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1 Zhou, G.; Wang, X.; Chen, W.; Li, X.; Chen, Z. 2020. Realization and application of geological cloud platform. Big Earth Data, 16p. (Online first) [doi: https://doi.org/10.1080/20964471.2020.1820175]

Geological data ; Technology ; Data processing ; Data analysis ; Spatial data ; Geographical information systems ; Models / USA / Nevada

(Location: IWMI HQ Call no: e-copy only Record No: H050029)

https://www.tandfonline.com/doi/abs/10.1080/20964471.2020.1820175?needAccess=true#aHR0cHM6Ly93d3cudGFuZGZvbmxpbmUuY29tL2RvaS9wZGYvMTAuMTA4MC8yMDk2NDQ3MS4yMDIwLjE4MjAxNzU/bmVlZEFjY2Vzcz10cnVlQEBAMA==
https://vlibrary.iwmi.org/pdf/H050029.pdf

(9.27 MB) (9.27 MB)

In recent years, with the progress of computer technology, some traditional industries such as geology are facing changes in industrial structure and application mode. So we try to apply big data and virtualization technology in the field of geoscience. This study aims at addressing the existing problems in geological applications, such as data sharing, data processing and computing performance. A Geological Cloud Platform has been designed and realized preliminarily with big data and virtualization technology. The application of the Geological Cloud Platform can be divided into two parts: 1) to nest the geological computing model in cloud platform and visualize the results and 2) to use relevant software to conduct data analysis and processing in virtual machines of Windows or Linux system. Finally, we prospect Carlin-type deposits in Nevada by using the spatial data model ArcSDM in the virtual machine.

2 Zhou, G.; Huan, Y.; Wang, L.; Zhang, R.; Liang, T.; Han, X.; Feng, Z. 2023. Constructing a multi-leveled ecological security pattern for improving ecosystem connectivity in the Asian water tower region. Ecological Indicators, 154:110597. (Online first) [doi: https://doi.org/10.1016/j.ecolind.2023.110597]

Ecosystem services ; Plateaus ; Sustainable Development Goals ; Biodiversity conservation ; Soil conservation ; Carbon sequestration ; Water conservation ; Land use ; Vegetation ; Landscape ; Models / Qinghai / Tibet

(Location: IWMI HQ Call no: e-copy only Record No: H052143)

https://www.sciencedirect.com/science/article/pii/S1470160X23007392/pdfft?md5=3ad8dcfb0e6d1bced43cd8c9ce2ecce5&pid=1-s2.0-S1470160X23007392-main.pdf
https://vlibrary.iwmi.org/pdf/H052143.pdf

(19.20 MB) (19.2 MB)

Serious ecological crises have emerged in the Asian Water Tower region (17 countries centered on the Qinghai-Tibetan Plateau), making it a major priority and challenge for Asian and even global ecological conservation efforts. Constructing a multi-leveled ecological security pattern (ESP) based on the synergies among multiple ecosystem services (ESs) for this region can enhance the structural integrity, functional stability, and spatial connectivity of ecosystems. Therefore, based on a series of GIS spatial analysis methods, the minimum cumulative resistance model, and the analytic hierarchy process, this study measured the importance of five key ESs focused by Sustainable Development Goal 15 (including water conservation, carbon sequestration, sand fixation, soil conservation, and biodiversity conservation); and took fishnet scale as data calculation unit to construct a hierarchical ESP (including three levels of ecological sources and corridors) to provide evidence-based support for identifying and prioritizing synergistic conservation actions across scales (regions, nations, and basins). Overall, the ESP included a total of 534 sources and 656 corridors. Some key conservation obstacles in the region (e.g., edge effects and several human activities) and corresponding priority actions are provided, such as integrating the ESPs into long-term planning, enhancing the conservation and the restoration of both the extent and the quality of forests (e.g., increasing tree species richness), and increasing collaboration across scales for resource mobilization and synergistic land use.

3 Zhou, G.; Li, Z.; Wang, W.; Wang, Q.; Yu, J. 2024. Understanding the impact of population dynamics on water use utilizing multi-source big data. Journal of Hydroinformatics, jh2024179. (Online first) [doi: https://doi.org/10.2166/hydro.2024.179]

Water use ; Big data ; Water supply ; Water demand ; Sewage ; Towns ; Villages ; Water resources ; Water levels ; Wastewater treatment / China / Beijing / Haidian / Shangzhuang Town / Xibeiwang Town / Wenquan Town / Sujiatuo Town

(Location: IWMI HQ Call no: e-copy only Record No: H052622)

https://iwaponline.com/jh/article-pdf/doi/10.2166/hydro.2024.179/1356725/jh2024179.pdf
https://vlibrary.iwmi.org/pdf/H052622.pdf

(1.42 MB) (1.42 MB)

Population movement, such as commuting, can affect water supply pressure and efficiency in modern cities. However, there is a gap in the research concerning the relationship between water use and population mobility, which is of great significance for urban water supply planning and supporting urban sustainable development. In this study, we analyzed the spatial–temporal dynamics of the population and its underlying mechanisms, using multi-source geospatial big data, including Baidu heat maps (BHMs), land use parcels, and point of interest. Combined with water consumption, sewage volume, and river depth data, the impact of population dynamics on water use was investigated. The results showed that there were obvious differences in population dynamics between weekdays and weekends with a ratio of 1.11 for the total population. Spatially, the population concentration was mainly observed in areas associated with enterprises, industries, shopping, and leisure activities during the daytime, while at nighttime, it primarily centered around residential areas. Moreover, the population showed a significant impact on water use, resulting in co-periods of 24 h and 7 days, and the water consumption as well as the wastewater production were observed to be proportional to the population density. This study can offer valuable implications for urban water resource allocation strategies.