Centre de documentation
scientifique

Dépouillements

Detecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa / Shenelle Lottering in Geocarto international, vol 37 n° 6 ([01/04/2022])  

Public [article]  inGeocarto international > vol 37 n° 6 [01/04/2022] . - pp 1574 - 1586 Titre : Detecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa Type de document : Article/Communication Auteurs : Shenelle Lottering, Auteur ; Paramu Mafongoyab, Auteur ; Romano Lottering, Auteur Année de publication : 2022 Article en page(s) : pp 1574 - 1586 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique du sud (état) [Termes IGN] cartographie thématique [Termes IGN] données météorologiques [Termes IGN] données multitemporelles [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-TM [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] sécheresse [Termes IGN] stress hydrique [Termes IGN] température au sol Résumé : (auteur) Drought has become a more frequent phenomenon under changing climatic conditions, particularly in Sub Saharan Africa. This study tested the utility of a newly proposed Temperature-Vegetation Water Stress Index (T-VWSI) in detecting drought severity using Landsat data for the years 2008, 2012, 2016 and 2018. This index was created using both NDVI and LST to detect drought severity within the region. The results show that the year 2016 experienced the most severe levels of drought, with the northern areas of the uMsinga region being most severely affected. SPI was used to corroborate the findings of the T-VWSI index and also established that the year 2016 was the year of severe drought in uMsinga. The results of this study have illustrated the potential of the T-VWSI index in effectively mapping and detecting drought over large spatial areas. Numéro de notice : A2022-473 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1783580 Date de publication en ligne : 08/07/2020 En ligne : https://doi.org/10.1080/10106049.2020.1783580 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100820 [article]

Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) / Safwan Mohammed in Geocarto international, vol 37 n° 6 ([01/04/2022])  

Public [article]  inGeocarto international > vol 37 n° 6 [01/04/2022] . - pp 1645 - 1663 Titre : Assessment of land suitability potentials for winter wheat cultivation by using a multi criteria decision Support-Geographic information system (MCDS-GIS) approach in Al-Yarmouk Basin (Syria) Type de document : Article/Communication Auteurs : Safwan Mohammed, Auteur ; Karam Alsafadi, Auteur ; Haidar Ali, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1645 - 1663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] blé (céréale) [Termes IGN] cultures [Termes IGN] données météorologiques [Termes IGN] état du sol [Termes IGN] MNS SRTM [Termes IGN] outil d'aide à la décision [Termes IGN] qualité du sol [Termes IGN] Syrie [Termes IGN] système d'information géographique Résumé : (auteur) In the last few years, the agricultural sector in Syria has suffered from major problems related to land degradation. To cope with this problem, a land suitability assessment has become an essential tool for sustainable land use management. The present research qualitatively evaluated the suitability of land in the Al-Yarmouk Basin (S-Syria) for rainfed winter wheat (Triticum aestivum) cultivation. In this study, a regional spatial approach involving three steps was developed, based on the method proposed by Sys et al. In the first step, a soil survey was carried out and 107 soil profiles were described, sampled and analyzed. In the second step, climatic gridded datasets from 1984–2014 MRm at a high spatial resolution (30 meters) and the Digital Elevation Model (DEM) were clipped from NASA's Shuttle Radar Topography Mission (SRTM) and prepared for the study area. In the third step, a land suitability assessment was performed using the geographical information system (GIS) and multi criteria decision support (MCDS). Soil survey outcomes showed that the study area was dominated by five soil orders: Mollisols, Inceptisols, Vertisols, Entisols and Aridisols. Also, results from the Sys model illustrated that more than 23.8% of the study area is highly suitable (S1–0) for wheat production without any limitations, whereas 38.7% and 37.5% are highly suitable (S1–1) and moderately suitable (S2), respectively. Also, the study emphasizes the important role of topographical factors in the study area for wheat cultivation. All in all, this research suggests W-Syria as a potential region for wheat cultivation, instead of the eastern area which is subject to climate change and a shortage of water. Integrating the Sys-approach and the GIS framework offers a good tool for policy-makers to apply in Syria for land suitability assessments. Numéro de notice : A2022-474 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1790674 Date de publication en ligne : 15/07/2020 En ligne : https://doi.org/10.1080/10106049.2020.1790674 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100821 [article]

Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery / Semiha Demirbaş Çağlayana in Geocarto international, vol 37 n° 6 ([01/04/2022])  

Public [article]  inGeocarto international > vol 37 n° 6 [01/04/2022] . - pp 1587 - 1606 Titre : Species level classification of Mediterranean sparse forests-maquis formations using Sentinel-2 imagery Type de document : Article/Communication Auteurs : Semiha Demirbaş Çağlayana, Auteur ; Ugur Murat Leloglu, Auteur ; Christian Ginzler, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1587 - 1606 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] Arbutus unedo [Termes IGN] carte de la végétation [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données multitemporelles [Termes IGN] Erica (genre) [Termes IGN] extraction de traits caractéristiques [Termes IGN] forêt méditerranéenne [Termes IGN] Genista (genre) [Termes IGN] gestion forestière durable [Termes IGN] image Sentinel-MSI [Termes IGN] maquis [Termes IGN] Olea europaea [Termes IGN] Turquie Résumé : (auteur) Essential forest ecosystem services can be assessed by better understanding the diversity of vegetation, specifically those of Mediterranean region. A species level classification of maquis would be useful in understanding vegetation structure and dynamics, which would be an indicator of degradation or succession in the region. Although remote sensing was regularly used for classification in the region, maquis are simply represented as one to three categories based on density or height. To fill this gap, we test the capability of Sentinel-2 imagery, together with selected ancillary variables, for an accurate mapping of the dominant maquis formations. We applied Recursive Feature Selection procedure and used a Random Forest classifier. The algorithm is tested using ground truth collected from site and reached 78% and 93% overall accuracy at species level and physiognomic level, respectively. Our results suggest species level characterization of dominant maquis is possible with Sentinel-2 spatial resolution. Numéro de notice : A2022-475 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1783581 Date de publication en ligne : 09/07/2020 En ligne : https://doi.org/10.1080/10106049.2020.1783581 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100822 [article]