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Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns / Damilola Eyelade in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 1037 - 1058 Titre : Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns Type de document : Article/Communication Auteurs : Damilola Eyelade, Auteur ; Keith C. Clarke, Auteur ; Ighodalo Ijagbone, Auteur Année de publication : 2022 Article en page(s) : pp 1037 - 1058 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] croissance urbaine [Termes IGN] dalle [Termes IGN] données spatiotemporelles [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] Nigéria [Termes IGN] OpenStreetMap Résumé : (auteur) The SLEUTH model provides a framework for understanding land use evolution around urban areas. Calibration of SLEUTH’s behavioral coefficients can be impacted by scale and nonlinear transitions due to the SLEUTH land use deltatron module’s assumption of linear Markov change probabilities. This study attempted to establish what spatial resolution and temporal scale produces the most accurate forecasts given the linear change assumption. The impact of tiling the input data was also examined. To determine these, SLEUTH was calibrated at four spatial and three temporal scales for Ibadan, Nigeria using both untiled and tiled data. Calibration results were evaluated using accuracy metrics including Figure of Merit (FOM) and mean uncertainty. The best mix of calibration metrics (FOM 0.26) and mean uncertainty (11.64) was achieved at 30 m resolution and an intermediate temporal interval. Tiling input data led to overfitting, allowing good model fit within individual tiles but a reduction in trend recognition across land use types. Subsequently, a 2040 projection that is as accurate as possible, and scientifically justifiable given the available data, was produced. The findings provide a framework for understanding the effect of spatiotemporal scale on SLEUTH inputs that require tiling particularly for urban areas in the global south. Numéro de notice : A2022-347 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2011292 Date de publication en ligne : 16/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2011292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100531 [article]

Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 7 (April-1 2022) . - n° 1698 Titre : Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data Type de document : Article/Communication Auteurs : Zihao Huang, Auteur ; Xuejian Li, Auteur ; Qiang Du, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1698 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] automate cellulaire [Termes IGN] changement climatique [Termes IGN] changement d'utilisation du sol [Termes IGN] Chine [Termes IGN] écosystème forestier [Termes IGN] forêt tropicale [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] interaction homme-milieu [Termes IGN] modèle de simulation [Termes IGN] modèle dynamique [Termes IGN] modèle numérique de surface [Termes IGN] puits de carbone [Termes IGN] simulation spatiale Résumé : (auteur) Future land use and cover change (LUCC) simulations play an important role in providing fundamental data to reveal the carbon cycle response of forest ecosystems to LUCC. Subtropical forests have great potential for carbon sequestration, yet their future dynamics under natural and human influences are unclear. Zhejiang Province in China is an important distribution area for subtropical forests. For forest management, it is of great significance to explore the future dynamic changes of subtropical forests in Zhejiang. As a popular LUCC spatial simulation model, the cellular automata (CA) model coupled with machine learning and LUCC quantitative demand models such as system dynamics (SD) can achieve effective LUCC simulation. Therefore, we first integrated a back propagation neural network (BPNN), a CA, and a SD model as a BPNN_CA_SD (BCS) coupled model for future LUCC simulation and then designed a slow development scenario (SD_Scenario), a harmonious development scenario (HD_Scenario), a baseline development scenario (BD_Scenario), and a fast development scenario (FD_Scenario), combining climate change and human disturbance. Thirdly, we obtained future land-use patterns in Zhejiang Province from 2014 to 2084 under multiple scenarios, and finally, we analyzed the temporal and spatial changes of land use and discussed the subtropical forest dynamics of the future. The results showed the following: (1) The overall accuracy was approximately 0.8, the kappa coefficient was 0.75, and the figure of merit (FOM) value was over 28% when using the BCS model to predict LUCC, indicating that the model could predict the consistent change of LUCC accurately. (2) The future evolution of the LUCC under different scenarios varied, with the growth of bamboo forests and the decline of coniferous forests in the FD_Scenario being prominent among the forest dynamics changes. Compared with 2014, the bamboo forest in 2084 will increase by 37%, while the coniferous forest will decrease by 25%. (3) Comparing the area and spatial change of the subtropical forests, the SD_Scenario was found to be beneficial for the forest ecology. These results can provide an important decision-making reference for land-use planning and sustainable forest development in Zhejiang Province. Numéro de notice : A2022-281 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14071698 Date de publication en ligne : 31/03/2022 En ligne : https://doi.org/10.3390/rs14071698 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100297 [article]

Historical Vltava River valley–various historical sources within web mapping environment / Jiří Krejčí in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 35 Titre : Historical Vltava River valley–various historical sources within web mapping environment Type de document : Article/Communication Auteurs : Jiří Krejčí, Auteur ; Jiří Cajthaml, Auteur Année de publication : 2022 Article en page(s) : n° 35 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] ArcGIS [Termes IGN] carte ancienne [Termes IGN] changement d'utilisation du sol [Termes IGN] données anciennes [Termes IGN] géoréférencement [Termes IGN] modélisation 3D [Termes IGN] point d'appui [Termes IGN] République Tchèque [Termes IGN] rivière [Termes IGN] système d'information historique [Termes IGN] vectorisation [Termes IGN] web mapping Résumé : (auteur) The article deals with a comprehensive information system of the historic Vltava River valley. This system contains a number of resources, which are described. For old maps, which are the basis of the whole system, their georeferencing and potential problems in creating seamless mosaics are described. Other sources of data include old photographs, which are localized and stored in the system, along with the definition point of the place from which they were probably taken. The vectorization of data is described, not only for area features used for the analysis of land-use changes, but also for the vectorization of contours. These were vectorized from old maps and are substantial for the creation of historic DEM. Vectorized footprints of buildings and vectors of other functional areas subsequently serve as a basis for the procedural modeling of the virtual 3D landscape. The creation of such a complex and broad information system cannot be described in one article. The aim of this text is to draw attention to a possible approach to the presentation and visualization of the historic landscape, along with links to important documents. Numéro de notice : A2022-038 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11010035 Date de publication en ligne : 04/01/2022 En ligne : https://doi.org/10.3390/ijgi11010035 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99380 [article]

Vegetation index and dynamics / Eusebio Cano Carmona (2022)  

Public Titre : Vegetation index and dynamics Type de document : Monographie Auteurs : Eusebio Cano Carmona, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2022 Importance : 350 p. ISBN/ISSN/EAN : 978-1-83969-385-4 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatiale [Termes IGN] analyse spectrale [Termes IGN] Autocad Map [Termes IGN] carte de la végétation [Termes IGN] changement d'utilisation du sol [Termes IGN] Colombie [Termes IGN] couvert forestier [Termes IGN] dynamique de la végétation [Termes IGN] écosystème urbain [Termes IGN] flore endémique [Termes IGN] image aérienne [Termes IGN] image captée par drone [Termes IGN] image RVB [Termes IGN] Inde [Termes IGN] indice de diversité [Termes IGN] indice de végétation [Termes IGN] milieu urbain [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] outil d'aide à la décision [Termes IGN] Pakistan [Termes IGN] pédologie locale [Termes IGN] Pennsylvanie (Etats-Unis) [Termes IGN] Pinus sylvestris [Termes IGN] système d'information géographique [Termes IGN] traitement d'image Index. décimale : 35.41 Applications de télédétection - végétation Résumé : (Editeur) The book contemplates different ways of approaching the study of vegetation as well as the type of indices to be used. However, all the works pursue the same objective: to know and interpret nature from different points of view, either through knowledge of nature in situ or the use of technology and mapping using satellite images. Chapters analyze the ecological parameters that affect vegetation, the species that make up plant communities, and the influence of humans on vegetation. Note de contenu : 1. Introductory Chapter: Methodological Aspects for the Study of Vegetation / Eusebio Cano Carmona, Ricardo Quinto Canas, Ana Cano Ortiz and Carmelo María Musarella 2. Using GIS and the Diversity Indices: A Combined Approach to Woody Plant Diversity in the Urban Landscape / Tuba Gül Doğan and Engin Eroğlu 3. Classical and Modern Remote Mapping Methods for Vegetation Cover / Algimantas Česnulevičius, Artūras Bautrėnas, Linas Bevainis and Donatas Ovodas 4. Assessment of the State of Forest Plant Communities of Scots Pine (Pinus sylvestris L.) in the Conditions of Urban Ecosystems / Elena Runova, Vera Savchenkova, Ekaterina Demina-Moskovskaya and Anastasia Baranenkova 5. Landscape Genetics and Phytogeography of Criollo Avocadoes Persea americana from Northeast Colombia / Clara Inés Saldamando-Benjumea, Gloria Patricia Cañas-Gutiérrez, Jorge Muñoz and Rafael Arango Isaza 6. The Use of NDVI and NDBI to Provide Subsidies to Public Manager’s Decision Making on Maintaining the Thermal Comfort in Urban Areas / Arthur Santos, Fernando Santil and Claudionor Silva 7. Detailed Investigation of Spectral Vegetation Indices for Fine Field-Scale Phenotyping / Maria Polivova and Anna Brook 8. Predictive Models for Reforestation and Agricultural Reclamation: A Clearfield County, Pennsylvania Case Study / Zhi Yue and Jon Bryan Burley 9. Dynamic-Catenal Phytosociology for Evaluating Vegetation / Sara del Río, Raquel Alonso-Redondo, Alejandro González-Pérez, Aitor Álvarez-Santacoloma, Giovanni Breogán Ferreiro Lera and Ángel Penas 10. Germination and Seedling Growth of Entandrophragma bussei Harms ex Engl. from Wild Populations / Samora M. Andrew, Siwa A. Kombo and Shabani A.O. Chamshama 11. Spatial Dynamics of Forest Cover and Land Use Changes in the Western Himalayas of Pakistan / Amjad ur Rahman, Esra Gürbüz, Semih Ekercin and Shujaul Mulk Khan 12. Understanding Past and Present Vegetation Dynamics Using the Palynological Approach: An Introductory Discourse / Sylvester Onoriode Obigba 13. Forest Vegetation and Dynamics Studies in India / Madan Prasad Singh, Manohara Tattekere Nanjappa, Sukumar Raman, Suresh Hebbalalu Satyanatayana, Ayyappan Narayanan, Ganesan Renagaian and Sreejith Kalpuzha Ashtamoorthy 14. Photosynthetic Antenna Size Regulation as an Essential Mechanism of Higher Plants Acclimation to Biotic and Abiotic Factors: The Role of the Chloroplast Plastoquinone Pool and Hydrogen Peroxide / Maria M. Borisova-Mubarakshina, Ilya A. Naydov, Daria V. Vetoshkina, Marina A. Kozuleva, Daria V. Vilyanen, Natalia N. Rudenko and Boris N. Ivanov 15. Rockbee Repellent Endemic Plant Species of Andaman-Nicobar Archipelago in the Bay of Bengal / Sam Paul Mathew and Raveendranpillai Prakashkumar 16. Evaluating Insects as Bioindicators of the Wetland Environment Quality (Arid Region of Algeria) / Brahimi Djamel, Rahmouni Abdelkader, Brahimi Abdelghani and Mesli Lotfi Numéro de notice : 26797 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87465 Date de publication en ligne : 23/02/2022 En ligne : https://doi.org/10.5772/intechopen.87465 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100059

The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4697 Titre : The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) Type de document : Article/Communication Auteurs : Muhammad Amir Siddique, Auteur ; Yu Wang, Auteur ; Ninghan Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatio-temporelle [Termes IGN] champ aléatoire de Markov [Termes IGN] changement d'occupation du sol [Termes IGN] changement d'utilisation du sol [Termes IGN] classification et arbre de régression [Termes IGN] coefficient de corrélation [Termes IGN] écosystème urbain [Termes IGN] flore urbaine [Termes IGN] ilot thermique urbain [Termes IGN] modèle de simulation [Termes IGN] Pékin (Chine) [Termes IGN] planification urbaine [Termes IGN] série temporelle [Termes IGN] température au sol [Termes IGN] urbanisation Résumé : (auteur) The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km2 (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km2 (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km2 (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots. Numéro de notice : A2021-860 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13224697 Date de publication en ligne : 20/11/2021 En ligne : https://doi.org/10.3390/rs13224697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99074 [article]

Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)  

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A comparison of a gradient boosting decision tree, random forests, and artificial neural networks to model urban land use changes: the case of the Seoul metropolitan area / Myung-Jin Jun in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

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Cellular automata based land-use change simulation considering spatio-temporal influence heterogeneity of light rail transit construction: A case in Nanjing, China / Jiaming Na in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)  

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Détection des zones de dégradation et de régénération de la couverture végétale dans le sud du Sénégal à travers l'analyse des tendances de séries temporelles MODIS NDVI et des changements d'occupation des sols à partir d'images LANDSAT / Boubacar Solly in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)  

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Characterizing urban land changes of 30 global megacities using nighttime light time series stacks / Qiming Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)  

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Unprecedented pluri-decennial increase in the growing stock of French forests is persistent and dominated by private broadleaved forests / Jean-Daniel Bontemps in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

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Uncertainty of forested wetland maps derived from aerial photography / Stephen P. Prisley in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)  

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Ancient forest statistics provide centennial perspective over the status and dynamics of forest area in France / Timothée Audinot in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

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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)  

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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)  

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