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An image-pyramid-based raster-to-vector conversion (IPBRTVC) framework for consecutive-scale cartography and synchronized generalization of classic objects / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 3 (March 2019) . - pp 169 - 178 Titre : An image-pyramid-based raster-to-vector conversion (IPBRTVC) framework for consecutive-scale cartography and synchronized generalization of classic objects Type de document : Article/Communication Auteurs : Chang Li, Auteur ; Xiaojuan Liu, Auteur ; Lu Wei, Auteur Année de publication : 2019 Article en page(s) : pp 169 - 178 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] contrôle qualité [Termes descripteurs IGN] détection d'objet [Termes descripteurs IGN] image DMSP-OLS [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] vectorisation Résumé : (Auteur) There are some key problems in raster-to-vector conversion and cartographic generalization, which include (1) deficient automation and low accuracy in the traditional raster-to-vector conversion processing; (2) data-source inconsistency in cartographic generation, i.e., different raster data sources converted to vector; and (3) how to acquire arbitrary-scale vector data. To solve these problems, we initially propose an innovative image-pyramid-based raster-to-vector conversion (IPBRTVC) framework with quality control for consecutive-scale cartography and synchronized generalization, of which details can be modified accordingly under the IPBRTVC framework. Landsat-8 imagery and Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) night-time light imagery are used as a test dataset to extract classic objects in the geometry level. Experimental results show that the IPBRTVC framework not only solves the aforementioned problems well but also (1) improves efficiency of data processing by avoiding problems of corresponding features matching and topology errors, (2) contributes to develop relevant parallel computing system, and (3) helps to integrate the raster-to-vector conversion and consecutive-scale cartography. Numéro de notice : A2019-146 Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.3.169 date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.14358/PERS.85.3.169 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92474 [article]

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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 descripteurs IGN] analyse des mélanges temporels [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] Enhanced vegetation index [Termes descripteurs IGN] factorisation de matrice non-négative [Termes descripteurs IGN] Fleuve bleu (Chine) [Termes descripteurs IGN] image DMSP-OLS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Kouangtoung (Chine) [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs 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 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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Dasymetric modelling of small-area population distribution using land cover and light emissions data / D.J. Briggs in Remote sensing of environment, vol 108 n° 4 (29 June 2007)

Public [article]  inRemote sensing of environment > vol 108 n° 4 (29 June 2007) . - pp 451 - 466 Titre : Dasymetric modelling of small-area population distribution using land cover and light emissions data Type de document : Article/Communication Auteurs : D.J. Briggs, Auteur ; J. Gulliver, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 451 - 466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] Corine Land Cover [Termes descripteurs IGN] densité de population [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données statistiques [Termes descripteurs IGN] figuration de la densité [Termes descripteurs IGN] flux lumineux [Termes descripteurs IGN] image DMSP-OLS [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] interpolation inversement proportionnelle à la distance [Termes descripteurs IGN] krigeage [Termes descripteurs IGN] régression Résumé : (Auteur) Despite the improvements made in census procedures over recent decades, the availability of detailed population data is limited. For many applications, including environmental and health analyses, methods are therefore needed to model population distribution at the small-area level. With the development of GIS and remote sensing techniques, the ability to develop such models has greatly improved. This paper describes a GIS-based approach using remotely sensed land cover and nighttime light emissions data to model population distribution at the land parcel level across the European Union. Light emission data from the DMSP satellites were first resampled and modelled using kriging and inverse distance weighting methods to provide a 200-m resolution light emissions map. This was then matched to CORINE land cover classes across the EU. Regression methods were used to derive models of relationships between census population counts (at NUTS 5 level) and land cover area and light emissions. Models were developed at both national and EU scale, using a range of different modelling strategies. Model performance, as indicated by the regression statistics, was seen to be good, with R2 typically in the order of 0.8–0.9 and SEE ca. 4000 people. In southern countries, especially, incorporation of light emissions data was found to improve model performance considerably compared to models based only on land cover data. More detailed post hoc validation in Great Britain, using independent data on population at census tract (enumeration district and output area) and postcode level, for 1991 and 2001, showed that models gave good predictions of population at the 1 km level (R2 > 0.9), but were less reliable at resolutions below ca. 500 m. Impending enhancements in the available land cover and light emissions data are expected to improve the capability of this modelling approach in the future. Numéro de notice : A2007-300 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28663 [article]

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Active forest monitoring in Uttaranchal state, India using multi-temporal DMSP-OLS and MODIS data / T.R. Kiranchand in International Journal of Remote Sensing IJRS, vol 28 n° 10 (May 2007)

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 28 n° 10 (May 2007) . - pp 2123 - 2132 Titre : Active forest monitoring in Uttaranchal state, India using multi-temporal DMSP-OLS and MODIS data Type de document : Article/Communication Auteurs : T.R. Kiranchand, Auteur ; K.V.S. Badarinath, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 2123 - 2132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] bande visible [Termes descripteurs IGN] corrélation automatique de points homologues [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] image DMSP-OLS [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] Inde [Termes descripteurs IGN] surveillance forestière Résumé : (Auteur) This paper gives an account of day-night active forest fire monitoring conducted over the sub-tropical and moist temperate forests of the Uttaranchal State, India, during 2005 using the Defence Meteorological Satellite Program - Operational Line Scan system (DMSP-OLS) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The state experienced heavy fire episodes during May-June 2005 and daily datasets of DMSP-OLS (night-time) and selected cloud-free MODIS (daytime) datasets were used in mapping active fire locations. DMSP-OLS collects data in visible (0.5 to 0.9 um) and thermal (10.5 to 12.5 um) bands and detects dim sources of lighting on the earth's surface, including fires. The enhanced fire algorithm for active fire detection (version 4) was used in deriving fire products from MODIS datasets. Fire locations derived from DMSP-OLS and MODIS data were validated with limited ground data from forest department and media reports. Results of the study indicated that the state experienced heavy fire episodes, most of them occurring during night-time rather than daytime. Validation of satellite-derived fires with ground data showed a high degree of spatial correlation. Copyright Taylor & Francis Numéro de notice : A2007-288 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28651 [article]

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Evaluation of remote sensing-based active fire datasets in Indonesia / F. Stolle in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 25 n° 2 (January 2004) . - pp 471 - 479 Titre : Evaluation of remote sensing-based active fire datasets in Indonesia Type de document : Article/Communication Auteurs : F. Stolle, Auteur ; R.A. Dennis, Auteur ; I. Kurniwan, Auteur ; Eric F. Lambin, Auteur Année de publication : 2004 Article en page(s) : pp 471 - 479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Along Track Scanning Radiometer [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] détection [Termes descripteurs IGN] image DMSP-OLS [Termes descripteurs IGN] image NOAA-AVHRR [Termes descripteurs IGN] incendie [Termes descripteurs IGN] Indonésie [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] Moderate Resolution Imaging Spectroradiometer [Termes descripteurs IGN] TRMM Résumé : (Auteur) Eight different fire datasets for Indonesia were compared with each other and to fine spatial resolution burnscar maps. Results show that each dataset detects different fires. More than two-thirds of the fires detected by one dataset are not detected by any other dataset. None of the datasets detect fires in all test areas. Fire regime, satellite sensor characteristics and fire detection algorithms all influence which fires are detected. Fire datasets were not complementing each other as they all had commission as well as omission errors. Numéro de notice : A2004-059 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26587 [article]

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