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- Geospatial analysis (1)
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Articles 1 - 4 of 4
Full-Text Articles in Geography
Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu
Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu
Forestry and Natural Resources Faculty Publications
Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability …
Accounting For Spatial Autocorrelation In Modeling The Distribution Of Water Quality Variables, Lorrayne Miralha
Accounting For Spatial Autocorrelation In Modeling The Distribution Of Water Quality Variables, Lorrayne Miralha
Theses and Dissertations--Geography
Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R²) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary …
Leveraging Overhead Imagery For Localization, Mapping, And Understanding, Scott Workman
Leveraging Overhead Imagery For Localization, Mapping, And Understanding, Scott Workman
Theses and Dissertations--Computer Science
Ground-level and overhead images provide complementary viewpoints of the world. This thesis proposes methods which leverage dense overhead imagery, in addition to sparsely distributed ground-level imagery, to advance traditional computer vision problems, such as ground-level image localization and fine-grained urban mapping. Our work focuses on three primary research areas: learning a joint feature representation between ground-level and overhead imagery to enable direct comparison for the task of image geolocalization, incorporating unlabeled overhead images by inferring labels from nearby ground-level images to improve image-driven mapping, and fusing ground-level imagery with overhead imagery to enhance understanding. The ultimate contribution of this thesis …
Exploring Spatial And Temporal Variability Of Soil And Crop Processes For Irrigation Management, Javier Reyes
Exploring Spatial And Temporal Variability Of Soil And Crop Processes For Irrigation Management, Javier Reyes
Theses and Dissertations--Plant and Soil Sciences
Irrigation needs to be applied to soils in relatively humid regions such as western Kentucky to supply water for crop uptake to optimize and stabilize yields. Characterization of soil and crop variability at the field scale is needed to apply site specific management and to optimize water application. The objective of this work is to propose a characterization and modeling of soil and crop processes to improve irrigation management. Through an analysis of spatial and temporal behavior of soil and crop variables the variability in the field was identified. Integrative analysis of soil, crop, proximal and remote sensing data was …