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Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models / Subit Chakrabarti in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)
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Titre : Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models Type de document : Article/Communication Auteurs : Subit Chakrabarti, Auteur ; Jasmeet Judge, Auteur ; Tara Bongiovanni, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4629 - 4641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme d'apprentissage
[Termes IGN] cultures
[Termes IGN] désagrégation
[Termes IGN] Floride (Etats-Unis)
[Termes IGN] humidité du sol
[Termes IGN] modèle de régressionRésumé : (Auteur) In this paper, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRMs) using high-resolution correlated information from auxiliary sources. It includes regularized clustering that assigns soft memberships to each pixel at a fine scale followed by a kernel regression that computes the value of the desired variable at all pixels. Coarse-scale remotely sensed SM was disaggregated from 10 to 1 km using land cover (LC), precipitation, land surface temperature, leaf area index, and in situ observations of SM. This algorithm was evaluated using multiscale synthetic observations in NC Florida for heterogeneous agricultural LCs. It was found that the rmse for 96% of the pixels was less than 0.02 m 3/m3. The clusters generated represented the data well and reduced the rmse by up to 40% during periods of high heterogeneity in LC and meteorological conditions. The Kullback-Leibler divergence (KLD) between the true SM and the disaggregated estimates is close to zero, for both vegetated and bare-soil LCs. The disaggregated estimates were compared with those generated by the principle of relevant information (PRI) method. The rmse for the PRI disaggregated estimates is higher than the rmse for the SRRM on each day of the season. The KLD of the disaggregated estimates generated by the SRRM is at least four orders of magnitude lower than those for the PRI disaggregated estimates, whereas the computational time needed was reduced by three times. The results indicate that the SRRM can be used for disaggregating SM with complex nonlinear correlations on a grid with high accuracy. Numéro de notice : A2016-888 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2547389 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2547389 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83068
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4629 - 4641[article]Determining forest degradation, ecosystem state and resilience using a standard stand stocking measurement diagram: theory into practice / Carlos Bahamondez in Forestry, an international journal of forest research, vol 89 n° 3 (July 2016)
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Titre : Determining forest degradation, ecosystem state and resilience using a standard stand stocking measurement diagram: theory into practice Type de document : Article/Communication Auteurs : Carlos Bahamondez, Auteur ; Ian D. Thompson, Auteur Année de publication : 2016 Article en page(s) : pp 290 - 300 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Chili
[Termes IGN] dégradation de la flore
[Termes IGN] écosystème forestier
[Termes IGN] forêt de production
[Termes IGN] Nothofagus (genre)
[Termes IGN] productivité
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Forest degradation is a major issue for policy-makers that is exacerbated by no clear and globally accepted definition of the term. For forest managers, a loss of forest productive capacity is one form of forest degradation. We present a quantitative method to assess forest degradation from a productivity perspective. Our method uses a standard stocking chart and calculation methods based on standard forest inventory data, to derive a clear threshold value for stocking, below which a forest should be considered degraded. The method is illustrated using the example of a self-regenerating Nothofagus production forest type from Chile. For that forest type, we determined that harvesting trees to below a specific basal area relative to site type, resulted in a loss of resilience, an unpredictable shift in ecosystem state, and a degraded condition. Our method illustrates how over-harvesting can degrade the long-term productivity of a stand and forest resilience. Nevertheless, it is important to consider that forests can also be degraded from other perspectives, such as loss of biodiversity, carbon, or protective functions as a result of excessive disturbances. Ecosystem management requires that managers consider degradation from a range of perspectives. We see the quantified approach used here as a way to provide practitioners with, in part, a transition from sustained yield to ecosystem management with an ultimate objective of providing a pathway towards adaptive management of complex systems and avoiding degradation. Numéro de notice : A2016--136 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpv052 Date de publication en ligne : 12/01/2016 En ligne : https://doi.org/10.1093/forestry/cpv052 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85779
in Forestry, an international journal of forest research > vol 89 n° 3 (July 2016) . - pp 290 - 300[article]Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery / Mary Pyott Freeman in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
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Titre : Object-based image mapping of conifer tree mortality in San Diego county based on multitemporal aerial ortho-imagery Type de document : Article/Communication Auteurs : Mary Pyott Freeman, Auteur ; Douglas A. Stow, Auteur ; Dar A. Roberts, Auteur Année de publication : 2016 Article en page(s) : pp 571 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] arbre mort
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] image aérienne
[Termes IGN] image multitemporelle
[Termes IGN] orthoimage
[Termes IGN] Pinophyta
[Termes IGN] San DiegoRésumé : (Auteur) Two GEOBIA approaches are compared for their effectiveness in mapping dead trees within island montane forests of Southern California: a spatial contextual approach using an artificial neural network classifier, and a segmentation and multi-pixel classification approach. Both approaches are tested with multitemporal aerial orthoimagery having varying spatial resolutions. Spectral transformation inputs are also tested. An object-based accuracy assessment is conducted. Accuracies range between 30 percent to 90 percent for the dead tree class and are significantly higher for the spatial-contextual approach. Inclusion of spectral transforms increased accuracies by 5 percent for the true object-based approach, up to 13 percent for the spatial contextual approach, and reduced commission error up to 10 percent for both approaches. Masking techniques increased accuracies of the spatial contextual approach by 20 percent. With manual editing, the most accurate maps of individual live and dead trees from the spatial contextual approach are suitable for studying spatio-temporal trends in montane conifer mortality. Numéro de notice : A2016-518 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.7.571 En ligne : http://dx.doi.org/10.14358/PERS.82.7.571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81589
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 7 (juillet 2016) . - pp 571 - 580[article]Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series / Meng Lu in ISPRS Journal of photogrammetry and remote sensing, vol 117 (July 2016)
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Titre : Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series Type de document : Article/Communication Auteurs : Meng Lu, Auteur ; Edzer J. Pebesma, Auteur ; Alber Sanchez, Auteur ; Jan Verbesselt, Auteur Année de publication : 2016 Article en page(s) : pp 227 – 236 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Amazonie
[Termes IGN] Brésil
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] points de rupture
[Termes IGN] série temporelleRésumé : (auteur) Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis. Numéro de notice : A2016-586 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.03.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.03.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81727
in ISPRS Journal of photogrammetry and remote sensing > vol 117 (July 2016) . - pp 227 – 236[article]The bottom line / José Alexis Primelles Cardenas in GEO: Geoconnexion international, vol 15 n° 7 (July - August 2016)
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Titre : The bottom line Type de document : Article/Communication Auteurs : José Alexis Primelles Cardenas, Auteur ; Jorge F. Rodriguez, Auteur Année de publication : 2016 Article en page(s) : pp 34 - 36 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] Panama, canal de
[Termes IGN] surveillance d'ouvrage
[Termes IGN] technologieRésumé : (éditeur) Multi-beam technology is being used to ensure the 77km-long Panama canal continues to remain open at all times. José Alexis Primelles Cardenas and Jorge F. Rodriguez report Numéro de notice : A2016-500 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81523
in GEO: Geoconnexion international > vol 15 n° 7 (July - August 2016) . - pp 34 - 36[article]An evaluation of unsupervised and supervised learning algorithms for clustering landscape types in the United States / Jochen Wendel in Cartography and Geographic Information Science, Vol 43 n° 3 (June 2016)
PermalinkPredicting palustrine wetland probability using random forest machine learning and digital elevation data-derived terrain variables / Aaron E. Maxwell in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 6 (June 2016)
PermalinkA spatial analysis of GEOID03 and GEOID09 in Connecticut / Kazi Arifuzzaman in Journal of applied geodesy, vol 10 n° 2 (June 2016)
PermalinkTechnical considerations for modernizing Nova Scotia’s Coordinate Referencing System / Jason Bond in Geomatica, vol 70 n° 2 (June 2016)
PermalinkEvaluating the use of GPS heights in water conservation applications / Ahmed F. Elaksher in Survey review, vol 48 n° 348 (May 2016)
PermalinkFrom consumer to pro / Monica Miller Rodgers in GEO: Geoconnexion international, vol 15 n° 5 (May 2016)
PermalinkStorm event representation and analysis based on a directed spatiotemporal graph model / W. Liu in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
PermalinkEstimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)
PermalinkInvestigating the possible impact of atmospheric CO2 increase on Araucaria araucana wood density / Paulina E. Pinto in European Journal of Forest Research, vol 135 n° 2 (April 2016)
PermalinkAutomatic detection and reconstruction of 2-D/3-D building shapes from spaceborne TomoSAR point clouds / Muhammad Shahzad in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)
PermalinkEstimating spatial efficiency using cyber search, GIS, and spatial optimization: a case study of fire service deployment in Los Angeles County / R.L. Church in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
PermalinkLe GPS dévoile les liens entre les grands séismes de subduction au Chili / Emilie Klein in XYZ, n° 146 (mars - mai 2016)
PermalinkMapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm / Nguyen-Thanh Son in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)
PermalinkPermalinkA parallel algorithm for coverage optimization on multi-core architectures / Ran Wei in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
PermalinkPrivacy and spatial pattern preservation in masked GPS trajectory data / Dara E. Seidl in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)
PermalinkThe Canadian Geodetic Vertical Datum of 2013 (CGVD2013) / Marc Véronneau in Geomatica, vol 70 n° 1 (March 2016)
PermalinkGeo-localization using volumetric representations of overhead imagery / Ozge C. Ozcanli in International journal of computer vision, vol 116 n° 3 (February 2016)
PermalinkSpatial data infrastructure in Chile is mature and expanding / Alvaro Monett Hernandéz in GIM international, vol 30 n° 2 (February 2016)
PermalinkLe contentieux frontalier terrestre franco-surinamien ou Contesté du Maroni, 1. Mémoire / Godefroy Garon (2016)
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