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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)  

Public [article]  inSustainable Cities and Society > vol 93 (June 2023) . - n° 104488 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 sol Résumé : (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 [article]

Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak / A.P. Rudke in Remote sensing of environment, vol 289 (May 2003)  

Public [article]  inRemote sensing of environment > vol 289 (May 2003) . - n° 113514 Titre : Evaluating TROPOMI and MODIS performance to capture the dynamic of air pollution in São Paulo state: A case study during the COVID-19 outbreak Type de document : Article/Communication Auteurs : A.P. Rudke, Auteur ; J.A. Martins, Auteur ; R. Hallak, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] correction atmosphérique [Termes IGN] dioxyde d'azote [Termes IGN] épidémie [Termes IGN] image Sentinel-5P-TROPOMI [Termes IGN] image Terra-MODIS [Termes IGN] pollution atmosphérique [Termes IGN] qualité de l'air [Termes IGN] Sao Paulo Résumé : (auteur) Atmospheric pollutant data retrieved through satellite sensors are continually used to assess changes in air quality in the lower atmosphere. During the COVID-19 pandemic, several studies started to use satellite measurements to evaluate changes in air quality in many different regions worldwide. However, although satellite data is continuously validated, it is known that its accuracy may vary between monitored areas, requiring regionalized quality assessments. Thus, this study aimed to evaluate whether satellites could measure changes in the air quality of the state of São Paulo, Brazil, during the COVID-19 outbreak; and to verify the relationship between satellite-based data [Tropospheric NO2 column density and Aerosol Optical Depth (AOD)] and ground-based concentrations [NO2 and particulate material (PM; coarse: PM10 and fine: PM2.5)]. For this purpose, tropospheric NO2 obtained from the TROPOMI sensor and AOD retrieved from MODIS sensor data by using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm were compared with concentrations obtained from 50 automatic ground monitoring stations. The results showed low correlations between PM and AOD. For PM10, most stations showed correlations lower than 0.2, which were not significant. The results for PM2.5 were similar, but some stations showed good correlations for specific periods (before or during the COVID-19 outbreak). Satellite-based Tropospheric NO2 proved to be a good predictor for NO2 concentrations at ground level. Considering all stations with NO2 measurements, correlations >0.6 were observed, reaching 0.8 for specific stations and periods. In general, it was observed that regions with a more industrialized profile had the best correlations, in contrast with rural areas. In addition, it was observed about 57% reductions in tropospheric NO2 throughout the state of São Paulo during the COVID-19 outbreak. Variations in air pollutants were linked to the region economic vocation, since there were reductions in industrialized areas (at least 50% of the industrialized areas showed >20% decrease in NO2) and increases in areas with farming and livestock characteristics (about 70% of those areas showed increase in NO2). Our results demonstrate that Tropospheric NO2 column densities can serve as good predictors of NO2 concentrations at ground level. For MAIAC-AOD, a weak relationship was observed, requiring the evaluation of other possible predictors to describe the relationship with PM. Thus, it is concluded that regionalized assessment of satellite data accuracy is essential for assertive estimates on a regional/local level. Good quality information retrieved at specific polluted areas does not assure a worldwide use of remote sensor data. Numéro de notice : A2023-170 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2023.113514 Date de publication en ligne : 21/02/2023 En ligne : https://doi.org/10.1016/j.rse.2023.113514 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102930 [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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 196 (February 2023) . - pp 93 - 104 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 saisonnière Résumé : (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 [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)  

Public [article]  inGIScience and remote sensing > vol 60 n° 1 (2023) . - n° 2163070 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 Nam Résumé : (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 [article]

A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band / Xinjie Liu in Remote sensing of environment, vol 284 (January 2023)  

Public [article]  inRemote sensing of environment > vol 284 (January 2023) . - n° 113341 Titre : A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band Type de document : Article/Communication Auteurs : Xinjie Liu, Auteur ; Liangyun Liu, Auteur ; Cédric Bacour, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113341 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] canopée [Termes IGN] chlorophylle [Termes IGN] fluorescence [Termes IGN] image Sentinel-5P-TROPOMI [Termes IGN] image Terra-MODIS [Termes IGN] production primaire brute [Termes IGN] rayonnement proche infrarouge [Termes IGN] réflectance de surface [Termes IGN] réflectance végétale Résumé : (auteur) Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information than NIRvP, NIRvP can have higher data quality and spatio-temporal resolution. Therefore, the two variables can be considered complementary for GPP monitoring. Here, we propose a simple framework to combine SIF and NIRvP data from different data sources to generate an enhanced SIF product (eSIF). The original SIF data comes from the TROPOMI instrument onboard the Sentinel-5P mission, whereas NIRvP data are derived from MODIS spectral reflectance and ERA5 reanalysis data. The resulting eSIF product has a spatial resolution of 0.05° and a temporal resolution of 8 days, as well as a higher signal-to-noise ratio and a lower angular dependency than the original TROPOMI SIF data. Our results demonstrate that eSIF has similar spatial patterns to the original SIF but is more spatially continuous and less noisy. Comparisons with the FLUXCOM global GPP product show that eSIF has a more universal relationship with GPP than NIRvP for different grass/crop plant functional types (the coefficients of variation are 18.9% for slopes of GPP to eSIF and 27.3% for slopes of GPP to NIRvP), but NIRvP outperforms eSIF for tracking GPP for forest PFTs exclude BoENF. Moreover, eSIF is able to better track the seasonal variations in GPP related to environmental stresses. This study highlights that our methodology based on the combination of SIF and NIRvP is a promising approach for better monitoring of GPP. Numéro de notice : A2023-017 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113341 Date de publication en ligne : 07/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113341 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102151 [article]

Estimating 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)  

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Sea surface temperature prediction model for the Black Sea by employing time-series satellite data: a machine learning approach / Hakan Oktay Aydınlı in Applied geomatics, vol 14 n° 4 (December 2022)  

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Spatio-temporal patterns of wildfires in Siberia during 2001–2020 / Oleg Tomshin in Geocarto international, vol 37 n° 25 ([01/12/2022])  

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Modelling 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])  

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The FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation / Shuaijun Liu in Remote sensing of environment, vol 279 (September-15 2022)  

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Large-area high spatial resolution albedo retrievals from remote sensing for use in assessing the impact of wildfire soot deposition on high mountain snow and ice melt / André Bertoncini in Remote sensing of environment, vol 278 (September 2022)  

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Mapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression / Haoyu Wang in Remote sensing of environment, vol 278 (September 2022)  

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An investigation into heat storage by adopting local climate zones and nocturnal-diurnal urban heat island differences in the Tokyo Prefecture / Christopher O'Malley in Sustainable Cities and Society, vol 83 (August 2022)  

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Mainstreaming remotely sensed ecosystem functioning in ecological niche models / Adrián Regos in Remote sensing in ecology and conservation, vol 8 n° 4 (August 2022)  

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Heat wave-induced augmentation of surface urban heat islands strongly regulated by rural background / Shiqi Miao in Sustainable Cities and Society, vol 82 (July 2022)  

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