Descripteur
Documents disponibles dans cette catégorie (35)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
VNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada / Kathleen E. Johnson in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 11 (November 2020)
[article]
Titre : VNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada Type de document : Article/Communication Auteurs : Kathleen E. Johnson, Auteur ; Krzysztof Koperski, Auteur Année de publication : 2020 Article en page(s) : pp 695 - 700 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie géologique
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] image proche infrarouge
[Termes IGN] image Worldview
[Termes IGN] minéralogie
[Termes IGN] Nevada (Etats-Unis)
[Termes IGN] réalité de terrain
[Termes IGN] Short Waves InfraRedRésumé : (Auteur) Cuprite, Nevada, is a location well known for numerous studies of its hydrothermal mineralogy. This region has been used to validate geological interpretations of airborne hyperspectral imagery (AVIRIS HSI ), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ) imagery, and most recently eight-band WorldView-3 shortwave infrared (SWIR ) imagery. WorldView-3 is a high-spatial-resolution commercial multispectral satellite sensor with eight visible-to-near-infrared (VNIR ) bands (0.42–1.04 μm) and eight SWIR bands (1.2–2.33 μm). We have applied mineral mapping techniques to all 16 bands to perform a geological analysis of the Cuprite, Nevada, location. Ground truth for the training and validation was derived from AVIRIS hyperspectral data and United States Geological Survey mineral spectral data for this location. We present the results of a supervised mineral-mapping classification applying a random-forest classifier. Our results show that with good ground truth, WorldView-3 SWIR + VNIR imagery produces an accurate geological assessment. Numéro de notice : A2020-709 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.11.695 Date de publication en ligne : 01/11/2020 En ligne : https://doi.org/10.14358/PERS.86.11.695 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96395
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 11 (November 2020) . - pp 695 - 700[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 105-2020111 SL Revue Centre de documentation Revues en salle Disponible Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed / Qinghu Jiang in Remote sensing, vol 12 n° 18 (September-2 2020)
[article]
Titre : Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed Type de document : Article/Communication Auteurs : Qinghu Jiang, Auteur ; Yiyun Chen, Auteur ; Jialiang Hu, Auteur ; Feng Liu, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] bassin hydrographique
[Termes IGN] érosion
[Termes IGN] étalonnage de modèle
[Termes IGN] image proche infrarouge
[Termes IGN] image visible
[Termes IGN] réflectance spectrale
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] sol arable
[Termes IGN] spectroscopie
[Termes IGN] surface cultivée
[Termes IGN] utilisation du solRésumé : (auteur) This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region Numéro de notice : A2020-631 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12183103 Date de publication en ligne : 22/09/2020 En ligne : https://doi.org/10.3390/rs12183103 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96052
in Remote sensing > vol 12 n° 18 (September-2 2020) . - 16 p.[article]Physical, chemical and mechanical wood properties of Pinus nigra growing in Portugal / Alexandra Dias in Annals of Forest Science, vol 77 n° 3 (September 2020)
[article]
Titre : Physical, chemical and mechanical wood properties of Pinus nigra growing in Portugal Type de document : Article/Communication Auteurs : Alexandra Dias, Auteur ; Ana Carvalho, Auteur ; Maria Emilia Silva, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois sur pied
[Termes IGN] dendrométrie
[Termes IGN] densité du bois
[Termes IGN] image proche infrarouge
[Termes IGN] Pinus nigra
[Termes IGN] Portugal
[Termes IGN] qualité du bois
[Termes IGN] reboisement
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Key message: The wood of Pinus nigra populations planted in Portugal, comparatively to Pinus pinaster , has higher total extractive content, lower Klason lignin and H/G ratio, and similar mechanical properties, presenting advantages for industrial purposes.
Context: P. nigra was used in the reforestation of mountainous areas in Portugal, but its wood chemical and mechanical properties were never studied.
Aims: This work intends to evaluate the chemical and mechanical wood properties of the P. nigra populations planted in Portugal, to relate these properties with previously characterised physical features and to compare these data with other European P. nigra stands and species, namely, P. pinaster.
Methods: Wood chemical and mechanical properties were analysed in 90 trees from six Portuguese sites, using near-infrared (NIR) spectrometry and the three-point bending test.
Results: The wood of the P. nigra populations planted in Portugal presented average values of total extractive content = 9.4%, Klason lignin = 26.69%, MORRad = 14.93 MPa and MOERad = 1200.98 MPa. Ring density showed no significant correlation with ring width.
Conclusion: The P. nigra populations planted in Portugal presented qualitative and quantitative properties similar to P. pinaster wood, the main resinous species in Portugal. Facing the lack of raw material for wood industry due to frequent forest fires in the Mediterranean region, P. nigra could be used to reforest mountainous areas of those regions.Numéro de notice : A2020-591 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00984-8 Date de publication en ligne : 22/07/2020 En ligne : https://doi.org/10.1007/s13595-020-00984-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95922
in Annals of Forest Science > vol 77 n° 3 (September 2020) . - 11 p.[article]Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping / Alvin B. Baloloy in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)
[article]
Titre : Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping Type de document : Article/Communication Auteurs : Alvin B. Baloloy, Auteur ; Ariel C. Blanco, Auteur ; Raymund Rhommel StaAna, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 95 - 117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spectrale
[Termes IGN] Asie du sud-est
[Termes IGN] carte de la végétation
[Termes IGN] espèce exotique envahissante
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] orthophotographie
[Termes IGN] Philippines
[Termes IGN] surveillance du littoralRésumé : (auteur) Advancement in Remote Sensing allows rapid mangrove mapping without the need for data-intensive methodologies, complex classifiers, and skill-dependent classification techniques. This study proposes a new index, the Mangrove Vegetation Index (MVI), to rapidly and accurately map mangroves extent from remotely-sensed imageries. The MVI utilizes three Sentinel-2 bands green, Near Infrared (NIR) and Shortwave Infrared (SWIR) in the form |NIR-Green|/|SWIR-Green| to discriminate the distinct greenness and moisture of mangroves from terrestrial vegetation and other land cover. Spectral band analysis shows that the |NIR-Green| part of MVI captures the differences of greenness between mangrove forests and terrestrial vegetation. The |SWIR-Green| part of the index expresses the distinct moisture of mangroves without the need for additional intertidal data and water indices. The MVI value increases with the increasing probability of a pixel being classified as mangroves. Eleven mangrove forests in the Philippines and one mangrove park in Japan were then mapped using MVI. Accuracy assessment was done using field inventory data and high-resolution drone orthophotos. MVI have successfully separated the mangroves from other cover especially terrestrial vegetation, with an overall index accuracy of 92%. The MVI was applied to Landsat 8 images using the equivalent bands to test the universality of the index. Comparable MVI mangrove maps were produced between Sentinel-2 and Landsat images, with an optimal minimum threshold of 4.5 and 4.6, respectively. MVI can effectively highlight the greenness and moisture information in mangroves as reflected by its moderate to high correlation value (r = 0.63 and 0.84, α = 0.05) with the Sentinel-derived chlorophyll-a (Ca) and canopy water (Cw) biophysical products. This study developed and implemented two automated platforms: an offline IDL-based ‘MVI Mapper’ and an online Google Earth Engine-based MVI mapping interface. The MVI implemented in Google Earth Engine was used in generating the latest mangrove extent map of the Philippines. Additionally, the application of MVI were tested to four additional mangrove forests in Southeast Asia: Thailand, Vietnam, Indonesia and Cambodia; and to selected mangroves forests in South America, Africa and Australia. Numéro de notice : A2020-354 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.06.001 Date de publication en ligne : 11/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.06.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95240
in ISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 95 - 117[article]Réservation
Réserver ce documentExemplaires (3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020083 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020082 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Shrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)
[article]
Titre : Shrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification Type de document : Article/Communication Auteurs : Jose Aranha, Auteur ; Teresa Enes, Auteur ; Ana Calvão, Auteur ; Hélder Viana, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbuste
[Termes IGN] biomasse
[Termes IGN] classification dirigée
[Termes IGN] gestion forestière
[Termes IGN] image proche infrarouge
[Termes IGN] image RVB
[Termes IGN] image Sentinel-MSI
[Termes IGN] incendie de forêt
[Termes IGN] modèle de croissance végétale
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Portugal
[Termes IGN] signature spectrale
[Termes IGN] sous-bois
[Termes IGN] système d'information géographique
[Termes IGN] zone sinistréeRésumé : (auteur) Shrubs growing in former burnt areas play two diametrically opposed roles. On the one hand, they protect the soil against erosion, promote rainwater infiltration, carbon sequestration and support animal life. On the other hand, after the shrubs’ density reaches a particular size for the canopy to touch and the shrubs’ biomass accumulates more than 10 Mg ha−1, they create the necessary conditions for severe wild fires to occur and spread. The creation of a methodology suitable to identify former burnt areas and to track shrubs’ regrowth within these areas in a regular and a multi temporal basis would be beneficial. The combined use of geographical information systems (GIS) and remote sensing (RS) supported by dedicated land survey and field work for data collection has been identified as a suitable method to manage these tasks. The free access to Sentinel images constitutes a valuable tool for updating the GIS project and for the monitoring of regular shrubs’ accumulated biomass. Sentinel 2 VIS-NIR images are suitable to classify rural areas (overall accuracy = 79.6% and Cohen’s K = 0.754) and to create normalized difference vegetation index (NDVI) images to be used in association to allometric equations for the shrubs’ biomass estimation (R2 = 0.8984, p-value Numéro de notice : A2020-654 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f11050555 Date de publication en ligne : 14/05/2020 En ligne : https://doi.org/10.3390/f11050555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96116
in Forests > vol 11 n° 5 (May 2020) . - 19 p.[article]A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)PermalinkPlant survival monitoring with UAVs and multispectral data in difficult access afforested areas / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkRed-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)PermalinkPermalinkRegional-scale forest mapping over fragmented landscapes using global forest products and Landsat time series classification / Viktor Myroniuk in Remote sensing, vol 12 n° 1 (January 2020)PermalinkAutomatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)PermalinkUn été brûlant sous l’oeil des satellites / Laurent Polidori in Géomètre, n° 2173 (octobre 2019)PermalinkA machine learning approach to detect crude oil contamination in a real scenario using hyperspectral remote sensing / Ran Pelta in International journal of applied Earth observation and geoinformation, vol 82 (October 2019)PermalinkIndividual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])PermalinkPermalink