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An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 24 p. Titre : An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis Type de document : Article/Communication Auteurs : Lei Zhou, Auteur ; Siyu Wang, Auteur ; Mingyi Du, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bassin hydrographique [Termes IGN] changement climatique [Termes IGN] changement d'utilisation du sol [Termes IGN] Chine [Termes IGN] couvert végétal [Termes IGN] désert [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] image Landsat [Termes IGN] image Terra-MODIS [Termes IGN] modèle de simulation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] série temporelle [Termes IGN] surface cultivée Résumé : (auteur) The combined study of vegetation coverage (VC) and land use change provides important scientific guidance for the restoration and protection of arid regions. Taking Hongjian Nur (HJN) Lake in the desert region as a case study, the VC of this area was calculated using a normalized difference vegetation index (NDVI), which is based on a mixed pixel decomposition method. A grey forecasting model (GM) (1, 1) was used to predict future VC. The driving factors of VC and land use change were analyzed. The results indicate that the average VC of the whole watershed showed a gradual increase from 0.29 to 0.49 during 2000–2017. The prediction results of the GM VC showed that the greening trend is projected to continue until 2027. The area of farmland in the watershed increased significantly and its area was mainly converted from unused land, grassland, and forest. The reason for increased VC may be that the combination of the exploitation of unused land and climate change, which is contrary to the country’s sustainable development goals (SDG; goal 15). Therefore, the particularities of the local ecological environment in China’s desert area needs to be considered in the development of ecological engineering projects. Numéro de notice : A2020-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060364 Date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060364 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95163 [article]

Method for the analysis and visualization of similar flow hotspot patterns between different regional groups / Haiping Zhang in ISPRS International journal of geo-information, vol 7 n° 8 (August 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 8 (August 2018) Titre : Method for the analysis and visualization of similar flow hotspot patterns between different regional groups Type de document : Article/Communication Auteurs : Haiping Zhang, Auteur ; Xingxing Zhou, Auteur ; Xin Gu, Auteur ; Lei Zhou, Auteur ; Genlin Ji, Auteur ; Guoan Tang, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] données de flux [Termes IGN] interaction spatiale [Termes IGN] système d'information géographique [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) Interaction among different regions can be illustrated in the form of a stream. For example, the interaction between the flows of people and information among different regions can reflect city network structures, as well as city functions and interconnections. The popularization of big data has facilitated the acquisition of flow data for various types of individuals. The application of the regional interaction model, which is based on the summary level of individual flow data mining, is currently a hot research topic. Thus far, however, previous research on spatial interaction methods has mainly focused on point-to-point and area-to-area interaction patterns, and investigations on the patterns of interaction hotspots between two regional groups with predefined neighborhood relationships, that being with two regions, remain scarce. In this study, a method for the identification of similar interaction hotspot patterns between two regional groups is proposed, and geo-information Tupu methods are applied to visualize interaction patterns. China’s air traffic flow data are used as an example to illustrate the performance of the proposed method to identify and analyze interaction hotspot patterns between regional groups with adjoining relationships across China. Research results indicate that the proposed method efficiently identifies the patterns of interaction flow hotspots between regional groups. Moreover, it can be applied to analyze any flow space in the excavation of the patterns of regional group interaction hotspots. Numéro de notice : A2018-350 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7080328 Date de publication en ligne : 15/08/2018 En ligne : https://doi.org/10.10.3390/ijgi7080328 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90585 [article]