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Estimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis / S.M. de Jong in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)
[article]
Titre : Estimating spatial patterns of rainfall interception from remotely sensed vegetation indices and spectral mixture analysis Type de document : Article/Communication Auteurs : S.M. de Jong, Auteur ; V.G. Jetten, Auteur Année de publication : 2007 Article en page(s) : pp 529 - 545 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] érosion hydrique
[Termes IGN] évapotranspiration
[Termes IGN] image HYMAP
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] Leaf Area Index
[Termes IGN] pluie
[Termes IGN] ruissellementRésumé : (Auteur) Rainfall interception by vegetation is an important factor in the water balance. Consequently, rainfall interception should also be an important factor in models simulating processes such as evaporation, transpiration, surface runoff, soil erosion, and crop growth. In practice, however, it is difficult to make quantitative assessments of the spatial and temporal distribution of rainfall interception loss at the catchment level, for instance, and to make these values available as model input. In this paper, we present a novel method using earth observation images to estimate local quantitative values of rainfall interception loss. Leaf Area Index (LAI) and fractional vegetation cover per grid cell are important process variables for rainfall interception. These two variables are estimated from images using spectral vegetation indices and using spectral mixture analysis, respectively. Relations between canopy storage capacity and LAI exist for several plant species and vegetation types, but limited data are found on crops, and more research is needed in this field. The new method is explained and illustrated for a study area in southern France with a variety of land-cover types. It is found to be a valuable and practical approach to quantitatively assess spatial patterns of interception loss for given rainfall events. Copyright Taylor & Francis Numéro de notice : A2007-135 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810601064884 En ligne : https://doi.org/10.1080/13658810601064884 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28498
in International journal of geographical information science IJGIS > vol 21 n° 5 (may 2007) . - pp 529 - 545[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-07031 RAB Revue Centre de documentation En réserve L003 Disponible 079-07032 RAB Revue Centre de documentation En réserve L003 Disponible Urban surface biophysical descriptors and land surface temperature variations / D. Weng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)
[article]
Titre : Urban surface biophysical descriptors and land surface temperature variations Type de document : Article/Communication Auteurs : D. Weng, Auteur ; Dong Lu, Auteur ; B. Liang, Auteur Année de publication : 2006 Article en page(s) : pp 1275 - 1286 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] albedo
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] émission thermique
[Termes IGN] flore locale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indianapolis
[Termes IGN] milieu urbain
[Termes IGN] morphologie urbaine
[Termes IGN] occupation du sol
[Termes IGN] surface imperméable
[Termes IGN] température de surface
[Termes IGN] variable biophysique (végétation)
[Termes IGN] zone urbaineRésumé : (Auteur) In remote sensing studies of land surface temperatures (LST), thematic land-use and land-cover (LULC) data are frequently employed for simple correlation analyses between LULC types and their thermal signatures. Development of quantitative surface descriptors could improve our capabilities for modeling urban thermal landscapes and advance urban climate research. This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying the urban landscape in Indianapolis, Indiana. A Landsat Enhanced Thematic Mapper Plus image of the study area, acquired on 22 June 2002, was spectrally unmixed into four fraction endmembers, namely, green vegetation, soil, high and low albedo. Impervious surface was then computed from the high and low albedo images. A hybrid classification procedure was developed to classify the fraction images into seven land-use and land-cover classes. Next, pixel-based LST measurements were related to urban surface biophysical descriptors derived from spectral mixture analysis (SMA). Correlation analyses were conducted to investigate land-cover based relationships between LST and impervious surface and green vegetation fractions for an analysis of the causes of LST variations. Results indicate that fraction images derived from SMA were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables such as vegetation abundance, soil, and impervious surface. An examination of LST variations within census block groups and their relationships with the compositions of LULC types, biophysical descriptors, and other relevant spatial data shows that LST possessed a weaker relation with the LULC compositions than with other variables (including urban biophysical descriptors, remote sensing biophysical variables, GIS-based impervious surface variables, and population density). Further research should be directed to refine spectral mixture modeling. The use of multi-temporal remote sensing data for urban time-space modeling and comparison of urban morphology in different geographical settings are also feasible. Copyright ASPRS Numéro de notice : A2006-493 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.11.1275 En ligne : https://doi.org/10.14358/PERS.72.11.1275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28217
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 11 (November 2006) . - pp 1275 - 1286[article]Comparative analysis of urban reflectance and surface temperature / C. Small in Remote sensing of environment, vol 104 n° 2 (30 September 2006)
[article]
Titre : Comparative analysis of urban reflectance and surface temperature Type de document : Article/Communication Auteurs : C. Small, Auteur Année de publication : 2006 Article en page(s) : pp 168 - 189 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] données de terrain
[Termes IGN] données hétérogènes
[Termes IGN] image Landsat-ETM+
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] réalité de terrain
[Termes IGN] réflectance urbaine
[Termes IGN] température au sol
[Termes IGN] variabilitéRésumé : (Auteur) Urban environmental conditions are strongly dependent on the biophysical properties and radiant thermal field of the land cover elements in the urban mosaic. Observations of urban reflectance and surface temperature provide valuable constraints on the physical properties that are determinants of mass and energy fluxes in the urban environment. Consistencies in the covariation of surface temperature with reflectance properties can be parameterized to represent characteristics of the surface energy flux associated with different land covers and physical conditions. Linear mixture models can accurately represent Landsat ETM+ reflectances as fractions of generic spectral endmembers that correspond to land surface materials with distinct physical properties. Modeling heterogeneous land cover as mixtures of rock and/or soil Substrate, Vegetation and non-reflective Dark surface (SVD) generic endmembers makes it possible to quantify the dependence of aggregate surface temperature on the relative abundance of each physical component of the land cover, thereby distinguishing the effects of vegetation abundance, soil exposure, albedo and shadowing. Comparing these covariations in a wide variety of urban settings and physical environments provides a more robust indication of the global variability in these parameter spaces than could be inferred from a single study area. A comparative analysis of 24 urban areas and their non-urban peripheries illustrates the variability in the urban thermal fields and its dependence on biophysical land surface components. Contrary to expectation, moderate resolution intra-urban variations in surface temperature are generally as large as regional surface heat island signatures in these urban areas. Many of the non-temperate urban areas did not have surface heat island signatures at all. However, the multivariate distributions of surface temperature and generic endmember fractions reveal consistent patterns of thermal fraction covariation resulting from land cover characteristics. The Thermal-Vegetation (TV) fraction space illustrates the considerable variability in the well-known inverse correlation between surface temperature and vegetation fraction at moderate ( Numéro de notice : A2006-402 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.10.029 En ligne : https://doi.org/10.1016/j.rse.2005.10.029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28126
in Remote sensing of environment > vol 104 n° 2 (30 September 2006) . - pp 168 - 189[article]Subpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization / S. Lee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 6 (June 2006)
[article]
Titre : Subpixel analysis of Landsat ETM/sup +/ using self-organizing map (SOM) neural networks for urban land cover characterization Type de document : Article/Communication Auteurs : S. Lee, Auteur ; R.G. Lathrop, Auteur Année de publication : 2006 Article en page(s) : pp 1642 - 1654 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse infrapixellaire
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] apprentissage automatique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de Kohonen
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] surface imperméable
[Termes IGN] végétation
[Termes IGN] zone urbaineRésumé : (Auteur) This paper examines the subpixel analysis of Landsat ETM+ data to estimate the percent cover of impervious surface, lawn, and woody tree cover in typical urban/suburban land-scapes. By combining Self-Organizing Map (SOM), Learning Vector Quantization (LVQ), and Gaussian Mixture Model (GMM) methods, the posterior probability of the various land cover components were estimated for each pixel as a means of sub-pixel analysis. The estimation of impervious surface and the differentiation of urban vegetation grass versus woody tree coverage the main objectives of this paper. Overall, the output estimates compared favorably with those obtained using higher spatial resolution aerial photograph and IKONOS satellite image and traditional hard classification techniques as independent reference. The SOM-LVQ-GMM mode! showed a moderate degree of similarity in the estimates of impervious surface [root mean-square errors (RMSEs) of Numéro de notice : A2006-261 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.869984 En ligne : https://doi.org/10.1109/TGRS.2006.869984 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27988
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 6 (June 2006) . - pp 1642 - 1654[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06061 RAB Revue Centre de documentation En réserve L003 Disponible Incorporating remote sensing information in modelling house values: a regression tree approach / D. Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 2 (February 2006)
[article]
Titre : Incorporating remote sensing information in modelling house values: a regression tree approach Type de document : Article/Communication Auteurs : D. Yu, Auteur ; C. Wu, Auteur Année de publication : 2006 Article en page(s) : pp 129 - 138 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de la valeur
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] bati
[Termes IGN] coefficient de corrélation
[Termes IGN] erreur moyenne arithmétique
[Termes IGN] habitat (urbanisme)
[Termes IGN] image Landsat-ETM+
[Termes IGN] Milwaukee
[Termes IGN] régression linéaire
[Termes IGN] zone urbaineRésumé : (Auteur) This paper explores the possibility of incorporating remote sensing information in modeling house values in the City of Milwaukee, Wisconsin, U.S.A. In particular, a Landsat ETM+ image was utilized to derive environmental characteristics, including the fractions of vegetation, impervious surface, and soil, with a linear spectral mixture analysis approach. These environmental characteristics, together with house structural attributes, were integrated to house value models. Two modeling techniques, a global OLS regression and a regression tree approach, were employed to build the relationship between house values and house structural and environmental characteristics. Analysis of results indicates that environmental characteristics generated from remote sensing technologies have strong influences on house values, and the addition of them improves house value modeling performance significantly. Moreover, the regression tree model proves as a better alternative to the OLS regression models in terms of predicting accuracy. In particular, based on the testing dataset, the mean average error (MAE) and relative error (RE) dropped from 0.202 and 0.434 for the OLS model to 0.134 and 0.280 for the regression tree model, while the correlation coefficient between the predicted and observed values increased from 0.903 to 0.960. Further, as a nonparametric and local model, the regression tree method alleviates the problems with the OLS techniques and provides a means in delineating urban housing submarkets. Numéro de notice : A2006-037 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.14358/PERS.72.2.129 En ligne : https://doi.org/10.14358/PERS.72.2.129 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27764
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 2 (February 2006) . - pp 129 - 138[article]Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA / L. Li in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkMapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery / J. Falcone in Geocarto international, vol 20 n° 4 (December 2005 - February 2006)PermalinkSub-pixel estimation of urban land cover components with linear mixture model analysis and Landsat Thematic Mapper imagery / S. Lee in International Journal of Remote Sensing IJRS, vol 26 n° 22 (November 2005)PermalinkImages, modèles et biomasse immergée : cartographie des herbiers de zostères en Camargue à partir d'images SPOT-5 / C. Puech in Revue internationale de géomatique, vol 15 n° 2 (juin – août 2005)PermalinkA land cover distribution composite image from coarse spatial resolution images using an unmixing method / T.M. Uenishi in International Journal of Remote Sensing IJRS, vol 26 n° 5 (March 2005)PermalinkA global analysis urban reflectance / C. Small in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)PermalinkNormalized spectral mixture analysis for monitoring urban composition using ETM+ imagery / C. Wu in Remote sensing of environment, vol 93 n° 4 (15/12/2004)PermalinkA comparison of error metrics and constraints for multiple endmember spectral analysis and spectral angle mapper / P.E. Dennison in Remote sensing of environment, vol 93 n° 3 (15/11/2004)PermalinkThe contribution of the sources separation method in the decomposition of mixed pixels / Mohamed Saber Naceur in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)PermalinkSpectral 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)PermalinkUrban land-cover change analysis in central Puget Sound / M. Alberti in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkChange detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkReducing signature variability in unmixing coastal marsh Thematic Mapper scenes using spectral indices / A.S. Rogers in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkEstimation of subpixel target size for remotely sensed imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)PermalinkUsing Lidar and effective LAI data to evaluate Ikonos and Landsat 7 ETM+ vegetation cover estimates in a ponderosa pine forest / X. Chen in Remote sensing of environment, vol 91 n° 1 (15/05/2004)PermalinkLinear mixture analysis-based compression for hyperspectral image analysis / Q. Du in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)PermalinkEstimation 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)PermalinkSnow-cover mapping in forest by constrained linear spectral unimixing of MODIS data / D. Vikhamar in Remote sensing of environment, vol 88 n° 3 (15/12/2003)PermalinkHigh spatial resolution spectral mixture analysis of urban reflectance / C. Small in Remote sensing of environment, vol 88 n° 1 (30/11/2003)PermalinkMapping forest degradation in the Eastern Amazon SPOT 4 through spectral mixture models / Cristiano B. Souza in Remote sensing of environment, vol 87 n° 4 (15/11/2003)Permalink