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Assessing spatial-temporal evolution processes and driving forces of karst rocky desertification / Fei Chen in Geocarto international, vol 36 n° 3 ([15/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 3 [15/02/2021] . - pp 262 - 280 Titre : Assessing spatial-temporal evolution processes and driving forces of karst rocky desertification Type de document : Article/Communication Auteurs : Fei Chen, Auteur ; Shijie Wang, Auteur ; Xiaoyong Bai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 262 - 280 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatio-temporelle [Termes IGN] carte d'utilisation du sol [Termes IGN] Chine [Termes IGN] classification et arbre de régression [Termes IGN] désertification [Termes IGN] données spatiotemporelles [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] karst [Termes IGN] lithologie Résumé : (auteur) Karst Rocky Desertification (KRD) has become the most serious ecological disaster in Southwest China. We used the data of Thematic Mapper (TM) images from 1990, 1995, 2000, 2004, and 2011 and the 2016 Operational Land Imager (OLI) image. These sensing images were pre-processed by removing non-karst areas based on lithology and cutting away the land types impossibly generating KRD from land use maps. Then, we used a Classification And Regression Tree (CART) to classify the KRD. We want to improve the interpretation accuracy of KRD through the above steps. The results were as follows: (1) The KRD experiences the evolution process of ‘first deterioration and then improvement’. The rate is −4.94 km2.a−1 over a period of 1990 to 2004, and the rate is 36.48 km2.a−1 from 2004 to 2016; (2) The most influential factors causing KRD formation are the lithology and the resident population density, with contribution rates of 30.17% and 25.86%, respectively. Numéro de notice : A2021-140 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595175 Date de publication en ligne : 18/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595175 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97036 [article]

Integrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques / Hamid Karimi in Geocarto international, vol 36 n° 3 ([15/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 3 [15/02/2021] . - pp 320 - 339 Titre : Integrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques Type de document : Article/Communication Auteurs : Hamid Karimi, Auteur ; Hossein Zeinivand, Auteur Année de publication : 2021 Article en page(s) : pp 320 - 339 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte hydrographique [Termes IGN] combinaison linéaire ponderée [Termes IGN] couche thématique [Termes IGN] eau pluviale [Termes IGN] écoulement des eaux [Termes IGN] étang [Termes IGN] Iran [Termes IGN] modèle hydrographique [Termes IGN] processus de hiérarchisation analytique [Termes IGN] ruissellement Résumé : (auteur) Rainwater harvesting (RWH) is one of the major techniques that is investigated in the present study using Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methods as two tools for decision-making, weighting and combining different thematic layers include land use, slope, drainage density and hydrological soil groups (HSG). The runoff map obtained by the distributed spatial-physical WetSpa model is considered as a useful layer that is integrated with other thematic layers in the geographic information system (GIS) environment for identifying RWH sites. Kakareza watershed (1132 km2) in Iran was selected as a study area to carry out the foregoing approach. The results showed that 256 km2 of the study area is good for RWH, 360 km2 is moderate and 516 km2 is poor. Thus, about 22.61% (256 km2) of Kakareza watershed is highly suitable for farm ponds. This article recommends the RWH suitable sites to a judicious decision for better water management in the area. Numéro de notice : A2021-141 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1608590 Date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1608590 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97037 [article]