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Characterizing the relationship between land use land cover change and land surface temperature / Duy X. Tran in ISPRS Journal of photogrammetry and remote sensing, vol 124 (February 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 124 (February 2017) . - pp 119 - 132 Titre : Characterizing the relationship between land use land cover change and land surface temperature Type de document : Article/Communication Auteurs : Duy X. Tran, Auteur ; Filiberto Pla, Auteur ; Pedro Latorre-Carmona, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 119 - 132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement d'occupation du sol [Termes IGN] changement d'utilisation du sol [Termes IGN] Hanoï [Termes IGN] ilot thermique urbain [Termes IGN] modèle de simulation [Termes IGN] occupation du sol [Termes IGN] outil d'aide à la décision [Termes IGN] température au sol [Termes IGN] urbanisation [Termes IGN] utilisation du sol Résumé : (Auteur) Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management. Numéro de notice : A2017-072 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.01.001 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.01.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84308 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017021	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017023	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017022	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation / Matthew Maimaitiyiming in ISPRS Journal of photogrammetry and remote sensing, vol 89 (March 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 89 (March 2014) . - pp 59 - 66 Titre : Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation Type de document : Article/Communication Auteurs : Matthew Maimaitiyiming, Auteur ; Abduwasit Ghulam, Auteur ; Tashpolat Tiyip, Auteur ; Filiberto Pla, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 59 - 66 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] développement durable [Termes IGN] espace vert [Termes IGN] image Landsat-TM [Termes IGN] image thermique [Termes IGN] milieu urbain [Termes IGN] température de surface Résumé : (Auteur) The urban heat island (UHI) refers to the phenomenon of higher atmospheric and surface temperatures occurring in urban areas than in the surrounding rural areas. Mitigation of the UHI effects via the configuration of green spaces and sustainable design of urban environments has become an issue of increasing concern under changing climate. In this paper, the effects of the composition and configuration of green space on land surface temperatures (LST) were explored using landscape metrics including percentage of landscape (PLAND), edge density (ED) and patch density (PD). An oasis city of Aksu in Northwestern China was used as a case study. The metrics were calculated by moving window method based on a green space map derived from Landsat Thematic Mapper (TM) imagery, and LST data were retrieved from Landsat TM thermal band. A normalized mutual information measure was employed to investigate the relationship between LST and the spatial pattern of green space. The results showed that while the PLAND is the most important variable that elicits LST dynamics, spatial configuration of green space also has significant effect on LST. Though, the highest normalized mutual information measure was with the PLAND (0.71), it was found that the ED and PD combination is the most deterministic factors of LST than the unique effects of a single variable or the joint effects of PLAND and PD or PLAND and ED. Normalized mutual information measure estimations between LST and PLAND and ED, PLAND and PD and ED and PD were 0.7679, 0.7650 and 0.7832, respectively. A combination of the three factors PLAND, PD and ED explained much of the variance of LST with a normalized mutual information measure of 0.8694. Results from this study can expand our understanding of the relationship between LST and street trees and vegetation, and provide insights for sustainable urban planning and management under changing climate. Numéro de notice : A2014-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.12.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.12.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33030 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2014031	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Unsupervised Image Segmentation based on Texems for Hyperspectral data / Adolfo Martinez-Uso (2008)

Public Titre : Unsupervised Image Segmentation based on Texems for Hyperspectral data Type de document : Article/Communication Auteurs : Adolfo Martinez-Uso, Auteur ; Filiberto Pla, Auteur ; Pedro Garcia-Sevilla, Auteur Editeur : Society for Imaging Science and Technology Année de publication : 2008 Conférence : CGIV 2008 & MCS 2008, 4th European conference on colour in graphics, imaging, and vision & 10th international symposium on Multispectral colour science 09/06/2008 13/06/2008 Barcelone Espagne Importance : pp 312 - 315 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] image hyperspectrale [Termes IGN] segmentation d'image Résumé : (auteur) There is no doubt about how useful and valuable the information provided by the hyperspectral sensors can be. Image segmentation procedures can take advantage of this information to increase the ability for separating different textures in an image. A multiscale approach for segmenting hyperspectral images is presented in this work. The method is based on the recently proposed texem model which has been extended in this work to spaces of high dimensionality. Furthermore, the hyperspectral extension of the texem-based segmentation would be computationally impracticable without a prior step for reducing the dimensionality. Thus, a band selection process based on the mutual information among bands has also been applied. The complete process is particularly useful in applications for remote sensing or quality inspection tasks. Numéro de notice : C2008-035 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103092