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DK Eyewitness Travel Guide: Belgium & Luxembourg will lead you straight to the best attractions these countries have to offer. Packed with photographs, illustrations, and maps of Belgium and Luxembourg, the guide includes in-depth coverage of the region's best attractions, from fine art in Brussels to the canals of Bruges, the battlefields of Flanders and the best castles, museums, and architecture in between.

WalRB project: translation of the legend of the soil map of Belgium into World Reference Base for Soil Resources (WRB). Soil maps are among the most important reference maps in environmental and agriculture fields. Determination of land, agricultural potential, erosion thread, land management or soil pollution are some topics that need spatial soil data. Attention to cross-border environmental matters, such as soil protection, has become an international concern that requires harmonized soil information. This is why the World Reference Base for Soil Resources has been selected by European Union as official soil classification system (IUSS Working Group WRB, 2007). Belgium is one of the first nations to have achieved the whole country soil survey at large scale (1:20,000). The legend of the soil map of Belgium is based on three or four main soil specifications, texture, drainage class, profile development and stoniness nature (for stony soil), each one represented by a letter. Those three or four letters all together form the main soil series. Prefix and suffix may be added to further detail it. The WRB system based on soil morphology is formed of two levels, 32 Reference Soil Groups (RSGs), and various qualifiers (prefix, suffix or both). A common methodology between Flanders, Luxembourg and Wallonia (that use the same soil map legend) is requested to carry out the translation. Data from different databases, digital soil maps, soil profile descriptions, soil analytical data, Digital Elevation Model, other thematic maps (e.g. flooding hazard areas) are collected and organized under a common PostgreSQL database [Belgian Soil Profile Database (BSP)], with PostGIS geographical extension, hosted under a dedicated server. Data validation is proposed to be done under the auspices of National Soil Committee of Royal Academy for Sciences and Arts of Belgium. Algorithms are implemented in Perl and R languages.

\"Focusing on the most important achievements by Rubens, this is a unique atlas-based approach, uniting culture and tourism harmoniously in one book.\"--Source unspecified.

Pour la gestion du territoire et de l'environnement, les cartes des sols constituent un outil incontournable. Les problématiques de remembrement, d'affectation des terres, de potentiel agricole, d'érosion ou de pollution des sols sont autant de sujets nécessitant une information spatiale sur les sols. À l'échelle internationale, l'intérêt croissant dans ces matières et leur nature transfrontalière exigent une harmonisation des informations relatives aux sols. Consciente de ce besoin, l'Union européenne a choisi comme standard officiel le système international de classification des sols World Reference Base for Soil Resources (IUSS Working Group WRB, 2007). Suite à un gigantesque travail de cartographie, la Belgique est un des premiers pays à avoir réalisé une carte des sols à grande échelle (1/20 000) sur l'ensemble de son territoire. L'unité de base de la légende de la Carte des Sols est la série principale ; elle met l'accent sur la texture, le drainage naturel, le développement de profil et la nature de la charge caillouteuse pour les sols contenant plus de 15 % en éléments grossiers. Le système WRB est lui organisé selon deux niveaux, 32 Reference Soil Groups (RSGs), auxquels s'appliquent différents Qualifiers (préfixes, suffixes ou les deux). Une méthodologie commune entre la Flandre, la Wallonie et le Grand-Duché de Luxembourg (qui partage en grande partie sa légende des sols avec la Belgique) est indispensable pour mener au mieux la traduction du système belge dans le système WRB. Dans ce but, trois projets sont menés en parallèle en Wallonie, en Flandre et au Luxembourg. Pour mener à bien cette tâche, les données, cartes numériques des sols, descriptions des profils, données analytiques, modèles numériques de terrain et autres (cartes d'aléa d'inondation, etc.) sont collectées, organisées et centralisées dans une base de données de référence [Belgian Soil Profile Database (BSP)] sur un serveur dédié. Il est proposé que leur validation se fasse sous l'égide du Comité National des Sols de l'Académie Royale des Sciences et des Arts de Belgique. Le système de gestion de base de données est PostgreSQL avec extension géographique PostGIS ; les algorithmes de traitement des données sont implémentés en Perl et en R. WalRB project: translation of the legend of the soil map of Belgium into World Reference Base for Soil Resources (WRB). Soil maps are among the most important reference maps in environmental and agriculture fields. Determination of land, agricultural potential, erosion thread, land management or soil pollution are some topics that need spatial soil data. Attention to cross-border environmental matters, such as soil protection, has become an international concern that requires harmonized soil information. This is why the World Reference Base for Soil Resources has been selected by European Union as official soil classification system (IUSS Working Group WRB, 2007). Belgium is one of the first nations to have achieved the whole country soil survey at large scale (1:20,000). The legend of the soil map of Belgium is based on three or four main soil specifications, texture, drainage class, profile development and stoniness nature (for stony soil), each one represented by a letter. Those three or four letters all together form the main soil series. Prefix and suffix may be added to further detail it. The WRB system based on soil morphology is formed of two levels, 32 Reference Soil Groups (RSGs), and various qualifiers (prefix, suffix or both). A common methodology between Flanders, Luxembourg and Wallonia (that use the same soil map legend) is requested to carry out the translation. Data from different databases, digital soil maps, soil profile descriptions, soil analytical data, Digital Elevation Model, other thematic maps (e.g. flooding hazard areas) are collected and organized under a common PostgreSQL database [Belgian Soil Profile Database (BSP)], with PostGIS geographical extension, hosted under a dedicated server. Data validation is proposed to be done under the auspices of National Soil Committee of Royal Academy for Sciences and Arts of Belgium. Algorithms are implemented in Perl and R languages.

Detailed full hydrodynamic 1D-2D dual drainage models are a well-established approach to simulate urban pluvial floods. However, despite modelling advances and increasing computational power, this approach remains unsuitable for many real time applications. We propose and test two computationally efficient surrogate models. The first approach links a detailed 1D sewer model to a GIS-based overland flood network. For the second approach, we developed a conceptual sewer and flood model using data-driven and physically based structures, and coupled the model to pre-simulated flood maps. The city of Ghent (Belgium) is used as a test case. Both surrogate models can provide comparable results to the original model in terms of peak surface flood volumes and maximum flood extent and depth maps, with a significant reduction in computing time.

Reliable remote sensing-based Land Use and Land Cover (LULC) information is crucial for assessing Earth’s surface activities. Brazil’s agricultural dynamics, including year-round cropping, multiple cropping, and regional climate variability, make LULC monitoring a highly challenging task. The country has thirteen remote sensing-based LULC products specifically tailored for this purpose. However, the differences and the results of these products have not yet been synthesized to provide coherent guidance in assessing their spatio-temporal agricultural dynamics and identifying promising approaches and issues that affect LULC analysis. This review represents the first comprehensive assessment of the advantages, challenges, and limitations, highlighting the main issues when dealing with contrasting LULC maps. These challenges include incompatibility, a lack of updates, non-systematic classification ontologies, and insufficient data to monitor Brazilian LULC information. The consequences include impacts on intercropping estimation, diminished representation or misrepresentation of croplands; temporal discontinuity; an insufficient number of classes for subannual cropping evaluation; and reduced compatibility, comparability, and spectral separability. The study provides insights into the use of these products as primary input data for remote sensing-based applications. Moreover, it provides prospects for enhancing existing mapping efforts or developing new national-level initiatives to represent the spatio-temporal variation of Brazilian agriculture.

Land Use/Land Cover (LULC) mapping is the first step in monitoring urban sprawl and its environmental, economic and societal impacts. While satellite imagery and vegetation indices are commonly used for LULC mapping, the limited resolution of these images can hamper object recognition for Geographic Object-Based Image Analysis (GEOBIA). In this study, we utilize very high-resolution (VHR) optical imagery with a resolution of 50 cm to improve object recognition for GEOBIA LULC classification. We focused on the city of Nice, France, and identified ten LULC classes using a Random Forest classifier in Google Earth Engine. We investigate the impact of adding Gray-Level Co-Occurrence Matrix (GLCM) texture information and spectral indices with their temporal components, such as maximum value, standard deviation, phase and amplitude from the multi-spectral and multi-temporal Sentinel-2 imagery. This work focuses on identifying which input features result in the highest increase in accuracy. The results show that adding a single VHR image improves the classification accuracy from 62.62% to 67.05%, especially when the spectral indices and temporal analysis are not included. The impact of the GLCM is similar but smaller than the VHR image. Overall, the inclusion of temporal analysis improves the classification accuracy to 74.30%. The blue band of the VHR image had the largest impact on the classification, followed by the amplitude of the green-red vegetation index and the phase of the normalized multi-band drought index.

IONORING (IONOspheric RING) is a tool capable to provide the real-time monitoring and modeling of the ionospheric Total Electron Content (TEC) over Italy, in the latitudinal and longitudinal ranges of 35°N–48°N and 5°E–20°E, respectively. IONORING exploits the Global Navigation Satellite System (GNSS) data acquired by the RING (Rete Integrata Nazionale GNSS) network, managed by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). The system provides TEC real-time maps with a very fine spatial resolution (0.1° latitude x 0.1° longitude), with a refresh time of 10 min and a typical latency below the minute. The TEC estimated at the ionospheric piercing points from about 40 RING stations, equally distributed over the Italian territory, are interpolated using locally (weighted) regression scatter plot smoothing (LOWESS). The validation is performed by comparing the IONORING TEC maps (in real-time) with independent products: (i) the Global Ionospheric Maps (GIM) - final product- provided by the International GNSS Service (IGS), and (ii) the European TEC maps from the Royal Observatory of Belgium. The validation results are satisfactory in terms of Root Mean Square Error (RMSE) between 2 and 3 TECu for both comparisons. The potential of IONORING in depicting the TEC daily and seasonal variations is analyzed over 3 years, from May 2017 to April 2020, as well as its capability to account for the effect of the disturbed geospace on the ionosphere at mid-latitudes. The IONORING response to the X9.3 flare event of September 2017 highlights a sudden TEC increase over Italy of about 20%, with a small, expected dependence on the latitude, i.e., on the distance from the subsolar point. Subsequent large regional TEC various were observed in response to related follow-on geomagnetic storms. This storm is also used as a case event to demonstrate the potential of IONORING in improving the accuracy of the GNSS Single Point Positioning. By processing data in kinematic mode and by using the Klobuchar as the model to provide the ionospheric correction, the resulting Horizontal Positioning Error is 4.3 m, lowering to, 3.84 m when GIM maps are used. If IONORING maps are used as the reference ionosphere, the error is as low as 2.5 m. Real-times application and services in which IONORING is currently integrated are also described in the conclusive remarks.

In 2022, Europe emerged from eight of the hottest years on record, leading to significant spruce mortality across Europe. The particularly dry weather conditions of 2018 triggered an outbreak of bark beetles (Ips typographus), causing the loss of thousands of hectares of Norway spruce stands, including in Wallonia and North-eastern France. A methodology for detecting the health status of spruce was developed based on a dense time series of satellite imagery (Sentinel-2). The time series of satellite images allowed the modelling of the spectral response of healthy spruce forests over the seasons: a decrease in photosynthetic activity of the forest canopy causes deviations from this normal seasonal vegetation index trajectory. These anomalies are caused by a bark beetle attack and are detected automatically. The method leads in the production of an annual spruce health map of Wallonia and Grand-Est. The goal of this paper is to assess the damage caused by bark beetle using the resulting spruce health maps. A second objective was to compare the influence of basic variables on the mortality of spruce trees in these two regions. Lasted 6 years (2017-2022), bark beetle has destroyed 12.2% (23,674 ha) of the spruce area in Wallonia and Grand-Est of France. This study area is composed of three bioclimatic areas: Plains, Ardennes and Vosges, which have not been equally affected by bark beetle attacks. The plains were the most affected, with 50% of spruce forests destroyed, followed by the Ardennes, which lost 11.3% of its spruce stands. The Vosges was the least affected bioclimatic area, with 5.6% of spruce stands lost. For the most problematic sites, Norway spruce forestry should no longer be considered.

The goaf is an important factor that induces major accidents. Based on the quantitative analysis of the existing research results, summarize and sort out the research and prevention technology of the goaf disaster with the experience of experts. Temporally, the research on goaf disasters was divided into two stages: the embryonic stage and the rapid development stage. Spatially, a collaborative network with the United States, China, Germany, France, Turkey, and the United Kingdom as the core, including India, Japan, Belgium, Italy, South Korea, and Canada, was analyzed. By constructing a co-occurrence and clustering network of keywords and co-cited literature to explore the focus and hotspots of goaf disaster research, the hotspots of goaf disaster research are summarized into four main aspects, such as goaf detection technology, goaf disaster analysis, goaf risk assessment and goaf treatment technology, which grasp the content of goaf research from a macro perspective. The burst detection analysis of keywords and co-cited literature was conducted to obtain the research frontiers of goaf disaster research in different periods. At the current stage, the microstructural characteristics of surrounding rocks in the context of deep mining and complex goaf group effect and the mining technology of the integration of excavation, anchoring and supporting are the current frontier research directions. This combined qualitative and quantitative method is more helpful to grasp the development context of goaf disaster research and provides a new reference perspective for sorting out the process of goaf disaster research.