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Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
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Titre : Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? Type de document : Article/Communication Auteurs : Fabian E. Fassnacht, Auteur ; Daniel Mangold, Auteur ; Jannika Schäfer, Auteur ; Markus Immitzer, Auteur Année de publication : 2017 Article en page(s) : pp 613 - 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] espèce végétale
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The estimation of various forest inventory attributes from high spatial resolution airborne remote sensing data has been widely examined and proved to be successful at the experimental level. Nevertheless, the operational use of these data in automated procedures to support forest inventories and forest management is still limited to a small number of cases. The reasons for this are high data costs, limited availability of remote sensing data over large areas and resistance from practitioners. In this review the main aim is to stimulate debate about spaceborne very high resolution stereo-imagery (VHRSI) as an alternative to airborne remote sensing data by presenting: (1) a case study on the retrieval of stand density, aboveground biomass and tree species using a set of easy-to-calculate variables obtained from VHRSI data combined with image processing and nonparametric classification and modelling approaches; and (2) the results of an expert opinion survey on the potential of VHRSI as compared with Light Detection and Ranging (LiDAR), hyperspectral and airborne digital imagery to derive a range of forest inventory attributes. In the case study, stand density was estimated with r² = 0.71 and RMSE = 156 trees (rel./norm. RMSE = 24.9 per cent/12.4 per cent), biomass with r² = 0.64 and RMSE of 36.7 t/ha (rel./norm. RMSE = 20.0 per cent/12.8 per cent) while tree species classifications with five species reached overall accuracies of 84.2 per cent (kappa = 0.81). These results were comparable to earlier studies in the same test site, obtained with more expensive airborne acquisitions. Expert opinions were more diverse for VHRSI and aerial photographs (Shannon index values of 0.94 and 0.97) than for LiDAR and hyperspectral data (Shannon index values 0.69 and 0.88). In our opinion, this reflects the current state-of-the-art in the application of VHRSI for automatically retrieving forest inventory attributes. The number of studies using these data is still limited, and the full potential of these datasets is not yet completely explored. Compared with LiDAR and hyperspectral data, which both mostly received high scores for forest inventory products matching the sensor systems’ strengths, VHRSI and aerial photographs received more homogeneous scores indicating their potential as multi-purpose instruments to collect forest inventory information. In summary, considering the simpler acquisition, reasonable price and the comparably easy data format and handling of VHRSI compared with other sensor types, we recommend further research on the application of these data for supporting operational forest inventories. Numéro de notice : A2017-902 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx014 En ligne : https://doi.org/10.1093/forestry/cpx014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93196
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 613 - 631[article]Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery / Jose Alan A. Castillo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
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Titre : Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery Type de document : Article/Communication Auteurs : Jose Alan A. Castillo, Auteur ; Armando A. Apan, Auteur ; Tek N. Maraseni, Auteur ; Severino G. Salmo, Auteur Année de publication : 2017 Article en page(s) : pp 70 - 85 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] carte d'utilisation du sol
[Termes IGN] déboisement
[Termes IGN] estimation statistique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] mangrove
[Termes IGN] modèle de simulation
[Termes IGN] Philippines
[Termes IGN] régression linéaire
[Termes IGN] rétrodiffusion
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82–0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8–28.5 Mg ha−1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery. Numéro de notice : A2017-730 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88428
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 70 - 85[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques / Tarun Kumar in Geocarto international, vol 32 n° 12 (December 2017)
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Titre : Identification of rainwater harvesting sites using SCS-CN methodology, remote sensing and Geographical Information System techniques Type de document : Article/Communication Auteurs : Tarun Kumar, Auteur ; D. C. Jhariya, Auteur Année de publication : 2017 Article en page(s) : pp 1367 - 1388 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aquifère
[Termes IGN] conservation des ressources naturelles
[Termes IGN] eau pluviale
[Termes IGN] eau souterraine
[Termes IGN] identification automatique
[Termes IGN] image satellite
[Termes IGN] Inde
[Termes IGN] ressources en eau
[Termes IGN] ruissellement
[Termes IGN] site
[Termes IGN] système d'information géographiqueRésumé : (Auteur) This study presents a method to identify potential sites for soil and water conservation techniques for the demarcation of suitable sites for artificial recharge of groundwater aquifers, in the study area. The run-off derived by the Soil Conservation Service Curve Number method is a function of run-off potential which can be expressed in terms of run-off coefficient. The augmentation of water resource is proposed by the construction of rainwater harvesting structures like check dam, percolation pond, farm pond and gully check dam. The site suitability for different water harvesting structures is determined by considering spatially varying parameters like slope, infiltration, run-off potential, landuse/land cover, stream order, soil texture, land capability class, hydrological soil group and micro-watershed area. The determined suitable site has been validated with existing recharge structures of the study area. Accuracy assessment of the suitable sites for recharge structures potential maps of the Bindra watershed is 82.60%. Numéro de notice : A2017-674 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1213772 En ligne : https://doi.org/10.1080/10106049.2016.1213772 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87177
in Geocarto international > vol 32 n° 12 (December 2017) . - pp 1367 - 1388[article]InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico / Pascal Castellazzi in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)
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Titre : InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley, Mexico Type de document : Article/Communication Auteurs : Pascal Castellazzi, Auteur ; Jaime Garfias, Auteur ; Richard Martel, Auteur ; Charles Brouard, Auteur ; Alfonso Rivera, Auteur Année de publication : 2017 Article en page(s) : pp 33 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse diachronique
[Termes IGN] aquifère
[Termes IGN] bande C
[Termes IGN] image Envisat-ASAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Mexique
[Termes IGN] subsidence
[Termes IGN] urbanisationRésumé : (auteur) This paper illustrates how InSAR alone can be used to delineate potential ground fractures related to aquifer system compaction. An InSAR-derived ground fracturing map of the Toluca Valley, Mexico, is produced and validated through a field campaign. The results are of great interest to support sustainable urbanization and show that InSAR processing of open-access Synthetic Aperture Radar (SAR) data from the Sentinel-1 satellites can lead to reliable and cost-effective products directly usable by cities to help decision-making.
The Toluca Valley Aquifer (TVA) sustains the water needs of two million inhabitants living within the valley, a growing industry, an intensively irrigated agricultural area, and 38% of the water needs of the megalopolis of Mexico City, located 40 km east of the valley. Ensuring water sustainability, infrastructure integrity, along with supporting the important economic and demographic growth of the region, is a major challenge for water managers and urban developers. This paper presents a long-term analysis of ground fracturing by interpreting 13 years of InSAR-derived ground displacement measurements. Small Baseline Subset (SBAS) and Persistent Scatterer Interferometry (PSI) techniques are applied over three SAR datasets totalling 93 acquisitions from Envisat, Radarsat-2, and Sentinel-1A satellites and covering the period from 2003 to 2016.
From 2003 to 2016, groundwater level declines of up to 1.6 m/yr, land subsidence up to 77 mm/yr, and major infrastructure damages are observed. Groundwater level data show highly variable seasonal responses according to their connectivity to recharge areas. However, the trend of groundwater levels consistently range from −0.5 to −1.5 m/yr regardless of the well location and depth. By analysing the horizontal gradients of vertical land subsidence, we provide a potential ground fracture map to assist in future urban development planning in the Toluca Valley.Numéro de notice : A2017-413 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.06.011 En ligne : https://doi.org/10.1016/j.jag.2017.06.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86300
in International journal of applied Earth observation and geoinformation > vol 63 (December 2017) . - pp 33 - 44[article]Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images / Yang Bo in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)
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Titre : Large-scale block adjustment without use of ground control points based on the compensation of geometric calibration for ZY-3 images Type de document : Article/Communication Auteurs : Yang Bo, Auteur ; Wang Mi, Auteur ; Wen Xu, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1 - 14 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] angle de visée
[Termes IGN] compensation par bloc
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] erreur systématique
[Termes IGN] étalonnage géométrique
[Termes IGN] image ZiYuan-3
[Termes IGN] méthode du gradient conjugué
[Termes IGN] modèle géométrique de prise de vue
[Termes IGN] point d'appui virtuel
[Termes IGN] points homologues
[Termes IGN] précision géométrique (imagerie)Résumé : (Auteur) The potential of large-scale block adjustment (BA) without ground control points (GCPs) has long been a concern among photogrammetric researchers, which is of effective guiding significance for global mapping. However, significant problems with the accuracy and efficiency of this method remain to be solved. In this study, we analyzed the effects of geometric errors on BA, and then developed a step-wise BA method to conduct integrated processing of large-scale ZY-3 satellite images without GCPs. We first pre-processed the BA data, by adopting a geometric calibration (GC) method based on the viewing-angle model to compensate for systematic errors, such that the BA input images were of good initial geometric quality. The second step was integrated BA without GCPs, in which a series of technical methods were used to solve bottleneck problems and ensure accuracy and efficiency. The BA model, based on virtual control points (VCPs), was constructed to address the rank deficiency problem caused by lack of absolute constraints. We then developed a parallel matching strategy to improve the efficiency of tie points (TPs) matching, and adopted a three-array data structure based on sparsity to relieve the storage and calculation burden of the high-order modified equation. Finally, we used the conjugate gradient method to improve the speed of solving the high-order equations. To evaluate the feasibility of the presented large-scale BA method, we conducted three experiments on real data collected by the ZY-3 satellite. The experimental results indicate that the presented method can effectively improve the geometric accuracies of ZY-3 satellite images. This study demonstrates the feasibility of large-scale mapping without GCPs. Numéro de notice : A2017-727 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.10.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.10.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88413
in ISPRS Journal of photogrammetry and remote sensing > vol 134 (December 2017) . - pp 1 - 14[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017121 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017122 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017123 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities / Hèou Maléki Badjana in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)PermalinkOpen land cover from OpenStreetMap and remote sensing / Michael Schultz in International journal of applied Earth observation and geoinformation, vol 63 (December 2017)PermalinkPer-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling : A case study in environmental remote sensing / Jing Gao in ISPRS Journal of photogrammetry and remote sensing, vol 134 (December 2017)PermalinkThorough statistical comparison of machine learning regression models and their ensembles for sub-pixel imperviousness and imperviousness change mapping / Wojciech Drzewiecki in Geodesy and cartography, vol 66 n° 2 (December 2017)PermalinkTracking the relationship between changing skyline and population growth of an Indian megacity using earth observation technology / Joy Sanyal in Geocarto international, vol 32 n° 12 (December 2017)PermalinkUnsupervised-restricted deconvolutional neural network for very high resolution remote-sensing image classification / Yiting Tao in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)PermalinkBayesian data combination for the estimation of ionospheric effects in SAR interferograms / Giorgio Gomba in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)PermalinkExtraction du bâti sur le territoire de la wilaya de Blida (Algérie) / Siham Bougdour in Géomatique expert, n° 119 (novembre - décembre 2017)PermalinkFusing microwave and optical satellite observations to simultaneously retrieve surface soil moisture, vegetation water content, and surface soil roughness / Yohei Sawada in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)PermalinkGIS-based MCDA–AHP modelling for avalanche susceptibility mapping of Nubra valley region, Indian Himalaya / Satish Kumar in Geocarto international, vol 32 n° 11 (November 2017)Permalink