Centre dedocumentation
scientifique

Visualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 5 (May 2020) . - 14 p. Titre : Visualizing when, where, and how fires happen in U.S. parks and protected areas Type de document : Article/Communication Auteurs : Nicole C. Inglis, Auteur ; Jelena Vukomanovic, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] aire protégée [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] géodatabase [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] lutte contre l'incendie [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] parc naturel national [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] réserve naturelle [Termes descripteurs IGN] variation saisonnière [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Fire management in protected areas faces mounting obstacles as climate change alters disturbance regimes, resources are diverted to fighting wildfires, and more people live along the boundaries of parks. Evidence-based prescribed fire management and improved communication with stakeholders is vital to reducing fire risk while maintaining public trust. Numerous national fire databases document when and where natural, prescribed, and human-caused fires have occurred on public lands in the United States. However, these databases are incongruous and non-standardized, making it difficult to visualize spatiotemporal patterns of fire and engage stakeholders in decision-making. We created interactive decision analytics (“VISTAFiRe”) that transform fire history data into clear visualizations of the spatial and temporal dimensions of fire and its management. We demonstrate the utility of our approach using Big Cypress National Preserve and Everglades National Park as examples of protected areas experiencing fire regime change between 1980 and 2017. Our open source visualizations may be applied to any data from the National Park Service Wildland Fire Events Geodatabase, with flexibility to communicate shifts in fire regimes over time, such as the type of ignition, duration and magnitude, and changes in seasonal occurrence. Application of the tool to Everglades and Big Cypress revealed that natural wildfires are occurring earlier in the wildfire season, while human-caused and prescribed wildfires are becoming less and more common, respectively. These new avenues of stakeholder communication are allowing the National Park Service to devise research plans to prepare for environmental change, guide resource allocation, and support decision-making in a clear and timely manner. Numéro de notice : A2020-298 Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9050333 date de publication en ligne : 20/05/2020 En ligne : https://doi.org/10.3390/ijgi9050333 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95138 [article]

Optimizing arbovirus surveillance using risk mapping and coverage modelling / Joni A. Downs in Annals of GIS, Vol 26 n°1 (January 2020)  

Public [article]  inAnnals of GIS > Vol 26 n°1 (January 2020) . - pp 13 - 23 Titre : Optimizing arbovirus surveillance using risk mapping and coverage modelling Type de document : Article/Communication Auteurs : Joni A. Downs, Auteur ; Mehrdad Vaziri, Auteur ; George Deskins, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 13 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] épizootie [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] maladie infectieuse [Termes descripteurs IGN] modélisation spatiale [Termes descripteurs IGN] optimisation spatiale [Termes descripteurs IGN] surveillance sanitaire [Termes descripteurs IGN] système d'information géographique Résumé : (auteur) Diseases carried by mosquitoes and other arthropods endanger human health globally. Though costly, surveillance efforts are vital for disease control and prevention This paper describes an approach for strategically configuring targeted disease surveillance sites across a study area. The methodology combines risk index mapping and spatial optimization modelling. The risk index is used to identify demand for surveillance, and the maximum covering location problem is used to select a specified number of candidate surveillance sites that covers the maximum amount of risk. The approach is demonstrated using a case study where optimal locations for sentinel surveillance sites are selected for the purposes of detecting eastern equine encephalitis virus in a county in the state of Florida. Optimal sentinel sites were selected under a number of scenarios that modelled different target populations (horses or humans), coverage distances (0.5, 1.0, and 1.5 km), and numbers of sites to select (1–12). Sentinel site selections for the horse and human models displayed different spatial patterns, with horse sites located largely in the west-central region and human ones in the north-central. Minor amounts of spatial overlap between the horse and human sites were observed, especially as coverage distances and numbers of sites were increased. Additionally, a near linear increase in risk coverage was observed as sites were incrementally added to the scenarios. This finding suggests that the number of sentinel sites within the ranges explored should be based on the maximum that can be funded, since they provide similar levels of benefit. Numéro de notice : A2020-117 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475683.2019.1688391 date de publication en ligne : 18/11/2019 En ligne : https://doi.org/10.1080/19475683.2019.1688391 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94736 [article]

Total Vertical Uncertainty (TVU) modeling for topo-bathymetric LIDAR systems / Firat Eren in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 8 (August 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 8 (August 2019) . - pp 585 - 596 Titre : Total Vertical Uncertainty (TVU) modeling for topo-bathymetric LIDAR systems Type de document : Article/Communication Auteurs : Firat Eren, Auteur ; Jaehoon Jung, Auteur ; Christopher E. Parrish, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 585 - 596 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] incertitude géométrique [Termes descripteurs IGN] lidar bathymétrique [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] modèle d'incertitude [Termes descripteurs IGN] modèle numérique bathymétrique [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] propagation d'incertitude [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surface de l'eau Résumé : (Auteur) This paper presents a comprehensive total vertical uncertainty (TVU) model for topo-bathymetric Light Detection and Ranging (LIDAR) systems. The TVU model consists of a combination of analytical uncertainty propagation for the subaerial (above water) portion and Monte Carlo simulation models for the subaqueous portion (water surface to seafloor). The TVU model was tested on a topo-bathymetric LIDAR data set collected by National Oceanic and Atmospheric Administration's National Geodetic Survey (NGS) in Southwest Florida, U.S., in May 2016 using a Riegl VQ-880-G topo-bathymetric LIDARsystem. The TVU values were compared against the empirical standard deviation and were found to capture the variability of uncertainty with depth while providing (slightly) conservative estimates of uncertainty. The results may be used to inform data acquisition protocols and data processing models. The model implementation is now beginning to be used operationally at NGS for topo-bathymetric LIDAR projects. Numéro de notice : A2019-414 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.8.585 date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.14358/PERS.85.8.585 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93541 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019081	SL	Revue	Centre de documentation	Revues en salle	Disponible

Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models / Subit Chakrabarti in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 8 (August 2016) . - pp 4629 - 4641 Titre : Disaggregation of remotely sensed soil moisture in heterogeneous landscapes using holistic structure-based models Type de document : Article/Communication Auteurs : Subit Chakrabarti, Auteur ; Jasmeet Judge, Auteur ; Tara Bongiovanni, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 4629 - 4641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme d'apprentissage [Termes descripteurs IGN] cultures [Termes descripteurs IGN] désagrégation [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] modèle de régression Résumé : (Auteur) In this paper, a novel machine learning algorithm is presented for disaggregation of satellite soil moisture (SM) based on self-regularized regressive models (SRRMs) using high-resolution correlated information from auxiliary sources. It includes regularized clustering that assigns soft memberships to each pixel at a fine scale followed by a kernel regression that computes the value of the desired variable at all pixels. Coarse-scale remotely sensed SM was disaggregated from 10 to 1 km using land cover (LC), precipitation, land surface temperature, leaf area index, and in situ observations of SM. This algorithm was evaluated using multiscale synthetic observations in NC Florida for heterogeneous agricultural LCs. It was found that the rmse for 96% of the pixels was less than 0.02 m 3/m3. The clusters generated represented the data well and reduced the rmse by up to 40% during periods of high heterogeneity in LC and meteorological conditions. The Kullback-Leibler divergence (KLD) between the true SM and the disaggregated estimates is close to zero, for both vegetated and bare-soil LCs. The disaggregated estimates were compared with those generated by the principle of relevant information (PRI) method. The rmse for the PRI disaggregated estimates is higher than the rmse for the SRRM on each day of the season. The KLD of the disaggregated estimates generated by the SRRM is at least four orders of magnitude lower than those for the PRI disaggregated estimates, whereas the computational time needed was reduced by three times. The results indicate that the SRRM can be used for disaggregating SM with complex nonlinear correlations on a grid with high accuracy. Numéro de notice : A2016-888 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2547389 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83068 [article]

Combining hyperspectral and Lidar data for vegetation mapping in the Florida Everglades / Caiyun Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 8 (August 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 8 (August 2014) . - pp. 733 - 743 Titre : Combining hyperspectral and Lidar data for vegetation mapping in the Florida Everglades Type de document : Article/Communication Auteurs : Caiyun Zhang, Auteur Année de publication : 2014 Article en page(s) : pp. 733 - 743 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] cartographie thématique [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] Floride (Etats-Unis) [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] marais [Termes descripteurs IGN] traitement d'image [Termes descripteurs IGN] végétation Résumé : (Auteur)This study explored a combination of hyperspectral and lidar systems for vegetation mapping in the Florida Everglades. A framework was designed to integrate two remotely sensed datasets and four data processing techniques. Lidar elevation and intensity features were extracted from the original point cloud data to avoid the errors and uncertainties in the raster-based lidar methods. Lidar significantly increased the classification accuracy compared with the application of hyperspectral data alone. Three lidar-derived features (elevation, intensity, and topography) had the same contributions in the classification. A synergy of hyperspectral imagery with all lidar-derived features achieved the best result with an overall accuracy of 86 percent and a Kappa value of 0.82 based on an ensemble analysis of three machine learning classifiers. Ensemble analysis did not significantly increase the classification accuracy, but it provided a complementary uncertainty map for the final classified map. The study shows the promise of the synergy of hyperspectral and lidar systems for mapping complex wetlands. Numéro de notice : A2014-344 Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.8.733 En ligne : https://doi.org/10.14358/PERS.80.8.733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73717 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2014081	RAB	Revue	Centre de documentation	En réserve 3L	Disponible

Mapping and assessing of urban impervious areas using multiple endmember spectral mixture analysis: a case study in the city of Tampa, Florida / Fenqing Weng in Geocarto international, vol 28 n° 7-8 (November - December 2013)  

Permalink

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

Permalink

A process oriented areal interpolation technique: a coastal county example / B. Kar in Cartography and Geographic Information Science, vol 39 n° 1 (January 2012)  

Permalink

Influence of street reference data on geocoding quality / P. Zandbergen in Geocarto international, vol 26 n° 1 (February 2011)  

Permalink

Using geographical information system to model the effects of green space accessibility on mortality in Florida / C. Coutts in Geocarto international, vol 25 n° 6 (October 2010)  

Permalink

Evaluation of Terrasar-X observations for wetland INSAR application / S.H. Hong in IEEE Transactions on geoscience and remote sensing, vol 48 n° 2 (February 2010)  

Permalink

Hernando County, Florida, Develops Central GIS in ArcNews [en ligne], Vol 30 n° 2 (Summer 2008)  

Permalink

Keeping an eye on government services / Keith Mann in ArcUser, vol 11 n° 1 (October 2008)

Permalink

Geometric integration of aerial and high-resolution satellite imagery and application in shoreline mapping / R. Li in Marine geodesy, vol 31 n° 3 (September - November 2008)

Permalink

Integration of Ikonos and Quickbird imagery for geopositioning accuracy analysis / R. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 9 (September 2007)

Permalink