Centre de documentation
scientifique

Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis / Jiong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 161 (March 2020) . - pp 76 - 89 Titre : Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis Type de document : Article/Communication Auteurs : Jiong Wang, Auteur ; Olivier Schmitz, Auteur ; Meng Lu, Auteur ; Derek Karssenberg, Auteur Année de publication : 2020 Article en page(s) : pp 76 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] données spatiotemporelles [Termes IGN] factorisation de matrice non-négative [Termes IGN] image Aqua-MODIS [Termes IGN] image Landsat [Termes IGN] image Terra-MODIS [Termes IGN] image thermique [Termes IGN] mise à l'échelle [Termes IGN] Pays-Bas [Termes IGN] radiance [Termes IGN] réduction [Termes IGN] température de surface [Termes IGN] variation diurne Résumé : (Auteur) Due to the limitation in the availability of airborne imagery data that are high in both spatial and temporal resolution, land surface temperature (LST) dense in both space and time can only be obtained through downscaling of frequently acquired LST with coarse resolution. Many conventional downscaling techniques are only feasible in an ideal situation, where land surface factors as LST predictors are continuously available for downscaling the LST. These techniques are also applied only at large scales ignoring sub-regional variations. Based upon unmixing based approaches, this study presents an LST downscaling workflow, where only the coarse resolution of 1 km LST image at the prediction time is required. The conceptual backbone of the study is assuming that the LST patterns are governed by thermal behaviors of a fixed set of temperature sensitive land surface components. In operation, the study focuses on central Netherlands covering an area of 90 × 90 km. The MODIS and Landsat imagery acquired simultaneously are used as a coarse-fine resolution pair to derive downscaling mechanism which is then applied to coarse imagery at a time with missing fine resolution imagery. First, an optimal number of thermal components are extracted at fine resolution through the application of the non-negative matrix factorization (NMF). These components are assumed to possess unique temperature change patterns caused by combined effects of land cover change, radiance change, or both. Given the LST change and thermal components at coarse resolution, the LST change load of each component can then be obtained at the coarse resolution by solving a system of linear equations encoding thermal component-LST relationship. Such LST change load of thermal components is further unmixed to fine resolution and linearly weighted by the component distribution at fine resolution to obtain the fine resolution LST change. During the process, the coarse LST data is used directly without any resampling practice as shown in previous studies. Thus the technique is less time consuming even with a large downscaling factor of 30. The downscaled fine resolution LST represents an R-squared of over 0.7 outperforming classic downscaling techniques. The downscaled LST differentiates temperature over major land types and captures both seasonal and diurnal LST dynamics. Numéro de notice : A2020-063 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.01.014 Date de publication en ligne : 16/01/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.01.014 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94580 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020031	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020033	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020032	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt