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Full-Text Articles in Physical Sciences and Mathematics
Using Landsat-Based Phenology Metrics, Terrain Variables, And Machine Learning For Mapping And Probabilistic Prediction Of Forest Community Types In West Virginia, Faith M. Hartley
Using Landsat-Based Phenology Metrics, Terrain Variables, And Machine Learning For Mapping And Probabilistic Prediction Of Forest Community Types In West Virginia, Faith M. Hartley
Graduate Theses, Dissertations, and Problem Reports
This study investigates the mapping of forest community types for the entire state of West Virginia, USA using Global Land Analysis and Discovery (GLAD) Phenology Metrics analysis ready data (ARD) derived from the Landsat time series and digital terrain variables derived from a digital terrain model (DTM). Both classifications and probabilistic predictions were made using random forest (RF) machine learning (ML) and training data derived from ground plots provided by the West Virginia Natural Heritage Program (WVNHP). The primary goal of this study is to explore the use of globally consistent ARD data for operational forest type mapping over a …
Impact Of Multi-Scale Predictor Selection For Modeling Soil Properties, Bradley A. Miller, Sylvia Koszinski, Marc Wehrhan, Michael Sommer
Impact Of Multi-Scale Predictor Selection For Modeling Soil Properties, Bradley A. Miller, Sylvia Koszinski, Marc Wehrhan, Michael Sommer
Bradley A Miller
Applying a data mining tool used regularly in digital soil mapping, this research focuses on the optimal inclusion of predictors for soil–landscape modeling by utilizing as wide of a pool of variables as possible. Predictor variables for digital soil mapping are often chosen on the basis of data availability and the researcher's expert knowledge. Predictor variables commonly overlooked include alternative analysis scales for land-surface derivatives and additional remote sensing products. For this study, a pool of 412 potential predictors was assembled, which included qualitative location classes, elevation, land-surface derivatives (with a wide range of analysis scales), hydrologic indicators, as well …
Semantic Calibration Of Digital Terrain Analysis Scale, Bradley A. Miller
Semantic Calibration Of Digital Terrain Analysis Scale, Bradley A. Miller
Bradley A Miller
Digital terrain analysis (DTA) provides efficient, repeatable, and quantified metrics of landscape characteristics that are important to the Earth sciences, particularly for detailed soil mapping applications. However, DTA has not been field tested to the extent that traditional field metrics of topography have been. Human assessment of topography synthesizes multiple parameters at multiple scales to characterize a landscape, based on field experience. In order to capture the analysis scale used by field scientists, this study introduces a method for calibrating the analysis scale of DTA to field assessments. This method is used to calibrate land-surface derivatives of relative elevation, profile …
A Remote Sensing Approach To Characterize The Hydrogeology Of Mountainous Areas: Application To The Quito Aquifer System (Qas), Ecuador, Miriam Rios-Sanchez
A Remote Sensing Approach To Characterize The Hydrogeology Of Mountainous Areas: Application To The Quito Aquifer System (Qas), Ecuador, Miriam Rios-Sanchez
Dissertations, Master's Theses and Master's Reports - Open
Climate change, intensive use, and population growth are threatening the availability of water resources. New sources of water, better knowledge of existing ones, and improved water management strategies are of paramount importance. Ground water is often considered as primary water source due to its advantages in terms of quantity, spatial distribution, and natural quality. Remote sensing techniques afford scientists a unique opportunity to characterize landscapes in order to assess groundwater resources, particularly in tectonically influenced areas. Aquifers in volcanic basins are considered the most productive aquifers in Latin America. Although topography is considered the primary driving force for groundwater flows …