOI: 10.1890/1051-0761(2007)017[0235:ansmfc]2.0.co;2
PubMed: 17479848
Affiliations:
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Mildrexler</name><affiliation wicri:level="1"><nlm:affiliation>Numerical Terradynamic Simulation Group, Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana 59812, USA. drexler@ntsg.umt.edu</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Numerical Terradynamic Simulation Group, Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana 59812</wicri:regionArea><wicri:noRegion>Montana 59812</wicri:noRegion></affiliation></author><author><name sortKey="Zhao, Maosheng" sort="Zhao, Maosheng" uniqKey="Zhao M" first="Maosheng" last="Zhao">Maosheng Zhao</name></author><author><name sortKey="Heinsch, Faith Ann" sort="Heinsch, Faith Ann" uniqKey="Heinsch F" first="Faith Ann" last="Heinsch">Faith Ann Heinsch</name></author><author><name sortKey="Running, Steven W" sort="Running, Steven W" uniqKey="Running S" first="Steven W" last="Running">Steven W. 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Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">17479848</PMID><DateCompleted><Year>2007</Year><Month>05</Month><Day>31</Day></DateCompleted><DateRevised><Year>2019</Year><Month>09</Month><Day>17</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1051-0761</ISSN><JournalIssue CitedMedium="Print"><Volume>17</Volume><Issue>1</Issue><PubDate><Year>2007</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Ecological applications : a publication of the Ecological Society of America</Title><ISOAbbreviation>Ecol Appl</ISOAbbreviation></Journal><ArticleTitle>A new satellite-based methodology for continental-scale disturbance detection.</ArticleTitle><Pagination><MedlinePgn>235-50</MedlinePgn></Pagination><Abstract><AbstractText>The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. 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Running</name><name sortKey="Zhao, Maosheng" sort="Zhao, Maosheng" uniqKey="Zhao M" first="Maosheng" last="Zhao">Maosheng Zhao</name></noCountry><country name="États-Unis"><noRegion><name sortKey="Mildrexler, David J" sort="Mildrexler, David J" uniqKey="Mildrexler D" first="David J" last="Mildrexler">David J. Mildrexler</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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