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Termes IGN > environnement > écologie > écosystème > biotope > milieu naturel > prairie
prairie
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Herbage, Prairie artificielle, Prairie naturelle, Prairie permanente, Prairie temporaire, Pré. Campagne. >> Pâturage, Écologie des prairies. >>Terme(s) spécifique(s) : Savane, Steppe, Pelouse. Equiv. LCSH : Grasslands, Meadows, Prairies. Voir aussi |
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Landscape metrics for analysing urbanization-induced land use and land cover changes / Hua Liu in Geocarto international, vol 28 n° 7-8 (November - December 2013)
[article]
Titre : Landscape metrics for analysing urbanization-induced land use and land cover changes Type de document : Article/Communication Auteurs : Hua Liu, Auteur ; Qihao Weng, Auteur Année de publication : 2013 Article en page(s) : pp 582 - 593 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] changement d'utilisation du sol
[Termes IGN] classification dirigée
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-ASTER
[Termes IGN] Indianapolis
[Termes IGN] métrique
[Termes IGN] prairie
[Termes IGN] surface cultivée
[Termes IGN] urbanisationRésumé : (Auteur) The objective of this study is to assess the effectiveness of landscape metrics in quantifying the urbanization-induced land use and land cover (LULC) changes from a landscape ecology perspective using the City of Indianapolis, Indiana, USA as a case study. Two Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, acquired on 3 October 2000 and 13 October 2006, respectively, and two Landsat 5 Thematic Mapper images, acquired on 22 October 1989 and 20 October 2000, respectively, were used for the study. Seven LULC types were identified: urban, agriculture, grasslands, forest, water, barren lands and wetlands. A series of landscape metrics were then computed for each LULC type and these metrics were used to compare the two ASTER-derived LULC maps with the two Landsat-derived maps. Results show that urbanization contributed significantly to LULC changes in the study area. Agricultural lands decreased and forests became more disaggregated. Grassland increased slightly in size and aggregation level and improved in connectedness. Numéro de notice : A2013-699 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.752530 Date de publication en ligne : 06/02/2013 En ligne : https://doi.org/10.1080/10106049.2012.752530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32835
in Geocarto international > vol 28 n° 7-8 (November - December 2013) . - pp 582 - 593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2013041 RAB Revue Centre de documentation En réserve L003 Disponible A semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia, China / Hai Lan in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
[article]
Titre : A semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia, China Type de document : Article/Communication Auteurs : Hai Lan, Auteur ; Yichun Xie, Auteur Année de publication : 2013 Article en page(s) : pp 21 - 31 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification floue
[Termes IGN] classification hybride
[Termes IGN] fusion d'images
[Termes IGN] image CBERS
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] prairieRésumé : (Auteur) Remote sensing techniques offer effective means for mapping plant communities. However, mapping grassland with fine vegetative classes over large areas has been challenging for either the coarse resolutions of remotely sensed images or the high costs of acquiring images with high-resolutions. An improved hybrid-fuzzy-classifier (HFC) derived from a semi-ellipsoid-model (SEM) is developed in this paper to achieve higher accuracy for classifying grasslands with Landsat images. The Xilin River Basin, Inner Mongolia, China, is chosen as the study area, because an acceptable volume of ground truthing data was previously collected by multiple research communities. The accuracy assessment is based on the comparison of the classification outcomes from four types of image sets: (1) Landsat ETM+ August 14, 2004, (2) Landsat TM August 12, 2009, (3) the fused images of ETM+ with CBERS, and (4) TM with CBERS, respectively, and by three classifiers, the proposed HFC-SEM, the tetragonal pyramid model (TPM) based HFC, and the support vector machine method. In all twelve classification experiments, the HFC-SEM classifier had the best overall accuracy statistics. This finding indicates that the medium resolution Landsat images can be used to map grassland vegetation with good vegetative detail when the proper classifier is applied. Numéro de notice : A2013-605 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.07.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32741
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 21 - 31[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data / Abel Ramoelo in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)
[article]
Titre : Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data Type de document : Article/Communication Auteurs : Abel Ramoelo, Auteur ; Andrew K. Skidmore, Auteur ; Moses Azong Cho, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 27 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Afrique du sud (état)
[Termes IGN] azote
[Termes IGN] données environnementales
[Termes IGN] herbe
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] parc naturel national
[Termes IGN] parcours
[Termes IGN] phosphore
[Termes IGN] régression non linéaire
[Termes IGN] savaneRésumé : (Auteur) Grass nitrogen (N) and phosphorus (P) concentrations are direct indicators of rangeland quality and provide imperative information for sound management of wildlife and livestock. It is challenging to estimate grass N and P concentrations using remote sensing in the savanna ecosystems. These areas are diverse and heterogeneous in soil and plant moisture, soil nutrients, grazing pressures, and human activities. The objective of the study is to test the performance of non-linear partial least squares regression (PLSR) for predicting grass N and P concentrations through integrating in situ hyperspectral remote sensing and environmental variables (climatic, edaphic and topographic). Data were collected along a land use gradient in the greater Kruger National Park region. The data consisted of: (i) in situ-measured hyperspectral spectra, (ii) environmental variables and measured grass N and P concentrations. The hyperspectral variables included published starch, N and protein spectral absorption features, red edge position, narrow-band indices such as simple ratio (SR) and normalized difference vegetation index (NDVI). The results of the non-linear PLSR were compared to those of conventional linear PLSR. Using non-linear PLSR, integrating in situ hyperspectral and environmental variables yielded the highest grass N and P estimation accuracy (R2 = 0.81, root mean square error (RMSE) = 0.08, and R2 = 0.80, RMSE = 0.03, respectively) as compared to using remote sensing variables only, and conventional PLSR. The study demonstrates the importance of an integrated modeling approach for estimating grass quality which is a crucial effort towards effective management and planning of protected and communal savanna ecosystems. Numéro de notice : A2013-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32547
in ISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 27 - 40[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013081 RAB Revue Centre de documentation En réserve L003 Disponible The spatial prediction of tree species diversity in savanna woodlands of Southern Africa / G. Mutowo in Geocarto international, vol 27 n° 8 (December 2012)
[article]
Titre : The spatial prediction of tree species diversity in savanna woodlands of Southern Africa Type de document : Article/Communication Auteurs : G. Mutowo, Auteur ; Amon Murwira, Auteur Année de publication : 2012 Article en page(s) : pp 627 - 645 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbre (flore)
[Termes IGN] biodiversité
[Termes IGN] image Ikonos
[Termes IGN] image Terra-ASTER
[Termes IGN] indice de végétation
[Termes IGN] prédiction
[Termes IGN] radiance
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] régression linéaire
[Termes IGN] savane
[Termes IGN] ZimbabweRésumé : (Auteur) In this study, we tested the utility of remotely sensed data in predicting tree species diversity in savanna woodlands. Specifically, we developed linear regression functions based on a combination of the coefficient of variation of near infrared (NIR) radiance and the soil-adjusted vegetation index (SAVI), both derived from advanced space-borne thermal emission and reflection radiometer satellite imagery. Using the regression functions in a Geographic Information System (GIS), we predicted the spatial variations in tree species diversity. Our results showed that tree species diversity can be predicted using a combination of the coefficient of variation of NIR radiance and SAVI. We conclude that remotely sensed data can be used to spatially predict tree species diversity in savanna woodlands. Numéro de notice : A2012-550 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.662530 Date de publication en ligne : 29/02/2012 En ligne : https://doi.org/10.1080/10106049.2012.662530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31996
in Geocarto international > vol 27 n° 8 (December 2012) . - pp 627 - 645[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012081 RAB Revue Centre de documentation En réserve L003 Disponible A robust signal preprocessing chain for small-footprint waveform LiDAR / J. Wu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : A robust signal preprocessing chain for small-footprint waveform LiDAR Type de document : Article/Communication Auteurs : J. Wu, Auteur ; Jan Van Aardt, Auteur ; J. Mcglinchy, Auteur ; Gregory P. Asner, Auteur Année de publication : 2012 Article en page(s) : pp 3242 - 3255 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Afrique du sud (état)
[Termes IGN] biomasse
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage
[Termes IGN] forme d'onde
[Termes IGN] lasergrammétrie
[Termes IGN] prétraitement du signal
[Termes IGN] savane
[Termes IGN] signal lidarRésumé : (Auteur) The extraction of structural object metrics from a next-generation remote sensing modality, namely waveform Light Detection and Ranging (LiDAR), has garnered increasing interest from the remote sensing research community. However, the raw incoming (received) LiDAR waveform typically exhibits a stretched, misaligned, and relatively distorted character. In other words, the LiDAR signal is smeared and the effective temporal (vertical) resolution decreases, which is attributed to a fixed time span allocated for detection, the sensor's variable outgoing pulse signal, off-nadir scanning, the receiver impulse response impacts, and system noise. Theoretically, such a loss of resolution and increased data ambiguity can be remediated by using proven signal preprocessing approaches. In this paper, we present a robust signal preprocessing chain for waveform LiDAR calibration, which includes noise reduction, deconvolution, waveform registration, and angular rectification. This preprocessing chain was initially validated using simulated waveform data, which were derived via the digital imaging and remote sensing image generation modeling environment. We also verified the approach using real small-footprint waveform LiDAR data collected by the Carnegie Airborne Observatory in a savanna region of South Africa and specifically in terms of modeling woody biomass in this region. Metrics, including the spectral angle for cross-section recovery assessment and goodness-of-fit (R2) statistics, along with the root-mean-squared error for woody biomass estimation, were used to provide a comprehensive quantitative evaluation of the performance of this preprocessing chain. Results showed that our approach significantly increased our ability to recover the temporal signal resolution, improved geometric rectification of raw waveform LiDAR, and resulted in improved waveform-based woody biomass estimation. This preprocessing chain has the potential to be applied across the board for h- gh fidelity processing of small-footprint waveform LiDAR data, thereby facilitating the extraction of valid and useful structural metrics from ground objects. Numéro de notice : A2012-389 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178420 Date de publication en ligne : 04/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178420 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31835
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3242 - 3255[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible 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)PermalinkClassification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and LiDAR data in a Random Forest data mining environment / Laven Naidoo in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkDes structures paysagères à la dynamique des feux : Essai de typologie régionale des campagnes pyrophiles de l’ouest du Burkina Faso / S. Caillault in Revue internationale de géomatique, vol 21 n° 3 (septembre - novembre 2011)PermalinkInventorying management status and plant species richness in seminatural grasslands using high spatial resolution imagery / K. Hall in Applied Vegetation Science, vol 13 n° 2 (April 2010)PermalinkBiodiversité floristique, entomologique et ornithologique des vallées alluviales de Champagne-Ardenne / Alain Berthelot (2010)PermalinkHow do trees affect spatio-temporal heterogeneity of nutrient cycling in mediterranean annual grasslands? / Guillermo Gea-Izquierdo in Annals of Forest Science, vol 67 n° 1 (January-February 2010)PermalinkTraitement des données de télédétection / Michel-Claude Girard (2010)PermalinkDevelopment of alder carr after the abandonment of wet grasslands during the last 70 years / Jan Douda in Annals of Forest Science, Vol 66 n° 7 (October - November 2009)PermalinkRemote sensing with reflected signals: GNSS-R data processing software and test analysis / D. Yang in Inside GNSS, vol 4 n° 5 (September - October 2009)PermalinkSans carte, pas d'analyse de paysage : En Iran et en Afghanistan, comprendre l'organisation agricole des réseaux de qanat et de karez, conduites d'eaux souterraines dans les steppes et déserts / P. Gentelle in Le monde des cartes, n° 201 (septembre 2009)Permalinkn° 21 - Forêts et prairies abondent dans le réseau Natura 2000 (Bulletin de Le point sur, n° 21 [01/08/2009]) / Antoine LévêquePermalinkEstablishment limitation of holm oak (Quercus ilex subsp. ballota (Desf.) Samp.) in a Mediterranean savanna – forest ecosystem / Christian Smit in Annals of Forest Science, Vol 66 n° 5 (July - August 2009)PermalinkQuantifying indicators of riparian condition in Australian tropical savannas: integrating high spatial resolution imagery and field survey data / K. Johansen in International Journal of Remote Sensing IJRS, vol 29 n°23 - 24 (December 2008)PermalinkSuivi par télédétection de la dynamique des milieux savanicoles et forestiers gabonais : exemple de la forêt classée de la Mondah et du parc national de la Lope / Marcellin Nziengui in Photo interprétation, vol 44 n° 2 (Septembre 2008)PermalinkMulti-sensor model-data fusion for estimation of hydrologic and energy flux parameters / L. Renzullo in Remote sensing of environment, vol 112 n° 4 (15/04/2008)PermalinkAnalyse spatio-temporelle de l'occupation du sol dans le parc national de Waza entre 1986 et 2001 (Nord Cameroun) / G. Wafo Tabopda in Revue Française de Photogrammétrie et de Télédétection, n° 189 (Mars 2008)PermalinkDynamique spatio-temporelle de l'écosystème du site Ramsar du moyen Niger 1 : cas de la mare de Albarïze / Mahamane Ali in Revue Française de Photogrammétrie et de Télédétection, n° 187 -188 (Décembre 2007)PermalinkImpacts du changement climatique sur la prairie et adaptations possibles / Jean-François Soussana ; Gilles Lemaire in Rendez-vous techniques, Hors-série n° 3 (décembre 2007)PermalinkUtilisation des données spatiales pour le suivi de la dynamique des écosystèmes dans le milieu aride tunisien. Cas de la région de Menzel Habib entre 1975 et 2000 / Ali Hanafi in Revue Française de Photogrammétrie et de Télédétection, n° 187 -188 (Décembre 2007)PermalinkMonitoring herbaceaous fuel moisture content with Spot-Vegetation times-series for fire risk prediction in savanna ecosystems / Jan Verbesselt in Remote sensing of environment, vol 108 n° 4 (29 June 2007)Permalink