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Classification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis / R. Lawrence in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
[article]
Titre : Classification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis Type de document : Article/Communication Auteurs : R. Lawrence, Auteur ; A. Bunn, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 331 - 336 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification
[Termes IGN] décomposition d'image
[Termes IGN] image hyperspectrale
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] image PROBE
[Termes IGN] précision de la classification
[Termes IGN] sylvicultureRésumé : (Auteur) Classification tree analysis (CTA) provides an effective suite of algorithms for classifying remotely sensed data, but it has the limitations of (1) not searching for optimal tree structures and (2) being adversely affected by outliers, inaccurate training data, and unbalanced data sets. Stochastic gradient boosting (SGB) is a refinement of standard CTA that attempts to minimize these limitations by (1) using classification errors to iteratively refine the trees using a random sample of the training data and (2) combining the multiple trees iteratively developed to classify the data. We compared traditional CTA results to SGB for three remote sensing based data sets, an IKONOS image from the Sierra Nevada Mountains of California, a Probe-1 hyperspectral image from the Virginia City mining district of Montana, and a series of Landsat ETM+ images from the Greater Yellowstone Ecosystem (GYE). SGB improved the overall accuracy of the IKONOS classification from 84% to 95% and the Probe-1 classification from 83% to 93%. The worst performing classes using CTA exhibited the largest increases in class accuracy using SGB. A slight decrease in overall classification accuracy resulted from the SGB analysis of the Landsat data. Numéro de notice : A2004-200 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.01.007 En ligne : https://doi.org/10.1016/j.rse.2004.01.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26727
in Remote sensing of environment > vol 90 n° 3 (15/04/2004) . - pp 331 - 336[article]Topographic information of sand dunes as extracted from shading effects using Landsat images / N. Levin in Remote sensing of environment, vol 90 n° 2 (30/03/2004)
[article]
Titre : Topographic information of sand dunes as extracted from shading effects using Landsat images Type de document : Article/Communication Auteurs : N. Levin, Auteur ; Eyal Ben-Dor, Auteur ; A. Karnieli, Auteur Année de publication : 2004 Article en page(s) : pp 190 - 209 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] analyse comparative
[Termes IGN] angle azimutal
[Termes IGN] appariement d'histogramme
[Termes IGN] dénivelée
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] dune
[Termes IGN] extraction du relief
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image multitemporelle
[Termes IGN] image Terra-ASTER
[Termes IGN] Israël
[Termes IGN] ombre
[Termes IGN] pente
[Termes IGN] réflectanceRésumé : (Auteur) Topographic variations affect the reflectance properties of the Earth's surface and are often removed in remote sensing studies. especially when significant terrain variations exist. In this study, however, we show that shading effects assessed by Landsat can be treated as a signal that stores important topographic information, especially when the spectral characteristics of a surface are homogenous. The coastal transverse dunes of the Ashdod area, and the desert linear dunes of Nizzana (both located in Israel), were selected to investigate the above-mentioned idea. The dune heights in these areas are 10 m on average (relative to their surroundings) and have maximum slopes of 33°. An innovative method for extracting slope, aspect, and height data for sand dunes using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images was developed, based on the regularity and periodicity of dunes landscapes. Using two Landsat images representing different sun zenith and azimuth angles, reflectance values of each image were converted to cos(i) values (i =incident angle between the surface normal and the solar beam radiation), applying histogram matching methods. The slope and aspect of each pixel were determined as those that give the best prediction of the observed value of cos(i). Height profiles were then extracted, using simple trigonometric relationships. The accuracies of heights and slopes along selected profile lines were to the order of 1 m and 3°, respectively (at a spatial resolution of 15 m). Best results were obtained when the images included one from the summer and the other from the winter, corresponding to maximum difference in solar zenith and azimuth angles. Errors in heights were attributed to surface heterogeneity (e.g., presence of biogenic soil crusts in the rainy season), geometric correction errors, cast shadows, and Bidirectional Reflectance Distribution Function (BRDF) effects. Comparison to Advanced Thermal Emission and Reflection Radiometer (ASTER) 3D information showed that the proposed method is better in representing the topographic variation of the area than the digital elevation model (DEM) produced by ASTER. Numéro de notice : A2004-141 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.12.008 En ligne : https://doi.org/10.1016/j.rse.2003.12.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26668
in Remote sensing of environment > vol 90 n° 2 (30/03/2004) . - pp 190 - 209[article]Hyperion, Ikonos, ALI, and ETM+ sensors in the study of African rainforests / Prasad S. Thenkabail in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
[article]
Titre : Hyperion, Ikonos, ALI, and ETM+ sensors in the study of African rainforests Type de document : Article/Communication Auteurs : Prasad S. Thenkabail, Auteur ; E.A. Enclona, Auteur ; M.S. Ashton, Auteur ; C. Legg, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 23 - 43 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] Cameroun
[Termes IGN] carbone
[Termes IGN] carte de la végétation
[Termes IGN] classification
[Termes IGN] Congo (bassin)
[Termes IGN] forêt équatoriale
[Termes IGN] image EO1-ALI
[Termes IGN] image EO1-Hyperion
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] indice de végétation
[Termes IGN] masse végétale
[Termes IGN] occupation du solRésumé : (Auteur) The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and anced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semideciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes. The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors. When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed. Numéro de notice : A2004-127 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.11.018 En ligne : https://doi.org/10.1016/j.rse.2003.11.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26654
in Remote sensing of environment > vol 90 n° 1 (15/03/2004) . - pp 23 - 43[article]The spatial distribution of indigenous forest and its composition in the Wellington region, New Zealand, from ETM+ satellite imagery / J.R. Dymond in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
[article]
Titre : The spatial distribution of indigenous forest and its composition in the Wellington region, New Zealand, from ETM+ satellite imagery Type de document : Article/Communication Auteurs : J.R. Dymond, Auteur ; J.D. Shepherd, Auteur Année de publication : 2004 Article en page(s) : pp 116 - 125 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biodiversité
[Termes IGN] carte de la végétation
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] éclairement énergétique
[Termes IGN] Fagus (genre)
[Termes IGN] feuillu
[Termes IGN] forêt
[Termes IGN] image Landsat-ETM+
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Nouvelle-Zélande
[Termes IGN] Pinophyta
[Termes IGN] réflectance végétaleRésumé : (Auteur) In order to improve biodiversity management in the Wellington region of New Zealand, it is necessary to make an inventory of the indigenous forest-where is it, and what type is it? The single greatest impediment to making a spatially (i.e., 1:50,000 scale) and thematically detailed inventory from satellite imagery has been the topography of the three mountainous ranges in the Wellington region. The effective irradiance of incoming light varies with slope orientation, as does the proportion of light that is reflected towards the satellite (the bidirectional reflectance). In this paper, we show how satellite imagery may be processed to standardised spectral reflectance, which is a property of the vegetation alone, independent of sun position, slope, and view direction. Because of this, the use of automatic methods to map vegetation and provide spatially and thematically detailed maps is greatly simplified. Using this method, we produce a land-cover map of the Wellington region, with eight classes, to a classification accuracy of approximately 95%. We also show how the proportions of conifer, broadleaved, and beech trees may be determined for indigenous forest to provide a framework for forest-type inventory. Numéro de notice : A2004-131 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.11.013 En ligne : https://doi.org/10.1016/j.rse.2003.11.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26658
in Remote sensing of environment > vol 90 n° 1 (15/03/2004) . - pp 116 - 125[article]Delineation of forest/nonforest land use classes using nearest neighbor methods / R. Haapanen in Remote sensing of environment, vol 89 n° 3 (15/02/2004)
[article]
Titre : Delineation of forest/nonforest land use classes using nearest neighbor methods Type de document : Article/Communication Auteurs : R. Haapanen, Auteur ; A.R. Ek, Auteur ; Andrew O. Finley, Auteur ; M.E. Bauer, Auteur Année de publication : 2004 Article en page(s) : pp 265 - 271 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification barycentrique
[Termes IGN] délimitation
[Termes IGN] forêt
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] occupation du solRésumé : (Auteur) The k-Nearest Neighbor (kNN) method of forest attribute estimation and mapping has become an integral part of national forest inventory methods in Finland in the last decade. This success of kNN method in facilitating multisource inventory has encouraged trials of the method in the Great Lakes Region of the United States. Here we present results from applying the method to Landsat TM and ETM+ data and land cover data collected by the USDA Forest Service's Forest Inventory and Analysis (FIA) program. In 1999, the FIA program in the state of Minnesota moved to a new annual inventory design to reach its targeted full sampling intensity over a 5-year period. This inventory design also utilizes a new 4-subplot cluster plot configuration. Using this new plot design together with 1 year of field plot observations, the kNN classification of forest/nonforest/water achieved overall accuracies ranging from 87% to 91%. Our analysis revealed several important behavioral features associated with kNN classification using the new FIA sample plot design. Results demonstrate the simplicity and utility of using kNN to produce FIA defined forest/nonforest/water classifications. Numéro de notice : A2004-017 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.10.002 En ligne : https://doi.org/10.1016/j.rse.2003.10.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26545
in Remote sensing of environment > vol 89 n° 3 (15/02/2004) . - pp 265 - 271[article]Application of stereoscopic satellite images for studying Quaternary tectonics in arid regions / B. Fu in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)PermalinkLineament detection on Mount Cameroon during the 1999 volcanic eruptions using Landsat ETM / E.E. Nama in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)PermalinkEvaluation of the runoff potential in high relief semi-arid regions using remote sensing data: application to Bolivia / T. Ouattara in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)PermalinkMapping rice field anopheline breeding habitats in Mali, West Africa, using Landsat ETM+ sensor data / M.A. Diuk-Wasser in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)PermalinkComparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS / W.B. Cohen in Remote sensing of environment, vol 88 n° 3 (15/12/2003)PermalinkImprovements in land use mapping for irrigated agriculture from satellite sensor data using a multi-stage maximum likelihood classification / I.A. El-Magd in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)PermalinkModeling urban population growth from remotely sensed imagery and TIGER GIS road data / F. Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkUrban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data / L. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkImpact of topographic normalization on land-cover classification accuracy / S.R. Hale in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 7 (July 2003)PermalinkComparison of Earth observing-1 ALI and Landsat ETM+ for crop identification and yield prediction in Mexico / D.B. Lobell in IEEE Transactions on geoscience and remote sensing, vol 41 n° 6 (June 2003)PermalinkEvaluation of airborne video data for land-cover classification accuracy assessment / I.T. Grierson in Geocarto international, vol 18 n° 2 (June - August 2003)PermalinkProcessing Hyperion and ALI for forest classification / D.G. Goodenough in IEEE Transactions on geoscience and remote sensing, vol 41 n° 6 (June 2003)PermalinkSpace mapping the arctic tundra / Gita Laidler in GEO:connexion, vol 2 n° 5 (may 2003)PermalinkAnalyse multidate et multiresolution pour l'étude de la productivité végétale en zone climatique tempérée : bassin versant "arroyo Sanchez", Uruguay / F. Anno in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 170 (Avril 2003)PermalinkA comparative analysis of scanned maps and imagery for mapping applications / Costas Armenakis in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 5-6 (April - May 2003)PermalinkScale dependence in multitemporal mapping of forest fragmentation in Bolivia: implications for explaining temporal trends in landscape ecology and applications to biodiversity conservation / A.C. Millington in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 4 (February - March 2003)PermalinkAdaptation du modèle orbitographique Spot 4 aux satellites / J.C. Clerget (2002)PermalinkMapping vegetation species succession in a mountainous grassland ecosystem using Landsat, ASTER MI, and Sentinel-2 data / Efosa Gbenga Adagbasa in Plos one, vol 17 n° 1 (January 2022)PermalinkMapping wildfire burns severity in southern California forests and shrub lands using enhanced Thematic Mapper imagery / J. Rogan in Geocarto international, vol 16 n° 4 (December 2001 - February 2002)PermalinkImproved classification of small-scale urban watersheds, using Thematic Mapper simulator data / M. Owe in International Journal of Remote Sensing IJRS, vol 5 n° 5 (October 1984)Permalink