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Comparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery / S. Vigneshwaran in Geocarto international, vol 36 n° 13 ([15/07/2021])  

Public [article]  inGeocarto international > vol 36 n° 13 [15/07/2021] . - pp 1429 - 1442 Titre : Comparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery Type de document : Article/Communication Auteurs : S. Vigneshwaran, Auteur ; S. Vasantha Kumar, Auteur Année de publication : 2021 Article en page(s) : pp 1429 - 1442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte de la végétation [Termes IGN] classification dirigée [Termes IGN] classification non dirigée [Termes IGN] classification orientée objet [Termes IGN] espace vert [Termes IGN] flore urbaine [Termes IGN] image à très haute résolution [Termes IGN] image Worldview [Termes IGN] Inde [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] urbanisme Résumé : (auteur) Urban green space (UGS) plays a vital role in maintaining the ecological balance of a city and in ensuring healthy living of the city inhabitants. It is generally suggested that one-third of the city should be covered by green and to ensure this, the city administrators must have an accurate map of the existing UGS. Such a map would be useful to visualize the distribution of the existing green cover and also to find out the areas that can possibly be converted to UGS. Reported studies on UGS mapping have mostly used medium and high resolution images such as Landsat-TM, ETM+, Sentinel-2A, IKONOS, etc. However, studies on the use of very high resolution images for UGS extraction are very limited. The present study is a first attempt in utilizing the very high resolution Worldview-3 image for UGS extraction. Performance of different classification methods such as unsupervised, supervised, object based and normalized difference vegetation index (NDVI) were compared using the pan sharpened Worldview-3 image covering part of New Delhi in India. It was found that the unsupervised classification followed by manual recoding method showed superior performance with overall accuracy (OA) of 99% and κ coefficient of 0.98. Also, the OA achieved in the present study is the highest when compared to other reported studies on UGS extraction. The map of UGS revealed that almost 40% of the study area is covered by green which is more than the recommended value of 33% (one-third). In order to check the universality of the unsupervised classification approach in extracting UGS, Worldview-3 image covering Rio in Brazil was tested. It was found that an OA of 98% and κ coefficient of 0.95 were obtained which clearly indicate that the proposed approach would work very well in extracting UGS from any Worldview-3 imagery. Numéro de notice : A2021-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1665714 Date de publication en ligne : 18/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1665714 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98104 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021131	RAB	Revue	Centre de documentation	En réserve L003	Disponible

An integrated methodology for surface soil moisture estimating using remote sensing data approach / Rida Khellouk in Geocarto international, vol 36 n° 13 ([15/07/2021])  

Public [article]  inGeocarto international > vol 36 n° 13 [15/07/2021] . - pp 1443 - 1458 Titre : An integrated methodology for surface soil moisture estimating using remote sensing data approach Type de document : Article/Communication Auteurs : Rida Khellouk, Auteur ; Ahmed Barakat, Auteur ; Aafaf El Jazouli, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1443 - 1458 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] évapotranspiration [Termes IGN] humidité du sol [Termes IGN] image Terra-MODIS [Termes IGN] indice d'humidité [Termes IGN] Maroc [Termes IGN] modèle numérique de surface [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] température au sol [Termes IGN] texture du sol Résumé : (auteur) The present study aimed to propose an operational approach for estimating surface soil moisture from Moderate Resolution Imaging Spectroradiometer (MODIS) data by considering diverse environmental variables such as Normalized Difference Vegetation Index (NDVI), land surface temperature (Ts), evapotranspiration, topographic parameters (elevation and aspect) and soil texture (clay, loam and silt). A soil moisture index (SMI) derived from NDVI-Ts space is combined to all other variables, based on stepwise multiple regression, to develop a new SSMC model. Performance of this model was assessed using field-measured data of SSM. Accuracy was performed by the k-fold cross validation method, it showed a R2 (coefficients of determination) of 0.70, RMSE of 1.58% and unRMSE of 0.5%. In addition, the results of the developed model were compared with another soil moisture model SMM proposed in the irrigated perimeter of Tadla (Morocco), and revealed that the established model provided effectiveness results in the study areas. Numéro de notice : A2021-554 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1655797 Date de publication en ligne : 12/12/2019 En ligne : https://doi.org/10.1080/10106049.2019.1655797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98105 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021131	RAB	Revue	Centre de documentation	En réserve L003	Disponible