K. Charvát, Dmitrij Kozhukh, M. Kepka, P. Hájek, Herman Snevajs, M. Kollerová, Hana Kubícková, Tuula Löytty, Ronald Ssembajwe, Akaninyene Obot, Antoine Kantiza, Shadrack Stephene, G. Ravid, E. Gelb
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引用次数: 0
摘要
土地利用和土地覆盖信息与来自重要数据集的其他专题数据集相关的地方详细参考空间数据相结合,用于不同领域的不同类型分析。目前,在可持续发展目标战略、绿色协议、目的地地球和地球数字孪生体建设方面,还没有一个模型和数据库能够有效地收集到足够详细和复杂关系的地球表面信息。与欧洲相比,非洲的情况要糟糕得多,因为整个非洲只有来自公共资源的分散地图层,比如Africover和CCI Land Cover 2016。此外,另一个封闭的选项“开放街道地图”(OpenStreetMap)覆盖整个大陆,在自愿的基础上以最小的属性收集数据。出于这个原因,提供这些数据的验证和协调是谨慎的。因此,重点是开发和优化基于开放土地使用(OLU) 2.0数据模型的新解决方案。OLU 2.0数据库将各种主题数据与最详细的参考几何图形结合在一起。专题数据集主要集中于土地利用和土地覆盖信息,此外还包括土壤、地形特征、气候参数、遥感数据分类数据、野外块体植被指数等不同时间段的专题数据。通过这种方式,OLU4Africa 2.0定义了一个模型,该模型在非洲具有很大的高端应用潜力,例如粮食安全模型;环境、生物多样性和生态系统保护;规划目的;保护森林和水。值得一提的是,OLU4Africa 2.0应用程序已被提名为2022年WSIS奖项。
Optimization of African LULC Database for Sustainable Development
Land use and land cover information in combination with other thematic datasets related to detailed reference spatial data in localities from an important dataset for different types of analyses in different domains. At the time being, when it comes to the strategy of the SDG, Green Deal, Destination Earth, and construction of Earth’s digital twins, there is no model and database that would effectively gather information about the Earth’s surface in sufficient detail and complex relations. The situation is much worse in Africa compared to Europe since there exist only scattered map layers from public sources across all Africa like Africover and CCI Land Cover 2016. Moreover, the other close option ‘OpenStreetMap’ with a continent-wide coverage collects data on a voluntary basis with minimal attributes. For this reason, it’s prudent to provide validation and harmonisation of this data. Therefore, there was a focus on developing and optimising a new solution based on the Open Land Use (OLU) 2.0 data model. The OLU 2.0 database combined various thematic data with the most detailed reference geometry available. Thematic datasets were focused primarily on the information of land use and land cover and additionally on other themes like soil, topographic characteristics, climatic parameters, data from classification of remote sensing data, vegetation indices of field blocks, etc. and in different time periods. In this way, OLU4Africa 2.0 defined a model which can have large potential in Africa for high-end applications such as food security modelling; environment, biodiversity, and ecosystem protection; planning purposes; forest and water protection. It is worth mentioning that the OLU4Africa 2.0 application has been nominated among WSIS Prizes 2022.