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Comparison of landslide susceptibility mapping based on statistical index, certainty factors, weights of evidence and evidential belief function models / Kai Cui in Geocarto international, vol 32 n° 9 (September 2017)  

Public [article]  inGeocarto international > vol 32 n° 9 (September 2017) . - pp 935 - 955 Titre : Comparison of landslide susceptibility mapping based on statistical index, certainty factors, weights of evidence and evidential belief function models Type de document : Article/Communication Auteurs : Kai Cui, Auteur ; Dong Lu, Auteur ; Wei Li, Auteur Année de publication : 2017 Article en page(s) : pp 935 - 955 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aléa [Termes IGN] analyse comparative [Termes IGN] cartographie des risques [Termes IGN] Chine [Termes IGN] effondrement de terrain [Termes IGN] inventaire [Termes IGN] pondération [Termes IGN] risque naturel [Termes IGN] système d'information géographique [Termes IGN] théorie de Dempster-Shafer [Termes IGN] vulnérabilité Résumé : (Auteur) The main aim of this study was to produce landslide susceptibility maps using statistical index (SI), certainty factors (CF), weights of evidence (WoE) and evidential belief function (EBF) models for the Long County, China. Firstly, a landslide inventory map, including a total of 171 landslides, was compiled on the basis of earlier reports, interpretation of aerial photographs and supported by extensive field surveys. Thereafter, all landslides were randomly separated into two data sets: 70% landslides (120 points) were selected for establishing the model and the remaining landslides (51 points) were used for validation purposes. Eleven landslide conditioning factors, such as slope aspect, slope angle, plan curvature, profile curvature, altitude, distance to faults, distance to roads, distance to rivers, lithology, NDVI and land use, were considered for landslide susceptibility mapping in this study. Then, the SI, CF, WoE and EBF models were used to produce the landslide susceptibility maps for the study area. Finally, the four models were validated using area under the curve (AUC) method. According to the validation results, the EBF model (AUC = 78.93%) has a higher prediction accuracy than the SI model (AUC = 77.72%), the WoE model (AUC = 77.62%) and the CF model (AUC = 77.72%). Similarly, the validation results also indicate that the EBF model has the highest training accuracy of 80.25%, followed by SI (79.80%), WoE (79.71%) and CF (79.67%) models. Numéro de notice : A2017-457 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.0/10106049.2016.1195886 Date de publication en ligne : 16/06/2016 En ligne : http://dx.doi.org108/10.0/10106049.2016.1195886 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86382 [article]

Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China / Jianqin Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 9 (September 2012) . - pp 935 - 946 Titre : Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China Type de document : Article/Communication Auteurs : Jianqin Huang, Auteur ; Dong Lu, Auteur ; Jin Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 935 - 946 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte pédologique [Termes IGN] Chine [Termes IGN] écosystème forestier [Termes IGN] érosion [Termes IGN] estimation statistique [Termes IGN] forêt tropicale [Termes IGN] gradient de pente [Termes IGN] image Landsat-TM [Termes IGN] modèle numérique de surface [Termes IGN] modèle RUSLE [Termes IGN] régression multiple [Termes IGN] risque naturel [Termes IGN] système d'information géographique Résumé : (Auteur) Estimation of soil loss using the Revised Universal Soil Loss Equation (rusle) has long been an active research topic, but its application in a large area is a challenge due to data availability and quality. In this study, the RUSLE model was used to evaluate soil erosion risk based on soil samples, a soil type map, digital elevation model (dem) data, and Landsat Thematic Mapper (tm) images. Multiple regression analysis was used to identify major factors influencing soil erosion risks. A regression model based on DEM-derived slope gradient and TM-derived fractional soil and vegetation images was developed to map soil erosion risk distribution in a forest ecosystem in Zhejiang, China. The developed method has the potential to quickly examine spatial distri-bution of soil erosion risks. This study provides a new insight for evaluating soil erosion risks in forest ecosystems with the integration of remote sensing and GIS. Numéro de notice : A2012-441 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.9.935 En ligne : https://doi.org/10.14358/PERS.78.9.935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31887 [article]

Application of time series Landsat images to examining land-use / land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 7 (July 2012) . - pp 747 - 755 Titre : Application of time series Landsat images to examining land-use / land-cover dynamic change Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; S. Hetrick, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 747 - 755 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse diachronique [Termes IGN] changement d'occupation du sol [Termes IGN] détection de changement [Termes IGN] élevage [Termes IGN] image Landsat [Termes IGN] Mato Grosso [Termes IGN] savane [Termes IGN] série temporelle [Termes IGN] surface cultivée [Termes IGN] surface imperméable Résumé : (Auteur) A hierarchical-based classification method was designed to develop time series land-use/land-cover datasets from Landsat images between 1977 and 2008 in Lucas do Rio Verde, Mato Grosso, Brazil. A post-classification comparison approach was used to examine land-use/land-cover change trajectories, which emphasis is on the conversions from vegetation or agropasture to impervious surface area, from vegetation to agropasture, and from agropasture to regenerat-ing vegetation. Results of this research indicated that increase in impervious surface area mainly resulted from the loss of cerrado in the initial decade of the study period and from loss of agricultural lands in the last two decades. Increase in agropasture was mainly at the expense of losing cerrado in the first two decades and relatively evenly from the loss of primary forest and cerrado in the last decade. When impervious surface area was less than approximately 40 km2 before 1999, impervious surface area was negatively related to cerrado and forest, and positively related to agropasture areas, but after impervious surface area reached 40 km2 in 1999, no obvious relationship exists between them. Numéro de notice : A2012-324 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358%2Fpers.78.7.747 En ligne : https://doi.org/10.14358%2Fpers.78.7.747 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31770 [article]

Application of time series Landsat images to examining land-use/land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 7 (July 2012) . - pp 747 - 755 Titre : Application of time series Landsat images to examining land-use/land-cover dynamic change Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; S. Hetrick, Auteur ; E. Moran, Auteur ; G. Li, Auteur Année de publication : 2012 Article en page(s) : pp 747 - 755 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] analyse diachronique [Termes IGN] classification ascendante hiérarchique [Termes IGN] détection de changement [Termes IGN] image Landsat [Termes IGN] Mato Grosso [Termes IGN] occupation du sol [Termes IGN] série temporelle [Termes IGN] surface imperméable [Termes IGN] utilisation du sol Résumé : (Auteur) A hierarchical-based classification method was designed to develop time series land-use/land-cover datasets from Landsat images between 1977 and 2008 in Lucas do Rio Verde, Mato Grosso, Brazil. A post-classification comparison approach was used to examine land-use/land-cover change trajectories, which emphasis is on the conversions from vegetation or agropasture to impervious surface area, from vegetation to agropasture, and from agropasture to regenerating vegetation. Results of this research indicated that increase in impervious surface area mainly resulted from the loss of cerrado in the initial decade of the study period and from loss of agricultural lands in the last two decades. Increase in agropasture was mainly at the expense of losing cerrado in the first two decades and relatively evenly from the loss of primary forest and cerrado in the last decade. When impervious surface area was less than approximately 40 km2 before 1999, impervious surface area was negatively related to cerrado and forest, and positively related to agropasture areas, but after impervious surface area reached 40 km2 in 1999, no obvious relationship exists between them. Numéro de notice : A2012-360 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358%2Fpers.78.7.747 En ligne : https://doi.org/10.14358%2Fpers.78.7.747 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31806 [article]

A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region / Dong Lu ; E. Moran ; et al. in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 26 - 38 Titre : A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; E. Moran, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 26 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse comparative [Termes IGN] bande C [Termes IGN] bande L [Termes IGN] classification dirigée [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar [Termes IGN] image Radarsat [Termes IGN] occupation du sol [Termes IGN] zone tropicale humide Résumé : (Auteur) This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected textural images and correlation coefficients between them were then used to determine the best combination of texture images for land-cover classification. Classification results based on different scenarios with maximum likelihood classifier were compared. Based on the identified best scenarios, different classification algorithms – maximum likelihood classifier, classification tree analysis, Fuzzy ARTMAP (a neural-network method), k-nearest neighbor, object-based classification, and support vector machine were compared for examining which algorithm was suitable for land-cover classification in the tropical moist region. This research indicates that the combination of radiometric images and their textures provided considerably better classification accuracies than individual datasets. The L-band data provided much better land-cover classification than C-band data but neither L-band nor C-band was suitable for fine land-cover classification system, no matter which classification algorithm was used. L-band data provided reasonably good classification accuracies for coarse land-cover classification system such as forest, succession, agropasture, water, wetland, and urban with an overall classification accuracy of 72.2%, but C-band data provided only 54.7%. Compared to the maximum likelihood classifier, both classification tree analysis and Fuzzy ARTMAP provided better performances, object-based classification and support vector machine had similar performances, and k-nearest neighbor performed poorly. More research should address the use of multitemporal radar data and the integration of radar and optical sensor data for improving land-cover classification. Numéro de notice : A2012-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31733 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2012041	SL	Revue	Centre de documentation	Revues en salle	Disponible

Pixel-based Minnaert correction method for reducing topographic effects on a Landsat 7 ETM+ Image / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 11 (November 2008)  

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Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data / Dong Lu in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)  

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Detection and substitution of clouds/hazes and their cast shadows on Ikonos images / Dong Lu in International Journal of Remote Sensing IJRS, vol 28 n°17-18 (September 2007)  

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Urban surface biophysical descriptors and land surface temperature variations / D. Weng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)  

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Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)  

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Change detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)  

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Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies / Q. Wenger in Remote sensing of environment, vol 89 n° 4 (29/02/2004)  

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