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Social and Behavioral Sciences Commons™
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Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
From Pixels To Plants: Remote Sensing Of California Invasive Plants, Kenneth Rangel
From Pixels To Plants: Remote Sensing Of California Invasive Plants, Kenneth Rangel
Master's Projects and Capstones
Invasive plants cause significant impacts to ecosystems, the economy, and human health. California has experienced significant plant invasions and is well suited to future invasion because of its Mediterranean climate and human disturbance. Eradication or control of invasive plant species requires a detailed understanding of their spatial distribution, which typically involves on the ground surveys that can be expensive or inconsistent. Remote sensing offers a potential alternative or supplement to in-person invasive plant mapping. This study performed a comparative analysis of 41 remote sensing studies that mapped the distribution of California invasive plants. I found that while high spectral resolution …
Soil Moisture Profile Estimation By Combining P-Band Sar Polarimetry With Hydrological And Multi-Layer Scattering Models, Anke Fluhrer, Thomas Jagdhuber, Carsten Montzka, Maike Schumacher, Hamed Alemohammad, Alireza Tabatabaeenejad, Harald Kunstmann, Dara Entekhabi
Soil Moisture Profile Estimation By Combining P-Band Sar Polarimetry With Hydrological And Multi-Layer Scattering Models, Anke Fluhrer, Thomas Jagdhuber, Carsten Montzka, Maike Schumacher, Hamed Alemohammad, Alireza Tabatabaeenejad, Harald Kunstmann, Dara Entekhabi
Geography
An approach for estimating vertically continuous soil moisture profiles under varying vegetation covers by combining remote sensing with soil (hydrological) modeling is proposed. The approach uses decomposed soil scattering components, after the removal of the vegetation scattering components from fully polarimetric P-band SAR observations. By comparing these with hydrological simulations, soil moisture profiles from the soil surface until a soil depth of 30 cm (assumed average P-band penetration depth) are estimated. Here, the hydrological model HYDRUS-1D, as a representative of any soil hydrological model, is employed to simulate an ensemble of realistic soil moisture profiles, which are used for a …
Microwave Emission Model Parameter Tuning For Surface Soil Moisture Retrieval Using Uav-Mounted Dual Polarization L-Band Radiometer, Santiago Hoyos Echeverri
Microwave Emission Model Parameter Tuning For Surface Soil Moisture Retrieval Using Uav-Mounted Dual Polarization L-Band Radiometer, Santiago Hoyos Echeverri
Open Access Theses & Dissertations
Surface soil moisture retrieval from L-band brightness temperature has been developed for the past decades due to multiple beneficial characteristics of 1-2 GHz frequency bands for remote sensing of the environment. Numerous microwave emission models have been proposed for tower and satellite-based operations with successful retrieval of surface soil moisture and vegetation water content. As a result of the development of cost-effective and low-mass microwave L-band radiometers such as the Portable L-band Radiometer (PoLRa), surface soil moisture surveying traditionally developed by satellite missions SMOS and SMAP can now be developed at local scales, bringing these operations to commercial small unmanned …
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Nowcasting Heavy Rainfall With Convolutional Long Short-Term Memory Networks: A Pixelwise Modeling Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Soorok Ryu, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos
Institute for ECHO Articles and Research
The recent decades have seen an increasing academic interest in leveraging machine learning approaches to nowcast, or forecast in a highly short-term manner, precipitation at a high resolution, given the limitations of the traditional numerical weather prediction models on this task. To capture the spatiotemporal associations of data on input variables, a deep learning (DL) architecture with the combination of a convolutional neural network and a recurrent neural network can be an ideal design for nowcasting rainfall. In this study, a long short-term memory (LSTM) modeling structure is proposed with convolutional operations on input variables. To resolve the issue of …
Relocating Lubra Village And Visualizing Himalayan Flood Damages With Remote Sensing, Ronan Wallace, Yungdrung Tsewang Gurung, Ryan Kastner
Relocating Lubra Village And Visualizing Himalayan Flood Damages With Remote Sensing, Ronan Wallace, Yungdrung Tsewang Gurung, Ryan Kastner
Journal of Critical Global Issues
As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community-driven solutions. In Himalayan Mustang, Nepal, indigenous Lubra Village faces threats of increasing flash flooding. After every flood, residual muddy sediment hardens across the riverbed like concrete, causing the riverbed elevation to rise. As elevation increases, sediment encroaches on Lubra’s agricultural fields and homes, magnifying flood vulnerability. In the last monsoon season alone, the Lubra community witnessed floods swallowing several agricultural fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as …
Evaluating The Use Of Unpiloted Aerial Systems To Detect And Monitor Beech Bark Disease In New England Forests, Isabelle Lopez, Benjamin T. Fraser, Russell G. Congalton
Evaluating The Use Of Unpiloted Aerial Systems To Detect And Monitor Beech Bark Disease In New England Forests, Isabelle Lopez, Benjamin T. Fraser, Russell G. Congalton
The Geographical Bulletin
The American beech (Fagus grandifolia) plays a key role throughout eastern North American forests. However, beech bark disease (BBD) causes widespread mortality of beech trees. We investigated whether imagery collected using an unpiloted aerial system (UAS) could differentiate beech tree health. Reference data were collected from 140 beech trees in New Hampshire and were visually classified as having “no/trace damage,” “moderate damage,” or “heavy damage.” Multispectral imagery was collected from a UAS, and 44 image features were derived for each beech crown. We used machine learning to identify the importance of each feature in distinguishing between the three health classes …
Patterns Of Infringement, Risk, And Impact Driven By Coal Mining Permits In Indonesia, Tim T. Werner, Tessa Toumbourou, Victor Maus, Martin C. Lukas, Laura J. Sonter, Muhamad Muhdar, Rebecca K. Runting, Anthony J. Bebbington
Patterns Of Infringement, Risk, And Impact Driven By Coal Mining Permits In Indonesia, Tim T. Werner, Tessa Toumbourou, Victor Maus, Martin C. Lukas, Laura J. Sonter, Muhamad Muhdar, Rebecca K. Runting, Anthony J. Bebbington
Geography
Coal mining is known for its contributions to climate change, but its impacts on the environment and human lives near mine sites are less widely recognised. This study integrates remote sensing, GIS, stakeholder interviews and extensive review of provincial data and documents to identify patterns of infringement, risk and impact driven by coal mining expansion across East Kalimantan, Indonesia. Specifically, we map and analyse patterns of mining concessions, land clearing, water cover, human settlement, and safety risks, and link them with mining governance and regulatory infractions related to coal mining permits. We show that excessive, improper permit granting and insufficient …
Mapping And Spatial Analysis To Expand Rural Broadband Access, John C. Kostelnick, Jonathan B. Thayn, Koushik Sinha
Mapping And Spatial Analysis To Expand Rural Broadband Access, John C. Kostelnick, Jonathan B. Thayn, Koushik Sinha
Faculty Publications-- Geography, Geology, and the Environment
High-speed broadband internet access is a critically important issue for many aspects of daily life, yet populations in rural areas are often unserved or underserved with reliable internet connectivity. Expanding broadband internet coverage in rural areas may have significant economic potential, especially since it enables precision farming which in turn increases yields, particularly for row crops such as corn and soybeans. This paper introduces methods that utilize GIS spatial analysis and remote sensing to assist in efforts to expand rural broadband access using case study counties in Illinois. Specifically, the methods presented here: (1) quantify current cropland production as well …