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Forest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest / Pavel Daněk in Forest ecology and management, vol 504 (15 January 2022)  

Public [article]  inForest ecology and management > vol 504 (15 January 2022) . - n° 119802 Titre : Forest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest Type de document : Article/Communication Auteurs : Pavel Daněk, Auteur ; Pavel Šamonil, Auteur ; Libor Hort, Auteur Année de publication : 2021 Article en page(s) : n° 119802 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois mort [Termes IGN] canopée [Termes IGN] Fagus sylvatica [Termes IGN] humidité du sol [Termes IGN] litière [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] régénération (sylviculture) [Termes IGN] République Tchèque [Termes IGN] semis (sylviculture) [Termes IGN] sol forestier [Vedettes matières IGN] Foresterie Résumé : (auteur) Natural regeneration of European beech (Fagus sylvatica) and Norway spruce (Picea abies) plays a crucial role in the future of many European mountain forests. It is affected by various soil and stand-related factors whose relative importance, especially in mixed stands, is still not known. In this study, we assessed the importance of stand composition, soil wetness, disturbances and different microsites and seedbeds for regeneration of beech and spruce in a mixed old-growth mountain forest. We also focused on how the effects of these factors change as regeneration gets older. We sampled all regeneration in 563 plots from different microsite types (deadwood, intact soil, treethrow pits and mounds), distinguishing three seedbeds (mosses, beech litter, bare substrate) for seedlings. We used soil survey and tree census data with generalized linear mixed models and variance partitioning to identify the main factors driving tree regeneration and their relative importance. Although beech was slightly less abundant in the canopy than spruce, it strongly outnumbered spruce in regeneration. Beech regeneration showed an affinity for beech litter-rich microsites and drier soils, while spruce was more common on deadwood and moister soils and its response to the seedbed was microsite-specific. The regeneration of both species was positively related to the proportion of their own species in the canopy, but more so in seedlings than in older regeneration cohorts, where soil wetness was more important. The overall pattern of tree regeneration thus resulted from a complex interplay between site conditions and their alterations by current and former generations of canopy trees through the creation of new microsites (deadwood, uprooting mounds) or litter production. Where beech regeneration is not suppressed by excess soil wetness, it is much more successful than spruce due to its shade tolerance and ability to be established in the beech litter that dominates the forest floor. On the other hand, spruce regeneration is mostly restricted to elevated microsites with lower litter accumulation, such as deadwood and treethrow mounds. Our results indicate that both species exhibit an ability to modify their environment in favor of their own regeneration, but under current conditions, beech is more successful than spruce and can be expected to increase its dominance in the future. Numéro de notice : A2022-022 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119802 Date de publication en ligne : 04/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99214 [article]

Improving soil moisture retrieval from GNSS-interferometric reflectometry: parameters optimization and data fusion via neural network / Yajie Shi in International Journal of Remote Sensing IJRS, vol 42 n° 23 (1-10 December 2021)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 42 n° 23 (1-10 December 2021) Titre : Improving soil moisture retrieval from GNSS-interferometric reflectometry: parameters optimization and data fusion via neural network Type de document : Article/Communication Auteurs : Yajie Shi, Auteur ; Chao Ren, Auteur ; Zhiheng Yan, Auteur ; Jianmin Lai, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] fusion de données [Termes IGN] humidité du sol [Termes IGN] optimisation (mathématiques) [Termes IGN] réflectométrie par GNSS [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Soil moisture is a vital surface physical quantity in studying the earth’s ecology. It plays a crucial role in the hydrological cycle, crop yield estimation, and ecological monitoring. Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technology inversion to obtain high accuracy soil moisture is a hot topic of current research. However, due to the limited available sites, it’s difficult to obtain an extensive and continuous range of soil moisture based on this technique. It is necessary to build algorithms for encryption based on known sites’ data, combined with the corresponding geographic environmental elements. This paper extracted the surface environmental factors affecting soil moisture using high-precision optical remote sensing images. The contribution of each surface environmental element to the soil moisture inversion was analysed using back propagation (BP) neural network optimized by the genetic algorithm (GA). Based on this, ten surface environmental elements (latitude and longitude information, precipitation, temperature, land cover type, normalized difference vegetation index (NDVI), elevation, slope, slope direction, and shading) were identified as critical factors, and a multi-data fusion soil moisture inversion model was constructed. The results showed that the constructed model could better describe the relationship between soil moisture and these elements, and the Pearson correlation coefficient R reached 0.8724, and the RMSE was 0.0346 cm3 cm−3. GNSS-IR technology provides an effective technical means for inversing soil moisture over a large area with high spatial and temporal resolution. Numéro de notice : A2021-786 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2021.1988186 Date de publication en ligne : 24/10/2021 En ligne : https://doi.org/10.1080/01431161.2021.1988186 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98972 [article]

Python software to transform GPS SNR wave phases to volumetric water content / Angel Martín in GPS solutions, vol 26 n° 1 (January 2022)  

Public [article]  inGPS solutions > vol 26 n° 1 (January 2022) . - n° 7 Titre : Python software to transform GPS SNR wave phases to volumetric water content Type de document : Article/Communication Auteurs : Angel Martín, Auteur ; Ana Belén Anquela, Auteur ; Sara Ibáñez, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] humidité du sol [Termes IGN] phase [Termes IGN] Python (langage de programmation) [Termes IGN] rapport signal sur bruit [Termes IGN] réflectométrie par GNSS [Termes IGN] signal GPS [Termes IGN] teneur en vapeur d'eau Résumé : (auteur) The global navigation satellite system interferometric reflectometry is often used to extract information about the environment surrounding the antenna. One of the most important applications is soil moisture monitoring. This manuscript presents the main ideas and implementation decisions needed to write the Python code to transform the derived phase of the interferometric GPS waves, obtained from signal-to-noise ratio data continuously observed during a period of several weeks (or months), to volumetric water content. The main goal of the manuscript is to share the software with the scientific community to help users in the GPS-IR computation. Numéro de notice : A2022-004 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-021-01190-3 Date de publication en ligne : 27/10/2021 En ligne : https://doi.org/10.1007/s10291-021-01190-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98919 [article]

Estimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 9 (September 2021) . - pp 649-660 Titre : Estimating regional soil moisture with synergistic use of AMSR2 and MODIS images Type de document : Article/Communication Auteurs : Majid Rahimzadegan, Auteur ; Arash Davari, Auteur ; Ali Sayadi, Auteur Année de publication : 2021 Article en page(s) : pp 649-660 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Advanced Microwave Scanning Radiometer [Termes IGN] coefficient de corrélation [Termes IGN] humidité du sol [Termes IGN] image Aqua-AMSR [Termes IGN] image Terra-MODIS [Termes IGN] indice d'humidité [Termes IGN] Iran [Termes IGN] polarisation [Termes IGN] réflectance du sol Résumé : (Auteur) Soil moisture content (SMC), product of Advanced Microwave Scanning Radiometer 2 (AMSR2), is not at an adequate level of accuracy on a regional scale. The aim of this study is to introduce a simple method to estimate SMC while synergistically using AMSR2 and Moderate Resolution Imaging Spectroradiometer (MODIS) measurements with a higher accuracy on a regional scale. Two MODIS products, including daily reflectance (MYD021) and nighttime land surface temperature (LST) products were used. In 2015, 1442 in situ SMC measurements from six stations in Iran were used as ground-truth data. Twenty models were evaluated using combinations of polarization index (PI), index of soil wetness (ISW), normalized difference vegetation index (NDVI), and LST. The model revealed the best results using a quadratic combination of PI and ISW, a linear form of LST, and a constant value. The overall correlation coefficient, root-mean-square error, and mean absolute error were 0.59, 4.62%, and 3.01%, respectively. Numéro de notice : A2021-673 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00085 Date de publication en ligne : 01/09/2021 En ligne : https://doi.org/10.14358/PERS.20-00085 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98835 [article]

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Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7308 - 7321 Titre : Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops Type de document : Article/Communication Auteurs : Davide Palmisano, Auteur ; Francesco Mattia, Auteur ; Anna Balenzano, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7308 - 7321 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse de sensibilité [Termes IGN] angle d'incidence [Termes IGN] bande C [Termes IGN] carte agricole [Termes IGN] Castille-et-Leon (Espagne) [Termes IGN] corrélation temporelle [Termes IGN] cultures [Termes IGN] humidité du sol [Termes IGN] image Sentinel-SAR [Termes IGN] Pouilles (Italie) [Termes IGN] réseau hydrographique [Termes IGN] rétrodiffusion [Termes IGN] transfert radiatif Résumé : (auteur) Approximately, 30% of the Sentinel-1 (S-1) swath over land is imaged with incidence angles higher than 40°. Still, the interplay among the scattering mechanisms taking place at such a high incidence and their implications on the backscatter information content is often disregarded. This article investigates, through an experimental and numerical study, the S-1 sensitivity to the surface soil moisture (SSM) over agricultural fields observed at low (~33°) and high (~43°) incidence angles and quantifies the impact of the incidence angle on the SSM retrieval accuracy. The study sites are the Apulian Tavoliere (Italy) and REd de MEDición de la HUmedad del Suelo (REMEDHUS) (Spain), which are both instrumented with a hydrologic network continuously measuring SSM. At low incidence angles, results confirm that for crops such as wheat and barley, dominated in C-band by surface scattering, there exists a good sensitivity of S-1 VV to SSM. At high incidence angles, the sensitivity to SSM holds through the combination of the soil attenuated and double bounce scattering. Conversely, over crops dominated by volume scattering, such as sugar beet, the S-1 VV signal is not correlated with the in situ SSM observations, neither at low nor at high incidence. For all the crops, the sensitivity of S-1 to SSM in VH is found significantly lower than in VV. The impact of the incidence angle on the SSM retrieval has been studied with a recursive algorithm based on a short-term change detection approach. An upper and lower bounds for the worsening of the S-1 VV retrieval performance at far versus near range observations have been estimated. In the worst-case scenario, the root mean square error (RMSE) increases from ~0.056 m 3 /m 3 , at low incidence, to ~0.071 m 3 /m 3 , at high incidence. The mechanism that lowers the retrieval accuracy at high incidence angles is further investigated in the synthetic experiment and its impact on the RMSE is estimated in terms of the volume scattering contribution. Numéro de notice : A2021-646 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3033887 Date de publication en ligne : 10/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3033887 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98351 [article]

Using electrical resistivity tomography to detect wetwood and estimate moisture content in silver fir (Abies alba Mill.) / Ludovic Martin in Annals of Forest Science [en ligne], vol 78 n° 3 (September 2021)  

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Random forests with bagging and genetic algorithms coupled with least trimmed squares regression for soil moisture deficit using SMOS satellite soil moisture / Pashrant K. Srivastava in ISPRS International journal of geo-information, vol 10 n° 8 (August 2021)  

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An integrated methodology for surface soil moisture estimating using remote sensing data approach / Rida Khellouk in Geocarto international, vol 36 n° 13 ([15/07/2021])  

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Characterization of mixed and monospecific stands of Scots pine and Maritime pine: soil profile, physiography, climate and vegetation cover data / Daphne Lopez-Marcos in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

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A combined drought monitoring index based on multi-sensor remote sensing data and machine learning / Hongzhu Han in Geocarto international, vol 36 n° 10 ([01/06/2021])  

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Temporal mosaicking approaches of Sentinel-2 images for extending topsoil organic carbon content mapping in croplands / Emmanuelle Vaudour in International journal of applied Earth observation and geoinformation, vol 96 (April 2021)  

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Use of ground penetrating radar in the evaluation of wood structures: A review / Brunela Pollastrelli Rodrigues in Forests, vol 12 n° 4 (April 2021)  

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Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden in Plant ecology, vol 222 n° 3 (March 2021)  

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Diurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)  

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Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data / C.M. Bhatt in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

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