根据荷兰 "同一健康 "共享社会经济路径绘制的荷兰未来土地利用图。

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2024-11-16 DOI:10.1038/s41597-024-04059-5

Martha Dellar, Gertjan Geerling, Kasper Kok, Peter M van Bodegom, Gerard van der Schrier, Maarten Schrama, Eline Boelee

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引用次数: 0

摘要

为了能够详细研究未来的各种健康挑战，我们根据荷兰 "同一健康 "共享社会经济路径 (SSP) 绘制了荷兰 2050 年的未来土地利用图。这项工作是利用 DynaCLUE 建模框架完成的。未来的土地使用基于海拔高度、土壤特性、地下水、盐度、洪水风险、农业用地价格、与交通枢纽的距离和气候。我们还考虑了对不同土地利用类型的预期需求、历史土地利用变化和潜在的空间限制。这些土地利用地图可用于模拟人类、动物和环境面临的多种不同健康风险，如疾病、水质和污染。此外，荷兰还可以为其他快速城市化的三角洲提供范例，这些三角洲的许多健康风险都与荷兰类似。

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Future land use maps for the Netherlands based on the Dutch One Health Shared Socio-economic Pathways.

To enable detailed study of a wide variety of future health challenges, we have created future land use maps for the Netherlands for 2050, based on the Dutch One Health Shared Socio-economic Pathways (SSPs). This was done using the DynaCLUE modelling framework. Future land use is based on altitude, soil properties, groundwater, salinity, flood risk, agricultural land price, distance to transport hubs and climate. We also account for anticipated demand for different land use types, historic land use changes and potential spatial restrictions. These land use maps can be used to model many different health risks to people, animals and the environment, such as disease, water quality and pollution. In addition, the Netherlands can serve as an example for other rapidly urbanising deltas where many of the health risks will be similar.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.