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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Manifold Learning Based Spectral Unmixing Of Hyperspectral Remote Sensing Data, Jun-Hwa Chi
Manifold Learning Based Spectral Unmixing Of Hyperspectral Remote Sensing Data, Jun-Hwa Chi
Open Access Dissertations
Nonlinear mixing effects inherent in hyperspectral data are not properly represented in linear spectral unmixing models. Although direct nonlinear unmixing models provide capability to capture nonlinear phenomena, they are difficult to formulate and the results are not always generalizable. Manifold learning based spectral unmixing accommodates nonlinearity in the data in the feature extraction stage followed by linear mixing, thereby incorporating some characteristics of nonlinearity while retaining advantages of linear unmixing approaches. Since endmember selection is critical to successful spectral unmixing, it is important to select proper endmembers from the manifold space. However, excessive computational burden hinders development of manifolds for …
Adaptive Targeting: Engaging Farmers To Assess Perceptions And Improve Watershed Modeling, Optimization, And Adoption Of Agricultural Conservation Practices, Margaret Mccahon Kalcic
Adaptive Targeting: Engaging Farmers To Assess Perceptions And Improve Watershed Modeling, Optimization, And Adoption Of Agricultural Conservation Practices, Margaret Mccahon Kalcic
Open Access Dissertations
Targeting agricultural conservation practices to farmland that has the greatest impact on surface water quality has received wide support from scientists and watershed managers. The targeting approach has, however, been politically contentious as many believe farmers will oppose the approach on grounds such as privacy invasion and unfair distribution of government incentives. Targeting conservation practices using complex optimization models has become common in the scientific community, and yet targeted results are underutilized in practice because of difficulties such as knowledge transfer and absence of a political framework for their use. For targeting to be successful, it must be politically supported …
Simulating Land Use Land Cover Change Using Data Mining And Machine Learning Algorithms, Amin Tayyebi
Simulating Land Use Land Cover Change Using Data Mining And Machine Learning Algorithms, Amin Tayyebi
Open Access Dissertations
The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue's Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States …