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Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data / K. Gallo in Remote sensing of environment, vol 99 n° 3 (30/11/2005)
[article]
Titre : Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data Type de document : Article/Communication Auteurs : K. Gallo, Auteur ; L. Ji, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 221 - 231 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] capteur (télédétection)
[Termes IGN] image NOAA-AVHRR
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation IndexRésumé : (Auteur) The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/ Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 andNOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. Numéro de notice : A2005-458 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.08.014 En ligne : https://doi.org/10.1016/j.rse.2005.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27594
in Remote sensing of environment > vol 99 n° 3 (30/11/2005) . - pp 221 - 231[article]Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm / K.M. Bergen in Remote sensing of environment, vol 97 n° 4 (15/09/2005)
[article]
Titre : Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm Type de document : Article/Communication Auteurs : K.M. Bergen, Auteur ; Daniel G. Brown, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 434 - 446 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse diachronique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] données hétérogènes
[Termes IGN] Etats-Unis
[Termes IGN] forêt
[Termes IGN] image NOAA-AVHRR
[Termes IGN] occupation du sol
[Termes IGN] photographie aérienneRésumé : (Auteur) A ca.1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S.. To derive useful land-cover change data using a heterogeneous dataset and to validate our results, we a) stratified the classification using predefined ecoregions, b) developed statistical relationships by ecoregion between land-cover proportions derived from the 1980 national-level classification and aggregate statistical data that were available in times series for all regions in the U.S., c) classified multi-temporal AVHRR data using a process that constrained the results to the estimated proportions of land covers in ecoregions within a multi-objective land allocation (MOLA) procedure, d) interpreted land cover from a sample of a aerial photographs from 2000, following the protocols used to land-cover change results for the MOLA method with an unsupervised classification alone. Overall accuracies for the 2000 MOLA and unsupervised land-cover classifications were 85% and 82% respectively. On average, the 1980-2000 land-cover changes RMSEs were one order of magnitude lower using the MOLA methods compared with those based on the unsupervised data. Numéro de notice : A2005-394 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.03.016 En ligne : https://doi.org/10.1016/j.rse.2005.03.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27530
in Remote sensing of environment > vol 97 n° 4 (15/09/2005) . - pp 434 - 446[article]Separating surface emissivity and temperature using two-channel spectral indices and emissivity composites and comparison with a vegetation fraction method / P. Dash in Remote sensing of environment, vol 96 n° 1 (15/05/2005)
[article]
Titre : Separating surface emissivity and temperature using two-channel spectral indices and emissivity composites and comparison with a vegetation fraction method Type de document : Article/Communication Auteurs : P. Dash, Auteur ; F. Göttsche, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] correction atmosphérique
[Termes IGN] données de terrain
[Termes IGN] données météorologiques
[Termes IGN] éclairement énergétique
[Termes IGN] emissivité
[Termes IGN] erreur
[Termes IGN] image NOAA-AVHRR
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] radiance
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] saison
[Termes IGN] simulation de surface
[Termes IGN] température au sol
[Termes IGN] thermal infrared multispectral scannerRésumé : (Auteur) The temperature-independent thermal infrared spectral indices (TISI) method is employed for the separation of land surface temperature (LST) and emissivity from surface radiances (atmospherically corrected satellite data). The daytime reflected solar irradiance and the surface emission at ~3.8 um have comparable magnitudes. Using surface radiances and a combination of day-night 2-channel TISI ratios, the ~3.8 um reflectivity is derived. For implementing the TISI method, coefficients for NOAA 9-16 AVHRR channels are obtained. A numerical analysis with simulated surface radiances shows that for most surface types (showing nearly Lambertian behavior) the achievable accuracy is ~0.005 for emissivity (AVHRR channel-5) and ~1.5 K for LST. Data from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used for calculation of atmospheric attenuation. Comparisons are made over a part of central Europe on two différent dates (seasons). Clouds pose a major problem to surface observations; hence, monthly emissivity composites are derived. Additionally, using TISI-based monthly composites of emissivities, a normalized difference vegetation index (NDVI)-based method is tuned to the particular study area and the results are intercompared. Once the coefficients are known, the NDVI method is easily implemented but holds well only for vegetated areas. The error of the NDVI-based emissivities (with respect to the TISI results) ranges between -0.038 and 0.032, but for vegetated areas the peak of the error-histogram is at ~0.002. The algorithm for retrieving emissivity via TISI was validated with synthetic data. Due to the different spatial scales of satellite and surface measurements and the lack of homogeneous areas, which are representative for low-resolution pixels and ground measurements, ground-validation is a daunting task. However, for operational products ground-truth validation is necessary. Therefore, also an approach to identify suitable validation sites for meteorological satellite products in Europe is described. Numéro de notice : A2005-209 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.12.023 En ligne : https://doi.org/10.1016/j.rse.2004.12.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27346
in Remote sensing of environment > vol 96 n° 1 (15/05/2005) . - pp 1 - 17[article]Calculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: a case study in the Marsabit district Kenya / K. Tachiiri in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 3 (May 2005)
[article]
Titre : Calculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: a case study in the Marsabit district Kenya Type de document : Article/Communication Auteurs : K. Tachiiri, Auteur Année de publication : 2005 Article en page(s) : pp 103 - 114 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] correction atmosphérique
[Termes IGN] image NOAA-AVHRR
[Termes IGN] Kenya
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression linéaire
[Termes IGN] Total ozone mapping spectrometerRésumé : (Auteur) A detailed atmospheric correction method for NOAA/AVHRR images using 6S code, easily accessible data sets, and the images themselves is proposed. The parameters that 6S requires (aerosol optical depth, precipitable water, ozone content, and elevation) were obtained using data from the images, the Total Ozone Mapping Spectrometer, and the GTOP030 elevation data set, with reference to existing studies. The proposed methodology is validated through a case study of the Marsabit District, northern Kenya, which includes a broad range of precipitation, elevation, and vegetation types. The Normalized Difference Vegetation Index (NDVI) of desert, grassland, and forested areas from August 1987 to August 1988 was calculated after making the atmospheric correction. The intercept of the regression line, between the reflectance of before and after correction, is almost the same for each land cover type., while the slope is around 1.7 to 1.8 for grassland/bushland, it is smaller in the desert, where the range of the NDVI is limited. The NDVI in dense vegetation is more sensitive to the atmospheric correction, which is a result of the effect of path radiance. After the atmospheric correction, the range of NDVI increased, with the characteristic that the greater the NDVI, the larger was the atmospheric effect. In the case study, as well, the NDVI increased after the atmospheric correction, especially in pixels with initially high NDVI. A more detailed, entirely pixel-by-pixel, atmospheric correction requires individual pixel information for aerosol optical depth and precipitable water. This will be possible using data collected by the recent sensors such as MODIS. Copyright ISPRS Numéro de notice : A2005-227 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2004.09.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2004.09.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27364
in ISPRS Journal of photogrammetry and remote sensing > vol 59 n° 3 (May 2005) . - pp 103 - 114[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-05011 SL Revue Centre de documentation Revues en salle Disponible Land covers change detection at coarse spatial scales based on iterative estimation and previous state information / Sylvie Le Hégarat-Mascle in Remote sensing of environment, vol 95 n° 4 (30/04/2005)
[article]
Titre : Land covers change detection at coarse spatial scales based on iterative estimation and previous state information Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; Catherine Ottle, Auteur ; Christiane Guérin, Auteur Année de publication : 2005 Article en page(s) : pp 464 - 479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] bassin hydrographique
[Termes IGN] chaîne de Markov
[Termes IGN] détection de changement
[Termes IGN] estimation statistique
[Termes IGN] image à basse résolution
[Termes IGN] image NOAA-AVHRR
[Termes IGN] image SPOT-Végétation
[Termes IGN] itération
[Termes IGN] occupation du sol
[Termes IGN] pixel
[Termes IGN] Saône (rivière)
[Termes IGN] sylvicultureRésumé : (Auteur) This study focuses on the use of coarse spatial resolution (CR, pixel size about 1kM2) remote sensing data for land cover change detection and qualification. Assuming the linear mixing model for CR pixels, the problem is that both the multitemporal class feature and the pixel composition in terms of classes are unknown. The proposed algorithm is then based on the iterative alternate estimation of each unknown variable. At each iteration, the class features are estimated, thanks to the knowledge of the composition of so pixels, and then the pixel composition is re-estimated knowing the class features. The subset of known composition pixels is the sub of pixels where no change has occurred, i.e. the previous land cover map is still valid. It is derived automatically by removing at each iteration the pixels where the new composition estimation disagrees with the former one. Finally, for the final estimation of the pixel composition, a Markovian chain model is used to guide the solution, i.e. the previous land cover map is used as a 'reminder' 'memory' term. This approach has been first validated using simulated data with different spatial resolution ratios. Then, the detection of forest change with SPOT-VGT-S 10 has been considered as an actual application case. Finally, the method has been applied to change detection on the Val de Saône watershed between the 1980s and 2000. The results obtained from three coarse resolution series, NOAA/AVHRR, SPOT/VGT-S 10 and SPOT/VGT-P, have been compared. Numéro de notice : A2005-187 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.01.011 En ligne : https://doi.org/10.1016/j.rse.2005.01.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27324
in Remote sensing of environment > vol 95 n° 4 (30/04/2005) . - pp 464 - 479[article]A method for detecting large-scale forest covers change using coarse spatial resolution imagery / R.H. Fraser in Remote sensing of environment, vol 95 n° 4 (30/04/2005)PermalinkDiurnal variations in AVHRR SST [sea surface temperature] fields: a strategy for removing warm layer effects from daily images / B.B. Nardelli in Remote sensing of environment, vol 95 n° 1 (15/03/2005)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)PermalinkAutomated detection of thermal features of active volcanoes by means of infrared AVHRR records / N. Pergola in Remote sensing of environment, vol 93 n° 3 (15/11/2004)PermalinkRegional simulation of ecosystem CO2 and water vapor exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data: Application to Zealand, Denmark / Rasmus M. Houborg in Remote sensing of environment, vol 93 n° 1 (30/10/2004)PermalinkMapping soil moisture in the central Ebro river valley (NorthEast Spain) with Landsat and NOAA satellite imagery: a comparison with meteorological data / S.M. Vicente-Serrano in International Journal of Remote Sensing IJRS, vol 25 n° 20 (October 2004)PermalinkEstimation of interannual variation in productivity of global vegetation using NDVI data / Z.M. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 16 (August 2004)PermalinkDerivation of a threshold function for the advanced very high resolution radiometer 3, 75um channel and its application in automatic cloud discrimination over snow/ice surfaces / X. Xiong in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)PermalinkUncertainty and confidence in land cover classification using a hybrid classifier approach / W. Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 8 (August 2004)PermalinkA land cover classification product over France at 1 km resolution using Spot4-Vegetation data / K.S. Han in Remote sensing of environment, vol 92 n° 1 (15 July 2004)PermalinkCombining weather prediction and remote sensing data for the calculation of evapotranspiration rates: application to Denmark / E. Boegh in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)PermalinkMapping micro-urban heat islands using NOAA/AVHRR images and CORINE Land Cover : an application to coastal of Greece / M. Stathopoulou in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkPotential of using NOAA-AVHRR data for estimating irrigated area to help solve an inter-state water dispute / V.K. Boken in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)PermalinkAssessing the effects of human-induced land degradation in the former homelands of northern South Africa with a 1 km AVHRR NDVI time-series / K.J. Wessels in Remote sensing of environment, vol 91 n° 1 (15/05/2004)PermalinkAtmospheric correction of Advanced Very High Resolution Radiometer imagery / Mhd. Suhyb Salama in International Journal of Remote Sensing IJRS, vol 25 n° 7 (April 2004)PermalinkValidation and calibration of Canada-wide coarse-resolution satellite burned-area maps / R.H. Fraser in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 4 (April 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)PermalinkCarbon mass fluxes of forests in Belgium determined with low resolution optical sensors / F. Veroustraete in International Journal of Remote Sensing IJRS, vol 25 n° 4 (February 2004)PermalinkSystematic corrections of AVHRR image composites for temporal studies / J. Cihlar in Remote sensing of environment, vol 89 n° 2 (30/01/2004)PermalinkEvaluation of remote sensing-based active fire datasets in Indonesia / F. Stolle in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)Permalink