Browsing by Author "Quaife, Tristan"
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Item Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling(2015-06) Stoy, Paul C.; Quaife, TristanUpscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.Item Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling [dataset](Montana State University ScholarWorks, 2015-05) Stoy, Paul C.; Quaife, TristanMATLAB code to perform two-dimensional Tikhonov Regularization (2DTR). Subheaders refer to MATLAB function names. A simulated landscape with a Lagrange multiplier gamma = 10^.85, a mean value of 0.54, and a variance of 0.009 can be generated using: [Rgamma] = doDisaggExperiment(rand(64), 10^.85, 0.009, 0.54 ). The Stoy Lab adheres to an open data policy. Data collected by the Stoy Lab are free to anyone to use with two caveats: 1. Coauthorship may be requested if intellectual input is provided. Intellectual input is defined in this case as an analysis that is critical to outcomes that could not otherwise be performed. 2. Graduate students operate the towers and analyze the data. They must be given the opportunity to be coauthors on your work. Please email paul dot stoy at gmail dot com with any questions.