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Multi-sensor aboveground biomass estimation in the broadleaved hyrcanian forest of Iran / Ghasem Ronoud in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])
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Titre : Multi-sensor aboveground biomass estimation in the broadleaved hyrcanian forest of Iran Titre original : Estimation multi-capteurs de la biomasse aérienne de la forêt de feuillus hyrcanienne d’Iran Type de document : Article/Communication Auteurs : Ghasem Ronoud, Auteur ; Parviz Fatehi, Auteur ; Ali Asghar Darvishsefat, Auteur Année de publication : 2021 Article en page(s) : pp 818 - 834 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] estimation statistique
[Termes IGN] Fagus orientalis
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Iran
[Termes IGN] régression multiple
[Vedettes matières IGN] Inventaire forestierMots-clés libres : Support Vector Regression Résumé : (auteur) In this study, the capability of Landsat-8 (L8), Sentinel-2 (S2), Sentinel-1 (S1), and their combination was investigated for estimating aboveground biomass (AGB). A pure stand of Fagus Orientalis located in the Hyrcanian forest of Iran was selected as the study area. The performance of a parametric approach, i.e., Multiple Linear Regression (MLR) model and non-parametric approaches, i.e., k-Nearest Neighbor (k-NN), Random Forest (RF), and Support Vector Regression (SVR), were also evaluated for AGB estimations. Our results indicated that among S2 metrics, the FAPAR canopy biophysical index and NDVI index based on the red-edge band (NIR-b8a) have the highest correlation coefficient (r) of 0.420 and 0.417, respectively. The results of AGB estimation showed that a combination of S2 and S1 datasets using the k-NN algorithm had the best accuracy (R2 of 0.57 and rRMSE of 14.68%). The best rRMSE using L8, S2, and S1 datasets was 18.95, 16.99, and 19.17% using k-NN, k-NN, and MLR algorithms, respectively. The combination of L8 with S1 dataset also improved the rRMSE relative to L8 and S1 separately by 0.96 and 1.18%, respectively. We concluded that the combination of optical data (L8 or S2) with SAR data (S1) improves the broadleaved Hyrcanian AGB estimation. Numéro de notice : A2021-956 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article DOI : 10.1080/07038992.2021.1968811 Date de publication en ligne : 07/09/2021 En ligne : https://doi.org/10.1080/07038992.2021.1968811 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99982
in Canadian journal of remote sensing > vol 47 n° 6 [01/11/2021] . - pp 818 - 834[article]Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region / Paulo Victor N. Araújo in Natural Hazards and Earth System Sciences, vol 21 n° 11 (November 2021)
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Titre : Tidal flood area mapping in the face of climate change scenarios: case study in a tropical estuary in the Brazilian semi-arid region Type de document : Article/Communication Auteurs : Paulo Victor N. Araújo, Auteur ; Venerando E. Amaro, Auteur ; Leonlene S. Aguiar, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3353 - 3366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Brésil
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] changement climatique
[Termes IGN] données lidar
[Termes IGN] estuaire
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] image Radarsat
[Termes IGN] marée océanique
[Termes IGN] modèle numérique de surface
[Termes IGN] montée du niveau de la mer
[Termes IGN] risque naturel
[Termes IGN] submersion marine
[Termes IGN] zone inondable
[Termes IGN] zone semi-arideRésumé : (auteur) Previous studies on tidal flood mapping are mostly through continental- and/or global-scale approaches. Moreover, the few works on local-scale perception are concentrated in Europe, Asia, and North America. Here, we present a case study approaching a tidal flood risk mapping application in the face of climate change scenarios in a region with a strong environmental and social appeal. The study site is an estuarine cut in the Brazilian semi-arid region, covering part of two state conservation units, which has been suffering severe consequences from tidal flooding in recent years. In this case study, we used high-geodetic-precision data (lidar DEM), together with robust tidal return period statistics and data from current sea level rise scenarios. We found that approximately 327.60 km2 of the estuary is under tidal flood risk and in need of mitigation measures. This case study can serve as a basis for future management actions, as well as a model for applying risk mapping in other coastal areas. Numéro de notice : A2021-127 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.5194/nhess-21-3353-2021 Date de publication en ligne : 09/11/2021 En ligne : https://doi.org/10.5194/nhess-21-3353-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99321
in Natural Hazards and Earth System Sciences > vol 21 n° 11 (November 2021) . - pp 3353 - 3366[article]Field scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques / Rajkumar Dhakar in Geocarto international, vol 36 n° 18 ([01/10/2021])
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Titre : Field scale wheat LAI retrieval from multispectral Sentinel 2A-MSI and LandSat 8-OLI imagery: effect of atmospheric correction, image resolutions and inversion techniques Type de document : Article/Communication Auteurs : Rajkumar Dhakar, Auteur ; Vinay Kumar Sehgal, Auteur ; Debasish Chakraborty, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2044 - 2064 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] blé (céréale)
[Termes IGN] correction atmosphérique
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] Inde
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] réseau neuronal artificielRésumé : (auteur) This study assessed the effect of atmospheric correction algorithms, inversion techniques and image spatial and spectral resolution on wheat crop LAI retrieval using Sentinel-2 MSI and Landsat-8 OLI imagery. The LAI retrievals were validated with in-situ measurements collected in farmers’ fields. The MSI-based LAI retrievals improved significantly when images were atmospherically corrected using MODTRAN than using the libRadtran code. Among the two PROSAIL inversion approaches, look-up table outperforms artificial neural network for LAI retrievals. Using the best strategy of atmospheric correction and inversion, the effect of spatial resolution from 20 m (MSI) to 30 m (OLI) while using common six bands, showed non-significant improvement in LAI retrievals. The inclusion of additional two red-edge bands as available in MSI significantly reduced the uncertainly in LAI retrievals over that obtained by using six bands, while inclusion of only additional VNIR band did not show any significant effect on LAI retrievals. Numéro de notice : A2021-742 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1687591 Date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1687591 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98666
in Geocarto international > vol 36 n° 18 [01/10/2021] . - pp 2044 - 2064[article]Spectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method / Saket Gowravaram in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)
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Titre : Spectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method Type de document : Article/Communication Auteurs : Saket Gowravaram, Auteur ; Haiyang Chao, Auteur ; Andrew Molthan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 735 - 746 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aéronef
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] étalonnage croisé
[Termes IGN] forêt
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] image multibande
[Termes IGN] image proche infrarouge
[Termes IGN] Kansas (Etats-Unis ; état)
[Termes IGN] orthoimage
[Termes IGN] orthorectification
[Termes IGN] prairie
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance spectraleRésumé : (Auteur) This paper introduces a satellite-based cross-calibration (SCC) method for spectral reflectance estimation of unmanned aircraft system (UAS) multispectral imagery. The SCC method provides a low-cost and feasible solution to convert high-resolution UAS images in digital numbers (DN) to reflectance when satellite data is available. The proposed method is evaluated using a multispectral data set, including orthorectified KHawk UAS DN imagery and Landsat 8 Operational Land Imager Level-2 surface reflectance (SR) data over a forest/grassland area. The estimated UAS reflectance images are compared with the National Ecological Observatory Network's imaging spectrometer (NIS) SR data for validation. The UAS reflectance showed high similarities with the NIS data for the near-infrared and red bands with Pearson's r values being 97 and 95.74, and root-mean-square errors being 0.0239 and 0.0096 over a 32-subplot hayfield. Numéro de notice : A2021-676 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00091R2 En ligne : https://doi.org/10.14358/PERS.20-00091R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98863
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 735 - 746[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2021101 SL Revue Centre de documentation Revues en salle Disponible Development of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)
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Titre : Development of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt Type de document : Article/Communication Auteurs : Soha A. Mohamed, Auteur Année de publication : 2021 Article en page(s) : pp 2739 - 2763 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse multicritère
[Termes IGN] crue
[Termes IGN] densité de population
[Termes IGN] Egypte
[Termes IGN] image Landsat-OLI
[Termes IGN] message d'alerte
[Termes IGN] modèle numérique de surface
[Termes IGN] précipitation
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] surveillance hydrologique
[Termes IGN] système d'information géographiqueRésumé : (auteur) Egypt is one Arab country that is vulnerable to flash floods caused by heavy and intensive rainfall. Different locations in Egypt are vulnerable to the hazards of flash floods, especially in Upper Egypt. Throughout history, Egypt witnessed a series of events of flash floods that lead to mortality, damages, and economic losses. The intensity and frequency of flash floods in Egypt vary from year to year according to a number of hydrological and climatological variables. Although several previous flash floods studies have been conducted in Egypt, studies on the governorate of Asyut are still limited. This study integrates the physical and social parameters in order to assess the vulnerability to flash floods. The objectives of this study are to shed light on flash floods in the study area, develop a vulnerability model to determine the regions vulnerable to the impacts of flash floods, and propose a flash flood alert system in the governorate of Asyut in Egypt to mitigate the impacts of flash floods and to avoid the loss of life and property. The AHP (analytical hierarchy process) is used for assigning the optimal criterion weight of the considered vulnerability parameters based on the responses of eight expert respondents to an online Google forms questionnaire. The highest weighted flash floods causative parameters are population density (27.4%), precipitation (22.1%), total population (16.4%), and elevation (10.2%), respectively. The results reveal that Asyut is one of the Egyptian governorates pro ne to flash floods’ impacts, especially in Dayrut, Al-Qusiyah, and Abnub, urban districts. The findings of this study are expected to be useful to policymakers and responsible authorities for better disaster risk management and for dealing with the flash floods events in the future. Numéro de notice : A2021-598 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-021-04799-2 Date de publication en ligne : 28/05/2021 En ligne : https://doi.org/10.1007/s11069-021-04799-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98229
in Natural Hazards > vol 108 n° 3 (September 2021) . - pp 2739 - 2763[article]The real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)
PermalinkRemote sensing method for extracting topographic information on tidal flats using spatial distribution features / Yang Lijun in Marine geodesy, vol 44 n° 5 (September 2021)
PermalinkSpatiotemporal analysis of urban heat island intensification in the city of Minneapolis-St. Paul and Chicago metropolitan areas using Landsat data from 1984 to 2016 / Mbongowo J. Mbuh in Geocarto international, vol 36 n° 14 ([01/08/2021])
PermalinkDetecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)
PermalinkEvaluation of sum-NDVI values to estimate wheat grain yields using multi-temporal Landsat OLI data / Asadollah Mirasi in Geocarto international, vol 36 n° 12 ([01/07/2021])
PermalinkFluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)
PermalinkMulti-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)
PermalinkMapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine / Tongxi Hu in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)
PermalinkModel-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)
PermalinkRapid ecosystem change at the southern limit of the Canadian Arctic, Torngat Mountains National Park / Emma L. Davis in Remote sensing, vol 13 n° 11 (June-1 2021)
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