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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)  

Public [article]  inSustainable Cities and Society > vol 83 (August 2022) . - n° 103959 Titre : An investigation into heat storage by adopting local climate zones and nocturnal-diurnal urban heat island differences in the Tokyo Prefecture Type de document : Article/Communication Auteurs : Christopher O'Malley, Auteur ; Hideki Kikumoto, Auteur Année de publication : 2022 Article en page(s) : n° 103959 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie thématique [Termes IGN] climat local [Termes IGN] distribution spatiale [Termes IGN] ilot thermique urbain [Termes IGN] image Landsat-8 [Termes IGN] image Terra-MODIS [Termes IGN] nuit [Termes IGN] pente [Termes IGN] stockage [Termes IGN] température au sol [Termes IGN] Tokyo (Japon) [Termes IGN] variation diurne Résumé : (auteur) This study aims to identify urban forms that are prone to heat storage in the Tokyo Prefecture in Japan. First, local climate zones (LCZ) were identified with 100 m pixel resolution using Landsat 8 data. LCZs include urban forms that are predominantly defined by building compactness and height. The spatial distribution of urban heat island intensity was obtained using LCZs and MODIS 100 m resolution land surface temperatures from 2013 to 2021. The difference between diurnal and nocturnal heat island intensity (∆UHI) was evaluated as an indicator of the relative heat storage effect between the LCZs. Lower ∆UHIs suggest increased relative heat-storage capacities. Seasonal average ∆UHIs for compact and super high-rise, high-rise, mid-rise, and low-rise LCZs were 3.1 °C, 4.1 °C, 5.8 °C, and 8.3 °C, respectively. Additionally, ∆UHIs for open and super high-rise, high-rise, and mid-rise LCZs were 5.8 °C, 6.4 °C, and 7.8 °C, respectively. Slope data also validated the LCZ height. LCZ and slope analyzes found lower ∆UHI magnitudes in all LCZs with high-rise buildings. Also, compact LCZs had lower ∆UHI magnitudes than open LCZs at corresponding heights. Therefore, higher-rise and compact LCZs are suggested to have larger relative heat storage effects than lower-rise and open LCZs. Numéro de notice : A2022-486 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2022.103959 Date de publication en ligne : 19/05/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103959 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100951 [article]

About tree height measurement: Theoretical and practical issues for uncertainty quantification and mapping / Samuele De petris in Forests, vol 13 n° 7 (July 2022)  

Public [article]  inForests > vol 13 n° 7 (July 2022) . - n°969 Titre : About tree height measurement: Theoretical and practical issues for uncertainty quantification and mapping Type de document : Article/Communication Auteurs : Samuele De petris, Auteur ; Philippo Sarvia, Auteur ; Enrico Borgogno Mondino, Auteur Année de publication : 2022 Article en page(s) : n°969 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de sensibilité [Termes IGN] biome [Termes IGN] carte forestière [Termes IGN] Google Earth Engine [Termes IGN] hauteur des arbres [Termes IGN] incertitude de mesurage [Termes IGN] modèle de simulation [Termes IGN] pente [Termes IGN] statistiques [Termes IGN] variance [Vedettes matières IGN] Foresterie Résumé : (auteur) Forest height is a fundamental parameter in forestry. Tree height is widely used to assess a site’s productivity both in forest ecology research and forest management. Thus, a precise height measure represents a necessary step for the estimation of carbon storage at the local, national, and global scales. In this context, error in height measurement necessarily affects the accuracy of related estimates. Ordinarily, forest height is surveyed by ground sampling adopting hypsometers. The latter suffers from many errors mainly related to the correct tree apex identification (not always well visible in dense stands) and to the measurement process itself. In this work, a statistically based operative method for estimating height measurement uncertainty (σH) was proposed using the variance propagation law. Some simulations were performed involving several combinations of terrain slope, tree height, and survey distances by modelling the σH behaviour and its sensitivity to such parameters. Results proved that σH could vary between 0.5 m and up to 20 m (worst case). Sensitivity analysis shows that terrain slopes and distance poorly affect σH, while angles are the main drivers of height uncertainty. Finally, to give a practical example of such deductions, tree height uncertainty was mapped at the global scale using Google Earth Engine and summarized per forest biomes. Results proved that tropical biomes have higher uncertainty (from 1 m to 4 m) while shrublands and tundra have the lowest (under 1 m). Numéro de notice : A2022-546 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f13070969 Date de publication en ligne : 22/06/2022 En ligne : https://doi.org/10.3390/f13070969 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101131 [article]

Using vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 2 (February 2022) . - pp 382 - 404 Titre : Using vertices of a triangular irregular network to calculate slope and aspect Type de document : Article/Communication Auteurs : Guanghui Hu, Auteur ; Chun Wang, Auteur ; Sijin Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 382 - 404 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] bassin hydrographique [Termes IGN] géomorphologie [Termes IGN] grille [Termes IGN] loess [Termes IGN] maillage [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle numérique de surface [Termes IGN] noeud [Termes IGN] pente [Termes IGN] point d'appui [Termes IGN] Triangulated Irregular Network Résumé : (auteur) Terrain derivative calculations from triangulated irregular network (TIN)-based digital elevation models (DEMs) have been extensively explored in geomorphometry. However, most calculation methods focus on the triangulation facets of TIN-based DEMs and ignore the vertices. In fact, these vertices are the original sampling points from the terrain surface and serve as the basis for triangulation. In this study, we argue that terrain derivative calculations using TIN-based DEMs should focus on the vertices. Employing examples with slope and aspect, we applied the TIN vertex-based method to a mathematical surface and a real topography using TIN-based DEMs with a range of sampling point densities. We performed a comparative analysis of the TIN vertex-based, TIN facet-based, and grid-based methods. Assessments on the mathematical surface showed that the TIN vertex-based method achieved the highest accuracy among the three methods. Error analysis for the real landform case indicated that the TIN vertex-based method performed slightly better than the grid-based method for slope calculation and slightly worse than the grid-based method for aspect calculation. Among the three methods, the TIN facet-based method was most sensitive to error. The TIN vertex-based method can provide a reference for the slope and aspect calculation based on point clouds. Numéro de notice : A2022-165 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1933493 Date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.1080/13658816.2021.1933493 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99788 [article]

Forest fire susceptibility assessment using google earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 n° 1 (2022) . - pp 432 - 450 Titre : Forest fire susceptibility assessment using google earth engine in Gangwon-do, Republic of Korea Type de document : Article/Communication Auteurs : Yong Piao, Auteur ; Dongkun Lee, Auteur ; Sangjin Park, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 432 - 450 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aléa [Termes IGN] cartographie des risques [Termes IGN] classification et arbre de régression [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] Corée du sud [Termes IGN] Google Earth Engine [Termes IGN] incendie de forêt [Termes IGN] pente [Termes IGN] risque naturel [Termes IGN] vulnérabilité Résumé : (auteur) Forest fires are one of the most frequently occurring natural hazards, causing substantial economic loss and destruction of forest cover. As the Gangwon-do region in Korea has abundant forest resources and ecological diversity as Korea's largest forest area, spatial data on forest fire susceptibility of the region are urgently required. In this study, a forest fire susceptibility map (FFSM) of Gangwon-do was constructed using Google Earth Engine (GEE) and three machine learning algorithms: Classification and Regression Trees (CART), Random Forest (RF), and Boosted Regression Trees (BRT). The factors related to climate, topography, hydrology, and human activity were constructed. To verify the accuracy, the area under the receiver operating characteristic curve (AUC) was used. The AUC values were 0.846 (BRT), 0.835 (RF), 0.751 (CART). Factor importance analysis was performed to identify the important factors of the occurrence of forest fires in Gangwon-do. The results show that the most important factor in the Gangwon-do region is slope. A slope of approximately 17° (moderately steep) has a considerable impact on the occurrence of forest fires. Human activity and interference are the other important factors that affect forest fires. The established FFSM can support future efforts on forest resource protection and environmental management planning in Gangwon-do. Numéro de notice : A2022-445 Affiliation des auteurs : non IGN Nature : Article DOI : 10.1080/19475705.2022.2030808 Date de publication en ligne : 02/02/2022 En ligne : https://doi.org/10.1080/19475705.2022.2030808 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99942 [article]

A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping / Khalil Valizadeh Kamran in Applied geomatics, vol 13 n° 4 (December 2021)  

Public [article]  inApplied geomatics > vol 13 n° 4 (December 2021) . - pp 837 - 851 Titre : A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping Type de document : Article/Communication Auteurs : Khalil Valizadeh Kamran, Auteur ; Bakhtiar Feizizadeh, Auteur ; Behnam Khorrami, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 837 - 851 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] apprentissage automatique [Termes IGN] cartographie des risques [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] effondrement de terrain [Termes IGN] fonction de base radiale [Termes IGN] Iran [Termes IGN] méthode fondée sur le noyau [Termes IGN] occupation du sol [Termes IGN] pente [Termes IGN] risque naturel [Termes IGN] système d'information géographique [Termes IGN] utilisation du sol Résumé : (auteur) Landslides are among the most destructive natural hazards with severe socio-economic ramifications all around the world. Understanding the critical combination of geoenvironmental factors involved in the occurrence of landslides can mitigate the adverse impacts ascribed to them. Among the several scenarios for studying and investigating this phenomenon, landslide susceptibility mapping (LSM) is the most prominent method. Applying the machine learning (ML) algorithms integrated with the geographic information systems (GIS) has become a trending means for accurate and rapid landslide mapping practices in the scientific community. Support vector machine (SVM) has been the most commonly applied ML algorithm for LSM in recent years. The current study aims to implement different SVM kernel functions including polynomial kernel function (PKF) (degree 1 to 5), radial basis function (RBF), sigmoid, and linear kernels, for a GIS-based LSM over the Tabriz Basin (TB). To this end, a total number of 9 conditioning parameters being involved in the occurrence of the landslide events were determined and utilized. The LSM maps of the TB were generated based on the different SVM kernels and were statistically validated according to the landslide inventory. The findings revealed that the polynomial-degree-2 (PKF-2) model (AUC = 0.9688) outperforms the rest of the utilized kernels. According to the SLM map generated through PKF-2, the northernmost parts of the TB are extremely susceptible to slope failures than the rest; therefore, the developmental policies over these parts have to be taken into account with privileged priority to hinder any humanitarian as well as environmental catastrophes. Numéro de notice : A2021-858 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s12518-021-00393-0 Date de publication en ligne : 28/08/2021 En ligne : https://doi.org/10.1007/s12518-021-00393-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99066 [article]

OBIA-based extraction of artificial terrace damages in the Loess plateau of China from UAV photogrammetry / Xuan Fang in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)  

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Quantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, vol 36 n° 15 ([15/08/2021])  

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An adaptive filtering algorithm of multilevel resolution point cloud / Youyuan Li in Survey review, Vol 53 n° 379 (July 2021)  

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Evaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications / Benjamin Misiuk in Marine geodesy, vol 44 n° 4 (July 2021)  

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Progressive TIN densification with connection analysis for urban Lidar data / Tao Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)  

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Slope engineering / Ali Ismet Kanlı (2021)  

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Soil erosion assessment using RUSLE model and its validation by FR probability model / Amiya Gayen in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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Assessment of landslide susceptibility at a local spatial scale applying the multi-criteria analysis and GIS: a case study from Slovakia / Jana Vojteková in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)  

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Evaluation of crop mapping on fragmented and complex slope farmlands through random forest and object-oriented analysis using unmanned aerial vehicles / Re-Yang Lee in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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Modeling soil erosion after mechanized logging operations on steep terrain in the Northern Black Forest, Germany / Julian Haas in European Journal of Forest Research, vol 139 n°4 (August 2020)  

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