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Urban surface biophysical descriptors and land surface temperature variations / D. Weng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 11 (November 2006) . - pp 1275 - 1286 Titre : Urban surface biophysical descriptors and land surface temperature variations Type de document : Article/Communication Auteurs : D. Weng, Auteur ; Dong Lu, Auteur ; B. Liang, Auteur Année de publication : 2006 Article en page(s) : pp 1275 - 1286 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] albedo [Termes IGN] analyse des mélanges spectraux [Termes IGN] émission thermique [Termes IGN] flore locale [Termes IGN] image Landsat-ETM+ [Termes IGN] Indianapolis [Termes IGN] milieu urbain [Termes IGN] morphologie urbaine [Termes IGN] occupation du sol [Termes IGN] surface imperméable [Termes IGN] température de surface [Termes IGN] variable biophysique (végétation) [Termes IGN] zone urbaine Résumé : (Auteur) In remote sensing studies of land surface temperatures (LST), thematic land-use and land-cover (LULC) data are frequently employed for simple correlation analyses between LULC types and their thermal signatures. Development of quantitative surface descriptors could improve our capabilities for modeling urban thermal landscapes and advance urban climate research. This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying the urban landscape in Indianapolis, Indiana. A Landsat Enhanced Thematic Mapper Plus image of the study area, acquired on 22 June 2002, was spectrally unmixed into four fraction endmembers, namely, green vegetation, soil, high and low albedo. Impervious surface was then computed from the high and low albedo images. A hybrid classification procedure was developed to classify the fraction images into seven land-use and land-cover classes. Next, pixel-based LST measurements were related to urban surface biophysical descriptors derived from spectral mixture analysis (SMA). Correlation analyses were conducted to investigate land-cover based relationships between LST and impervious surface and green vegetation fractions for an analysis of the causes of LST variations. Results indicate that fraction images derived from SMA were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables such as vegetation abundance, soil, and impervious surface. An examination of LST variations within census block groups and their relationships with the compositions of LULC types, biophysical descriptors, and other relevant spatial data shows that LST possessed a weaker relation with the LULC compositions than with other variables (including urban biophysical descriptors, remote sensing biophysical variables, GIS-based impervious surface variables, and population density). Further research should be directed to refine spectral mixture modeling. The use of multi-temporal remote sensing data for urban time-space modeling and comparison of urban morphology in different geographical settings are also feasible. Copyright ASPRS Numéro de notice : A2006-493 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.11.1275 En ligne : https://doi.org/10.14358/PERS.72.11.1275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28217 [article]