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Trends Of Autumn Phenology In Response To Environmental And Meteorological Variables, Meagan Renee Maguire

Masters Theses

Previous studies have identified that changes in plant phenology are most likely induced by climate variability. One such change is the end of season (EOS) for deciduous forests in the United States. In essence, the EOS represents the end of plant productivity for a given year; the phase in which plant dormancy is reached. However, our wealth of knowledge on plant phenology largely overlooks the phases that occur in autumn, especially the EOS, with many previous studies focusing on spring phenology. This study uses remote sensing MODIS aerial imagery data and historical meteorological data to analyze any relationships that may …

Responses Of Land Surface Phenology To Wildfire Disturbances In The Western United States Forests, Jianmin Wang

Electronic Theses and Dissertations

Land surface phenology (LSP) characterizes the seasonal dynamics in the vegetation communities observed for a satellite pixel and it has been widely associated with global climate change. However, LSP and its long-term trend can be influenced by land disturbance events, which could greatly interrupt the LSP responses to climate change. Wildfire is one of the main disturbance agents in the western United States (US) forests, but its impacts on LSP have not been investigated yet. To gain a comprehensive understanding of the LSP responses to wildfires in the western US forests, this dissertation focused on three research objectives: (1) to …

Crown-Level Mapping Of Tree Species And Health From Remote Sensing Of Rural And Urban Forests, Fang Fang

Graduate Theses, Dissertations, and Problem Reports

Tree species composition and health are key attributes for rural and urban forest biodiversity, and ecosystem services preservation. Remote sensing has facilitated extraordinary advances in estimating and mapping tree species composition and health. Yet previous sensors and algorithms were largely unable to resolve individual tree crowns and discriminate tree species or health classes at this essential spatial scale due to the low image spectral and spatial resolution. However, current available very high spatial resolution (VHR) remote sensing data can begin to resolve individual tree crowns and measure their spectral and structural qualities with unprecedented precision. Moreover, various machine learning algorithms …

Decadal Land Surface Phenology And Water Quality In The Headwaters Illinois River Watershed, Justin Ray Rollans

Graduate Theses and Dissertations

Over 25 percent of the world’s population either lives on or obtains water from karst aquifers. The complex interactions between subsurface karst geologic features, the constant motion of the plant life cycle, and significant water resource demand all suggest the need to better define those interactions. The relationship of historical land surface phenology and water quality in karst topography were investigated in the Headwaters Illinois River watershed in Northwest Arkansas (NWA). This area represents high vulnerability to surface water and groundwater contamination, with both natural and anthropogenic processes such as over application of broil litter for enhanced cattle browse, affecting …

Fusing Satellite Data To Monitor The Urban Area's Effect On Plant Phenology, Norman Gervais

Legacy Theses & Dissertations (2009 - 2024)

This dissertation centrally focuses on developing and validating the use of fused satellite imagery to monitor the effects of the urban area on plant phenology, specifically the timing of the start and end of the growing season (SOS and EOS, respectively). In the first paper, Chapter 2, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat were fused together using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to produce a time series of a high spatial and high temporal resolution vegetation index. From this time series, the SOS and EOS were extracted and compared between the urban …

Integration Of Multi-Temporal Optical And L-Band Synthetic Aperture Radar (Sar) Imagery For Hierarchical Agricultural Crop Classification In Northeastern Ontario, Canada, Autumn A. Gambles

Electronic Thesis and Dissertation Repository

This study integrated multi-temporal, multispectral optical and L-band synthetic aperture radar (SAR) imagery to classify agricultural crops throughout a single growing season in northeastern Ontario, Canada. Various optical and SAR band/date combinations were tested to identify optimal dates and datasets for crop classification at various phenological stages using both object-based decision tree rulesets and traditional per-pixel strategies. Object-based decision tree classification of 2 pairs of SPOT-5 optical and L-Band ALOS SAR imagery yielded crop identification accuracy results comparable with hierarchically masked per-pixel classification, with corn classes regularly achieving high classification accuracies (+90%). Regardless of classification approach, results indicate that at …

Classification Of Satellite Time Series-Derived Land Surface Phenology Focused On The Northern Fertile Crescent, Brian Embree Bunker

Graduate Theses and Dissertations

Land surface phenology describes events in a seasonal vegetation cycle and can be used in a variety of applications from predicting onset of future drought conditions, to revealing potential limits of historical dry farming, to guiding more accurate dating of archeological sites. Traditional methods of monitoring vegetation phenology use data collected in situ. However, vegetation health indices derived from satellite remote sensor data, such as the normalized difference vegetation index (NDVI), have been used as proxy for vegetation phenology due to their repeated acquisition and broad area coverage. Land surface phenology is accessible in the NDVI satellite record when images …

Monitoring Ecosystem Dynamics In An Arctic Tundra Ecosystem Using Hyperspectral Reflectance And A Robotic Tram System, Santonu Goswami

Open Access Theses & Dissertations

Global change, which includes climate change and the impacts of human disturbance, is altering the provision and sustainability of ecosystem goods and services. These changes have the capacity to initiate cascading affects and complex feedbacks through physical, biological and human subsystems and interactions between them. Understanding the future state of the earth system requires improved knowledge of ecosystem dynamics and long term observations of how these are being impacted by global change. Improving remote sensing methods is essential for such advancement because satellite remote sensing is the only means by which landscape to continental-scale change can be observed.

The Arctic …