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Urban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method / Qiang Chen in Remote sensing, vol 13 n° 1 (January 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January 2021) . - n° 158 Titre : Urban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method Type de document : Article/Communication Auteurs : Qiang Chen, Auteur ; Qianhao Cheng, Auteur ; Jinfei Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 158 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] analyse spectrale [Termes descripteurs IGN] construction [Termes descripteurs IGN] déchet [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] gestion urbaine [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] morphologie [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] segmentation hiérarchique [Termes descripteurs IGN] urbanisation Résumé : (auteur) With rapid urbanization, the disposal and management of urban construction waste have become the main concerns of urban management. The distribution of urban construction waste is characterized by its wide range, irregularity, and ease of confusion with the surrounding ground objects, such as bare soil, buildings, and vegetation. Therefore, it is difficult to extract and identify information related to urban construction waste by using the traditional single spectral feature analysis method due to the problem of spectral confusion between construction waste and the surrounding ground objects, especially in the context of very-high-resolution (VHR) remote sensing images. Considering the multi-feature analysis method for VHR remote sensing images, we propose an optimal method that combines morphological indexing and hierarchical segmentation to extract the information on urban construction waste in VHR images. By comparing the differences between construction waste and the surrounding ground objects in terms of the spectrum, geometry, texture, and other features, we selected an optimal feature subset to improve the separability of the construction waste and other objects; then, we established a classification model of knowledge rules to achieve the rapid and accurate extraction of construction waste information. We also chose two experimental areas of Beijing to validate our algorithm. By using construction waste separability quality evaluation indexes, the identification accuracy of construction waste in the two study areas was determined to be 96.6% and 96.2%, the separability indexes of the construction waste and buildings reached 1.000, and the separability indexes of the construction waste and vegetation reached 1.000 and 0.818. The experimental results show that our method can accurately identify the exposed construction waste and construction waste covered with a dust screen, and it can effectively solve the problem of spectral confusion between the construction waste and the bare soil, buildings, and vegetation. Numéro de notice : A2021-073 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010158 date de publication en ligne : 05/01/2021 En ligne : https://doi.org/10.3390/rs13010158 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96809 [article]

Semantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 6 (December 2020) . - 1482 - 1503 Titre : Semantic‐based urban growth prediction Type de document : Article/Communication Auteurs : Marvin Mc Cutchan, Auteur ; Simge Özdal‐Oktay, Auteur ; Ioannis Giannopoulos, Auteur Année de publication : 2020 Article en page(s) : 1482 - 1503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] dynamique spatiale [Termes descripteurs IGN] Europe (géographie politique) [Termes descripteurs IGN] information sémantique [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] modélisation spatiale [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] organisation spatiale [Termes descripteurs IGN] OWL [Termes descripteurs IGN] prévision [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] urbanisation [Termes descripteurs IGN] ville durable Résumé : (Auteur) Urban growth is a spatial process which has a significant impact on the earth’s environment. Research on predicting this complex process makes it therefore especially fruitful for decision‐making on a global scale, as it enables the introduction of more sustainable urban development. This article presents a novel method of urban growth prediction. The method utilizes geospatial semantics in order to predict urban growth for a set of random areas in Europe. For this purpose, a feature space representing geospatial configurations was introduced which embeds semantic information. Data in this feature space was then used to perform deep learning, which ultimately enables the prediction of urban growth with high accuracy. The final results reveal that geospatial semantics hold great potential for spatial prediction tasks. Numéro de notice : A2020-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12655 date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1111/tgis.12655 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96657 [article]

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 descripteurs IGN] adjacence [Termes descripteurs IGN] analyse combinatoire (maths) [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] changement d'utilisation du sol [Termes descripteurs IGN] Chine [Termes descripteurs IGN] construction [Termes descripteurs IGN] extraction de modèle [Termes descripteurs IGN] filtrage spatiotemporel [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] polygone [Termes descripteurs IGN] région [Termes descripteurs IGN] relation spatiale [Termes descripteurs IGN] surface cultivée [Termes descripteurs IGN] urbanisation [Termes descripteurs IGN] utilisation du sol [Termes descripteurs 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]

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A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data / Haiyan Tao in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 3 (March 2020) . - pp 604 - 624 Titre : A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data Type de document : Article/Communication Auteurs : Haiyan Tao, Auteur ; Keli Wang, Auteur ; Li Zhuo, Auteur Année de publication : 2020 Article en page(s) : pp 604 - 624 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] Chine [Termes descripteurs IGN] diffusion spatiale [Termes descripteurs IGN] distribution de Poisson [Termes descripteurs IGN] données socio-économiques [Termes descripteurs IGN] hétérogénéité environnementale [Termes descripteurs IGN] hétérogénéité spatiale [Termes descripteurs IGN] maladie infectieuse [Termes descripteurs IGN] migration humaine [Termes descripteurs IGN] mobilité territoriale [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] modèle mathématique [Termes descripteurs IGN] origine - destination [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] risque sanitaire [Termes descripteurs IGN] urbanisation Résumé : (auteur) International communication and global cooperation have greatly accelerated the worldwide spread of dengue fever, increasing the impact of imported cases on dengue outbreaks in non-naturally endemic areas. Existing studies mostly focus on describing the quantitative relationship between imported cases and local transmission but ignore the space-time diffusion mode of imported cases under the influence of individual mobility. In this paper, we propose a comprehensive framework at a fine scale to establish the disease transmission network and a mathematical model, which constructs ‘source-sink’ links between the imported and indigenous cases on a regular grid with a spatial resolution of 1 km to explore the diffusion pattern and spatiotemporal heterogeneity of imported cases. An application to Guangzhou, China, reveals the main flow and transmission path of imported cases under the influence of human movement and identifies the spatiotemporal distribution of transmission speed according to the time lag of each source-sink link. In addition, we demonstrate that using individual-based movement data and socio-economic factors to study human mobility and imported cases can help to understand the driving forces of dengue spread. Our research provides a comprehensive framework for the analysis of early dengue transmission patterns with benefits to similar urban applications. Numéro de notice : A2020-107 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684497 date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684497 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94707 [article]

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Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1696 - 1717 Titre : Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection Type de document : Article/Communication Auteurs : Da He, Auteur ; Yanfei Zhong, Auteur ; Liangpei Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 1696 - 1717 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] changement d'occupation du sol [Termes descripteurs IGN] classification du maximum a posteriori [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] distribution spatiale [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image Quickbird [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] optimisation spatiale [Termes descripteurs IGN] précision infrapixellaire [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] urbanisation [Termes descripteurs IGN] Wuhan (Chine) [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) The maximum a posteriori (MAP) estimation model-based sub-pixel mapping (SPM) method is an alternative way to solve the ill-posed SPM problem. The MAP estimation model has been proven to be an effective SPM approach and has been extensively developed over the past few years, as a result of its effective regularization capability that comes from the spatial regularization model. However, various spatial regularization models do not always truly reflect the detailed spatial distribution in a real situation, and the over-smoothing effect of the spatial regularization model always tends to efface the detailed structural information. In this article, under the scenario of time-series observation by remote sensing imagery, the joint spectral–spatial–temporal MAP-based (SST_MAP) model for SPM is proposed. In SST_MAP, a newly developed temporal regularization model is added to the MAP model, based on the prerequisite for a temporally close fine image covering the same study region. This available fine image can provide the specific spatial structures most closely conforming to the ground truth for a more precise constraint, thereby reducing the over-smoothing effect. Furthermore, the three dimensions are mutually balanced and mutually constrained, to reach an equilibrium point and achieve restoration of both smooth areas for the homogeneous land-cover classes and a detailed structure for the heterogeneous land-cover classes. Four experiments were designed to validate the proposed SST_MAP: three synthetic-image experiments and one real-image experiment. The restoration results confirm the superiority of the proposed SST_MAP model. Notably, under the background of time-series observation, SST_MAP provides an alternative way of land-cover change detection (LCCD), achieving both detailed spatial-scale and high-frequency temporal LCCD observation for the study case of urbanization analysis within the city of Wuhan in China. Numéro de notice : A2020-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947708 date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947708 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94662 [article]

La biodiversité à l’épreuve des choix d’aménagement : une approche par la modélisation appliquée à la Région Occitanie / Coralie Calvet in Sciences, eaux & territoires, n° 31 (janvier 2020)  

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Pour la recherche urbaine / Félix Ardisson (2020)  

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Pressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)  

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Innovative geo-information tools for governance / Yola Georgiadou (2019)  

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Innovative Methods and Products of the " Urbanization and Artificialization" Scientific Expertise Centre / Anne Puissant (2019)  

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Urban growth simulations in order to represent the impacts of constructions and environmental constraints on urban sprawl / Mojtaba Eslahi (2019)  

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A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis / Xiya Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)  

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InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)  

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Measuring the effect of an ongoing urbanization process on biodiversity conservation suitability index : integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS) / Mehdi Sheikh Goodarzi in Geocarto international, vol 32 n° 8 (August 2017)  

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Depicting urban boundaries from a mobility network of spatial interactions : a case study of Great Britain with geo-located Twitter data / Junjun Yin in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)  

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