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Retrieving spatial variations of land surface temperatures from satellite data–Cairo region, Egypt / Mohamed E. Hereher in Geocarto international, vol 32 n° 5 (May 2017)  

Public [article]  inGeocarto international > vol 32 n° 5 (May 2017) . - pp 556 - 568 Titre : Retrieving spatial variations of land surface temperatures from satellite data–Cairo region, Egypt Type de document : Article/Communication Auteurs : Mohamed E. Hereher, Auteur Année de publication : 2017 Article en page(s) : pp 556 - 568 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] Egypte [Termes IGN] image Terra-MODIS [Termes IGN] Le Caire [Termes IGN] température de surface [Termes IGN] zone industrielle [Termes IGN] zone rurale Résumé : (Auteur) Cairo region is characterized by a range of physiographic features, including: flat agricultural lands, bare sandy deserts, highlands, calcareous terrains and urban land use. A time series data-set (300 images) acquired from the Moderate Resolution Imaging Spectroradiometer for the period July 2002–June 2015 were utilized to retrieve the spatial variations in the mean land surface temperature (LST) for the above-mentioned surface features. Results showed that vegetation, topography and surface albedo have negative correlations with LST. Vegetation/LST correlation has the maximum regression coefficient (R2 = 0.68) and albedo/LST has the minimum (R2 = 0.03). Cultivated lands reveal the lowest mean LST (40 °C) of Cairo region. There is a considerable urban heat island formed at Helwan south of Cairo, where heavy industries are settled. Industrial activities raised the mean LST of the region by at least 4 °C than the surrounding urban lands. Numéro de notice : A2017-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1161077 Date de publication en ligne : 17/03/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1161077 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85301 [article]

Evaluation of multisource data for glacier terrain mapping : a neural net approach / Aparna Shukla in Geocarto international, vol 32 n° 5 (May 2017)  

Public [article]  inGeocarto international > vol 32 n° 5 (May 2017) . - pp 569 - 587 Titre : Evaluation of multisource data for glacier terrain mapping : a neural net approach Type de document : Article/Communication Auteurs : Aparna Shukla, Auteur ; Bisma Yousuf, Auteur Année de publication : 2017 Article en page(s) : pp 569 - 587 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bande infrarouge [Termes IGN] carte topographique [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par réseau neuronal [Termes IGN] couche thématique [Termes IGN] données auxiliaires [Termes IGN] données multisources [Termes IGN] glacier [Termes IGN] image Landsat-TM [Termes IGN] image multibande Résumé : (Auteur) Spectrally similar nature of land covers in a glacierized terrain hampers their automated mapping from multispectral satellite data, which may be overcome by using multisource data. In the present study, an artificial neural network (ANN)-based information extraction approach was applied for mapping the Kolahoi glacier and adjoining areas, using Landsat TM (Thematic Mapper) data and several ancillary layers such as image transformations and topographic attributes. Results reveal that ANN (highest overall accuracy (OA): 83.74%) outperforms maximum likelihood classifier (highest OA: 66.90%) and the incorporation of ancillary data into the classification process significantly enhances the mapping accuracy (>9%), particularly the addition of Near Infrared Red/Short Wave Infrared (NIR/SWIR) data to the spectral data. A nine-band combination dataset (spectral data, slope, Red/NIR and decorrelation stretch) was found to be the best multisource dataset. Results of the Z-tests (at 95% confidence level) also corroborate and statistically validate the above findings. Numéro de notice : A2017-274 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1161078 Date de publication en ligne : 28/03/2016 En ligne : http://dx.doi.org/10.1080/10106049.2016.1161078 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85303 [article]