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Evaluation of the horizontal resolution of SRTM elevation data / L. Pierce 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 1235 - 1244 Titre : Evaluation of the horizontal resolution of SRTM elevation data Type de document : Article/Communication Auteurs : L. Pierce, Auteur ; J. Kelindorf, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 1235 - 1244 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie spatiale [Termes IGN] lever topographique [Termes IGN] limite de résolution géométrique [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] précision géométrique (imagerie) [Termes IGN] qualité géométrique (image) [Termes IGN] raisonnement inductif Résumé : (Auteur) The SRTM dataset is available at the USGS seamless website with one arc-second pixel spacing for the U.S. Recently, the value for horizontal resolution has been questioned. One paper (Smith and Sandwell, 2003) suggests that 60 meters may be more accurate, implying that the resolution is twice the provided spacing. For users of this data, the horizontal resolution is very important for their analyses. Hence, this paper addresses this important question by using two different approaches: coherence spectra and step-response. The coherence spectra approach uses statistical techniques to compare the SRTM dataset against a more accurate one, while the step response approach uses the observed step response in many areas of the dataset to estimate the width of the averaging function used to produce the SRTM data. Results from this study show that the resolution is between 1 and 1.6 pixels, depending on the local variability of the elevation data; with higher resolution near sharp edges and corners, and lower resolution in smoother areas. Copyright ASPRS Numéro de notice : A2006-492 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.11.1235 En ligne : https://doi.org/10.14358/PERS.72.11.1235 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28216 [article]

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]