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An improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 64 - 77 Titre : An improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data Type de document : Article/Communication Auteurs : Li Zhuo, Auteur ; Qingli Shi, Auteur ; Haiyan Tao, Auteur ; Jing Zheng, Auteur ; Qiuping Li, Auteur Année de publication : 2018 Article en page(s) : pp 64 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges temporels [Termes IGN] détection de changement [Termes IGN] Enhanced vegetation index [Termes IGN] factorisation de matrice non-négative [Termes IGN] Fleuve bleu (Chine) [Termes IGN] image DMSP-OLS [Termes IGN] image Terra-MODIS [Termes IGN] Kouangtoung (Chine) [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] surface imperméable Résumé : (Auteur) Impervious surface area (ISA) is an important indicator for monitoring the intensity of human activity and ecological environment changes. Developing effective methods for estimation of ISA at different scales has thus been pursued by many scientists. The temporal mixture analysis (TMA), which is a variant of spectral mixture analysis that makes full use of the phenological information of different land cover types, is suitable for estimating the ISA fraction at a large scale. The existing TMA-based ISA fraction estimation methods rely on the assumption that pure pixels exist for all the endmembers, which, however, is not true in the case of coarse-resolution datasets. Moreover, the existing method cannot effectively differentiate bare soil from ISA effectively, which may lead to overestimation of the ISA fraction. To address these problems, we propose a new ISA estimation method based on TMA in this study, using a Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) products, the GlobeLand30 product, and the Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) data. The proposed method contains four major steps. First, the MODIS NDVI time-series datasets and GlobeLand30 land cover product were used to create an NDVI temporal profile subset for the TMA model. Second, a preliminary ISA fraction map was derived on the basis of optimized endmember temporal profiles, which were generated by unmixing the selected NDVI temporal profile subset through an improved spatial-spectral preprocessing nonnegative matrix factorization algorithm (ISSPP-NMF). Then, the preliminary ISA fraction was further optimized by incorporating the EVI-adjusted night-time light index (EANTLI), which can mitigate both saturation problems and the blooming effect of the DMSP-OLS data. An effective threshold method was introduced in this step to reduce the impact of bare soil on the ISA estimation. Finally, the estimated fraction of ISA was evaluated through accuracy assessment. The proposed method was tested in two study areas, namely, Guangdong Province and the Yangtze River Delta (YRD) of China, to prove its applicability in different regions. Effectiveness of the proposed method was proven through the comparison between the proposed method with traditional TMA-based methods. The results from these analyses indicate that the proposed method outperforms the others in ISA estimation, with an overall root mean square error (RMSE) of 9.2% and a coefficient of determination (R2) of 0.8872 in Guangdong and a RMSE of 8.9% and R2 of 0.8923 in YRD. This study also proves that the ISSPP-NMF method can produce more appropriate endmembers regardless of the existence of pure pixels. The post-processing with the EANLTI procedure can effectively reduce the bare soil effect in TMA-based ISA estimation. Numéro de notice : A2018-292 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.016 Date de publication en ligne : 05/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90409 [article]

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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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Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 90 - 98 Titre : Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan Type de document : Article/Communication Auteurs : F. Yang, Auteur ; B. Matsushita, Auteur ; T. Fukushima, Auteur ; W. Yang, Auteur Année de publication : 2012 Article en page(s) : pp 90 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges temporels [Termes IGN] image Aqua-MODIS [Termes IGN] image Landsat-TM [Termes IGN] image optique [Termes IGN] Japon [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] série temporelle [Termes IGN] surface imperméable Résumé : (Auteur) As a proxy measure of the human ecological footprint, impervious surface area (ISA) has recently become a key concept in the field of urban remote sensing, with a focus on estimation of the ISA at a city-scale by using Landsat-style satellite images. However, ISA estimation is also in demand in disciplines such as the environmental assessment and policy making at a national scale. This paper proposes a new method for estimating the ISA fraction in Japan based on a temporal mixture analysis (TMA) technique. The required inputs for the proposed method are rearranged MODIS NDVI time-series datasets at the temporal stable zone (i.e., the first to the sixth largest NDVI values in a year). Three ISA distribution maps obtained from Landsat-5 TM data were used as reference maps to evaluate the performance of the proposed method. The results showed that the proposed TMA-based method achieved a large reduction in the effects of endmember variability compared with the previous methods (e.g., SMA and NSMA), and thus the new method has promising accuracy for estimating ISA in Japan. The overall root mean square error (RMSE) of the proposed method was 8.7%, with a coefficient of determination of 0.86, and there was no obvious underestimation or overestimation for the whole ISA range. Numéro de notice : A2012-495 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31941 [article]

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Monitoring elevation variations in leaf phenology of deciduous broadleaf forests from SPOT/VEGETATION time-series / Dominique Guyon in Remote sensing of environment, vol 115 n° 2 ([15/02/2011])  

Public [article]  inRemote sensing of environment > vol 115 n° 2 [15/02/2011] . - pp 615 - 627 Titre : Monitoring elevation variations in leaf phenology of deciduous broadleaf forests from SPOT/VEGETATION time-series Type de document : Article/Communication Auteurs : Dominique Guyon, Auteur ; Marie Guillot, Auteur ; Yann Vitasse, Auteur ; et al., Auteur Année de publication : 2011 Article en page(s) : pp 615 - 627 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] analyse des mélanges temporels [Termes IGN] analyse diachronique [Termes IGN] Fagus (genre) [Termes IGN] feuillu [Termes IGN] image SPOT-Végétation [Termes IGN] indice de végétation [Termes IGN] phénologie [Termes IGN] Pyrénées (montagne) [Termes IGN] Quercus (genre) [Termes IGN] variation saisonnière Mots-clés libres : Phenology  Leaf unfolding  Deciduous forest  Elevation  VEGETATION  Perpendicular vegetation index  temporal unmixing Résumé : (auteur) In mountain forest ecosystems where elevation gradients are prominent, temperature gradient-based phenological variability can be high. However, there are few studies that assess the capability of remote sensing observations to monitor ecosystem phenology along elevation gradients, despite their relevance under climate change. We investigated the potential of medium resolution remotely sensed data to monitor the elevation variations in the seasonal dynamics of a temperate deciduous broadleaf forested ecosystem. Further, we explored the impact of elevation on the onset of spring leafing. This study was based on the analysis of multi-annual time-series of VEGETATION data acquired over the French Pyrenees Mountain Region (FPMR), in conjunction with simultaneous ground-based observations of leaf phenology made for two dominant tree species in the region (oak and beech). The seasonal variations in the perpendicular vegetation index (PVI) were analyzed during a five-year period (2002 to 2006). The five years of data were averaged into a one sole year in order to fill the numerous large spatio-temporal gaps due to cloud and snow presence – frequent in mountains – without altering the temporal resolution. Since a VEGETATION pixel (1 km²) includes several types of land cover, the broadleaf forest-specific seasonal dynamics of PVI was reconstructed pixel-by-pixel using a temporal unmixing method based on a non-parametric statistical approach. The spatial pattern of the seasonal response of PVI was clearly consistent with the relief. Nevertheless the elevational or geographic range of tree species, which differ in their phenology sensitivity to temperature, also has a significant impact on this pattern. The reduction in the growing season length with elevation was clearly observable from the delay in the increase of PVI in spring and from the advance of its decrease in the fall. The elevation variations in leaf flushing timing were estimated from the temporal change in PVI in spring over the study area. They were found to be consistent with those measured in situ (R2 > 0.95). It was deduced that, over FPMR, the mean delay of leaf flushing timing for every 100 m increase in elevation was estimated be approximately 2.3 days. The expected estimation error of satellite-based leaf unfolding date for a given elevation was approximately 2 days. This accuracy can be considered as satisfactory since it would allow us to detect changes in leafing timing of deciduous broadleaf forests with a magnitude equivalent to that due to an elevation variation of 100 m (2.3 days on average), or in other words, to that caused by a variation in the mean annual air temperature of 0.5 °C. Although averaging the VEGETATION data over five years led to a loss of interannual information, it was found to be a robust approach to characterise the elevation variations in spring leafing and its long-term trends. Numéro de notice : A2011-563 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2010.10.006 En ligne : https://doi.org/10.1016/j.rse.2010.10.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74834 [article]