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Towards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping / Sandro Martinis in Remote sensing of environment, vol 278 (September 2022)  

Public [article]  inRemote sensing of environment > vol 278 (September 2022) . - n° 113077 Titre : Towards a global seasonal and permanent reference water product from Sentinel-1/2 data for improved flood mapping Type de document : Article/Communication Auteurs : Sandro Martinis, Auteur ; Sandro Groth, Auteur ; Marc Wieland, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113077 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] Allemagne [Termes IGN] Australie [Termes IGN] carte thématique [Termes IGN] fusion d'images [Termes IGN] image radar moirée [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] Inde [Termes IGN] inondation [Termes IGN] Mozambique [Termes IGN] prévention des risques [Termes IGN] série temporelle [Termes IGN] Soudan [Termes IGN] surveillance hydrologique [Termes IGN] variation saisonnière [Termes IGN] zone à risque Résumé : (auteur) Satellite-based flood mapping has become an important part of disaster response. In order to accurately distinguish flood inundation from normally present conditions, up-to-date, high-resolution information on the seasonal water cover is crucial. This information is usually neglected in disaster management, which may result in a non-reliable representation of the flood extent, mainly in regions with highly dynamic hydrological conditions. In this study, we present a fully automated method to generate a global reference water product specifically designed for the use in global flood mapping applications based on high resolution Earth Observation data. The proposed methodology combines existing processing pipelines for flood detection based on Sentinel-1/2 data and aggregates permanent as well as seasonal water masks over an adjustable reference time period. The water masks are primarily based on the analysis of Sentinel-2 data and are complemented by Sentinel-1-based information in optical data scarce regions. First results are demonstrated in five selected study areas (Australia, Germany, India, Mozambique, and Sudan), distributed across different climate zones and are systematically compared with external products. Further, the proposed product is exemplary applied to three real flood events in order to evaluate the impact of the used reference water mask on the derived flood extent. Results show, that it is possible to generate a consistent reference water product at 10–20 m spatial resolution, that is more suitable for the use in rapid disaster response than previous masks. The proposed multi-sensor approach is capable of producing reasonable results, even if only few or no information from optical data is available. Further it becomes clear, that the consideration of seasonality of water bodies, especially in regions with highly dynamic hydrological and climatic conditions, reduces potential over-estimation of the inundation extent and gives a more reliable picture on flood-affected areas. Numéro de notice : A2022-467 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113077 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113077 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100801 [article]

Climatic sensitivities derived from tree rings improve predictions of the forest vegetation simulator growth and yield model / Courtney L. Giebink in Forest ecology and management, vol 517 (1 August 2022)  

Public [article]  inForest ecology and management > vol 517 (1 August 2022) . - n° 120256 Titre : Climatic sensitivities derived from tree rings improve predictions of the forest vegetation simulator growth and yield model Type de document : Article/Communication Auteurs : Courtney L. Giebink, Auteur ; R. Justin DeRose, Auteur ; Mark Castle, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120256 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] gestion forestière [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] Picea (genre) [Termes IGN] Pinus ponderosa [Termes IGN] Pseudotsuga menziesii [Termes IGN] puits de carbone [Termes IGN] rendement [Termes IGN] Utah (Etas-Unis) [Termes IGN] variation saisonnière [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forest management has the potential to contribute to the removal of greenhouse gasses from the atmosphere via carbon sequestration and storage. To identify management actions that will maximize carbon removal and storage over the long term, models are needed that accurately and realistically represent forest responses to changing climate. The most widely used growth and yield model in the United States (U.S.), the Forest Vegetation Simulator (FVS), which also forms the basis for several forest carbon calculators, does not currently include the direct effect of climate variation on tree growth. We incorporated the effects of climate on tree diameter growth by combining tree-ring data with forest inventory data to parameterize a suite of alternative models characterizing the growth of three dominant tree species in the arid and moisture-limited state of Utah. These species, Pinus ponderosa Dougl. ex Laws, Pseudotsuga menziesii var. glauca Mayr (Franco), and Picea engelmannii Parry ex Engelm., encompass the full elevational range of montane forest types. The alternative models we considered differed progressively from the current FVS large-tree diameter growth model, first by changing to an annual time step, then by adding interannual climate effects, followed by model simplification (removal of predictors), and finally, complexification, including effects of spatial variation in climate and two-way interactions between predictors. We validated diameter growth predictions from these models with independent observations, and evaluated model performance in terms of accuracy, precision, and bias. We then compared predictions of future growth made by the existing large-tree diameter growth model used in FVS, i.e., without climate effects, to those of our updated models, including those with climate effects. We found that simpler models of tree growth outperform the current FVS model, and that the incorporation of climate effects improves model performance for two out of three species, in which growth is currently overpredicted by FVS. Diameter growth projected with improved, climate-sensitive models is less than the future tree growth projected by the current climate-insensitive FVS model. Tree rings can be used to identify and incorporate drivers of growth variation into a stand-level growth and yield model, giving more accurate predictions of the carbon uptake potential of forests under climate change. Numéro de notice : A2022-390 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120256 Date de publication en ligne : 12/05/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120256 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100681 [article]

Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea / Mehmet Emin Ayhan in Marine geodesy, vol 45 n° 4 (July 2022)  

Public [article]  inMarine geodesy > vol 45 n° 4 (July 2022) . - pp 329 - 359 Titre : Effects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea Type de document : Article/Communication Auteurs : Mehmet Emin Ayhan, Auteur Année de publication : 2022 Article en page(s) : pp 329 - 359 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Nivellement [Termes IGN] autocorrélation [Termes IGN] correction [Termes IGN] marégraphe [Termes IGN] Méditerranée, mer [Termes IGN] modèle statistique [Termes IGN] niveau de la mer [Termes IGN] niveau moyen des mers [Termes IGN] Turquie [Termes IGN] valeur aberrante [Termes IGN] variation saisonnière Résumé : (auteur) Antalya 2 tide gauge (TG) station is located on the coast of Turkey within the Eastern Mediterranean Sea. Relative sea level trends 6.0 ± 1.5 and 6.44 ± 0.45 mm/year over 1985–2009 at Antalya 2 TG are different from the trend (1.6 ± 1.5 mm/year over 1935–1977) at Antalya TG within 10 km. In order to investigate this trend discrepancy, the monthly mean series at Antalya 2 TG is re-analyzed for offsets, outliers and trend estimation. The Zivot-Andrews method and the Qp outlier test result in one offset at 1994.0417 year with magnitude of 71.24 ± 13.48 mm and nine outliers. The series, corrected for the offset and outliers, de-seasonalized and filled for missed points, is identified as trend-stationary process and analyzed for trend estimation by various models. The optimal model providing the lowest Akaike Information Criteria is polynomial linear trend with multiplicative seasonal Autoregressive Moving Average (ARMA(2,0)x(1,0)12). The estimated relative sea level trend by the optimal model is 1.77 ± 0.65 mm/year. The large trend discrepancy at Antalya 2 TG is accounted for by one offset primarily (∼71%) and nine outliers (∼3%). Numéro de notice : A2022-516 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1080/01490419.2022.2047843 Date de publication en ligne : 11/03/2022 En ligne : https://doi.org/10.1080/01490419.2022.2047843 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101064 [article]

Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information / Murali Krishna Gumma in Geocarto international, vol 37 n° 7 ([15/06/2022])  

Public [article]  inGeocarto international > vol 37 n° 7 [15/06/2022] . - pp 1833 - 1849 Titre : Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information Type de document : Article/Communication Auteurs : Murali Krishna Gumma, Auteur ; Kimeera Tummala, Auteur ; Sreenath Dixit, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1833 - 1849 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] appariement spectral [Termes IGN] blé (céréale) [Termes IGN] carte de la végétation [Termes IGN] distribution spatiale [Termes IGN] image Sentinel-MSI [Termes IGN] Inde [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] série temporelle [Termes IGN] surface cultivée [Termes IGN] variation saisonnière Résumé : (auteur) Accurate monitoring of croplands helps in making decisions (for insurance claims, crop management and contingency plans) at the macro-level, especially in drylands where variability in cropping is very high owing to erratic weather conditions. Dryland cereals and grain legumes are key to ensuring the food and nutritional security of a large number of vulnerable populations living in the drylands. Reliable information on area cultivated to such crops forms part of the national accounting of food production and supply in many Asian countries, many of which are employing remote sensing tools to improve the accuracy of assessments of cultivated areas. This paper assesses the capabilities and limitations of mapping cultivated areas in the Rabi (winter) season and corresponding cropping patterns in three districts characterized by small-plot agriculture. The study used Sentinel-2 Normalized Difference Vegetation Index (NDVI) 15-day time-series at 10 m resolution by employing a Spectral Matching Technique (SMT) approach. The use of SMT is based on the well-studied relationship between temporal NDVI signatures and crop phenology. The rabi season in India, dominated by non-rainy days, is best suited for the application of this method, as persistent cloud cover will hamper the availability of images necessary to generate clearly differentiating temporal signatures. Our study showed that the temporal signatures of wheat, chickpea and mustard are easily distinguishable, enabling an overall accuracy of 84%, with wheat and mustard achieving 86% and 94% accuracies, respectively. The most significant misclassifications were in irrigated areas for mustard and wheat, in small-plot mustard fields covered by trees and in fragmented chickpea areas. A comparison of district-wise national crop statistics and those obtained from this study revealed a correlation of 96%. Numéro de notice : A2022-497 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1805029 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1080/10106049.2020.1805029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100989 [article]

Vegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas / Benedikt Hiebl in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2022 (2022 edition) . - pp 367 - 374 Titre : Vegetation cover mapping from RGB webcam time series for land surface emissivity retrieval in high mountain areas Type de document : Article/Communication Auteurs : Benedikt Hiebl, Auteur ; Andreas Mayr, Auteur ; Andreas Kollert, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 367 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte de la végétation [Termes IGN] données de terrain [Termes IGN] emissivité [Termes IGN] flore alpine [Termes IGN] image RVB [Termes IGN] image thermique [Termes IGN] modèle numérique de surface [Termes IGN] montagne [Termes IGN] série temporelle [Termes IGN] température au sol [Termes IGN] variation saisonnière Résumé : (auteur) Land Surface Temperature (LST) products from thermal infrared imaging rely on information about the spatial distribution of Land Surface Emissivity (LSE). For portable, broadband thermal cameras for drone- or ground-based measurements with camera to object distances up to a few kilometres and with meter-scale resolution, threshold-based retrieval of LSE from Fractional green Vegetation Cover (FVC) can be used. As seasonal changes in vegetation LSE over the year cannot be accounted for by single satellite images or aerial orthophotos, this study evaluates an approach for FVC retrieval via permanently installed RGB webcams and derived Excess Green vegetation index (ExG) time series at a high-mountain test site in the European Alps. Daily ExG values were derived from the imagery of 27 days between 12/07/2021 and 30/10/2021 and projected to a 0.5 m Digital Surface Model (DSM). FVC reference data from 765 in-situ vegetation plots were used to assess the relationship between ExG and the vegetation cover and to determine the thresholds of ExG for no vegetation cover and full vegetation cover. Despite the bad correlation between ExG and in-field FVC with an R² score of 0.15, an approach using a well-tested orthophoto-retrieved NDVI for FVC retrieval performs just slightly better. The comparison of the remotely sensed data and the field measurements therefore remains complex. Time series analysis of both ExG and FVC for highly vegetated areas showed a significant decrease from summer to autumn, which reflects the seasonal changes of LSE for senescent vegetation. Calculated emissivities for vegetated pixels ranged from the minimum of 0.95 to the maximum of 0.985 over the season, while emissivity values for less vegetated pixels stayed constant during the season. The results of this study will be used as input to a correction model for remote LST measurements in the context of micro-scale investigations of the thermal niche of Alpine flora. Numéro de notice : A2022-428 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-2-2022-367-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2022-367-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100735 [article]

Plastic waste cleanup priorities to reduce marine pollution: A spatiotemporal analysis for Accra and Lagos with satellite data / Susmita Dasgupta in Science of the total environment, vol 839 (May 2022)  

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A novel regression method for harmonic analysis of time series / Qiang Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 185 (March 2022)  

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Mapping burn severity in the western Italian Alps through phenologically coherent reflectance composites derived from Sentinel-2 imagery / Donato Morresi in Remote sensing of environment, vol 269 (February 2022)  

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Seasonal variations of vertical crustal motion in Australia observed by joint analysis of GPS and GRACE / Hao Wang in Geomatics and Information Science of Wuhan University, vol 47 n° 2 (February 2022)  

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Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies / Guangqin Song in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

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Simulation of the meltwater under different climate change scenarios in a poorly gauged snow and glacier-fed Chitral River catchment (Hindukush region) / Huma Hayat in Geocarto international, vol 37 n° 1 ([01/01/2022])  

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How geographic and climatic factors affect the adaptation of Douglas-fir provenances to the temperate continental climate zone in Europe / Marzena Niemczyk in European Journal of Forest Research, vol 140 n° 6 (December 2021)  

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Modelling the impact of climate change on the occurrence of frost damage in Sitka spruce (Picea sitchensis) in Great Britain / A.A. Atucha-Zamkova in Forestry, an international journal of forest research, vol 94 n° 5 (December 2021)  

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Snow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm / Mritunjay Kumar Singh in Geocarto international, vol 36 n° 20 ([01/12/2021])  

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GIS-based study on the environmental sensitivity to pollution and susceptibility to eutrophication in Burullus Lake, Egypt / Muhammad A. El-Alfy in Marine geodesy, vol 44 n° 6 (November 2021)  

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