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Fractional vegetation cover estimation algorithm for FY-3B reflectance data based on random forest regression method / Duanyang Liu in Remote sensing, vol 13 n° 11 (June-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 11 (June-1 2021) . - n° 2165 Titre : Fractional vegetation cover estimation algorithm for FY-3B reflectance data based on random forest regression method Type de document : Article/Communication Auteurs : Duanyang Liu, Auteur ; Kun Jia, Auteur ; Haiying jiang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2165 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Chine [Termes IGN] classification par forêts aléatoires [Termes IGN] couvert végétal [Termes IGN] image Feng-Yun [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] réflectance végétale [Termes IGN] régression Résumé : (auteur) As an important land surface vegetation parameter, fractional vegetation cover (FVC) has been widely used in many Earth system ecological and climate models. In particular, high-quality and reliable FVC products on the global scale are important for the Earth surface process simulation and global change studies. Recently, the FengYun-3 (FY-3) series satellites, which are the second generation of Chinese meteorological satellites, launched with the polar orbit and provide continuous land surface observations on a global scale. However, there is rare studying on the FVC estimation using FY-3 reflectance data. Therefore, the FY-3B reflectance data were selected as the representative data to develop a FVC estimation algorithm in this study, which would investigate the capability of the FY-3 reflectance data on the global FVC estimation. The spatial–temporal validation over the regional area indicated that the FVC estimations generated by the proposed algorithm had reliable continuities. Furthermore, a satisfactory accuracy performance (R2 = 0.7336, RMSE = 0.1288) was achieved for the proposed algorithm based on the Earth Observation LABoratory (EOLAB) reference FVC data, which provided further evidence on the reliability and robustness of the proposed algorithm. All these results indicated that the FY-3 reflectance data were capable of generating a FVC estimation with reliable spatial–temporal continuities and accuracy. Numéro de notice : A2021-439 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13112165 date de publication en ligne : 31/05/2021 En ligne : https://doi.org/10.3390/rs13112165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97824 [article]

Inversion of solar-induced chlorophyll fluorescence using polarization measurements of vegetation / Haiyan Yao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 5 (May 2021) . - pp 331-338 Titre : Inversion of solar-induced chlorophyll fluorescence using polarization measurements of vegetation Type de document : Article/Communication Auteurs : Haiyan Yao, Auteur ; Ziying Li, Auteur ; Yang Han, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 331-338 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] chlorophylle [Termes IGN] couvert végétal [Termes IGN] données polarimétriques [Termes IGN] fluorescence [Termes IGN] polarisation Résumé : (Auteur) In vegetation remote sensing, the apparent radiation of the vegetation canopy is often combined with three components derived from different parts of vegetation that have different production mechanisms and optical properties: volume scattering Lvol, polarized light Lpol, and chlorophyll fluorescence ChlF. The chlorophyll fluorescence plays a very important role in vegetation remote sensing, and the polarization information in vegetation remote sensing has become an effective way to characterize the physical characteristics of vegetation. This study analyzes the difference between these three types of radiation flux and utilizes polarization radiation to separate them from the apparent radiation of the vegetation canopy. Specifically, solar-induced chlorophyll fluorescence is extracted from vegetation canopy radiation data using standard Fraunhofer-line discrimination. The results show that polarization measurements can quantitatively separate Lvol, Lpol, and ChlF and extract the solar-induced chlorophyll fluorescence. This study improves our understanding of the light-scattering properties of vegetation canopies and provides insights for developing building models and research algorithms. Numéro de notice : A2021-365 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.5.331 date de publication en ligne : 01/05/2021 En ligne : https://doi.org/10.14358/PERS.87.5.331 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97694 [article]

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Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain / R. Niederheiser in GIScience and remote sensing, vol 58 n° 1 (February 2021)  

Public [article]  inGIScience and remote sensing > vol 58 n° 1 (February 2021) . - pp 120 - 137 Titre : Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain Type de document : Article/Communication Auteurs : R. Niederheiser, Auteur ; M. Winkler, Auteur ; V. Di Cecco, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 120 - 137 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre [Termes IGN] Alpes [Termes IGN] caméra numérique [Termes IGN] carte de la végétation [Termes IGN] classification par forêts aléatoires [Termes IGN] classification semi-dirigée [Termes IGN] couvert végétal [Termes IGN] distribution de Poisson [Termes IGN] données topographiques [Termes IGN] indice de végétation [Termes IGN] module linéaire [Termes IGN] montagne [Termes IGN] occupation du sol [Termes IGN] photogrammétrie métrologique [Termes IGN] semis de points Résumé : (auteur) In this paper we present a low-cost approach to mapping vegetation cover by means of high-resolution close-range terrestrial photogrammetry. A total of 249 clusters of nine 1 m2 plots each, arranged in a 3 × 3 grid, were set up on 18 summits in Mediterranean mountain regions and in the Alps to capture images for photogrammetric processing and in-situ vegetation cover estimates. This was done with a hand-held pole-mounted digital single-lens reflex (DSLR) camera. Low-growing vegetation was automatically segmented using high-resolution point clouds. For classifying vegetation we used a two-step semi-supervised Random Forest approach. First, we applied an expert-based rule set using the Excess Green index (ExG) to predefine non-vegetation and vegetation points. Second, we applied a Random Forest classifier to further enhance the classification of vegetation points using selected topographic parameters (elevation, slope, aspect, roughness, potential solar irradiation) and additional vegetation indices (Excess Green Minus Excess Red (ExGR) and the vegetation index VEG). For ground cover estimation the photogrammetric point clouds were meshed using Screened Poisson Reconstruction. The relative influence of the topographic parameters on the vegetation cover was determined with linear mixed-effects models (LMMs). Analysis of the LMMs revealed a high impact of elevation, aspect, solar irradiation, and standard deviation of slope. The presented approach goes beyond vegetation cover values based on conventional orthoimages and in-situ vegetation cover estimates from field surveys in that it is able to differentiate complete 3D surface areas, including overhangs, and can distinguish between vegetation-covered and other surfaces in an automated manner. The results of the Random Forest classification confirmed it as suitable for vegetation classification, but the relative feature importance values indicate that the classifier did not leverage the potential of the included topographic parameters. In contrast, our application of LMMs utilized the topographic parameters and was able to reveal dependencies in the two biomes, such as elevation and aspect, which were able to explain between 87% and 92.5% of variance. Numéro de notice : A2021-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2020.1859264 date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1080/15481603.2020.1859264 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97295 [article]

Modelling landslide hazards under global changes: the case of a Pyrenean valley / Séverine Bernardie in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)  

Public [article]  inNatural Hazards and Earth System Sciences > vol 21 n° 1 (January 2021) . - pp 147 - 169 Titre : Modelling landslide hazards under global changes: the case of a Pyrenean valley Type de document : Article/Communication Auteurs : Séverine Bernardie, Auteur ; Rosalie Vandromme, Auteur ; Yannick Thiery, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 147 - 169 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte topographique [Termes IGN] Cauterets [Termes IGN] changement climatique [Termes IGN] couvert végétal [Termes IGN] effondrement de terrain [Termes IGN] modèle de simulation [Termes IGN] modèle hydrographique [Termes IGN] modèle numérique de terrain [Termes IGN] occupation du sol [Termes IGN] Pyrénées (montagne) [Termes IGN] risque naturel [Termes IGN] utilisation du sol Résumé : (auteur) Several studies have shown that global changes have important impacts in mountainous areas, since they affect natural hazards induced by hydrometeorological events such as landslides. The present study evaluates, through an innovative method, the influence of both vegetation cover and climate change on landslide hazards in a Pyrenean valley from the present to 2100. We first focused on assessing future land use and land cover changes through the construction of four prospective socioeconomic scenarios and their projection to 2040 and 2100. Secondly, climate change parameters were used to extract the water saturation of the uppermost layers, according to two greenhouse gas emission scenarios. The impacts of land cover and climate change based on these scenarios were then used to modulate the hydromechanical model to compute the factor of safety (FoS) and the hazard levels over the considered area. The results demonstrate the influence of land cover on slope stability through the presence and type of forest. The resulting changes are statistically significant but small and dependent on future land cover linked to the socioeconomic scenarios. In particular, a reduction in human activity results in an increase in slope stability; in contrast, an increase in anthropic activity leads to an opposite evolution in the region, with some reduction in slope stability. Climate change may also have a significant impact in some areas because of the increase in the soil water content; the results indicate a reduction in the FoS in a large part of the study area, depending on the landslide type considered. Therefore, even if future forest growth leads to slope stabilization, the evolution of the groundwater conditions will lead to destabilization. The increasing rate of areas prone to landslides is higher for the shallow landslide type than for the deep landslide type. Interestingly, the evolution of extreme events is related to the frequency of the highest water filling ratio. The results indicate that the occurrences of landslide hazards in the near future (2021–2050 period, scenario RCP8.5) and far future (2071–2100 period, scenario RCP8.5) are expected to increase by factors of 1.5 and 4, respectively. Numéro de notice : A2021-135 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/nhess-21-147-2021 date de publication en ligne : 18/01/2021 En ligne : https://doi.org/10.5194/nhess-21-147-2021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96999 [article]

Evaluating the impact of declining tsetse fly (Glossina pallidipes) habitat in the Zambezi valley of Zimbabwe / Farai Matawa in Geocarto international, vol 35 n° 12 ([01/09/2020])  

Public [article]  inGeocarto international > vol 35 n° 12 [01/09/2020] . - pp 1373 - 1384 Titre : Evaluating the impact of declining tsetse fly (Glossina pallidipes) habitat in the Zambezi valley of Zimbabwe Type de document : Article/Communication Auteurs : Farai Matawa, Auteur ; Amon Murwira, Auteur ; Peter M. Atkinson, Auteur Année de publication : 2020 Article en page(s) : pp 1373 - 1384 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] biodiversité [Termes IGN] bovin [Termes IGN] couvert végétal [Termes IGN] diptère [Termes IGN] distance [Termes IGN] distribution spatiale [Termes IGN] forêt tropicale [Termes IGN] habitat d'espèce [Termes IGN] maladie parasitaire [Termes IGN] Zambèze (fleuve) [Termes IGN] Zimbabwe Résumé : (auteur) Tsetse flies transmit trypanosomes that cause Human African Trypanosomiasis (HAT) in humans and African Animal Trypanosomiasis (AAT) in animals. Understanding historical trends in the spatial distribution of tsetse fly habitat is necessary for planning vector control measures. The objectives of this study were (i) to test for evidence of any trends in suitable tsetse fly habitat and (ii) to test whether there is an association between trypanosomiasis detected from livestock sampled in dip tanks and local tsetse habitat in the project area. Results indicate a significant decreasing trend in the amount of suitable habitat. There is no significant correlation between trypanosomiasis prevalence rates in cattle and distance from patches of suitable tsetse habitat. The observed low trypanosomiasis prevalence and the lack of dependence on suitable tsetse fly habitat can be explained by the observed decreases in suitable tsetse habitat, which themselves are due to expansion of settlement and agriculture in North Western Zimbabwe. Numéro de notice : A2020-486 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576780 date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576780 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95653 [article]

Path length correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)  

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An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Developing shopping and dining walking indices using POIs and remote sensing data / Yingbin Deng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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Analyse automatique du couvert végétal pour la gestion du risque végétation en milieu ferroviaire à partir d'imagerie aérienne / Hélène Rouillon (2020)  

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Caractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde / Céline Vargel (2020)  

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Comparison of multi-seasonal Landsat 8, Sentinel-2 and hyperspectral images for mapping forest alliances in Northern California / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)  

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Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations / S. Hamed Alemohammad in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)  

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Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October 2019)  

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Quantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, vol 52 n° 4 (2019)  

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