Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- 3D Modelling (1)
- Biogeochemistry (1)
- Carbon cyling (1)
- Carbon sequestration (1)
- Community type (1)
-
- Decomposition (1)
- Digital terrain analysis (1)
- Ecosystem model (1)
- Fire Ecology (1)
- Fire Fuels (1)
- Forest type classification (1)
- Forests (1)
- Global change (1)
- LiDAR (1)
- Machine Learning (1)
- Machine learning (1)
- Nitrogen deposition (1)
- Nutrient acquisition (1)
- Phenology (1)
- Quantitative Structure Models (1)
- Remote Sensing (1)
- Soil organic matter (1)
- Temperate forest (1)
- West Virginia (1)
Articles 1 - 3 of 3
Full-Text Articles in Other Earth Sciences
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 …
The Burning Bush: Linking Lidar-Derived Shrub Architecture To Flammability, Michelle S. Bester
The Burning Bush: Linking Lidar-Derived Shrub Architecture To Flammability, Michelle S. Bester
Graduate Theses, Dissertations, and Problem Reports
Light detection and ranging (LiDAR) and terrestrial laser scanning (TLS) sensors are powerful tools for characterizing vegetation structure and for constructing three-dimensional (3D) models of trees, also known as quantitative structural models (QSM). 3D models and structural traits derived from them provide valuable information for biodiversity conservation, forest management, and fire behavior modeling. However, vegetation studies and 3D modeling methodologies often only focus on the forest canopy, with little attention given to understory vegetation. In particular, 3D structural information of shrubs is limited or not included in fire behavior models. Yet, understory vegetation is an important component of forested ecosystems, …
Frayed Connections: How Long-Term Nitrogen Additions Disrupt Plant-Soil Interactions And The Carbon Cycle Of A Temperate Forest, Brooke A. Eastman
Frayed Connections: How Long-Term Nitrogen Additions Disrupt Plant-Soil Interactions And The Carbon Cycle Of A Temperate Forest, Brooke A. Eastman
Graduate Theses, Dissertations, and Problem Reports
Forests are expected to mitigate some of the negative effects of climate change by sequestering anthropogenic carbon (C) from the atmosphere, but the degree to which they drawn down C will depend on the availability of key nutrients, such as nitrogen (N). There is a fair amount of uncertainty in the future of the forest C sink, mostly owing to the fate of soil organic matter (SOM) and soil heterotrophic respiration to future conditions. In N limited systems, plants allocate a significant amount of their photosynthate belowground for the acquisition of nutrients, but under conditions of chronic N deposition, plants …