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Mapping the human footprint from satellite measurements in Japan / Fan Yang in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 88 (February 2014) . - pp 80 - 90 Titre : Mapping the human footprint from satellite measurements in Japan Type de document : Article/Communication Auteurs : Fan Yang, Auteur ; Bunkei Matsushita, Auteur ; Wei Yang, Auteur ; Takehiko Fukushima, Auteur Année de publication : 2014 Article en page(s) : pp 80 - 90 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture [Termes IGN] analyse des mélanges temporels [Termes IGN] changement climatique [Termes IGN] empreinte écologique [Termes IGN] indice de végétation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] série temporelle Résumé : (Auteur) Due to increasing global urbanization and climate change, the quantification of “human footprints” has become an urgent goal in the fields of biodiversity conservation and regional environment management. A human footprint is defined as the impact of a particular human activity on the Earth’s surface, which can be represented mainly by impervious surfaces (related to industry and urbanization) and cropland (related to agriculture). Here we present a method called sorted temporal mixture analysis with post-classification (STMAP) for mapping impervious surfaces and cropland simultaneously at the subpixel level to fill the demand for precise human footprint information on a national scale. The STMAP method applies a four-endmember sorted temporal mixture analysis to provide the initial fractions of evergreen forests, deciduous forests, cropland, and impervious surfaces as a first step. Endmembers are selected from the sorted temporal profiles of the MODIS-normalized difference vegetation index (NDVI), as guided by a principal component analysis. The yearly maximum land surface temperatures and averaged stable nighttime light are then statistically analyzed to provide the thresholds for post-classification to further separate cropland from deciduous forest and bare land from impervious surface. As the four outputs of STMAP, the fractions of forest, cropland, impervious surfaces and bare land are derived. We used the reference maps of impervious surfaces and cropland obtained from the Landsat/TM and ALOS precise land-use/land-cover map at the subpixel level to evaluate the performance of the proposed method, respectively. Historical satellite images with high spatial resolution were used to further evaluate the cropland results derived with the STMAP method. The results showed that the STMAP method has promising accuracy for estimating impervious surfaces and cropland in Japan. The root mean square errors obtained with the STMAP method were 6.3% for the estimation of impervious surfaces and 9.8% for the estimation of cropland. Our findings can extend the applications of remote sensing technologies in ecological research and environment management on a large scale. Numéro de notice : A2014-086 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.020 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32991 [article]

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