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Landsat sub-pixel analysis in mapping impact of climatic variability on prairie pothole changes / B. Zhang in Transactions in GIS, vol 13 n° 2 (April 2009)
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[article]
Titre : Landsat sub-pixel analysis in mapping impact of climatic variability on prairie pothole changes Type de document : Article/Communication Auteurs : B. Zhang, Auteur ; F. Schwartz, Auteur ; D. Tong, Auteur Année de publication : 2009 Article en page(s) : pp 179 - 195 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse infrapixellaire
[Termes IGN] cartographie thématique
[Termes IGN] changement climatique
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification par arbre de décision
[Termes IGN] classification pixellaire
[Termes IGN] Dakota du Sud (Etats-Unis)
[Termes IGN] détection de changement
[Termes IGN] image Landsat
[Termes IGN] lac
[Termes IGN] sécheresse
[Termes IGN] système d'information géographique
[Termes IGN] variation saisonnière
[Termes IGN] zone humideRésumé : (Auteur) The Prairie Pothole Region in the United States contains millions of seasonal, semi-permanent, or permanent lakes and wetlands that typically range in size from 0.1 to 10 ha. These lakes and wetlands are vulnerable to climate change, especially in our study area in South Dakota, in which a period of deluge following a sharp drought considerably expanded the areal extent of prairie pothole lakes during the last decade of the twentieth century. Preliminary estimates of lake areas, determined using LANDSAT 5 and 7 images, had appreciable errors especially for the smallest of these lakes. This article describes a new sub-pixel approach integrated with a CART (Classification and Regression Tree) model using a GIS (Geographical Information System) to quantify mixed water pixels along lake boundaries to improve area estimations for pothole lakes. Errors in estimated area were typically 10% or less for lakes greater than 1 ha in size. An analysis of lakes in our study area demonstrates how lake area changed with the transition from drought to deluge. Small lakes exhibited a distinct seasonal variation in contrast to large lakes that tended to follow precipitation trends more broadly. The total water area of lakes is consistent with broad variation in rainfall. Numéro de notice : A2009-541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2009.01149.x En ligne : https://doi.org/10.1111/j.1467-9671.2009.01149.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30170
in Transactions in GIS > vol 13 n° 2 (April 2009) . - pp 179 - 195[article]Using Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)
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[article]
Titre : Using Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest Type de document : Article/Communication Auteurs : X. Chen, Auteur ; Lee Alexander Vierling, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 14 - 26 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse multicritère
[Termes IGN] couvert forestier
[Termes IGN] Dakota du Sud (Etats-Unis)
[Termes IGN] données lidar
[Termes IGN] forêt
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] indice de végétation
[Termes IGN] Leaf Area Index
[Termes IGN] Pinus ponderosaRésumé : (Auteur) Structural and functional analyses of ecosystems benefit when high accuracy vegetation coverages can be derived over large areas. In this study, we utilize IKONOS, Landsat 7 ETM+, and airborne scanning light detection and ranging (lidar) to quantify coniferous forest and understory grass coverages in a ponderosa pine (Pinus ponderosa) dominated ecosystem in the Black Hills of South Dakota. Linear spectral mixture analyses of IKONOS and ETM+ data were used to isolate spectral endmembers (bare soil, understory grass, and tree/shade) and calculate their subpixel fractional coverages. We then compared these endmember cover estimates to similar cover estimates derived from lidar data and field measures. The IKONOS-derived tree/shade fraction was significantly correlated with the field-measured canopy effective leaf area index (LAIe) (r2 = 0.55, p Numéro de notice : A2004-235 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.11.003 En ligne : https://doi.org/10.1016/j.rse.2003.11.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26762
in Remote sensing of environment > vol 91 n° 1 (15/05/2004) . - pp 14 - 26[article]