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Quantifying spatiotemporal post‐disturbance recovery using field inventory, tree growth, and remote sensing / Shengli Huang in Earth and space science, vol 6 n° 3 (March 2019)
[article]
Titre : Quantifying spatiotemporal post‐disturbance recovery using field inventory, tree growth, and remote sensing Type de document : Article/Communication Auteurs : Shengli Huang, Auteur ; C. Ramirez, Auteur ; M. McElhaney, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 489 - 504 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] croissance végétale
[Termes IGN] Etats-Unis
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Forest recovery following a disturbance lasts decades to centuries, and the rate depends on pre‐ and post‐disturbance condition and local environmental factors. Existing approaches of field observations, remote sensing, statistical chronosequence, and ecological modeling have one or more drawbacks, including short time frames, generalized details, indirect indicators, hard parameterization, and defective assumptions. Using aboveground live biomass (AGLB) as an example, we developed an approach called “Disturbance and Recovery Assessment across Space and Time (DRAST).” For a specific post‐disturbance year, DRAST utilizes Field Inventory and Analysis data sets and the Forest Vegetation Simulator, as well as pre‐ and post‐disturbance remote sensing to create two rasters: (1) what the AGLB would look like over the disturbed area had the disturbance not occurred and (2) what the AGLB would look like over the disturbed area in the actual presence of the disturbance. These two rasters are compared annually to examine the spatiotemporal recovery pattern. We demonstrated DRAST with the 2013 Rim fire in California, United States, by creating two sets of AGLB for 100 years. Our results showed that (1) the AGLB consumed by Rim fire was 3.52 Tg and (2) 45.9% of the burned area needs 95 years), 5.9% (10–15 years), 5.4% (15–20 years), 4.8% (20–25 years), and 4.3% (25–30 years). In conclusion, DRAST can provide spatially explicit and highly detailed ecological indicators for decades under the two scenarios of “no disturbance” and “actual disturbance occurrence” for recovery analysis. Numéro de notice : A2019-402 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1029/2018EA000489 Date de publication en ligne : 25/03/2019 En ligne : https://doi.org/10.1029/2018EA000489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93504
in Earth and space science > vol 6 n° 3 (March 2019) . - pp 489 - 504[article]Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis / Matheus Pinheiro Ferreira in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)
[article]
Titre : Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis Type de document : Article/Communication Auteurs : Matheus Pinheiro Ferreira, Auteur ; Fabien Hubert Wagner, Auteur ; Luiz E.O.C. Aragão, Auteur Année de publication : 2019 Article en page(s) : pp 119 - 131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse texturale
[Termes IGN] arbre (flore)
[Termes IGN] Brésil
[Termes IGN] canopée
[Termes IGN] classification dirigée
[Termes IGN] espèce végétale
[Termes IGN] forêt tropicale
[Termes IGN] houppier
[Termes IGN] image à très haute résolution
[Termes IGN] image infrarouge
[Termes IGN] image Worldview
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] matrice de co-occurrence
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] variation saisonnièreRésumé : (Auteur) Tropical forest conservation and management can significantly benefit from information about the spatial distribution of tree species. Very-high resolution (VHR) spaceborne platforms have been hailed as a promising technology for mapping tree species over broad spatial extents. WorldView-3, the most advanced VHR sensor, provides spectral data in 16 bands covering the visible to near-infrared (VNIR, 400–1040 nm) and shortwave-infrared (SWIR, 1210–2365 nm) wavelength ranges. It also collects images at unprecedented levels of details using a panchromatic band with 0.3-m of spatial resolution. However, the potential of WorldView-3 at its full spectral and spatial resolution for tropical tree species classification remains unknown. In this study, we performed a comprehensive assessment of WorldView-3 images acquired in the dry and wet seasons for tree species discrimination in tropical semi-deciduous forests. Classification experiments were performed using VNIR individually and combined with SWIR channels. To take advantage of the sub-metric resolution of the panchromatic band for classification, we applied an individual tree crown (ITC)-based approach that employed pan-sharpened VNIR bands and gray level co-occurrence matrix texture features. We determined whether the combination of images from the two annual seasons improves the classification accuracy. Finally, we investigated which plant traits influenced species detection. The new SWIR sensing capabilities of WorldView-3 increased the average producer’s accuracy up to 7.8%, by enabling the detection of non-photosynthetic vegetation within ITCs. The combination of VNIR bands from the two annual seasons did not improve the classification results when compared to the results obtained using images from each season individually. The use of VNIR bands at their original 1.2-m spatial resolution yielded average producer’s accuracies of 43.1 ± 3.1% and 38.8 ± 3% in the wet and dry seasons, respectively. The ITC-based approach improved the accuracy to 70 ± 8% in the wet and 68.4 ± 7.4% in the dry season. Texture analysis of the panchromatic band enabled the detection of species-specific differences in crown structure, which improved species detection. The use of texture analysis, pan-sharpening, and ITC delineation is a potential approach to perform tree species classification in tropical forests with WorldView-3 satellite images. Numéro de notice : A2019-117 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.019 Date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.019 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92444
in ISPRS Journal of photogrammetry and remote sensing > vol 149 (March 2019) . - pp 119 - 131[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019033 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019032 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern / Haley L. Wiggins in Forest ecology and management, vol 434 (28 February 2019)
[article]
Titre : Using LiDAR to develop high-resolution reference models of forest structure and spatial pattern Type de document : Article/Communication Auteurs : Haley L. Wiggins, Auteur ; Cara R. Nelson, Auteur ; Andrew J. Larson, Auteur ; Hugh D. Safford, Auteur Année de publication : 2019 Article en page(s) : pp 318 - 330 Note générale : bibliography Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse de groupement
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] caractérisation
[Termes IGN] coupe (sylviculture)
[Termes IGN] détection d'arbres
[Termes IGN] diamètre des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] Mexique
[Termes IGN] parc naturel national
[Termes IGN] restauration écologique
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] topographie localeRésumé : (auteur) Successful restoration of degraded forest landscapes requires reference models that adequately capture structural heterogeneity at multiple spatial scales and for specific landforms. Despite this need, managers often lack access to reliable reference information, in large part because field-based methods for assessing variation in forest structure are costly and inherently suffer from limited replication and spatial coverage and, therefore, yield limited insights about the ecological structure of reference forests at landscape scales. LiDAR is a cost-effective alternative that can provide high-resolution characterizations of variation in forest structure among landform types. However, managers and researchers have been reluctant to use LiDAR for characterizing structure because of low confidence in its capacity to approximate actual tree distributions. By calculating bias in LiDAR estimates for a range of tree-height cutoffs, we improved LiDAR’s ability to capture structural variability in terms of individual trees. We assessed bias in the processed LiDAR data by comparing datasets of field-measured and LiDAR-detected trees of various height classes in terms of overall number of trees and estimates of structure and spatial pattern in an important contemporary reference forest, the Sierra de San Pedro Martir National Park, Baja California, Mexico. Agreement between LiDAR- and field-based estimates of tree density, as well as estimates of forest structure and spatial pattern, was maximized by removing trees less than 12 m tall. We applied this height cutoff to LiDAR-detected trees of our study landscape, and asked if forest structure and spatial pattern varied across topographic settings. We found that canyons, shallow northerly, and shallow southerly slopes were structurally similar; each had a greater number of all trees, large trees, and large tree clumps than steep southerly slopes and ridges. Steep northerly slopes supported unique structures, with taller trees than ridges and shorter trees than canyons and shallow southerly slopes. Our results show that characterizations of forest structure based on LiDAR-detected trees are reasonably accurate when the focus is narrowed to the overstory. In addition, our finding of strong variation of forest structure and spatial pattern across topographic settings demonstrates the importance of developing reference models at the landscape scale, and highlights the need for replicated sampling among stands and landforms. Methods developed here should be useful to managers interested in using LiDAR to characterize distributions of medium and large overstory trees, particularly for the development of landscape-scale reference models. Numéro de notice : A2019-013 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.12.012 Date de publication en ligne : 24/12/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.12.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91616
in Forest ecology and management > vol 434 (28 February 2019) . - pp 318 - 330[article]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)
[article]
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]Quantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) / William J. Schmelz in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 2 (February 2019)
[article]
Titre : Quantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) Type de document : Article/Communication Auteurs : William J. Schmelz, Auteur ; Norbert P. Psuty, Auteur Année de publication : 2019 Article en page(s) : pp 133 - 144 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données topographiques
[Termes IGN] dune
[Termes IGN] erreur géométrique
[Termes IGN] géomorphologie locale
[Termes IGN] New York (Etats-Unis ; état)
[Termes IGN] plage
[Termes IGN] précision du positionnement
[Termes IGN] résiduRésumé : (Auteur) To establish a basis for the utilization of lidar topography as a data source for coastal geomorphological analyses, this study generated statistical metrics of lidar error through the comparison of a June 2014 USGS collection of airborne lidar with a concurrently collected high-accuracy GPS topographical survey collected within the beach and dunes of a portion of Fire Island National Seashore. The examination of bare earth lidar error within the experiment site revealed a complex association between accuracy and environment within the coastal landscape. Accuracy was constrained to better than 50 cm RMSE in areas with vegetated dune topography and, overall, a 38.9 cm RMSE was measured. Higher accuracies were achieved in the flat, non-vegetated beach. A three-dimensional minimization of residuals between the lidar and GPS surveys reduced the total RMSE to 25.2 cm, indicating a correctable systematic offset between the surface generated from the lidar and the true ground surface. Numéro de notice : A2019-060 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.2.133 Date de publication en ligne : 01/02/2019 En ligne : https://doi.org/10.14358/PERS.85.2.133 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92110
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 2 (February 2019) . - pp 133 - 144[article]Réservation
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