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Estimating irrigated agricultural water use through Landsat TM and a simplified surface energy balance modeling in the semi-arid environments of Arizona / S. Kaplan in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
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Titre : Estimating irrigated agricultural water use through Landsat TM and a simplified surface energy balance modeling in the semi-arid environments of Arizona Type de document : Article/Communication Auteurs : S. Kaplan, Auteur ; S.W. Myint, Auteur Année de publication : 2012 Article en page(s) : pp 849 - 859 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cultures irriguées
[Termes IGN] évapotranspiration
[Termes IGN] image Landsat-TM
[Termes IGN] Phoenix
[Termes IGN] ressources en eau
[Termes IGN] variation saisonnière
[Termes IGN] zone semi-arideRésumé : (Auteur) Quantifying evapotranspiration (ET) is a key element for achieving better water management, especially in regions where agriculture is the main water consumer. A hybrid model combining the SEBAL and RESET models (S-RESET) was developed to effectively estimate actual ET (water use) of the agriculture sector around the Phoenix metropolitan area. To examine how irrigated agriculture water consumption varies with climate, the S-RESET model was applied under wet and dry climatic conditions. Results show that the average ET for active agriculture is 9.3 mm/day (_ 3.8mm/day) during the study period. Seasonal water use was 438 mm for 2000 (drought) and 494 mm for 2008 (wet). Based on the seasonal ET, we concluded that farmers in arid region use the same amount of water regardless of climatic conditions, implying that the agriculture sector as a whole may not be sensitive to drought as long as there is sufficient water from irrigation. This finding carries significant implications for the region's water security. Numéro de notice : A2012-431 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.849 En ligne : https://doi.org/10.14358/PERS.78.8.849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31877
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 849 - 859[article]Mapping fragmented agricultural systems in the Sudano-Sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery / E. Vintrou in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
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Titre : Mapping fragmented agricultural systems in the Sudano-Sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery Type de document : Article/Communication Auteurs : E. Vintrou, Auteur ; M. Soumaré, Auteur ; Serge Bernard, Auteur ; Agnès Bégue, Auteur ; C. Baron, Auteur ; D. Lo Seen, Auteur Année de publication : 2012 Article en page(s) : pp 839 - 848 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse texturale
[Termes IGN] carte agricole
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Terra-MODIS
[Termes IGN] Mali
[Termes IGN] métrique
[Termes IGN] Sahel
[Termes IGN] zone arideRésumé : (Auteur) We worked on the assumption that agricultural systems shaped the landscape through human cropping practices, and that the resulting landscape can be described with a set of coarse resolution satellite-derived metrics (spectral, textural, temporal, and spatial metrics). A Random Forest classification model was developed at the village scale in South Mali, based on 100 samples, with data on the main type of agricultural system in each village (three-class typology), and 30 MODIS-derived and socio-environmental metrics calculated on agricultural areas. The model was found to perform well (overall accuracy of 60 percent) and was stable. Class A (food crops) and B (intensive agriculture) displayed good producer's accuracy (70 percent and 67 percent, respectively), while class C (mixed agriculture) was less accurate (50 percent). The most important metrics were shown to be the annual mean of NDVI, followed by the phenology transition dates and texture metrics. However, when considering each set of metrics separately, texture emerged as the most discriminating factor (with 53 percent of global accuracy). This result, i.e., that even coarse resolution imagery contains textural information that can be used for crop mapping, is new. Such maps could be used in food security systems as an indicator of system vulnerability, or as spatial inputs for crop yield models. Numéro de notice : A2012-430 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.839 En ligne : https://doi.org/10.14358/PERS.78.8.839 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31876
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 839 - 848[article]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)
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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 Analysis of C-band scatterometer moisture estimations derived over a semiarid region / R. Amri in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 1 (July 2012)
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Titre : Analysis of C-band scatterometer moisture estimations derived over a semiarid region Type de document : Article/Communication Auteurs : R. Amri, Auteur ; Mehrez Zribi, Auteur ; Zohra Lili-Chabaane, Auteur ; W. Wagner, Auteur Année de publication : 2012 Article en page(s) : pp 2630 - 2638 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Afrique du nord
[Termes IGN] bande C
[Termes IGN] humidité du sol
[Termes IGN] image MetOp-ASCAT
[Termes IGN] image radar
[Termes IGN] MetOp
[Termes IGN] sécheresse
[Termes IGN] zone semi-arideRésumé : (Auteur) Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport, and vegetation productivity. Their characterization offers numerous possibilities for the improvement of our understanding of complex land-surface-atmosphere interactions. In this paper, soil moisture dynamics at the soil's surface (the first centimeters) and in its root zone (at depths down to 1 m) are investigated using 25 x 25 km2 scale data (Advanced Scatterometer (ASCAT)/METorological OPerational (METOP) scatterometer), for a semiarid region in North Africa. Our study highlights the quality of the surface and root-zone soil moisture products, derived from ASCAT data recorded over a two-year period. Surface soil moisture tends to be highly variable because it is strongly influenced by atmospheric conditions (rain and evaporation). On the other hand, root-zone moisture is considerably less variable. A statistical drought-monitoring index, referred to as the “moisture anomaly index,” is derived from ASCAT and European Remote Sensing (ERS) time series. This index was tested with ERS and ASCAT products during the 1991-2010 study period. A strong correlation is found between the proposed index and the standardized precipitation index. Numéro de notice : A2012-354 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2186458 Date de publication en ligne : 12/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2186458 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31800
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 7 Tome 1 (July 2012) . - pp 2630 - 2638[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012071A 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)
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Titre : Application of time series Landsat images to examining land-use / land-cover dynamic change Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; S. Hetrick, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 747 - 755 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] détection de changement
[Termes IGN] élevage
[Termes IGN] image Landsat
[Termes IGN] Mato Grosso
[Termes IGN] savane
[Termes IGN] série temporelle
[Termes IGN] surface cultivée
[Termes IGN] surface imperméableRésumé : (Auteur) A hierarchical-based classification method was designed to develop time series land-use/land-cover datasets from Landsat images between 1977 and 2008 in Lucas do Rio Verde, Mato Grosso, Brazil. A post-classification comparison approach was used to examine land-use/land-cover change trajectories, which emphasis is on the conversions from vegetation or agropasture to impervious surface area, from vegetation to agropasture, and from agropasture to regenerat-ing vegetation. Results of this research indicated that increase in impervious surface area mainly resulted from the loss of cerrado in the initial decade of the study period and from loss of agricultural lands in the last two decades. Increase in agropasture was mainly at the expense of losing cerrado in the first two decades and relatively evenly from the loss of primary forest and cerrado in the last decade. When impervious surface area was less than approximately 40 km2 before 1999, impervious surface area was negatively related to cerrado and forest, and positively related to agropasture areas, but after impervious surface area reached 40 km2 in 1999, no obvious relationship exists between them. Numéro de notice : A2012-324 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358%2Fpers.78.7.747 En ligne : https://doi.org/10.14358%2Fpers.78.7.747 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31770
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 7 (July 2012) . - pp 747 - 755[article]Long term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia / M. Lyons in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
PermalinkContribution à l'étude des aulnaies marécageuses comtoises / Gilles Bailly in Nouvelles Archives de la Flore jurassienne et du nord-est de la France, n° 10 (2012)
PermalinkPlant species coexistence at local scale in temperate swamp forest: test of habitat heterogeneity hypothesis / Jan Douda in Oecologia, vol 169 n° 2 (June 2012)
PermalinkVariations saisonnière et annuelle de l'indice NDVI en relation avec les herbiers de zosteres (zostera noltii) par images satellites Spot : exemple du Bassin d'Arcachon (France) / J.M. Froidefond in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)
PermalinkEvaluation of SMOS soil moisture products over continental U.S. using the SCAN/SNOTEL network / A. Al Bitar in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)
PermalinkValidation of the SMOS L2 soil moisture data in the REMEDHUS network (Spain) / N. Sanchez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 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)
PermalinkUsing GRASS GIS to model solar irradiation on North Carolina aquatic habitats with canopy data / D. Newcomb in Transactions in GIS, vol 16 n° 2 (April 2012)
PermalinkClose range stereophotogrammetry and video imagery analyses in soil ecohydrology modelling / Maria J. Rossi in Photogrammetric record, vol 27 n° 137 (March - May 2012)
PermalinkCartographie des aires marines protégées dans les eaux sous juridiction française / Mathilde Le Duff (2012)
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