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Mining regional patterns of land use with adaptive adjacent criteria / Xinmeng Tu in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

Public [article]  inCartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 418 - 431 Titre : Mining regional patterns of land use with adaptive adjacent criteria Type de document : Article/Communication Auteurs : Xinmeng Tu, Auteur ; Zhenjie Chen, Auteur ; Beibei Wang, Auteur ; changqing Xu, Auteur Année de publication : 2020 Article en page(s) : pp 418 - 431 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] adjacence [Termes IGN] analyse combinatoire (maths) [Termes IGN] analyse de groupement [Termes IGN] analyse spatio-temporelle [Termes IGN] changement d'utilisation du sol [Termes IGN] Chine [Termes IGN] construction [Termes IGN] extraction de modèle [Termes IGN] filtrage spatiotemporel [Termes IGN] occupation du sol [Termes IGN] polygone [Termes IGN] région [Termes IGN] relation spatiale [Termes IGN] surface cultivée [Termes IGN] urbanisation [Termes IGN] utilisation du sol [Termes IGN] variogramme Résumé : (auteur) Land use/cover changes (LULC) are complicated and regionally diverse. When mining regional patterns, the use of a spatial relationship that is determined without considering the spatial correlation among geographical objects can lead to problematic results, e.g. mistakenly treating unrelated objects as adjacent. Additionally, traditional prevalence measures are unstable for uneven datasets such as LULC, wherein some land-use change types show small numbers and uneven quantities, and valuable rules for some land-use categories may be ignored. Therefore, we proposed a regional pattern mining method. First, we developed adaptive adjacent criteria, which can be automatically generated for each specific zone to define adjacency for better spatial-temporal mining. Then, a combinational decision model was built to improve the stability of the prevalence measure, which was used to filter out the insignificant spatial-temporal rules. Furthermore, we proposed two levels of land-use pattern mining, i.e. cluster-level mining and polygon-level mining, to first discover hot-spot areas where similar land-use change has occurred frequently and then to determine the location, frequency, and change time of rules related to different land-use activities. The proposed method was used for mining the dependence of land use and regional patterns on land-use changes. Results show that the proposed method can determine the spatial dependence between the land-use categories, as well as regional patterns of land-use changes. According to our research, the study area, Xinbei District, China, is undergoing land-use change involving rapid urbanization, extensive transportation construction, and losses of farmland. Numéro de notice : A2020-487 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1761452 Date de publication en ligne : 18/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1761452 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95655 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2020051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A topology-preserving polygon rasterization algorithm / Chen Zhou in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 6 (November 2018) . - pp 495 - 509 Titre : A topology-preserving polygon rasterization algorithm Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Dingmou Li, Auteur ; Ningchuan Xiao, Auteur ; Zhenjie Chen, Auteur ; Xiang Li, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 509 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données vectorielles [Termes IGN] polygone [Termes IGN] rastérisation [Termes IGN] relation topologique [Termes IGN] traitement de données localisées Résumé : (Auteur) Conventional algorithms for polygon rasterization are typically designed to maintain non-topological characteristics. Consequently, topological relationships, such as the adjacency between polygons, may also be lost or altered, creating topological errors. This paper proposes a topology-preserving polygon rasterization algorithm to avoid topological errors. Four types of topological error may occur during polygon rasterization. The algorithm starts from an initial polygon rasterization and uses a set of preserving strategies to increase topological accuracy. The count of the four types of error measures the topological errors of the conversion. Topological accuracy is summarized as 1 minus the ratio of actual topological errors to the total number of possible error cases. When applied to a land-use dataset with a data volume of 128 MB, 127,836 polygons, and extending 1352 km2, the algorithm achieves a topological accuracy of more than 99% when raster cell size is 30 m or smaller (100% for 5 and 10 m). The effects of cell size, polygon shape, and number of iterations on topological accuracy are also examined. Numéro de notice : A2018-473 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1401488 Date de publication en ligne : 21/11/2017 En ligne : https://doi.org/10.1080/15230406.2017.1401488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91256 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2018061	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs / Chen Zhou in Transactions in GIS, vol 21 n° 3 (June 2017)  

Public [article]  inTransactions in GIS > vol 21 n° 3 (June 2017) . - pp 608 – 631 Titre : A parallel scheme for large-scale polygon rasterization on CUDA-enabled GPUs Type de document : Article/Communication Auteurs : Chen Zhou, Auteur ; Zhenjie Chen, Auteur ; Yuzhe Pian, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 608 – 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] données massives [Termes IGN] maillage [Termes IGN] polygone [Termes IGN] processeur [Termes IGN] processeur graphique [Termes IGN] rastérisation [Termes IGN] temps [Termes IGN] traitement parallèle Résumé : (Auteur) This research develops a parallel scheme to adopt multiple graphics processing units (GPUs) to accelerate large-scale polygon rasterization. Three new parallel strategies are proposed. First, a decomposition strategy considering the calculation complexity of polygons and limited GPU memory is developed to achieve balanced workloads among multiple GPUs. Second, a parallel CPU/GPU scheduling strategy is proposed to conceal the data read/write times. The CPU is engaged with data reads/writes while the GPU rasterizes the polygons in parallel. This strategy can save considerable time spent in reading and writing, further improving the parallel efficiency. Third, a strategy for utilizing the GPU's internal memory and cache is proposed to reduce the time required to access the data. The parallel boundary algebra filling (BAF) algorithm is implemented using the programming models of compute unified device architecture (CUDA), message passing interface (MPI), and open multi-processing (OpenMP). Experimental results confirm that the implemented parallel algorithm delivers apparent acceleration when a massive dataset is addressed (50.32 GB with approximately 1.3 × 108 polygons), reducing conversion time from 25.43 to 0.69 h, and obtaining a speedup ratio of 36.91. The proposed parallel strategies outperform the conventional method and can be effectively extended to a CPU-based environment. Numéro de notice : A2017-626 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12213 En ligne : http://dx.doi.org/10.1111/tgis.12213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86941 [article]