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Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning / G. Zheng in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 2 (February 2013) . - pp 777 - 787 Titre : Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning Type de document : Article/Communication Auteurs : G. Zheng, Auteur ; L. Moskal, Auteur ; S.H. Kim, Auteur Année de publication : 2013 Article en page(s) : pp 777 - 787 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt [Termes IGN] image hémisphérique [Termes IGN] Leaf Area Index [Termes IGN] projection azimutale équivalente de lambert [Termes IGN] projection stéréographique [Termes IGN] rastérisation [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté [Termes IGN] télémétrie laser terrestre Résumé : (Auteur) Terrestrial laser scanner (TLS)-based leaf area index (LAI) retrieval is an appealing concept, due to the ability to capture structural information of canopies as 3D point cloud data (PCD). TLS-based LAI estimation methods promise a nondestructive tool for spatially explicit calibration of LAI estimated by aerial or satellite remote sensing techniques. These methods also overcome the sky condition restrictions of on-ground optical instruments such as hemispherical photography frequently used for LAI estimation. This paper presents a new method for estimating the effective LAI (LAIe) directly from PCD generated by TLS in heterogeneous forests. We converted the 3-D PCD into 2-D raster images, similar to hemispherical photographs, using two geometrical projection techniques in order to estimate gap fraction and LAIe using a linear least squares method. Our results indicated that the TLS-based algorithm was able to capture the variability in LAIe of forest stands with a range of densities. The TLS-based LAIe estimation method explained 89.1% (rmse = 0.01 ; p Numéro de notice : A2013-080 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2205003 En ligne : https://doi.org/10.1109/TGRS.2012.2205003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32218 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2013021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Web data retrieval: solving spatial range queries using k-nearest neighbor searches / W. Bae in Geoinformatica, vol 13 n° 4 (December 2009)  

Public [article]  inGeoinformatica > vol 13 n° 4 (December 2009) . - pp 483 - 514 Titre : Web data retrieval: solving spatial range queries using k-nearest neighbor searches Type de document : Article/Communication Auteurs : W. Bae, Auteur ; S.H. Kim, Auteur ; S. Alkobaisi, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 483 - 514 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données [Termes IGN] classification barycentrique [Termes IGN] géomatique web [Termes IGN] interface web [Termes IGN] recherche d'information géographique [Termes IGN] requête spatiale [Termes IGN] système d'information géographique Résumé : (Auteur) As Geographic Information Systems (GIS) technologies have evolved, more and more GIS applications and geospatial data are available on the web. Spatial objects in a given query range can be retrieved using spatial range query - one of the most widely used query types in GIS and spatial databases. However, it can be challenging to retrieve these data from various web applications where access to the data is only possible through restrictive web interfaces that support certain types of queries. A typical scenario is the existence of numerous business web sites that provide their branch locations through a limited “nearest location” web interface. For example, a chain restaurant’s web site such as McDonalds can be queried to find some of the closest locations of its branches to the user’s home address. However, even though the site has the location data of all restaurants in, for example, the state of California, it is difficult to retrieve the entire data set efficiently due to its restrictive web interface. Considering that k-Nearest Neighbor (k-NN) search is one of the most popular web interfaces in accessing spatial data on the web, this paper investigates the problem of retrieving geospatial data from the web for a given spatial range query using only k-NN searches. Based on the classification of k-NN interfaces on the web, we propose a set of range query algorithms to completely cover the rectangular shape of the query range (completeness) while minimizing the number of k-NN searches as possible (efficiency). We evaluated the efficiency of the proposed algorithms through statistical analysis and empirical experiments using both synthetic and real data sets. Copyright Springer Numéro de notice : A2009-336 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-008-0055-2 En ligne : https://doi.org/10.1007/s10707-008-0055-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29966 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
057-09041	RAB	Revue	Centre de documentation	En réserve L003	Disponible