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Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 177 (July 2021) . - pp 174 - 193 Titre : Detecting high-temperature anomalies from Sentinel-2 MSI images Type de document : Article/Communication Auteurs : Yongxue Liu, Auteur ; Zhi Weifeng, Auteur ; Bihua Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 174 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] anomalie thermique [Termes IGN] éruption volcanique [Termes IGN] image aérienne [Termes IGN] image Landsat-OLI [Termes IGN] image proche infrarouge [Termes IGN] image Sentinel-MSI [Termes IGN] image thermique [Termes IGN] incendie [Termes IGN] réflectance spectrale [Termes IGN] risque technologique [Termes IGN] série temporelle [Termes IGN] température au sol Résumé : (Auteur) High-temperature anomalies (HTAs) of the earth's surface, such as fires, volcanic activities, and industrial heat sources, have a profound impact on Earth's system. Sentinel-2 Multispectral Instrument (MSI) provides spatially-specific information for precisely measuring the location and extent of HTAs at a fine scale. However, detecting HTAs from MSI images remains challenging because the emitted radiance of an HTA in the short-wave infrared (SWIR) bands can be easily mixed with the reflected solar radiance background in the daytime; and an increasing number of atypical cases in MSI images need to be treated with the enhanced spatial resolution. A generic HTA detection approach that handles both anthropogenic and natural HTAs will broaden the scope of MSI applications. In this study, (i) we highlight two spectral characteristics of HTAs in the far-SWIR, near-SWIR, and NIR bands (i.e., (ρfar-SWIR - ρnear-SWIR)/ρNIR ≥ 0.45 and (ρfar-SWIR -ρnear-SWIR) ≥ ρnear-SWIR - ρNIR) that can effectively enhance HTAs from background geo-features, based on the reflectance spectra in airborne imaging spectrometer data. (ii) We propose a tri-spectral thermal anomaly index (TAI) that jointly uses the two high-temperature-sensitive SWIR bands and the high-temperature-insensitive NIR band to enhance HTAs, based on the above characteristics and a comprehensive sampling of different types of HTAs from 1,974 MSI images. (iii) We develop a TAI-based approach for MSI images to detect HTAs in general. The proposed approach was applied to detect different types of HTAs, including different biomass burnings, active volcanoes, and industrial HTAs, over a wide range of land-cover scenarios. Validations and comparisons demonstrate the proposed approach is reliable and performs better than the existing state-of-the-art HTA detection approaches. Evaluations on two types of small industrial HTAs, including operating kilns and enclosed landfill gas flares, show that the HTA detection probability of the TAI-based approach from time-series MSI images is ~ 84.91% and 88.23%, respectively. Further investigations show that the TAI-based approach also has good transferability in detecting HTAs from multispectral images acquired by Landsat-family satellites. Numéro de notice : A2021-372 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.05.008 date de publication en ligne : 23/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.05.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97808 [article]

The 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)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 6 (June 2021) . - n° 416 Titre : The use of land cover indices for rapid surface urban heat island detection from multi-temporal Landsat imageries Type de document : Article/Communication Auteurs : Nagihan Aslan, Auteur ; Dilek Koc-San, Auteur Année de publication : 2021 Article en page(s) : n° 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] ilot thermique urbain [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] image proche infrarouge [Termes IGN] Normalized Difference Built-up Index [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Normalized Difference Water Index [Termes IGN] occupation du sol [Termes IGN] Soil Adjusted Vegetation Index [Termes IGN] température au sol [Termes IGN] Turquie [Termes IGN] utilisation du sol Résumé : (auteur) The aims of this study were to determine surface urban heat island (SUHI) effects and to analyze the land use/land cover (LULC) and land surface temperature (LST) changes for 11 time periods from the years 2002 to 2020 using Landsat time series images. Bursa, which is the fourth largest metropolitan city in Turkey, was selected as the study area, and Landsat multi-temporal images of the summer season were used. Firstly, the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI) and index-based built-up index (IBI) were created using the bands of Landsat images, and LULC classes were determined by applying automatic thresholding. The LST values were calculated using thermal images and SUHI effects were determined. The results show that NDVI, SAVI, MNDWI and IBI indices can be used effectively for the determination of the urban, vegetation and water LULC classes for SUHI studies, with overall classification accuracies between 89.60% and 95.90% for the used images. According to the obtained results, generally the LST values increased for almost all land cover areas between the years 2002 and 2020. The SUHI magnitudes were computed by using two methods, and it was found that there was an important increase in the 18-year time period. Numéro de notice : A2021-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.3390/ijgi10060416 date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.3390/ijgi10060416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97936 [article]

Validation 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)  

Public [article]  inRemote sensing of environment > vol 257 (May 2021) . - n° 112344 Titre : Validation and analysis of Terra and Aqua MODIS, and SNPP VIIRS vegetation indices under zero vegetation conditions: A case study using Railroad Valley Playa Type de document : Article/Communication Auteurs : Tomoaki Miura, Auteur ; Charlotte Z. Smith, Auteur ; Hiroki Yoshioka, Auteur Année de publication : 2021 Article en page(s) : n° 112344 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Enhanced vegetation index [Termes IGN] image Aqua-MODIS [Termes IGN] image proche infrarouge [Termes IGN] image Terra-MODIS [Termes IGN] indice de végétation [Termes IGN] Nevada (Etats-Unis) [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] réflectance du sol Résumé : (auteur) Spectral vegetation index (VI) time series data from coarse resolution satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), have been utilized in studying vegetation dynamics. Numerous studies have evaluated how well VI products capture variations in vegetation biophysical or physiological conditions. Equally important is to evaluate VI products over “zero vegetation” surfaces consisting of soils, litters, and/or rocks, as they define the lower bound for vegetation detection. VIs, however, vary over zero vegetation surfaces as a function of soil moisture content and surface roughness. In this study, we evaluated the behavior of VIs from Terra MODIS (T-MODIS), Aqua MODIS (A-MODIS), and Suomi-National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (S-VIIRS) at Railroad Valley Playa, Nevada for a period from April 2013 to September 2019. The playa is a dried lakebed devoid of vegetation throughout the year. Long-term in situ reflectance measurements acquired over the 1 km-by−1 km Radiometric Calibration Test Site (RadCaTS) located on the playa were obtained from the Radiometric Calibration Network (RadCalNet) portal and used as a reference. Three VIs were analyzed, including the normalized difference VI (NDVI), enhanced VI (EVI), and two-band EVI (EVI2). RadCaTS NDVI, EVI, and EVI2 of the playa surface increased and decreased occasionally for the time period examined in this study, and the satellite NDVIs, EVIs, and EVI2s had comparable temporal signatures to the RadCaTS counterparts. T-MODIS and A-MODIS NDVI and EVI2 values were comparable to the RadCaTS counterparts, whereas T-MODIS and A-MODIS EVI values were lower than the RadCaTS counterparts by ~0.006 and ~ 0.01 EVI units, respectively. All the three VIs of S-VIIRS were consistently higher than their RadCaTS counterparts by ~0.008 VI units, due to the higher near-infrared (NIR) reflectances of S-VIIRS than the RadCaTS NIR reflectance. The red and NIR, and red and blue reflectances each formed linear relationships (i.e., soil lines) for each of the three sensors. Variations in reflectance due to surface conditions and observation geometries all appeared as variations along these soil lines. The satellite red-NIR soil lines were comparable to the RadCaTS counterparts, whereas the satellite red-blue soil lines had steeper slopes than the RadCaTS counterparts due to a negative bias in the satellite blue reflectances. This translated into the T-MODIS and A-MODIS EVI behaviors different from those depicted by RadCaTS EVI, and the satellite NDVI and EVI2 behaving more comparably with the RadCaTS counterparts and across the three sensors than the satellite EVI. Numéro de notice : A2021-277 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112344 date de publication en ligne : 19/02/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112344 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97370 [article]

Estimation of some stand parameters from textural features from WorldView-2 satellite image using the artificial neural network and multiple regression methods: a case study from Turkey / Alkan Günlü in Geocarto international, vol 36 n° 8 ([15/04/2021])  

Public [article]  inGeocarto international > vol 36 n° 8 [15/04/2021] . - pp 918 - 935 Titre : Estimation of some stand parameters from textural features from WorldView-2 satellite image using the artificial neural network and multiple regression methods: a case study from Turkey Type de document : Article/Communication Auteurs : Alkan Günlü, Auteur ; İlker Ercanlı, Auteur ; Muammer Şenyurt, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 918 - 935 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] classification par Perceptron multicouche [Termes IGN] échantillonnage [Termes IGN] fonction de base radiale [Termes IGN] gestion forestière [Termes IGN] image proche infrarouge [Termes IGN] image Worldview [Termes IGN] matrice de co-occurrence [Termes IGN] peuplement forestier [Termes IGN] Pinus nigra [Termes IGN] régression multiple [Termes IGN] réseau neuronal artificiel [Termes IGN] texture d'image [Termes IGN] Turquie Résumé : (auteur) The aim of this research is to assess some stand parameters such as stand volume (SV), basal area (BA), number of trees (NT) and aboveground biomass (AGB) of pure Crimean pine forest stands in Turkey by using ground measurements and remote sensing techniques. For this purpose, 86 sample plots were collected from pure Crimean pine stands of Yenice Forest Management Planning Unit in Ilgaz Forest Management Enterprise, Turkey. The stand parameters of each sample area were estimated using the data obtained from the sample plots. Subsequently, we calculated the values of contrast (CON), correlation (COR), dissimilarity (DIS), entropy (ENT), homogeneity (HOM), mean (M), second moment (SM) and variance (VAR) from WorldView-2 imagery using a grey-level co-occurrence matrix method. Eight textural features and twelve different window sizes ranging from 3 × 3 to 25 × 25 were generated from blue, green, red and near-infrared bands of the WorldView-2 satellite image. For predicting the relationships between WorldView-2 textural features and stand parameters of each sample plot, regression models were developed by using multiple linear regression (MLR) analysis. Additionally, artificial neural networks (ANNs) based on the multilayer perceptron (MLP) and the radial basis function (RBF) architectures were trained by comparing various numbers of neurons and activation functions in their network types. The results showed that the MLR models had low the coefficient of determination (R2) values (0.32 for SV, 0.35 for BA, 0.33 for NT and 0.34 for AGB), and the most of the ANNs models (MLP and RBF) were better than the regression models for estimating stand parameters. The ANNs model containing MLP and RBF for SV (R2 = 0.40; R2 = 0.56), for BA (R2 = 0.34; R2 = 0.51), for NT (R2 = 0.34; R2 = 0.37) and for AGB (R2 = 0.34, R2 = 0.57) were found the best results, respectively. Our results revealed that the ANNs models developed with WorldView-2 satellite image were beneficial to estimate stand parameters better than the MLR model in pure Crimean pine stands. Numéro de notice : A2021-484 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1629644 date de publication en ligne : 25/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1629644 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97443 [article]

Shoreline changes along Northern Ibaraki Coast after the great East Japan earthquake of 2011 / Quang Nguyen Hao in Remote sensing, vol 13 n° 7 (April 2021)  

Public [article]  inRemote sensing > vol 13 n° 7 (April 2021) . - n° 1399 Titre : Shoreline changes along Northern Ibaraki Coast after the great East Japan earthquake of 2011 Type de document : Article/Communication Auteurs : Quang Nguyen Hao, Auteur ; Satoshi Takewaka, Auteur Année de publication : 2021 Article en page(s) : n° 1399 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] détection de changement [Termes IGN] effondrement de terrain [Termes IGN] image ALOS-AVNIR2 [Termes IGN] image proche infrarouge [Termes IGN] image Sentinel-MSI [Termes IGN] image Terra-ASTER [Termes IGN] Japon [Termes IGN] Normalized Difference Water Index [Termes IGN] séisme [Termes IGN] surveillance du littoral [Termes IGN] trait de côte Résumé : (auteur) In this study, we analyze the influence of the Great East Japan Earthquake, which occurred on 11 March 2011, on the shoreline of the northern Ibaraki Coast. After the earthquake, the area experienced subsidence of approximately 0.4 m. Shoreline changes at eight sandy beaches along the coast are estimated using various satellite images, including the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), ALOS AVNIR-2 (Advanced Land Observing Satellite, Advanced Visible and Near-infrared Radiometer type 2), and Sentinel-2 (a multispectral sensor). Before the earthquake (for the period March 2001–January 2011), even though fluctuations in the shoreline position were observed, shorelines were quite stable, with the averaged change rates in the range of ±1.5 m/year. The shoreline suddenly retreated due to the earthquake by 20–40 m. Generally, the amount of retreat shows a strong correlation with the amount of land subsidence caused by the earthquake, and a moderate correlation with tsunami run-up height. The ground started to uplift gradually after the sudden subsidence, and shoreline positions advanced accordingly. The recovery speed of the beaches varied from +2.6 m/year to +6.6 m/year, depending on the beach conditions. Numéro de notice : A2021-351 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13071399 date de publication en ligne : 05/04/2021 En ligne : https://doi.org/10.3390/rs13071399 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97601 [article]

Bretagne, la végétation cartographiée / Marielle Mayo in Géomètre, n° 2185 (novembre 2020)

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Mapping tree species deciduousness of tropical dry forests combining reflectance, spectral unmixing, and texture data from high-resolution imagery / Astrid Helena Huechacona-Ruiz in Forests, vol 11 n°11 (November 2020)  

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VNIR-SWIR superspectral mineral mapping: An example from Cuprite, Nevada / Kathleen E. Johnson in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 11 (November 2020)  

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Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed / Qinghu Jiang in Remote sensing, vol 12 n° 18 (September-2 2020)  

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Physical, chemical and mechanical wood properties of Pinus nigra growing in Portugal / Alexandra Dias in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

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Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping / Alvin B. Baloloy in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

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Shrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)  

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A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

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Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 2 ([01/02/2020])  

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Red-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)  

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