Human sustainability is one of the most pressing issues of the 21st century. Coupled Human and Natural Systems (CHANS) offers a useful framework to focus on understanding the complex process and pattern that characterizes the dynamical interactions between human and natural systems. This dissertation research integrates the geospatial analysis into the CHANS framework from three perspectives: temporal, spatial, and organizational coupling.
Using the temporal coupling aspect, we monitor the risk of deforestation and biodiversity threats from energy investments in Southeast Asia. We assess the energy investment evaluate changes to forest morphology and the risk to biodiversity. In terms of land cover change, we find that hydroelectric power plants tend to have more extensive biodiversity impacts than coal-fired plants, which are usually built within proximity to major population centers.
Next, we explore spatial coupling by examining the spatial heterogeneity and homogeneity in home prices across Massachusetts, using Geographically Weighted Regression models with natural and socio-demographic variables. We discovered models that utilized spatial heterogeneity perform better. However, statistical tests of significance are required to determine the model specification to avoid over-fitting.
In the fourth chapter, we examined a critical refugium for endangered fish species in East Africa by mapping the organizational dynamics of aquatic vegetation on Lake Kyoga, Uganda. A CHANS organizational coupling involving the natural infrastructure of aquatic vegetation and fishes can adversely impact endangered species and the surrounding human communities. Floating aquatic vegetation can protect the native fishes from predation by Nile Perch by creating hypoxic barriers between water bodies. We developed an algorithm to locate and identify various types of aquatic vegetation. Profiles of lakes are created to examine the spatiotemporal dynamics of refugia. The results are valuable in shaping strategies to conserve both fish species and human livelihoods.
The fifth chapter explores emerging technologies, Virtual Reality, in communicating the complex CHANS coupling of green (trees) and gray infrastructure (gas pipelines). This chapter demonstrates the building of 3D urban landscapes from remote sensing data and the emerging use of VR to communicate, educate and empower the stakeholders on sustainability issues related to aging natural gas infrastructure and resulting methane emissions.
This dissertation research aims to build a set of methodologies based on extensive geospatial data, spatially explicit models, and tools essential for operationalizing and monitoring CHANS in studies ranging from local to regional scales. Each application builds or revises a new model or algorithm to address a real-world CHANS problem.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/43947 |
| Date | 02 March 2022 |
| Creators | Ma, Yaxiong |
| Contributors | Gopal, Sucharita |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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