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Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model / Xinyun Wang in Geocarto international, vol 33 n° 2 (February 2018)  

Public [article]  inGeocarto international > vol 33 n° 2 (February 2018) . - pp 148 - 162 Titre : Estimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model Type de document : Article/Communication Auteurs : Xinyun Wang, Auteur ; Yige Guo, Auteur ; Jie He, Auteur ; Lingtong Du, Auteur ; Tianhua Hu, Auteur Année de publication : 2018 Article en page(s) : pp 148 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] Chine [Termes IGN] image HJ-1B [Termes IGN] juniperus (genre) [Termes IGN] modèle de croissance végétale [Termes IGN] Pinophyta [Termes IGN] Pinus (genre) [Termes IGN] Populus (genre) [Termes IGN] réflectance végétale [Termes IGN] steppe [Termes IGN] structure d'un peuplement forestier [Termes IGN] Ulmus (genre) Mots-clés libres : stochastic Gradient boosting Résumé : (Auteur) Accurately estimating the spatial distribution of forest aboveground biomass (AGB) is important because of its carbon budget forms part of the global carbon cycle. This paper presented three methods for obtaining forest AGB based on a forest growth model, a Multiple-Forward-Mode (MFM) method and a stochastic gradient boosting (SGB) model. A Li-Strahler geometric-optical canopy reflectance model (GOMS) with the ZELIG forest growth model was run using HJ1B imagery to derive forest AGB. GOMS-ZELIG simulated data were used to train the SGB model and AGB estimation. The GOMS-ZELIG AGB estimation was evaluated for 24 field-measured data and compared against the GOMS-SGB model and GOMS-MFM biomass predictions from multispectral HJ1B data. The results show that the estimation accuracy of the GOMS-MFM model is slightly higher than that of the GOMS-SGB model. The GOMS-ZELIG and GOMS-MFM models are considerably more accurate at estimating forest AGB in arid and semiarid regions. Numéro de notice : A2018-032 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1232438 En ligne : https://doi.org/10.1080/10106049.2016.1232438 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89205 [article]

An integrated heterogeneous web service retrieval via combination of instance- and metadata-based schema matching method / Jie He in Geo-spatial Information Science, vol 18 n° 2 (August 2015)  

Public [article]  inGeo-spatial Information Science > vol 18 n° 2 (August 2015) . - pp 111 - 123 Titre : An integrated heterogeneous web service retrieval via combination of instance- and metadata-based schema matching method Type de document : Article/Communication Auteurs : Jie He, Auteur ; Wei Wang, Auteur Année de publication : 2015 Article en page(s) : pp 111 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] appariement de données localisées [Termes IGN] GeoServer [Termes IGN] instance [Termes IGN] métadonnées [Termes IGN] métadonnées géographiques [Termes IGN] Web Coverage Service [Termes IGN] Web Feature Service Résumé : (auteur) Schema matching is a critical step in the integration of heterogeneous web service, which contains various types of web services and multi-version services of the same type. Mapping loss or mismatch usually occurs due to schema differences in structure and content and the variety in concept definition and organization. Current instance schema matching methods are not mature enough for heterogeneous web service because they cannot deal with the instance data in web service domain and capture all the semantics, especially metadata semantics. The metadata-based and the instance-based matching methods, in the case of being employed individually, are not efficient to determine the concept relationships, which are crucial for finding high-quality matches between schema attributes. In this paper, we propose an improved schema matching method, based on the combination of instance and metadata (CIM) matcher. The main method of our approach is to utilize schema structure, element labels, and the corresponding instance data information. The matching process is divided into two phases. In the first phase, the metadata-based matchers are used to compute the element label similarity of multi-version open geospatial consortium web service schema, and the generated matching results are raw mappings, which will be reused in the next instance matching phase. In the second phase, the designed instance matching algorithms are employed to the instance data of the raw mappings and fine mappings are generated. Finally, the raw mappings and the fine mappings are combined, and the final mappings are obtained. Our experiments are executed on different versions of web coverage service and web feature service instance data deployed in Geoserver. The results indicate that, the CIM method can obtain more accurate matching results and is flexible enough to handle the web service instance data. Numéro de notice : A2015-761 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2015.1065075 En ligne : http://dx.doi.org/10.1080/10095020.2015.1065075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78797 [article]