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Termes IGN > 1- Descripteurs géographiques > monde (géographie politique) > Amérique (géographie politique) > Etats-Unis > New Hampshire (Etats-Unis)
New Hampshire (Etats-Unis) |
Documents disponibles dans cette catégorie (5)
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Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)
Titre : Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar Type de document : Article/Communication Auteurs : Yang Lei, Auteur ; Paul Siqueira, Auteur ; Nathan Torbick, Auteur ; Mark J. Ducey, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 770 - 787 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bande L
[Termes IGN] biomasse aérienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] image ALOS-PALSAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Maine (Etats-Unis)
[Termes IGN] New Hampshire (Etats-Unis)Résumé : (Auteur) This paper provides an overview of the scattering model, inversion approach, and validation of the application results for creating large-scale moderate-resolution (hectare-level) mosaics of forest height through using spaceborne repeat-pass SAR interferometry and lidar. By incorporating several improvements to the forest height inversion and mosaicking approach, the height estimation accuracy along with the robustness of this approach have been considerably enhanced from its originally reported accuracy of RMSE of 3-4 m at a 20-hectare aggregated pixel size to RMSE of 3-4 m on the order of 3-6 hectares. Furthermore, practical data processing schemes are provided in detail. Extensive validation results are demonstrated which include: 1) a forest height mosaic (total area of 11.6 million hectares) is generated for the U.S. states of Maine and New Hampshire using Japanese Aerospace Exploration Agency's (JAXA) ALOS-1 InSAR correlation data and a small airborne lidar strip (44 000 hectares); 2) the mosaic height estimates are further compared with the available airborne lidar data and field measurements over both flat and mountainous areas; and 3) feasibility of using modern repeat-pass InSAR satellites with short repeat interval is also examined by using JAXA's ALOS-2 data. This simple and efficient approach is a potential observational prototype with much smaller error budget for the future spaceborne repeat-pass L-band InSAR systems with small spatial baseline and moderate/large temporal baseline (such as NISAR) in combination with lidar (such as GEDI) on the application of large-scale forest height/biomass mapping. It also serves as a complementary tool to the spaceborne single-pass InSAR systems using InSAR/PolInSAR methods when full-pol data are not available and/or when the underlying topography slope causes problems for these approaches. Numéro de notice : A2019-109 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2860590 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2860590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92427
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 770 - 787[article]
Titre : Evaluating the uncertainty caused by Post Office Box addresses in environmental health studies: A restricted Monte Carlo approach Type de document : Article/Communication Auteurs : X. Shi, Auteur Année de publication : 2007 Article en page(s) : pp 325 - 340 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse de groupement
[Termes IGN] centroïde
[Termes IGN] géocodage par adresse postale
[Termes IGN] incertitude de position
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] New Hampshire (Etats-Unis)
[Termes IGN] polygone
[Termes IGN] simulationRésumé : (Auteur) A Monte Carlo approach is used to evaluate the uncertainty caused by incorporating Post Office Box (PO Box) addresses in point-cluster detection for an environmental-health study. Placing PO Box addresses at the centroids of postcode polygons in conventional geocoding can introduce significant error into a cluster analysis of the point data generated from them. In the restricted Monte Carlo method I presented in this paper, an address that cannot be matched to a precise location is assigned a random location within the smallest polygon believed to contain that address. These random locations are then combined with the locations of precisely matched addresses, and the resulting dataset is used for performing cluster analysis. After repeating this randomization-and-analysis process many times, one can use the variance in the calculated cluster evaluation statistics to estimate the uncertainty caused by the addresses that cannot be precisely matched. This method maximizes the use of the available spatial information, while also providing a quantitative estimate of the uncertainty in that utilization. The method is applied to lung-cancer data from Grafton County, New Hampshire, USA, in which the PO Box addresses account for more than half of the address dataset. The results show that less than 50% of the detected cluster area can be considered to have high certainty. Copyright Taylor & Francis Numéro de notice : A2007-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810600924211 En ligne : https://doi.org/10.1080/13658810600924211 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28477
in International journal of geographical information science IJGIS > vol 21 n° 3-4 (march - april 2007) . - pp 325 - 340[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-07021 RAB Revue Centre de documentation En réserve L003 Disponible 079-07022 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Land cover classification models using Shuttle Imaging Radar (SIR-C) data: a case study in New Hampshire, USA Type de document : Article/Communication Auteurs : R. Narayanan, Auteur ; Jing Zhang, Auteur Année de publication : 2002 Article en page(s) : pp 57 - 65 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] covariance
[Termes IGN] fréquence
[Termes IGN] image radar
[Termes IGN] image SIR-C
[Termes IGN] New Hampshire (Etats-Unis)
[Termes IGN] occupation du sol
[Termes IGN] polarisation
[Termes IGN] précision de la classification
[Termes IGN] réalité de terrain
[Termes IGN] varianceRésumé : (Auteur) Spaceborne synthetic aperture radar (SAR) systems have the ability to provide high resolution information on land cover characteristics under adverse conditions such as darkness or cloud cover. The use of multiple frequencies and multiple polarizations yields better classification accuracies. The results of various land cover classification algorithms using Shuttle Imaging Radar (SIR-C) SAR data as applied to a site in Suncook, New Hampshire, are described in this paper. Three classification models were developed and tested: minimum distance classification, maximum a posteriori probability classification, and neural network classification. Using the available ground truth information, land cover was classified into five distinct regions: water, swamp, sand, trees, and grass. All three methods were applied to the same site and results compared. The maximum a posteriori probability approach yielded the highest overall classification accuracy on a pixelbypixel basis. Although the minimum distance approach was simpler than the maximum a posteriori approach, its performance was not as good as the latter since it did not use the covariance information between the data channels. The neural network approach performed well and its results were comparable to the maximum a posteriori approach when the variance of the data was small; however, its performance degraded rapidly when the variance of the data was high. Numéro de notice : A2002-286 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542245 En ligne : https://doi.org/10.1080/10106040208542245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22197
in Geocarto international > vol 17 n° 3 (September - November 2002) . - pp 57 - 65[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-02031 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Assessing forest damage in high-elevation coniferous forests in Vermont and New-Hampshire using Thematic Mapper data Type de document : Article/Communication Auteurs : J.E. Vogelmann, Auteur ; B.N. Rock, Auteur Année de publication : 1988 Article en page(s) : pp 227 - 246 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] forêt
[Termes IGN] image Landsat-TM
[Termes IGN] masque
[Termes IGN] New Hampshire (Etats-Unis)
[Termes IGN] Pinophyta
[Termes IGN] Vermont (Etats-Unis)Numéro de notice : A1988-118 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/0034-4257(88)90027-2 En ligne : https://doi.org/10.1016/0034-4257(88)90027-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24697
in Remote sensing of environment > vol 24 n° 2 (March 1988) . - pp 227 - 246[article]Racing into tomorrow, 1985 ACSM ASPRS Fall convention / American society for photogrammetry and remote sensing (1985)
Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 56337-01 CG.85 Livre Centre de documentation En réserve M-103 Disponible
