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Land cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)
[article]
Titre : Land cover characterization of temperate east Asia using multi-temporal vegetation sensor data Type de document : Article/Communication Auteurs : S.H. Boles, Auteur ; X. Xiao-Ping, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 477 - 489 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] Asie orientale
[Termes IGN] base de données d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] Enhanced vegetation index
[Termes IGN] image Aqua-MODIS
[Termes IGN] image multitemporelle
[Termes IGN] image SPOT-Végétation
[Termes IGN] image Terra-MODIS
[Termes IGN] occupation du sol
[Termes IGN] photo-identification
[Termes IGN] zone tempéréeRésumé : (Auteur) Temperate East Asia (TEA) is characterized by diverse land cover types, including forest and agricultural lands, one of the world's largest temperate grasslands, and extensive desert and barren landscapes. In this paper, we explored the potential of SPOT-4 VEGETATION (VGT) data for the classification of land cover types in TEA. An unsupervised classification was performed using multi-temporal (March November 2000) VGT-derived spectral indices (Land Surface Water Index [LSWI] and Enhanced Vegetation Index [EVI]) to generate a land cover map of TEA (called VGT-TEA). Land cover classes from VGT-TEA were aggregated to broad, general class types, and then compared and validated with classifications derived from fine-resolution (Landsat) data. VGT-TEA produced reasonable results when compared to the Landsat products. Analysis of the seasonal dynamics of LSWI and EVI allows for the identification of distinct growth patterns between different vegetation types. We suggest that LSWI seasonal curves can be used to define the growing season for temperate deciduous vegetation, including grassland types. Seasonal curves of EVI tend to have a slightly greater dynamic range than LSWI during the peak growing season and can be useful in discriminating between vegetation types. By using these two complementary spectral indices, VGT data can be used to produce timely and detailed land cover and phenology maps with limited ancillary data needed. Numéro de notice : A2004-191 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.01.016 En ligne : https://doi.org/10.1016/j.rse.2004.01.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26718
in Remote sensing of environment > vol 90 n° 4 (30/04/2004) . - pp 477 - 489[article]Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture / D. Haboudane in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
[article]
Titre : Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture Type de document : Article/Communication Auteurs : D. Haboudane, Auteur ; J.R. Miller, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 337 - 352 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture de précision
[Termes IGN] analyse comparative
[Termes IGN] blé (céréale)
[Termes IGN] chlorophylle
[Termes IGN] cultures
[Termes IGN] données de terrain
[Termes IGN] Glycine max
[Termes IGN] Green Leaf Area Index
[Termes IGN] image CASI
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] maïs (céréale)
[Termes IGN] modèle de transfert radiatif
[Termes IGN] prévision
[Termes IGN] réflectance végétaleRésumé : (Auteur) A growing number of studies have focused on evaluating spectral indices in terms of their sensitivity to vegetation biophysical parameters, as well as to external factors affecting canopy reflectance. In this context, leaf and canopy radiative transfer models are valuable for modeling and understanding the behavior of such indices. In the present work, PROSPECT and SAILH models have been used to simulate a wide range of crop canopy reflectances in an attempt to study the sensitivity of a set of vegetation indices to green leaf area index (LAI), and to modify some of them in order to enhance their responsivity to LAI variations. The aim of the paper was to present a method for minimizing the effect of leaf chlorophyll content on the prediction of green LAI, and to develop new algorithms that adequately predict the LAI of crop canopies. Analyses based on both simulated and real hyperspectral data were carried out to compare performances of existing vegetation indices (Normalized Difference Vegetation Index [NDVI], Renormalized Difference Vegetation Index [RDVI], Modified Simple Ratio [MSR], Soil-Adjusted Vegetation Index [SAVI], Soil and Atmospherically Resistant Vegetation Index [SARVI], MSAVI, Triangular Vegetation Index [TVI], and Modified Chlorophyll Absorption Ratio Index [MCARI]) and to design new ones (MTVII, MCARII, MTV12, and MCAR12) that are both less sensitive to chlorophyll content variations and linearly related to green LAI. Thorough analyses showed that the above existing vegetation indices were either sensitive to chlorophyll concentration changes or affected by saturation at high LAI levels. Conversely, two of the spectral indices developed as a part of this study, a modified triangular vegetation index (MTV12) and a modified chlorophyll absorption ratio index (MCAR12), proved to be the best predictors of green LAI. Related predictive algorithms were tested on CASI (Compact Airborne Spectrographic Imager) hyperspectral images and, then, validated using ground truth measurements. The latter were collected simultaneously with image acquisition for different crop types (soybean, corn, and wheat), at different growth stages, and under various fertilization treatments. Prediction power analysis of proposed algorithms based on MCAR12 and MTV12 resulted in agreements between modeled and ground measurement of non-destructive LAI, with coefficients of determination (r) being 0.98 for soybean, 0.89 for com, and 0.74 for wheat. The corresponding RMSE for LAI were estimated at 0.28, 0.46, and 0.85, respectively. Numéro de notice : A2004-201 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.12.013 En ligne : https://doi.org/10.1016/j.rse.2003.12.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26728
in Remote sensing of environment > vol 90 n° 3 (15/04/2004) . - pp 337 - 352[article]Tree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI / J. Krishnaswamy in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)
[article]
Titre : Tree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI Type de document : Article/Communication Auteurs : J. Krishnaswamy, Auteur ; M.C. Kiran, Auteur ; K.N. Ganeshaiah, Auteur Année de publication : 2004 Article en page(s) : pp 1185 - 1205 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre (mathématique)
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] écosystème
[Termes IGN] Kappa de Cohen
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] végétationRésumé : (Auteur) Many vegetation classification strategies in tropical ecosystems involving conventional image processing of original satellite imagery bands require considerable prior site knowledge, statistical assumptions, and are difficult, expensive and inconsistent. In this paper we show that the intra-annual variation and rates of change in NDVI for different parts of a large forest area in combination with rules derived from a tree model can be used for detailed vegetation mapping. We used three-date NDVI data for the Biligiri Rangaswamy Temple Wildlife Sanctuary in Karnataka, southern India comprising mean NDVI, coefficient of variation (CV) and two NDVI change vectors corresponding to intraseasonal NDVI differences. A rule-based classification using a tree model was developed at two levels. The overall kappa statistic is 0.61 at level 1 classification. indicating a strong correspondence with the raster version of the available vector reference map based on ground data, even though the two maps are not strictly comparable. Several limitations of the available reference map have been highlighted by the new technique, especially the absence of ecotones. At level two the tree model map has provided detailed classification of dry deciduous forests and new classes not available in the reference map. The method in combination with reference data also provides a framework for fuzzy classification. This technique offers a relatively simple cost-effective alternative to existing classification strategies, especially for areas with diverse evergreen and deciduous vegetation elements. Numéro de notice : A2004-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000149989 En ligne : https://doi.org/10.1080/0143116031000149989 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26615
in International Journal of Remote Sensing IJRS > vol 25 n° 6 (March 2004) . - pp 1185 - 1205[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04061 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Airborne measurement of hot spot reflectance signatures / F. Camacho-De Coca in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
[article]
Titre : Airborne measurement of hot spot reflectance signatures Type de document : Article/Communication Auteurs : F. Camacho-De Coca, Auteur ; François-Marie Bréon, Auteur ; M. Leroy, Auteur ; F.J. Garcia-Haro, Auteur Année de publication : 2004 Article en page(s) : pp 63 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] ARAT
[Termes IGN] composition colorée
[Termes IGN] couvert végétal
[Termes IGN] cultures
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] Espagne
[Termes IGN] image DAIS
[Termes IGN] image en couleur composée
[Termes IGN] image HYMAP
[Termes IGN] image POLDER
[Termes IGN] Leaf Area Index
[Termes IGN] réflectance végétale
[Termes IGN] tâche claire
[Termes IGN] transfert radiatifRésumé : (Auteur) The so-called hot spot is a fine directional signature of the surface reflectance observed for phase angles close to zero. In this paper, we analyze and discuss several such signatures acquired from the airborne POLDER and HyMap instruments during the DAISEX'99 campaign over agricultural crops. The observed signatures are very similar to those acquired from space at a resolution of several tens of kilometers [J. Geophys. Res. 107 (2002)], which provides further evidence that the hot spot is a scale-free feature. The hot spots can be fitted by a twoparameter function (amplitude and width) of the phase angle derived from canopy radiative transfer modeling. The model predicts that the amplitude is directly related to the leaf reflectance, while the width is a function of the canopy structure. The retrieved leaf reflectance values over a wide spectral range are in very good agreement with noncoincident laboratory measurement. The retrieved half widths are on the order of 1° with no significant variability between the analyzed targets. There is an apparent spectral variability in the half width, a feature in contradiction with the modeling, although the variations are not larger than the uncertainties. Numéro de notice : A2004-128 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.11.019 En ligne : https://doi.org/10.1016/j.rse.2003.11.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26655
in Remote sensing of environment > vol 90 n° 1 (15/03/2004) . - pp 63 - 75[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]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)PermalinkMonitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data / F. Maselli in Remote sensing of environment, vol 89 n° 4 (29/02/2004)PermalinkEstimating fragmentation effects on simulated forest net primary productivity derived from satellite imagery / Nicholas C. Coops in International Journal of Remote Sensing IJRS, vol 25 n° 4 (February 2004)PermalinkImpacts of hydrologic soil properties on drought detection with MODIS thermal data / S. Park in Remote sensing of environment, vol 89 n° 1 (15/01/2004)PermalinkToward universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements / G. Le Maire in Remote sensing of environment, vol 89 n° 1 (15/01/2004)PermalinkHyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data / N. Oppelt in International Journal of Remote Sensing IJRS, vol 25 n° 1 (January 2004)PermalinkVegetation/SPOT: an operational mission for the Earth monitoring, presentation of new standard product / P. Maisongrande in International Journal of Remote Sensing IJRS, vol 25 n° 1 (January 2004)PermalinkCaractérisation par télédétection des paysages favorables aux culicoides vecteurs de la fièvre catarrhale ovine dans le bassin méditerranéen / H. Guis (2004)PermalinkTraitement des données de télédétection / Michel-Claude Girard (2004)PermalinkIntercalibration of vegetation indices from different sensor systems / M.D. Steven in Remote sensing of environment, vol 88 n° 4 (30/12/2003)Permalink