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Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 1 - 12 Titre : Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping Type de document : Article/Communication Auteurs : Mthembeni Mngadi, Auteur ; John Odindi, Auteur ; Kabir Peerbhay, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2021 Article en page(s) : pp 1 - 12 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse discriminante [Termes IGN] carte forestière [Termes IGN] Eucalyptus (genre) [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] KwaZulu-Natal (Afrique du Sud) [Termes IGN] Pinus (genre) [Termes IGN] télédétection spatiale Résumé : (Auteur) The successful launch and operation of the Sentinel satellite platform has provided access to freely available remotely sensed data useful for commercial forest species discrimination. Sentinel – 1 (S1) with a synthetic aperture radar (SAR) sensor and Sentinel – 2 (S2) multi-spectral sensor with additional and strategically positioned bands offer great potential for providing reliable information for discriminating and mapping commercial forest species. In this study, we sought to determine the value of S1 and S2 data characteristics in discriminating and mapping commercial forest species. Using linear discriminant analysis (LDA) algorithm, S2 multi-spectral imagery showed an overall classification accuracy of 84% (kappa = 0.81), with bands such as the red-edge (703.9–740.2 nm), narrow near infrared (835.1–864.8 nm), and short wave infrared (1613.7–2202.4 nm) particularly influential in discriminating individual forest species stands. When Sentinel 2’s spectral wavebands were fused with Sentinel 1’s (SAR) VV and VH polarimetric modes, overall classification accuracies improved to 87% (kappa = 0.83) and 88% (kappa = 0.85), respectively. These findings demonstrate the value of combining Sentinel’s multispectral and SAR structural information characteristics in improving commercial forest species discrimination. These, in addition to the sensors free availability, higher spatial resolution and larger swath width, offer unprecedented opportunities for improved local and large scale commercial forest species discrimination and mapping. Numéro de notice : A2021-050 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1585483 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1585483 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96719 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia / Meron Awoke Eshetae in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 60 - 75 Titre : Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia Type de document : Article/Communication Auteurs : Meron Awoke Eshetae, Auteur ; Binyam Tesfaw Hailu, Auteur ; Sebsebe Demissew, Auteur Année de publication : 2021 Article en page(s) : pp 60 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] distribution spatiale [Termes IGN] données de terrain [Termes IGN] données environnementales [Termes IGN] entropie maximale [Termes IGN] Ethiopie [Termes IGN] Musa (genre) [Termes IGN] surface cultivée Résumé : (Auteur) Enset (Ensete ventricosum) feeds around 20 million people in Ethiopia and is arguably the most important crop for food security and rural livelihoods in the country. Therefore, it is significant to know its spatial characterization and distribution in the country. We use spatial overlay analysis and the maximum entropy (MaxEnt) model for characterizing and modelling, respectively. Inputs for the model include 26 environmental variables—19 bioclimatic and seven biophysical—in addition to the geospatial location of enset field data. The model result was validated using Receiver Operating Characteristic curve method and the area under the curve (AUC) with 0.842 for cultivated enset and 0.760 (wild enset). The highest prediction (>0.5) of both varieties occurred in the southwestern, south-central and north-eastern parts of Ethiopia—17,293.67 km2 (cultivated) and 40,402 km2 (wild) area. The presence of both enset is probabilistically higher at the tropic-cool/sub-humid Agroecological Zones. Numéro de notice : A2021-051 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1588392 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1080/10106049.2019.1588392 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96773 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM / Samy Ismail Elmahdy in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 76 - 95 Titre : Automated detection of lineaments express geological linear features of a tropical region using topographic fabric grain algorithm and the SRTM DEM Type de document : Article/Communication Auteurs : Samy Ismail Elmahdy, Auteur ; Mohamed Mostafa Mohamed, Auteur ; Tarig A Ali, Auteur Année de publication : 2021 Article en page(s) : pp 76 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte géologique [Termes IGN] linéament [Termes IGN] Malaisie [Termes IGN] milieu tropical [Termes IGN] MNS SRTM [Termes IGN] modèle numérique de surface [Termes IGN] structure géologique Résumé : (Auteur) The availability of the large volume of remote sensing data has allowed for the developing of several automated algorithms for detecting linear geological features and more reliable analysis. However, most of the algorithms focus on edge detection and tone change on a satellite image, which represents all geological and non-geological features. In this study, a topographic fabric algorithm, which calculates the slope and aspect at each point in a DEM, is applied for automatically geological linear features mapping in Bau Goldfield, Malaysia using the new version of the Shuttle Radar Topographic Mission (SRTM) DEM. A series of topographic fabric input parameters was tested using different combinations of input values in order to decide the optimal parameters that provided the suitable detection parameters, best fit and the highest accuracy. Comparison with the geological map demonstrated that the tested parameters made the algorithm able to automatically detect geological structures. Numéro de notice : A2021-052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1594393 Date de publication en ligne : 29/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1594393 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96776 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Accurate assessment of protected area boundaries for land use planning using 3D GIS / Dilek Tezel in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 96 - 109 Titre : Accurate assessment of protected area boundaries for land use planning using 3D GIS Type de document : Article/Communication Auteurs : Dilek Tezel, Auteur ; Mehmet Buyukdemircioglu, Auteur ; Sultan Kocaman, Auteur Année de publication : 2021 Article en page(s) : pp 96 - 109 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aire protégée [Termes IGN] analyse de données [Termes IGN] analyse visuelle [Termes IGN] biodiversité [Termes IGN] conservation des ressources naturelles [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] planification [Termes IGN] SIG 3D [Termes IGN] Turquie Résumé : (Auteur) Protected areas (PAs) are essential for ensuring the sustainability of biodiversity and protecting human lives. Efficient and sustainable protection require cooperation of all stakeholders and anticipate the coherence of conservation aims and human use. PAs can limit the human activities and land use alternatives significantly. Participatory planning and monitoring can help to achieve the protection goals and 3D GIS can serve as the base platform for planning. This study investigates the potential of 3D GIS with high-resolution datasets for accurate definition of PA boundaries and demonstrates a case study in Cesme Peninsula, Turkey. The PA boundaries have been examined with respect to the property ownership boundaries and buildings using the 3D city model of Cesme. A conceptual approach for the determination of PA boundaries is proposed. The results show that 3D GIS can support the ecosystem conservation efforts while observing the interests of all stakeholders at the same time. Numéro de notice : A2021-053 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1590466 Date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1590466 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96778 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Steps-based tree crown delineation by analyzing local minima for counting the trees in very high resolution satellite imagery / Debasish Chakraborty in Geocarto international, vol 36 n° 1 ([01/01/2021])  

Public [article]  inGeocarto international > vol 36 n° 1 [01/01/2021] . - pp 110 - 120 Titre : Steps-based tree crown delineation by analyzing local minima for counting the trees in very high resolution satellite imagery Type de document : Article/Communication Auteurs : Debasish Chakraborty, Auteur ; Pranshu Kumar, Auteur Année de publication : 2021 Article en page(s) : pp 110 - 120 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] arborescence [Termes IGN] comptage [Termes IGN] détection de contours [Termes IGN] houppier [Termes IGN] image à haute résolution [Termes IGN] image à très haute résolution [Termes IGN] image satellite [Termes IGN] image Worldview [Termes IGN] itération [Termes IGN] segmentation d'image Résumé : (Auteur) In this study primarily, high-resolution (HR) satellite image is segmented into tree and non-tree regions. Thereafter plots the local minima in the segmented image. Point surrounded by the higher intensity values is called as local minima. The local minimum is the starting point for marking the tree crown boundary. The adjacent darker points along the local minima are plotted in a specific direction for marking the tree crown boundary. Subsequently a seven steps iterative procedure is followed for delineating and counting the tree crowns. The validation of the method is done on WorldView-2 data. Numéro de notice : A2021-054 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1611947 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1611947 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96779 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2021011	RAB	Revue	Centre de documentation	En réserve L003	Disponible