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Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes / Aniruddha Ghosh in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 76 - 93 Titre : Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes Type de document : Article/Communication Auteurs : Aniruddha Ghosh, Auteur ; P.K. Joshi, Auteur Année de publication : 2014 Article en page(s) : pp 76 - 93 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] image hyperspectrale [Termes IGN] occupation du sol [Termes IGN] régression [Termes IGN] température de surface Résumé : (Auteur)Land surface temperature (LST), a key parameter in understanding thermal behavior of various terrestrial processes, changes rapidly and hence mapping and modeling its spatio-temporal evolution requires measurements at frequent intervals and finer resolutions. We designed a series of experiments for disaggregation of LST (DLST) derived from the Landsat ETM + thermal band using narrowband reflectance information derived from the EO1-Hyperion hyperspectral sensor and selected regression algorithms over three geographic locations with different climate and land use land cover (LULC) characteristics. The regression algorithms applied to this end were: partial least square regression (PLS), gradient boosting machine (GBM) and support vector machine (SVM). To understand the scale dependence of regression algorithms for predicting LST, we developed individual models (local models) at four spatial resolutions (480 m, 240 m, 120 m and 60 m) and tested the differences between these using RMSE derived from cross-validated samples. The sharpening capabilities of the models were assessed by predicting LST at finer resolutions using models developed at coarser spatial resolution. The results were also compared with LST produced by DisTrad sharpening model. It was found that scale dependence of the models is a function of the study area characteristics and regression algorithms. Considering the sharpening experiments, both GBM and SVM performed better than PLS which produced noisy LST at finer spatial resolutions. Based on the results, it can be concluded that GBM and SVM are more suitable algorithms for operational implementation of this application. These algorithms outperformed DisTrad model for heterogeneous landscapes with high variation in soil moisture content and photosynthetic activities. The variable importance measure derived from PLS and GBM provided insights about the characteristics of the relevant bands. The results indicate that wavelengths centered around 457, 671, 1488 and 2013–2083 nm are the most important in predicting LST. Nevertheless, further research is needed to improve the performance of regression algorithms when there is a large variability in LST and to examine the utility of narrowband vegetation indices to predict the LST. The benefits of this research may extend to applications such as monitoring urban heat island effect, volcanic activity and wildfire, estimating evapotranspiration and assessing drought severity. Numéro de notice : A2014-385 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73812 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014101	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Analysing spatio-temporal footprints of urbanization on environment of Surat city using satellite-derived bio-physical parameters / Richa Sharma in Geocarto international, vol 28 n° 5-6 (August - October 2013)  

Public [article]  inGeocarto international > vol 28 n° 5-6 (August - October 2013) . - pp 420 - 438 Titre : Analysing spatio-temporal footprints of urbanization on environment of Surat city using satellite-derived bio-physical parameters Type de document : Article/Communication Auteurs : Richa Sharma, Auteur ; Aniruddha Ghosh, Auteur ; P.K. Joshi, Auteur Année de publication : 2013 Article en page(s) : pp 420 - 438 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] carte d'occupation du sol [Termes IGN] croissance urbaine [Termes IGN] données spatiotemporelles [Termes IGN] image Landsat-TM [Termes IGN] Inde [Termes IGN] occupation du sol [Termes IGN] urbanisation Résumé : (Auteur) Our study examines the relationships among various environmental variables in Surat city using remote sensing. Landsat Thematic Mapper satellite data were used in conjugation with geospatial techniques to study urbanization and correlation among satellite-derived biophysical parameters namely, normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), normalized difference bareness index (NDBaI) and land surface temperature (LST). A modified NDWI (MNDWI) was used for extracting areas under water. Land use/land cover classification was performed using hierarchical decision tree classification technique using ERDAS IMAGINE Expert classifier with an accuracy of 90.4% for 1990 and 85% for 2009. It was found that city has expanded over 42.75 sq.km within two decades. Built-up, fallow and sediment land use classes exhibited high dynamics with increase of nearly 200% and 50% and decrease of 55% respectively from 1990 to 2009. Vegetation and water classes were less dynamic with 20% decrease and 15% increase. The transformation of land parcels from vegetation to built-up, vegetation to fallow and fallow to built-up has resulted in increase of LST by 5.5 1 2.6°C, 6.7 1 3°C and 3.5 1 2.9°C, respectively. Numéro de notice : A2013-548 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.715208 Date de publication en ligne : 28/08/2012 En ligne : https://doi.org/10.1080/10106049.2012.715208 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32684 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2013031	RAB	Revue	Centre de documentation	En réserve L003	Disponible