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Extraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])  

Public [article]  inGeocarto international > vol 35 n° 10 [01/08/2020] . - pp 1049 - 1066 Titre : Extraction of urban built-up areas from nighttime lights using artificial neural network Type de document : Article/Communication Auteurs : Tingting Xu, Auteur ; Giovanni Coco, Auteur ; Jay Gao, Auteur Année de publication : 2020 Article en page(s) : pp 1049 - 1066 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] aménagement du territoire [Termes descripteurs IGN] bati [Termes descripteurs IGN] cartographie urbaine [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] développement durable [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] éclairage public [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] rayonnement lumineux [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] zone urbaine Résumé : (auteur) The spatial distribution of urban areas at the national and regional scales is critical for urban planners and governments to design sustainable and environment-friendly future development plans. The nighttime lights (NTL) data provide an effective way to monitor the urban at different scales however is usually achieved by using empirical threshold-based algorithms. This study proposed a novel Artificial Neural Network (ANN) approach, using moderate resolution imageries as NTL, MODIS NDVI and land surface temperature data, to map urban areas. Both random and maximum dissimilarity distance algorithm sampling methods were considered and compared. The validation of the urban areas extracted from MDA-based ANN against the 2011 US national land cover data showed a reasonable quality (overall accuracy = 97.84; Kappa = 0.74) and achieved more accurate result than the threshold method. This study demonstrates that ANN can provide an effective, rapid, and accurate alternative in extracting urban built-up areas from NTL. Numéro de notice : A2020-424 Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1559887 date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2018.1559887 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95488 [article]

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)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 22 p. Titre : Developing shopping and dining walking indices using POIs and remote sensing data Type de document : Article/Communication Auteurs : Yingbin Deng, Auteur ; Yingwei Yan, Auteur ; Yichun Xie, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 22 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] achat [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] distance [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] loisir [Termes descripteurs IGN] navigation pédestre [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] point d'intérêt [Termes descripteurs IGN] sport [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] trajet Résumé : (auteur) Walking is one of the most commonly promoted traveling methods and is garnering increasing attention. Many indices/scores have been developed by scholars to measure the walkability in a local community. However, most existing walking indices/scores involve urban planning-oriented, local service-oriented, regional accessibility-oriented, and physical activity-oriented walkability assessments. Since shopping and dining are two major leisure activities in our daily lives, more attention should be given to the shopping or dining-oriented walking environment. Therefore, we developed two additional walking indices that focus on shopping or dining. The point of interest (POI), vegetation coverage, water coverage, distance to bus/subway station, and land surface temperature were employed to construct walking indices based on 50-meter street segments. Then, walking index values were categorized into seven recommendation levels. The field verification illustrates that the proposed walking indices can accurately represent the walking environment for shopping and dining. The results in this study could provide references for citizens seeking to engage in activities of shopping and dining with a good walking environment. Numéro de notice : A2020-310 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060366 date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060366 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95157 [article]

Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 88 (June 2020) . - 10 p. Titre : Estimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data Type de document : Article/Communication Auteurs : Rochelle Schneider dos Santos, Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme du gradient [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] chaleur [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] Londres [Termes descripteurs IGN] modèle de régression [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] politique publique [Termes descripteurs IGN] Python (langage de programmation) [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] santé [Termes descripteurs IGN] station météorologique [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] température de l'air [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Urbanisation generates greater population densities and an increase in anthropogenic heat generation. These factors elevate the urban–rural air temperature (Ta) difference, thus generating the Urban Heat Island (UHI) phenomenon. Ta is used in the fields of public health and epidemiology to quantify deaths attributable to heat in cities around the world: the presence of UHI can exacerbate exposure to high temperatures during summer periods, thereby increasing the risk of heat-related mortality. Measuring and monitoring the spatial patterns of Ta in urban contexts is challenging due to the lack of a good network of weather stations. This study aims to produce a parsimonious model to retrieve maximum Ta (Tmax) at high spatio-temporal resolution using Earth Observation (EO) satellite data. The novelty of this work is twofold: (i) it will produce daily estimations of Tmax for London at 1 km2 during the summertime between 2006 and 2017 using advanced statistical techniques and satellite-derived predictors, and (ii) it will investigate for the first time the predictive power of the gradient boosting algorithm to estimate Tmax for an urban area. In this work, 6 regression models were calibrated with 6 satellite products, 3 geospatial features, and 29 meteorological stations. Stepwise linear regression was applied to create 9 groups of predictors, which were trained and tested on each regression method. This study demonstrates the potential of machine learning algorithms to predict Tmax: the gradient boosting model with a group of five predictors (land surface temperature, Julian day, normalised difference vegetation index, digital elevation model, solar zenith angle) was the regression model with the best performance (R² = 0.68, MAE = 1.60 °C, and RMSE = 2.03 °C). This methodological approach is capable of being replicated in other UK cities, benefiting national heat-related mortality assessments since the data (provided by NASA and the UK Met Office) and programming languages (Python) sources are free and open. This study provides a framework to produce a high spatio-temporal resolution of Tmax, assisting public health researchers to improve the estimation of mortality attributable to high temperatures. In addition, the research contributes to practice and policy-making by enhancing the understanding of the locations where mortality rates may increase due to heat. Therefore, it enables a more informed decision-making process towards the prioritisation of actions to mitigate heat-related mortality amongst the vulnerable population. Numéro de notice : A2020-448 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2020.102066 date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102066 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95524 [article]

Assessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using landsat-8 data / Divyesh Varade in Geocarto international, vol 35 n° 6 ([01/05/2020])  

Public [article]  inGeocarto international > vol 35 n° 6 [01/05/2020] . - pp 641 - 662 Titre : Assessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using landsat-8 data Type de document : Article/Communication Auteurs : Divyesh Varade, Auteur ; Onkar Dikshit, Auteur Année de publication : 2020 Article en page(s) : pp 641 - 662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] emissivité [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] hiver [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image Sentinel-3 [Termes descripteurs IGN] Inde [Termes descripteurs IGN] manteau neigeux [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] précision de détermination de surface [Termes descripteurs IGN] seuillage [Termes descripteurs IGN] température au sol Résumé : (auteur) In this study, we propose a modified thresholds method for the determination of land surface emissivity (LSE) for snow covered mountainous areas. The conventional Normalized Differenced Vegetation Index (NDVI) thresholds method (NDVITHM) does not discriminate the snow covered pixels with soil pixels in assigning the LSE based on NDVI thresholds. In the proposed approach, we incorporate different thresholding rules based on the Normalized Differenced Snow Index and the S3 index for incorporating separability in the LSE for the snow covered pixels. The LSE thus derived is used to determine the land surface temperature using the Single Channel Method. The approach was evaluated for a study area around the Kullu Valley in the lower Indian Himalayas for a dataset of the winter season of Landsat-8 multispectral data. The observed coefficient of determination values indicated that the proposed method yielded better results with respect to the conventional NDVITHM approach. Numéro de notice : A2020-203 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520928 date de publication en ligne : 26/12/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520928 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94878 [article]

Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 4 (April 2020) . - pp 225 - 233 Titre : Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Ainong Li, Auteur ; Zhengjian Zhang, Auteur ; Guangbin Lei, Auteur Année de publication : 2020 Article en page(s) : pp 225 - 233 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] corrélation d'images [Termes descripteurs IGN] GRASS [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] plateau [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] Tibet Résumé : (Auteur) Time series of leaf area index (LAI) products are now widely used, and the temporal validation is the prerequisite for their proper application. However, a systematical comparison between different products using both direct and indirect methods is still lacking. The objective of this paper is to assess and compare the temporal performances of four LAI products: Moderate Resolution Imaging Spectroradiometer (MODIS) LAI (MOD)15A2, MOD15A2h, Geoland2 Version 1 (GEOV1), and Global Land Surface Satellite (GLASS). The study area, which is dominated by grasslands, is located in the northeastern Tibetan Plateau (TP), and temperature is the main stress factor affecting grass growth. Both a correlation analysis with temperature and a direct comparison with temporally continuous LAI reference maps were implemented in our temporal validation experiments. The results show that no single product can capture the rapid change and the seasonal trend in LAI simultaneously, and the compositing period used in each product determines the quality of the corresponding LAI time series. The MOD15A2 and MOD15A2h products, which have short compositing windows (eight days), are suitable for detecting rapid change. A grazing-induced biomass decrease that occurred around day of year 205 in 2014 in our study area was clearly revealed in these two products. For the GEOV1 and GLASS products, which have compositing windows of 30 days and 1 year, respectively, the grazing date was shifted (GEOV1) or even invisible (GLASS). However, products with prolonged compositing windows may be more robust to observation noise, and the resulting products may be suitable for capturing the seasonal trend. This study highlights that the concurrent use of data from various sensors onboard different satellites, and the introduction of new generations of satellites (e.g., Gaofen-6), are two promising ways to further improve existing LAI time series. Numéro de notice : A2020-129 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.4.225 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.14358/PERS.86.4.225 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94804 [article]

Thermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis / Jiong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

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Forest gaps retard carbon and nutrient release from twig litter in alpine forest ecosystems / Bo Tan in European Journal of Forest Research, vol 139 n° 1 (February 2020)  

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MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n°1 (2020)  

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Object‐oriented tracking of thematic and spatial behaviors of urban heat islands / Rui Zhu in Transactions in GIS, Vol 24 n° 1 (February 2020)  

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Quantification of the adjacency effect on measurements in the thermal infrared region / Xiaopo Zheng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)  

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Multitemporal Landsat-MODIS fusion for cropland drought monitoring in El Salvador / Nguyen-Thanh Son in Geocarto international, vol 34 n° 12 ([15/09/2019])  

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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, sans n° (2019)  

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Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data : A case study of Wuhan, Central China / Xin Huang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)  

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Site and age-dependent responses of Picea abies growth to climate variability / Petr Čermák in European Journal of Forest Research, vol 138 n° 3 (June 2019)  

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Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data / Abdelhakim Amazirh in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

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