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An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis / Lei Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)
[article]
Titre : An integrated approach for detection and prediction of greening situation in a typical desert area in China and its human and climatic factors analysis Type de document : Article/Communication Auteurs : Lei Zhou, Auteur ; Siyu Wang, Auteur ; Mingyi Du, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] changement climatique
[Termes IGN] changement d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] couvert végétal
[Termes IGN] désert
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] image Landsat
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (auteur) The combined study of vegetation coverage (VC) and land use change provides important scientific guidance for the restoration and protection of arid regions. Taking Hongjian Nur (HJN) Lake in the desert region as a case study, the VC of this area was calculated using a normalized difference vegetation index (NDVI), which is based on a mixed pixel decomposition method. A grey forecasting model (GM) (1, 1) was used to predict future VC. The driving factors of VC and land use change were analyzed. The results indicate that the average VC of the whole watershed showed a gradual increase from 0.29 to 0.49 during 2000–2017. The prediction results of the GM VC showed that the greening trend is projected to continue until 2027. The area of farmland in the watershed increased significantly and its area was mainly converted from unused land, grassland, and forest. The reason for increased VC may be that the combination of the exploitation of unused land and climate change, which is contrary to the country’s sustainable development goals (SDG; goal 15). Therefore, the particularities of the local ecological environment in China’s desert area needs to be considered in the development of ecological engineering projects. Numéro de notice : A2020-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060364 Date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060364 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95163
in ISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 24 p.[article]Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])
[article]
Titre : Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India Type de document : Article/Communication Auteurs : Subrata Mondal, Auteur ; Sujit Mandal, Auteur Année de publication : 2020 Article en page(s) : pp 818 - 856 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] anthropisation
[Termes IGN] cartographie des risques
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie locale
[Termes IGN] Himalaya
[Termes IGN] lithologie
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance hydrologique
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] vulnérabilitéRésumé : (auteur) In the present study, data-driven evidential belief function model (belief function) was employed to generate landslides susceptibility index map of Darjeeling Himalaya considering 15 landslide causative factors, which grouped into six categories, i.e. geomorphological factors (elevation, aspect, slope, curvature), lithological factors (geology, soil, lineament density, distance to lineament), hydrologic factors (drainage density, distance to drainage, stream power index, topographic wetted index), triggering factor (rainfall), protective factor (normalized differential vegetation index) and anthropogenic factor (land use and land cover). Total 2079 landslide locations were mapped and randomly divided it into training datasets (70% landslide locations) and validation datasets (30% landslide locations). The resultant susceptibility map was divided into five different susceptibility zones i.e. very low, low, moderate, high and very high which covered 5.60%, 25.65%, 34.47%, 24.67% and 9.61% area respectively of the Darjeeling Himalaya. Receiver operating characteristics curve suggested that 80.20% prediction accuracy of the prepared map whereas frequency ratio plot indicated towards the ideal landslides susceptibility index map. Numéro de notice : A2020-274 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10106049.2018.1544288 Date de publication en ligne : 13/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544288 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95059
in Geocarto international > Vol 35 n° 8 [01/06/2020] . - pp 818 - 856[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)
[article]
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 IGN] achat
[Termes IGN] couvert végétal
[Termes IGN] distance
[Termes IGN] données environnementales
[Termes IGN] loisir
[Termes IGN] navigation pédestre
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] sport
[Termes IGN] température au sol
[Termes IGN] trajet (mobilité)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 Affiliation des auteurs : non IGN 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
in ISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 22 p.[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)
[article]
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 IGN] algorithme du gradient
[Termes IGN] apprentissage automatique
[Termes IGN] chaleur
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] ilot thermique urbain
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] Londres
[Termes IGN] modèle de régression
[Termes IGN] mortalité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] politique publique
[Termes IGN] Python (langage de programmation)
[Termes IGN] régression linéaire
[Termes IGN] santé
[Termes IGN] station météorologique
[Termes IGN] température au sol
[Termes IGN] température de l'air
[Termes IGN] zone urbaineRésumé : (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 Affiliation des auteurs : non IGN 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
in International journal of applied Earth observation and geoinformation > vol 88 (June 2020) . - 10 p.[article]Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science, Vol 77 n° 2 (June 2020)
[article]
Titre : Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Giannetti, Auteur ; Erica Mazza, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] brûlis
[Termes IGN] canopée
[Termes IGN] coupe rase (sylviculture)
[Termes IGN] dégradation du signal
[Termes IGN] forêt méditerranéenne
[Termes IGN] image Landsat
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] reconstruction du signal
[Termes IGN] régénération (sylviculture)
[Termes IGN] série temporelle
[Termes IGN] taillis
[Termes IGN] télémètre laser aéroportéRésumé : (auteur) Key message: This work analyses the rate of recovery of the spectral signal from clearcut areas of coppice Mediterranean forests using Landsat Time Series (LTS). The analysis revealed a more rapid rate of spectral signal recovery than what was found in previous investigations in boreal and temperate forests. Context: The rate of post-disturbance vegetation recovery is an important component of forest dynamics. Aims: In this study, we analyze the recovery of the spectral signal from forest clearcut areas in Mediterranean conditions when the coppice system of forest management is applied. Methods:
We used LTS surface reflectance data (1999–2015). We generated an annual reference database of clearcuts using visual interpretation and local forest inventory data, and then derived the Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) spectral trajectories for these clearcuts. From these spectral trajectories, we calculated the Years to Recovery or Y2R, the number of years it takes for a pixel to return to within a specified threshold (i.e., 70%, 80%, 90%, 100%) of its pre-disturbance value. Spectral recovery rates were then corroborated using measures of canopy height derived from airborne laser scanning (ALS) data. Results: The coppice system is associated with rapid recovery rates when compared to rates of recovery from seeds or seedlings in temperate and boreal forest conditions. We found that the Y2R derived from the spectral trajectories of post-clearcut NBR and NDVI provided similar characterizations of rapid recovery for the coppice system of forest management applied in our study area. The ALS measures of canopy height indicated that the Y2R metric accurately captured the rapid regeneration of coppice systems. Conclusion: The rapid rate of spectral recovery associated with the coppice system is 2–4 years, which contrasts with values reported in boreal and temperate forest environments, where spectral recovery was attained in approximately 10 years. NBR is an effective index for assessing rapid recovery in this forest system.Numéro de notice : A2020-293 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00936-2 Date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1007/s13595-020-00936-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95123
in Annals of Forest Science > Vol 77 n° 2 (June 2020)[article]Object-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery / Zhenhui Sun in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkThe geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors / Mi Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)PermalinkUnder-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkWheat leaf area index retrieval using RISAT-1 hybrid polarized SAR data / Thota Sivasankar in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkYear-to-year crown condition poorly contributes to ring width variations of beech trees in French ICP level I network / Clara Tallieu in Forest ecology and management, Vol 465 (1st June 2020)PermalinkAssessment 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])PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkModeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkAbove-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)Permalink