Centre de documentation
scientifique

Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar / Andrew W. Whelan in Remote sensing of environment, vol 284 (January 2023)  

Public [article]  inRemote sensing of environment > vol 284 (January 2023) . - n° 113362 Titre : Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar Type de document : Article/Communication Auteurs : Andrew W. Whelan, Auteur ; Jeffery B. Cannon, Auteur ; Seth W. Bigelow, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113362 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] classification par maximum de vraisemblance [Termes IGN] diagnostic foliaire [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Géorgie (Etats-Unis) [Termes IGN] modélisation de la forêt [Termes IGN] Pinus palustris [Termes IGN] structure d'un peuplement forestier [Termes IGN] surface forestière [Termes IGN] volume en bois [Termes IGN] voxel Résumé : (auteur) Modeling forest attributes using lidar data has been a useful tool for forest management but the need to correlate lidar to ground-based measurements creates challenges to modeling in diverse forest landscapes. Many lidar models have been based on metrics derived from summarizations of individual lidar returns over sample plot areas, but more recently, metrics based on summarization by volumetric pixel (voxel) have shown promise to better characterize forest structure and distinguish between diverse forest types. Voxel-based metrics may improve characterization of leaf area distribution and horizontal forest structure, which could help create general models of forest attributes applicable in complex landscapes composed of many distinct forest types. We modeled wood volume in longleaf pine woodlands and associated forests to compare how area- and voxel- based lidar metrics predicted wood volume in forest type specific and general predictive models. We created four area-based and six voxel-based metrics to fit models of wood volume using a multiplicative power function. We selected models and compared metric importance using AIC and evaluated model performance using cross-validated mean prediction error. We found that one area-based metric and four voxel-based metrics consistently improved model predictions We suggest that area-based metrics alone may have limitations for characterizing complex forest structure. Area-based summarizes of lidar returns are more heavily influenced by upper canopy returns because lidar returns attenuate below the canopy. By contrast, summarizing lidar returns into a single value per voxel prior to summarization over plots homogenizes point density, giving added weight to sub-canopy returns. Thus voxel-based metrics may be more sensitive to structural variation that may not be adequately captured by area-based metrics alone. This study highlights the potential of voxel-based metrics for characterizing complex forest structure and model generalization capable of accurate forest attribute prediction across diverse forest types. Numéro de notice : A2023-016 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113362 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102150 [article]

Modeling land use change and forest carbon stock changes in temperate forests in the United States / Lucia Fitts in Carbon Balance and Management, vol 16 ([01/02/2021])  

Public [article]  inCarbon Balance and Management > vol 16 [01/02/2021] . - n° 20 (2021) Titre : Modeling land use change and forest carbon stock changes in temperate forests in the United States Type de document : Article/Communication Auteurs : Lucia Fitts, Auteur ; Matthew B. Russell, Auteur ; Grant M. Domke, Auteur ; Joseph F. Knight, Auteur Année de publication : 2021 Article en page(s) : n° 20 (2021) Langues : Anglais (eng) Descripteur : [Termes IGN] changement d'occupation du sol [Termes IGN] Colorado (Etats-Unis) [Termes IGN] forêt tempérée [Termes IGN] Géorgie (Etats-Unis) [Termes IGN] impact sur l'environnement [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modélisation spatio-temporelle [Termes IGN] New York (Etats-Unis ; état) [Termes IGN] puits de carbone [Termes IGN] Texas (Etats-Unis) [Termes IGN] Wisconsin (Etats-Unis) [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Background : Forests provide the largest terrestrial sink of carbon (C). However, these C stocks are threatened by forest land conversion. Land use change has global impacts and is a critical component when studying C fluxes, but it is not always fully considered in C accounting despite being a major contributor to emissions. An urgent need exists among decision-makers to identify the likelihood of forest conversion to other land uses and factors affecting C loss. To help address this issue, we conducted our research in California, Colorado, Georgia, New York, Texas, and Wisconsin. The objectives were to (1) model the probability of forest conversion and C stocks dynamics using USDA Forest Service Forest Inventory and Analysis (FIA) data and (2) create wall-to-wall maps showing estimates of the risk of areas to convert from forest to non-forest. We used two modeling approaches: a machine learning algorithm (random forest) and generalized mixed-effects models. Explanatory variables for the models included ecological attributes, topography, census data, forest disturbances, and forest conditions. Model predictions and Landsat spectral information were used to produce wall-to-wall probability maps of forest change using Google Earth Engine. Results : During the study period (2000–2017), 3.4% of the analyzed FIA plots transitioned from forest to mixed or non-forested conditions. Results indicate that the change in land use from forests is more likely with increasing human population and housing growth rates. Furthermore, non-public forests showed a higher probability of forest change compared to public forests. Areas closer to cities and coastal areas showed a higher risk of transition to non-forests. Out of the six states analyzed, Colorado had the highest risk of conversion and the largest amount of aboveground C lost. Natural forest disturbances were not a major predictor of land use change. Conclusions : Land use change is accelerating globally, causing a large increase in C emissions. Our results will help policy-makers prioritize forest management activities and land use planning by providing a quantitative framework that can enhance forest health and productivity. This work will also inform climate change mitigation strategies by understanding the role that land use change plays in C emissions. Numéro de notice : A2021-501 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE Nature : Article DOI : 10.1186/s13021-021-00183-6 Date de publication en ligne : 03/07/2021 En ligne : https://doi.org/10.1186/s13021-021-00183-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98099 [article]

Road network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)  

Public [article]  inComputers, Environment and Urban Systems > vol 80 (March 2020) Titre : Road network structure and ride-sharing accessibility: A network science perspective Type de document : Article/Communication Auteurs : Mingshu Wang, Auteur ; Zheyan Chen, Auteur ; Lan Mu, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Atlanta (Géorgie) [Termes IGN] autopartage [Termes IGN] densité de population [Termes IGN] gestion urbaine [Termes IGN] migration pendulaire [Termes IGN] modèle conceptuel de données localisées [Termes IGN] OpenStreetMap [Termes IGN] réseau routier [Termes IGN] système d'information géographique Résumé : (auteur) The prosperity of ride-sharing services has rippled in the communities of GIScience, transportation, and urban planning. Meanwhile, road network structure has been analyzed from a network science perspective that focuses on nodes and relational links and aims to predictive models. However, limited empirical studies have explored the relationship between road network structure and ride-sharing accessibility through such perspective. This paper utilizes the spatial Durbin model to understand the relationship between road network structure and ride-sharing accessibility, proxied by Uber accessibility, through classical network measures of degree, closeness, and betweenness centrality. Taking the city of Atlanta as a case study, we have found in addition to population density and road network density, larger values of degree centrality and smaller values of closeness centrality of the road network are associated with better accessibility of Uber services. However, the effects of betweenness centrality are not significant. Furthermore, we have revealed heterogeneous effects of degree centrality and closeness centrality on the accessibility of Uber services, as the magnitudes of their effects vary by different time windows (i.e., weekday vs. weekend, rush hour in the morning vs. evening). Network science provides us both conceptual and methodological measures to understand the association between road network structure and ride-sharing accessibility. In this study, we constructed road network structure measures with OpenStreetMap, which is reproducible, replicable, and scalable because of its global coverage and public availability. The study resonates with the notion of cities as the set of interactions across networks, as we have observed time-sensitive heterogeneous effects of road network structure on ride-sharing accessibility. Numéro de notice : A2020-190 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2019.101430 Date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101430 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94852 [article]

Opening GIScience : A process-based approach / Jerry Shannon in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 32 n° 9-10 (September - October 2018) . - pp 1911 - 1926 Titre : Opening GIScience : A process-based approach Type de document : Article/Communication Auteurs : Jerry Shannon, Auteur ; Kyle Walker, Auteur Année de publication : 2018 Article en page(s) : pp 1911 - 1926 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] données démographiques [Termes IGN] Géorgie (Etats-Unis) [Termes IGN] participation du public [Termes IGN] production participative [Termes IGN] RStudio [Termes IGN] science citoyenne [Termes IGN] WebSIG Résumé : (Auteur) Many scholars have demonstrated growing interest in GIScience in recent years, including use of open data portals, shared code and options for open access publication. These practices have made both research and data more transparent and accessible for a broad audience. This research may be open only in a limited sense for populations without expertise in the technology and methods undergirding these data. Based on two case studies using RStudio’s Shiny web platform, we argue that a process-based approach focusing on how analysis is opened throughout the research process provides a supplementary way to define and reflect upon public facing geographic research. Reflecting upon decisions we made at key points in each case study project, we identify four key tensions inherent to work in open GIScience: standardized vs. flexible tools, expert vs. community-led design, single vs. multiple audiences and established vs. emerging metrics. Numéro de notice : A2018-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1464167 Date de publication en ligne : 03/05/2018 En ligne : https://doi.org/10.1080/13658816.2018.1464167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90465 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2018051	RAB	Revue	Centre de documentation	En réserve L003	Disponible

From consumer to pro / Monica Miller Rodgers in GEO: Geoconnexion international, vol 15 n° 5 (May 2016)

Public [article]  inGEO: Geoconnexion international > vol 15 n° 5 (May 2016) . - pp 22 - 24 Titre : From consumer to pro Type de document : Article/Communication Auteurs : Monica Miller Rodgers, Auteur ; Katherine Lehmuller, Auteur Année de publication : 2016 Article en page(s) : pp 22 - 24 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] aéroport [Termes IGN] Atlanta (Géorgie) [Termes IGN] carte d'intérieur [Termes IGN] données localisées des bénévoles [Termes IGN] positionnement en intérieur [Termes IGN] SIG nomade Résumé : (éditeur) The busiest passenger airport in the world has taken advantage of innovations in mobile GIS to improve its asset management processes and the accuracy of its data collection. Numéro de notice : A2016-195 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80630 [article]

Privacy and spatial pattern preservation in masked GPS trajectory data / Dara E. Seidl in International journal of geographical information science IJGIS, vol 30 n° 3-4 (March - April 2016)  

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Comparing individual-tree approaches for predicting height growth of underplanted seedlings / John M. Lhotka in Annals of Forest Science, vol 72 n° 4 (June 2015)  

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Challenges and lessons from a wetland LiDAR project: a case study of the Okefenokee Swamp, Georgia, USA / L. Shea Rose in Geocarto international, vol 28 n° 3-4 (June - July 2013)  

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Quantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region / George Xian in Geocarto international, vol 27 n° 6 (October 2012)  

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Synthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)  

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Interpolating spatial interaction data / W. Jang in Transactions in GIS, vol 15 n° 4 (August 2011)  

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A comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification / C.W. Emerson in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)  

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Potential of using NOAA-AVHRR data for estimating irrigated area to help solve an inter-state water dispute / V.K. Boken in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)  

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Land-use and land-cover change, urban heat island phenomenon, and health implications: a remote sensing approach / C.P. Lo in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)  

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Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data / L. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)  

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