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Drought-vulnerable vegetation increases exposure of disadvantaged populations to heatwaves under global warming: A case study from Los Angeles / Chunyu Dong in Sustainable Cities and Society, vol 93 (June 2023)
[article]
Titre : Drought-vulnerable vegetation increases exposure of disadvantaged populations to heatwaves under global warming: A case study from Los Angeles Type de document : Article/Communication Auteurs : Chunyu Dong, Auteur ; Yu Yan, Auteur ; Jie Guo, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104488 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] climat urbain
[Termes IGN] données socio-économiques
[Termes IGN] espace vert
[Termes IGN] ilot thermique urbain
[Termes IGN] image Terra-MODIS
[Termes IGN] Los Angeles
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] sécheresse
[Termes IGN] température au solRésumé : (auteur) Urban vegetation is valuable in alleviating local heatwaves. However, drought may decrease vegetation health and limit this cooling effect. Here we use satellite-based Normalized Difference Vegetation Index (NDVI) and Palmer Drought Severity Index (PDSI) to investigate the sensitivity of urban vegetation to drought in Coastal Greater Los Angeles (CGLA) from 2001 to 2020. We applied four statistical models to analyze the relations between 15 socioeconomic variables and the vegetation's sensitivity to drought. We then examined the changes in the cooling effect of the urban vegetation during drought and non-drought periods using remotely sensed land surface temperature (LST) data. The results suggest that economically disadvantaged areas with higher proportions of Hispanics and Blacks are typified by vegetation more sensitive to drought, which is likely linked to inequality in water use. Moreover, these populations experience a lower degree of vegetation cooling effects and higher exposure to heatwaves. The findings of this study imply that the potential of a community's vegetation in mitigating heatwaves is significantly influenced by the socioeconomic conditions of the community. Increasing the resilience of urban vegetation to drought in disadvantaged communities may help promote environmentally sustainable and socially resilient cities under a warming climate. Numéro de notice : A2023-191 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2023.104488 Date de publication en ligne : 26/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104488 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102972
in Sustainable Cities and Society > vol 93 (June 2023) . - n° 104488[article]Diversity and mean specific leaf area of Mediterranean woody vegetation changes in response to summer drought across a double stress gradient: The role of phenotypic plasticity / Alejandro Carrascosa in Journal of vegetation science, vol 34 n° 2 (April 2023)
[article]
Titre : Diversity and mean specific leaf area of Mediterranean woody vegetation changes in response to summer drought across a double stress gradient: The role of phenotypic plasticity Type de document : Article/Communication Auteurs : Alejandro Carrascosa, Auteur ; Mariola Silvestre, Auteur ; Laura Morgado, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° e13180 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbuste
[Termes IGN] climat méditerranéen
[Termes IGN] diagnostic foliaire
[Termes IGN] Espagne
[Termes IGN] facteur édaphique
[Termes IGN] indice foliaire
[Termes IGN] plante ligneuse
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : Aim: Many aspects of vegetation response to increased drought remain uncertain but it is expected that phenotypic plasticity may be key to early adaptation of plants to environmental stress. In this work we observe the response of specific leaf area (SLA) of woody shrub vegetation to the summer drought typical of the Mediterranean climate. In addition, to observe the possible interaction between the impact of drought and the environmental characteristics of the ecosystems, communities from different edaphic and structural contexts distributed along the double stress gradient of the Mediterranean mountains (high temperature and low precipitation at low elevation; low temperature and high irradiation at high elevation) have been analysed.
Location: Central Mountain range of the Iberian Peninsula.
Methods: Along the entire altitudinal gradient, 33 shrub communities belonging to different habitat typologies (shrublands, rocky areas, hedgerows, understorey) were sampled before and after the passage of summer, both in 2017 and 2019. A total of 1724 individuals and 15,516 leaves were collected and measured to estimate the mean values and diversity of SLA of each community.
Results: The community-weighted mean and functional divergence have inverse quadratic relationships with the environmental gradient. Shrub communities at both ends of the gradient have low mean SLA values and high functional divergence of this trait. Summer drought implies a generalised decrease in the mean SLA of the communities throughout the gradient, as well as an alteration in functional richness and uniformity. However, the effect of summer drought on the plant community is mediated by the microenvironmental characteristics of its habitat.
Conclusions: Drought acclimatisation of shrub communities through phenotypic plasticity leads to rapid changes in their functional leaf structure. In the long term, our results point to an increase in plant conservative strategies, reduced ecosystem productivity, slower nutrient recycling and the reduction of communities of specific habitats as drought increases.Numéro de notice : A2023-223 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/jvs.13180 Date de publication en ligne : 09/03/2023 En ligne : https://doi.org/10.1111/jvs.13180 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103172
in Journal of vegetation science > vol 34 n° 2 (April 2023) . - n° e13180[article]Improvement in crop mapping from satellite image time series by effectively supervising deep neural networks / Sina Mohammadi in ISPRS Journal of photogrammetry and remote sensing, vol 198 (April 2023)
[article]
Titre : Improvement in crop mapping from satellite image time series by effectively supervising deep neural networks Type de document : Article/Communication Auteurs : Sina Mohammadi, Auteur ; Mariana Belgiu, Auteur ; Alfred Stein, Auteur Année de publication : 2023 Article en page(s) : pp 272 - 283 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage dirigé
[Termes IGN] apprentissage profond
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par réseau neuronal récurrent
[Termes IGN] cultures
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelleRésumé : (auteur) Deep learning methods have achieved promising results in crop mapping using satellite image time series. A challenge still remains on how to better learn discriminative feature representations to detect crop types when the model is applied to unseen data. To address this challenge and reveal the importance of proper supervision of deep neural networks in improving performance, we propose to supervise intermediate layers of a designed 3D Fully Convolutional Neural Network (FCN) by employing two middle supervision methods: Cross-entropy loss Middle Supervision (CE-MidS) and a novel middle supervision method, namely Supervised Contrastive loss Middle Supervision (SupCon-MidS). This method pulls together features belonging to the same class in embedding space, while pushing apart features from different classes. We demonstrate that SupCon-MidS enhances feature discrimination and clustering throughout the network, thereby improving the network performance. In addition, we employ two output supervision methods, namely F1 loss and Intersection Over Union (IOU) loss. Our experiments on identifying corn, soybean, and the class Other from Landsat image time series in the U.S. corn belt show that the best set-up of our method, namely IOU+SupCon-MidS, is able to outperform the state-of-the-art methods by
scores of 3.5% and 0.5% on average when testing its accuracy across a different year (local test) and different regions (spatial test), respectively. Further, adding SupCon-MidS to the output supervision methods improves
scores by 1.2% and 7.6% on average in local and spatial tests, respectively. We conclude that proper supervision of deep neural networks plays a significant role in improving crop mapping performance. The code and data are available at: https://github.com/Sina-Mohammadi/CropSupervision.Numéro de notice : A2023-203 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2023.03.007 Date de publication en ligne : 29/03/2023 En ligne : https://doi.org/10.1016/j.isprsjprs.2023.03.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103105
in ISPRS Journal of photogrammetry and remote sensing > vol 198 (April 2023) . - pp 272 - 283[article]Amazon forest spectral seasonality is consistent across sensor resolutions and driven by leaf demography / Nathan B. Gonçalves in ISPRS Journal of photogrammetry and remote sensing, vol 196 (February 2023)
[article]
Titre : Amazon forest spectral seasonality is consistent across sensor resolutions and driven by leaf demography Type de document : Article/Communication Auteurs : Nathan B. Gonçalves, Auteur ; Ricardo Dalagnol, Auteur ; Jin Wu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 93 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Amazonie
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] image proche infrarouge
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] Leaf Area Index
[Termes IGN] réflectance spectrale
[Termes IGN] sécheresse
[Termes IGN] variation saisonnièreRésumé : (Auteur) Controversy surrounds the reported dry season greening of the Central Amazon forests based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS). As the solar zenith angle decreases during the dry season, it affects the sub-pixel shade content and artificially increases Near-infrared (NIR) reflectance and EVI. MODIS' coarse resolution also creates a challenge for cloud and terrain filtering. To reduce these artifacts and then validate MODIS seasonal spectral patterns we use 16 years of 1 km resolution MODIS-MAIAC (Multi-Angle Implementation of Atmospheric Correction) images, corrected to a nadir view and 45° solar zenith angle, together with an improved cloud filter. Then we show that the 30 m Landsat-8 Operational Land Imager (OLI) surface reflectance over two Landsat scenes provides independent evidence supporting the MODIS-MAIAC seasonality for EVI, NIR, and GCC (an additional important vegetation index, green chromatic coordinate). Our empirical method for controlling for sun-sensor geometry effects in Landsat scenes encompasses the use of seasonally distinct images that have similar solar zenith angles and cloud-free pixels on flat uplands having the same phase angle. We extended this validation to nine Amazon sub-basins comprising ∼546 Landsat-8 images. Our study shows that the dry-season green-up pattern observed by MODIS is corroborated by Landsat-8, and is independent of satellite data artifacts. To investigate the mechanisms driving these seasonal changes we further used Central Amazon tower-mounted RGB cameras providing a 4-year record at the Amazon Tall Tower (ATTO, 2°8′36″S, 59°0′2″W) and a 7-year record at the Manaus k34 tower (2°36′33″ S, 60°12′33″W) to obtain monthly upper canopy green leaf cover (a proxy for Leaf Area Index - LAI) and monthly leaf age class abundances (based on the age since leaf flushing, by crown). These were compared to seasonal patterns of GCC and EVI in small MODIS-MAIAC windows centered on each tower. MODIS-MAIAC GCC was positively correlated with newly flushed leaves (R2 = 0.76 and 0.44 at ATTO and k34, respectively). EVI correlated strongly with the abundance of mature leaves (R2 = 0.82 and 0.80) but was poorly correlated with LAI (R2 = 0.20 and 0.41, respectively). Therefore, seasonal spectral patterns in the Central Amazon are likely controlled by leaf age variation, not quantity of leaf area. Numéro de notice : A2023-065 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.12.001 Date de publication en ligne : 04/01/2023 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.12.001 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102423
in ISPRS Journal of photogrammetry and remote sensing > vol 196 (February 2023) . - pp 93 - 104[article]Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data / Thuong V. Tran in GIScience and remote sensing, vol 60 n° 1 (2023)
[article]
Titre : Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data Type de document : Article/Communication Auteurs : Thuong V. Tran, Auteur ; David Bruce, Auteur ; Cho-Ying Huang, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 2163070 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spectrale
[Termes IGN] changement d'occupation du sol
[Termes IGN] image Terra-MODIS
[Termes IGN] indice d'humidité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] parcelle agricole
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] surveillance agricole
[Termes IGN] variation temporelle
[Termes IGN] Viet NamRésumé : (auteur) Using a multivariate drought index that incorporates important environmental variables and is suitable for a specific geographical region is essential to fully understanding the pattern and impacts of drought severity. This study applied feature scaling algorithms to MODIS time-series imagery to develop an integrated Multivariate Drought Index (iMDI). The iMDI incorporates the vegetation condition index (VCI), the temperature condition index (TCI), and the evaporative stress index (ESI). The 54,474 km2 Vietnamese Central Highlands region, which has been significantly affected by drought severity for several decades, was selected as a test site to assess the feasibility of the iMDI. Spearman correlation between the iMDI and other commonly used spectral drought indices (i.e. the Drought Severity Index (DSI–12) and the annual Vegetation Health Index (VHI–12)) and ground-based drought indices (i.e. the Standardized Precipitation Index (SPI–12) and the Reconnaissance Drought Index (RDI–12)) was employed to evaluate performance of the proposed drought index. Pixel-based linear regression together with clustering models of the iMDI time-series was applied to characterize the spatiotemporal pattern of drought from 2001 to 2020. In addition, a persistent area of LULC types (i.e. forests, croplands, and shrubland) during the 2001–2020 period was used to understand drought variation in relation to LULC. Results suggested that the iMDI outperformed the other spectral drought indices (r > 0.6; p Numéro de notice : A2023-042 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2022.2163070 Date de publication en ligne : 03/01/2023 En ligne : https://doi.org/10.1080/15481603.2022.2163070 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102329
in GIScience and remote sensing > vol 60 n° 1 (2023) . - n° 2163070[article]How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data / Rongfang Lyu in Sustainable Cities and Society, vol 88 (January 2023)PermalinkImproving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)PermalinkRemote sensing techniques for water management and climate change monitoring in drought areas: case studies in Egypt and Tunisia / Lifan Ji in European journal of remote sensing, vol 56 n° 1 (2023)PermalinkInteractive effects of abiotic factors and biotic agents on Scots pine dieback: A multivariate modeling approach in southeast France / Jean Lemaire in Forest ecology and management, vol 526 (December-15 2022)PermalinkEstimating 10-m land surface albedo from Sentinel-2 satellite observations using a direct estimation approach with Google Earth Engine / Xingwen Lin in ISPRS Journal of photogrammetry and remote sensing, vol 194 (December 2022)PermalinkIntegration of geospatial technologies with multiple regression model for urban land use land cover change analysis and its impact on land surface temperature in Jimma City, southwestern Ethiopia / Mitiku Badasa Moisa in Applied geomatics, vol 14 n° 4 (December 2022)PermalinkThe contribution of understorey vegetation to ecosystem evapotranspiration in boreal and temperate forests: a literature review and analysis / Philippe Balandier in European Journal of Forest Research, vol 141 n° 6 (December 2022)PermalinkAn advanced bidirectional reflectance factor (BRF) spectral approach for estimating flavonoid content in leaves of Ginkgo plantations / Kai Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 193 (November 2022)PermalinkModelling and accessing land degradation vulnerability using remote sensing techniques and the analytical hierarchy process approach / Abebe Debele Tolche in Geocarto international, vol 37 n° 24 ([20/10/2022])PermalinkThe fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)PermalinkComparing Landsat-8 and Sentinel-2 top of atmosphere and surface reflectance in high latitude regions: case study in Alaska / Jiang Chen in Geocarto international, vol 37 n° 20 ([20/09/2022])PermalinkForest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)PermalinkHistorical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine / Luis Carrasco in ISPRS Journal of photogrammetry and remote sensing, vol 191 (September 2022)PermalinkIncorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping / Jwan Al-Doski in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 8 (August 2022)PermalinkMainstreaming remotely sensed ecosystem functioning in ecological niche models / Adrián Regos in Remote sensing in ecology and conservation, vol 8 n° 4 (August 2022)PermalinkMapping land-use intensity of grasslands in Germany with machine learning and Sentinel-2 time series / Maximilian Lange in Remote sensing of environment, vol 277 (August 2022)PermalinkRemote sensing and phytoecological methods for mapping and assessing potential ecosystem services of the Ouled Hannèche Forest in the Hodna Mountains, Algeria / Amal Louail in Forests, Vol 13 n° 8 (August 2022)PermalinkMultiscale assimilation of Sentinel and Landsat data for soil moisture and Leaf Area Index predictions using an ensemble-Kalman-filter-based assimilation approach in a heterogeneous ecosystem / Nicola Montaldo in Remote sensing, vol 14 n° 14 (July-2 2022)PermalinkGIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)PermalinkA phenology-based vegetation index classification (PVC) algorithm for coastal salt marshes using Landsat 8 images / Jing Zeng in International journal of applied Earth observation and geoinformation, vol 110 (June 2022)PermalinkThe interrelationship between LST, NDVI, NDBI, and land cover change in a section of Lagos metropolis, Nigeria / Alfred S. Alademomi in Applied geomatics, vol 14 n° 2 (June 2022)PermalinkVariance based fusion of VCI and TCI for efficient classification of agriculture drought using MODIS data / Anjana N.J. Kukunuri in Geocarto international, vol 37 n° 10 ([01/06/2022])PermalinkAnalyzing spatio-temporal pattern of the forest fire burnt area in Uttarakhand using Sentinel-2 data / Shailja Mamgain in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)PermalinkAlternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation / Toshihiro Sakamoto in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)PermalinkA continuous change tracker model for remote sensing time series reconstruction / Yangjian Zhang in Remote sensing, vol 14 n° 9 (May-1 2022)PermalinkDevelopment of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model / Han Ma in Remote sensing of environment, vol 273 (May 2022)PermalinkSignificant loss of ecosystem services by environmental changes in the Mediterranean coastal area / Adriano Conte in Forests, vol 13 n° 5 (May 2022)PermalinkThe role of blue green infrastructure in the urban thermal environment across seasons and local climate zones in East Africa / Xueqin Li in Sustainable Cities and Society, vol 80 (May 2022)PermalinkCrop 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 ([15/04/2022])PermalinkDetecting and mapping drought severity using multi-temporal Landsat data in the uMsinga region of KwaZulu-Natal, South Africa / Shenelle Lottering in Geocarto international, vol 37 n° 6 ([01/04/2022])PermalinkComparaison des images satellite et aériennes dans le domaine de la détection d’obstacles à la navigation aérienne et de leur mise à jour / Olivier de Joinville in XYZ, n° 170 (mars 2022)PermalinkEvaluating Sentinel-1A datasets for rice leaf area index estimation based on machine learning regression models / Lamin R. Mansaray in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkLand surface phenology retrieval through spectral and angular harmonization of Landsat-8, Sentinel-2 and Gaofen-1 data / Jun Lu in Remote sensing, vol 14 n° 5 (March-1 2022)PermalinkMonitoring of phenological stage and yield estimation of sunflower plant using Sentinel-2 satellite images / Omer Gokberk Narin in Geocarto international, vol 37 n° 5 ([01/03/2022])PermalinkAboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkDevelopment of earth observational diagnostic drought prediction model for regional error calibration: A case study on agricultural drought in Kyrgyzstan / Eunbeen Park in GIScience and remote sensing, vol 59 n° 1 (2022)PermalinkDynamic modelling of rice leaf area index with quad-source optical imagery and machine learning regression models / Lamin R. Mansaray in Geocarto international, vol 37 n° 3 ([01/02/2022])PermalinkSpatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria / Maninder Singh Dhillon in Remote sensing, vol 14 n° 3 (February-1 2022)PermalinkSymbolic regression-based allometric model development of a mangrove forest LAI using structural variables and digital hemispherical photography / Somnath Paramanik in Applied Geography, vol 139 (February 2022)Permalink3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkCombined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkMulti-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana / Ram Avtar in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkSoil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)PermalinkUse of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])PermalinkAbove-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data / Fardin Moradi in Annals of forest research, vol 65 n° 1 (January - June 2022)PermalinkApplication of deep learning with stratified K-fold for vegetation species discrimation in a protected mountainous region using Sentinel-2 image / Efosa Gbenga Adagbasa in Geocarto international, vol 37 n° 1 ([01/01/2022])PermalinkApport de la télédétection et des variables auxiliaires dans l'étude de l'évolution des périodes de sécheresse / Nesrine Farhani (2022)PermalinkClassification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkExamining the integration of Landsat operational land imager with Sentinel-1 and vegetation indices in mapping southern yellow pines (Loblolly, Shortleaf, and Virginia pines) / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)PermalinkMonitoring and analysis of crop irrigation dynamics in Central Italy through the use of MODIS NDVI data / Marta Chiesi in European journal of remote sensing, vol 55 n° 1 (2022)PermalinkMonitoring grassland dynamics by exploiting multi-modal satellite image time series / Anatol Garioud (2022)PermalinkMonitoring 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)PermalinkSenRVM: A multi-modal deep learning regression methodology for continuous vegetation monitoring with dense temporal NDVI time series / Anatol Garioud (2022)PermalinkPermalinkUnderstory plant community responses to widespread spruce mortality in a subalpine forest / Trevor A. Carter in Journal of vegetation science, vol 33 n° 1 (January 2022)PermalinkPermalinkEarly detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany / Kathrin Einzmann in Remote sensing of environment, vol 266 (December 2021)PermalinkMulti-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images / Yiying Hua in Forests, vol 12 n° 12 (December 2021)PermalinkNational scale mapping of larch plantations for Wales using the Sentinel-2 data archive / Suvarna M. Punalekar in Forest ecology and management, vol 501 (December-1 2021)PermalinkIdentifying surface urban heat island drivers and their spatial heterogeneity in China’s 281 cities: An empirical study based on multiscale geographically weighted regression / Lu Niu in Remote sensing, vol 13 n° 21 (November-1 2021)PermalinkA novel cotton mapping index combining Sentinel-1 SAR and Sentinel-2 multispectral imagery / Lan Xun in ISPRS Journal of photogrammetry and remote sensing, Vol 181 (November 2021)PermalinkSuperpixel-based regional-scale grassland community classification using genetic programming with Sentinel-1 SAR and Sentinel-2 multispectral images / Zhenjiang Wu in Remote sensing, vol 13 n° 20 (October-2 2021)PermalinkField 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])PermalinkImproving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)PermalinkRecurrent-based regression of Sentinel time series for continuous vegetation monitoring / Anatol Garioud in Remote sensing of environment, vol 263 (15 September 2021)PermalinkClassification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)PermalinkGeoglam, l'agriculture par satellite / Laurent Polidori in Géomètre, n° 2194 (septembre 2021)PermalinkMonitoring forest disturbance using time-series MODIS NDVI in Michoacán, Mexico / Yao Gao in Geocarto international, vol 36 n° 15 ([15/08/2021])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])PermalinkSurface modelling of forest aboveground biomass based on remote sensing and forest inventory data / Xiaofang Sun in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkAn integrated methodology for surface soil moisture estimating using remote sensing data approach / Rida Khellouk in Geocarto international, vol 36 n° 13 ([15/07/2021])PermalinkComparison of classification methods for urban green space extraction using very high resolution worldview-3 imagery / S. Vigneshwaran in Geocarto international, vol 36 n° 13 ([15/07/2021])PermalinkEstimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods / Paulina Dukat in Forests, vol 12 n° 7 (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])PermalinkSemantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)PermalinkApplication of feature selection methods and machine learning algorithms for saltmarsh biomass estimation using Worldview-2 imagery / Sikdar M. M. Rasel in Geocarto international, vol 36 n° 10 ([01/06/2021])PermalinkA 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])PermalinkFractional 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)PermalinkIdentifying the effects of chronic saltwater intrusion in coastal floodplain swamps using remote sensing / Elliott White Jr in Remote sensing of environment, vol 258 (June 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)PermalinkOn the relationship between normalized difference vegetation index and land surface temperature: MODIS-based analysis in a semi-arid to arid environment / Salahuddin M. Jaber in Geocarto international, vol 36 n° 10 ([01/06/2021])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)PermalinkThe use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries / Nagihan Aslan in ISPRS International journal of geo-information, vol 10 n° 6 (June 2021)PermalinkDetection of rainstorm pattern in arid regions using MODIS NDVI time series analysis / Mohamed E. Hereher in Geocarto international, vol 36 n° 8 ([01/05/2021])PermalinkMapping and quantification of the dwarf eelgrass Zostera noltii using a random forest algorithm on a SPOT 7 satellite image / Salma Benmokhtar in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)PermalinkSensitivity of voxel-based estimations of leaf area density with terrestrial LiDAR to vegetation structure and sampling limitations: A simulation experiment / Maxime Soma in Remote sensing of environment, vol 257 (May 2021)PermalinkValidation and analysis of Terra and Aqua MODIS, and SNPP VIIRS vegetation indices under zero vegetation conditions: A case study using Railroad Valley Playa / Tomoaki Miura in Remote sensing of environment, vol 257 (May 2021)PermalinkAssessing forest phenology: A multi-scale comparison of near-surface (UAV, spectral reflectance sensor, PhenoCam) and satellite (MODIS, Sentinel-2) remote sensing / Shangharsha Thapa in Remote sensing, vol 13 n° 8 (April-2 2021)PermalinkLeaf area index estimation of wheat crop using modified water cloud model from the time-series SAR and optical satellite data / Vijay Pratap Yadav in Geocarto international, vol 36 n° 7 ([15/04/2021])PermalinkThe delineation of tea gardens from high resolution digital orthoimages using mean-shift and supervised machine learning methods / Akhtar Jamil in Geocarto international, vol 36 n° 7 ([15/04/2021])PermalinkTemporal 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)PermalinkApport des images Landsat à l’étude de l’évolution de l’occupation du sol dans la plaine de Saïss au Maroc, pour la période 1987-2018 / Abdelkader El Garouani in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkDétection des zones de dégradation et de régénération de la couverture végétale dans le sud du Sénégal à travers l'analyse des tendances de séries temporelles MODIS NDVI et des changements d'occupation des sols à partir d'images LANDSAT / Boubacar Solly in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)PermalinkEvaluation du potentiel des series d’images multi-temporelles optique et radar des satellites Sentinel 1 & 2 pour le suivi d’une zone côtière en contexte tropical: cas de l’estuaire du Cameroun pour la période 2015-2020 / Nourdi Njutapvoui in Revue Française de Photogrammétrie et de Télédétection, n° 223 (mars - décembre 2021)Permalink