Centre de documentation
scientifique

Developing a web-based system for supervised classification of remote sensing images / Ziheng Sun in Geoinformatica, vol 20 n° 4 (October - December 2016)  

Public [article]  inGeoinformatica > vol 20 n° 4 (October - December 2016) . - pp 629 - 649 Titre : Developing a web-based system for supervised classification of remote sensing images Type de document : Article/Communication Auteurs : Ziheng Sun, Auteur ; H. Fang, Auteur ; Liping Di, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 629 - 649 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] application web [Termes IGN] classification automatique [Termes IGN] classification dirigée Résumé : (Auteur) Web-based image classification systems aim to provide users with an easy access to image classification function. The existing work mainly focuses on web-based unsupervised classification systems. This paper proposes a web-based supervised classification system framework which includes three modules: client, servlet and service. It comprehensively describes how to combine the procedures of supervised classification into the development of a web system. A series of methods are presented to realize the modules respectively. A prototype system of the framework is also implemented and a number of remote sensing (RS) images are tested on it. Experiment results show that the prototype is capable of accomplishing supervised classification of RS images on the Web. If appropriate algorithms and parameter values are used, the results of the web-based solution could be as accurate as the results of traditional desktop-based systems. This paper lays the foundation on both theoretical and practical aspects for the future development of operational web-based supervised classification systems. Numéro de notice : A2016-812 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-016-0252-3 En ligne : http://dx.doi.org/10.1007/s10707-016-0252-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82612 [article]

Spatially and temporally continuous LAI data sets based on an integrated filtering method: examples from North America / H. Fang in Remote sensing of environment, vol 112 n° 1 (15/01/2008)  

Public [article]  inRemote sensing of environment > vol 112 n° 1 (15/01/2008) . - pp 75 - 93 Titre : Spatially and temporally continuous LAI data sets based on an integrated filtering method: examples from North America Type de document : Article/Communication Auteurs : H. Fang, Auteur ; Shunlin Liang, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 75 - 93 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de filtrage [Termes IGN] Amérique du nord [Termes IGN] analyse comparative [Termes IGN] analyse diachronique [Termes IGN] données spatiotemporelles [Termes IGN] image Landsat-ETM+ [Termes IGN] image Terra-MODIS [Termes IGN] Leaf Area Index [Termes IGN] qualité des données Résumé : (Auteur) Leaf Area Index (LAI) is an important biophysical variable for characterizing the land surface vegetation. Global LAI product has been routinely produced from the MODerate resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellite platforms. However, the MODIS standard LAI product is not continuous both spatially and temporally. To fill the gaps and improve the quality, we have developed a data filtering algorithm. This filter, called the temporal spatial filter (TSF), integrates both spatial and temporal characteristics for different plant functional types. The spatial gaps are first filled with the multi-year averages of the same day. If the values are missing over all years, the pixel is filled with a new estimate using the vegetation continuous field–ecosystem curve fitting method. The TSF integrates both the multi-seasonal average trend (background) and the seasonal observation. We implement this algorithm using the MODIS Collection 4 LAI product over North America. Comparison of the TSF results with the Savitzky–Golay filter indicates that the TSF performs much better in restoring the spatial and temporal distribution of seasonal LAI trends. The new LAI product has been validated by comparing with field measurements and the derived LAI maps from ETM+ data at a broadleaf forest site and an agricultural site. The validation results indicate that the new LAI product agrees better with both the field measurements and LAI values obtained from the ETM+ than does the MODIS LAI standard product, which usually shows higher LAI values. Copyright Elsevier Numéro de notice : A2008-026 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.07.026 En ligne : https://doi.org/10.1016/j.rse.2006.07.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29021 [article]

Improved estimation of aerosol optical depth from MODIS imagery over land surfaces / B. Zhong in Remote sensing of environment, vol 104 n° 4 (30/10/2006)  

Public [article]  inRemote sensing of environment > vol 104 n° 4 (30/10/2006) . - pp 416 - 425 Titre : Improved estimation of aerosol optical depth from MODIS imagery over land surfaces Type de document : Article/Communication Auteurs : B. Zhong, Auteur ; Shunlin Liang, Auteur ; H. Fang, Auteur Année de publication : 2006 Article en page(s) : pp 416 - 425 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] aérosol [Termes IGN] changement climatique [Termes IGN] épaisseur optique [Termes IGN] image Terra-MODIS [Termes IGN] luminance lumineuse [Termes IGN] occupation du sol [Termes IGN] végétation Résumé : (Auteur) Estimation of aerosol loadings is of great importance to the studies on global climate changes. The current Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol estimation algorithm over land is based on the “dark-object” approach, which works only over densely vegetated (“dark”) surfaces. In this study, we develop a new aerosol estimation algorithm that uses the temporal signatures from a sequence of MODIS imagery over land surfaces, particularly “bright” surfaces. The estimated aerosol optical depth is validated by Aerosol Robotic Network (AERONET) measurements. Case studies indicate that this algorithm can retrieve aerosol optical depths reasonably well from the winter MODIS imagery at seven sites: four sites in the greater Washington, DC area, USA; Beijing City, China; Banizoumbou, Niger, Africa; and Bratts Lake, Canada. The MODIS aerosol estimation algorithm over land (MOD04), however, does not perform well over these non-vegetated surfaces. This new algorithm has the potential to be used for other satellite images that have similar temporal resolutions. Copyright Elsevier Numéro de notice : A2006-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.05.016 En ligne : https://doi.org/10.1016/j.rse.2006.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28218 [article]