Innovative Geospatial and Cartographic Approaches to Identification, Analysis, and Visualisation of Land Degradation
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Abstract. Land degradation has increasingly been recognised as a serious environmental problem throughout the whole world. Six major threats may be identified that place soil fertility at risk, namely, soil erosion, loss of organic matter, soil biodiversity, soil compaction, soil salinity, and soil pollution. Several of those risks could be effectively identified, analysed, visualised and consequently limited by approaches originating from the geospatial domain.The China – European Union research and innovation project “SIEUSOIL” (SIno-EU Soil Observatory for Intelligent Land Use Management), funded between 2019 and 2022, as well as the European Big Data flagship research and innovation project “DataBio” (Data-Driven Bioeconomy), funded between 2017 and 2019, aim at the above mentioned challenges of land degradation from innovative geospatial perspectives.Such innovative approaches include local geological, geomorphological, climate, yield maps as well as global soil maps provided commonly by the European Commission (Directorate General Joint Research Centre) and the Chinese Academy of Sciences. Among the data inputs there are farm machinery tracking and interpreted satellite images. The second level of activities consists of selected standards and specification of ontologies for the integration and sharing of soil related data, facilitating their reuse and understanding. The resulting ontology and other selected models provide the basis for the integration, publication, and querying of the source datasets using Linked data as a federated layer. Besides offering an integrated view of the datasets, this layer also enables new insights through the discovery of links.From the cartographic perspective, several visualization techniques are deployed; from static maps to interactive visualisations. The main focus of visualization techniques is therefore given to the interactivity through utilizing the concept of Multiple Coordinated Views (also known as visual analytics tools) and dynamic queries to emphasize the impact of changes of various phenomena in space and time. For instance, see Figure 1 on monitoring of machinery fleet movement and especially its spatiotemporal changes that can bring new insights into the consequences of human decisions from many areas. Economic reasons are related to economic evidence for a farmer, including fuel consumption, efficiency of trajectory, etc. to revenue authority or subsidies management. On the other hand, ecologic motivations aim to decrease of environmental burden caused e.g. by high CO2 emissions due to a lack of movement optimisation, water pollution by nitrogen due to excessive fertilisation, etc.The outcomes of the above mentioned research are intended as a feedback to (inter)national policies within the environmental domain including the Montreal Protocol (on substances that deplete the Ozone Layer), European Common Agricultural Policy, Nitrates Directive, Air Quality Framework Directive, Water Framework Directive, the Chinese Water Pollution Prevention Law, etc.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle