Remote Sensing Commons^™

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 …

Agricultural Groundcover Update January 2024, Justin Laycock

Natural resources published reports

Summary

• About 94% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in January 2024.
• In the northern half of the grainbelt, a larger-than-average area has 51–60% groundcover, which is expected to decrease to below 50% over the coming months.
• Just under 6% of the grainbelt (855,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. West Midlands Ag Soil Zone had the highest risk of wind erosion and 14.5% of this farmland had inadequate groundcover.
• Less than 0.5% of the grainbelt had a high to very high risk of wind …

Inventory Of Western United States Glaciers- 2020, Shrinidhi Ambinakudige, Bernard Abubakari

CAS Publications

The dataset employed for delineating glacier boundaries in the Western United States comprises a compilation of original Sentinel-2 images obtained from the European Space Agency's Copernicus website. These images were instrumental in generating the glacier inventory. Additionally, the dataset includes a Python and R script specifically crafted for processing and classifying Sentinel images. The outcome of this process is represented in an ESRI shapefile, which contains an inventory of glaciers extracted from Sentinel images.

Spatial Analyses On Pre-Earthquake Ionospheric Anomalies And Magnetic Storms Observed By China Seismo-Electromagnetic Satellite In August 2018, Jann-Yeng Tiger Liu, Xuhui Shen, Fu-Yuan Chang, Yuh-Ing Chen, Yang-Yi Sun, Chieh‑Hung Chen, Sergey Pulinets, Katsumi Hattori, Dimitar Ouzounov, Valerio Tramutoli, Michel Parrot, Wei-Sheng Chen, Cheng-Yan Liu, Fei Zhang, Dapeng Liu, Xue-Min Zhang, Rui Yan, Qiao Wang

Mathematics, Physics, and Computer Science Faculty Articles and Research

The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric …

Evaluation Of Seven Satellite-Based And Two Reanalysis Global Terrestrial Evapotranspiration Products, Zijing Xie, Yunjun Yao, Qingxin Tang, Meng Liu, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Kun Jia, Yufu Li, Ke Shang, Bo Jiang, Junming Yang, Ruiyang Yu, Xueyi Zhang, Xiaozheng Guo, Lu Liu, Jing Ning, Jiahui Fan, Lilin Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Although comprehensive evaluation of different types of global terrestrial evapotranspiration (ET) products has been conducted, the satellite remote sensing techniques have prompted the development of several available global ET products, warranting a reassessment as products continue to evolve. Recently, we produced the long-term Global LAnd Surface Satellite (GLASS) ET product, but there is a lack of comparison and evaluation with other ET products and EC observations on a global scale. In this study, we evaluated the accuracy and uncertainty of seven satellite-based (GLASS-AVHRR, GLASS-MODIS, BESS, FLUXCOM, GLEAM, MOD16, and PML_V2) and two reanalysis (ERA5 and MERRA2) global terrestrial ET products …

Regional And Landscape Scale Examination And Attribution Of Vegetation Changes To Social-Environmental System Drivers In Kazakhstan, Venkatesh Kolluru

Dissertations and Theses

Kazakhstan (KZ) experienced widespread changes in ecosystem structure and function. The country is a climate and land cover/use change “hotspot” owing to political reforms, intensified grazing, and extreme climatic events. Despite their importance, there is a lack of consensus about vegetation changes, trends, and drivers in KZ. Addressing this knowledge gap is crucial for effectively managing and restoring grassland ecosystems. However, a pressing challenge is discerning anthropogenic-driven vegetation changes from climate variability and decomposing the responses to the complex human-environmental forcings. Motivated by these challenges, I employed statistical and machine learning algorithms to detect and attribute vegetation changes to social-environmental …

Near-Real-Time Monitoring Of Crop Progress At Field Scales By Fusing Observations From Both Polar-Orbiting And Geostationary Satellites, Yu Shen

Electronic Theses and Dissertations

No abstract provided.

Quantifying Structural Vegetation Change On Arctic Tundra: A Multi-Decadal Study Integrating Remotely Sensed Imagery And Traditional Field Measurements, Anna M. Moser

Graduate Student Theses, Dissertations, & Professional Papers

Arctic regions have experienced an amplified rate of climate warming in recent decades, contributing to well-documented increases in tundra vegetation productivity. Satellite remote sensing has historically played a crucial role in detecting and quantifying trends at regional and biome scales; however, coarse resolution imagery has proven insufficient for capturing fine-scale variability in vegetation response. Considering the spatial heterogeneity of tundra vegetation, high resolution, plot-scale remote sensing observations are necessary. This study couples traditional field measurements with high-resolution unmanned aerial vehicle (UAV) imagery and plane-based aerial photos to quantify changes in vegetation on the North Slope of Alaska over a 28-year …

Aboveground Biomass Density Estimation Using Deep Learning: Insight From Neon Ground-Truth Data And Simulated Gedi Waveform, Ashish Mahaur

Dissertations, Master's Theses and Master's Reports

Accurately estimating Aboveground Biomass Density (AGBD) is crucial for managing Earth's carbon cycle and informing climate strategies. NASA's GEDI mission advances global forest mapping, but traditional linear models often yield less reliable AGBD estimates. This study enhances AGBD estimation using deep learning models with NEON ground-truth data and simulated GEDI waveforms. We compared 1D CNNs, LSTMs, and pre-trained CNNs to traditional models. The ResNet152 model outperformed linear regression, achieving an R² of 0.68, demonstrating a 17% improvement. Our experiments also demonstrate the importance of large, diverse datasets, particularly for training deep learning models.

Investigating Flash Flood Occurrence Using Negative Binomial Models In Maryland, United States Of America, Zainab O. Akinsemoyin

College of Graduate Studies: Theses & Dissertations

Globally, as extreme weather patterns intensify, flash floods have emerged as one of the most destructive and immediate environmental threats. In Maryland, flash floods are particularly concerning due to its diverse topography and increasing urban development, which exacerbates runoff and overwhelms drainage systems. The state has experienced significant flash flood events, highlighting the need for effective models to manage risks and inform mitigation strategies. While regression models such as the Negative Binomial (NB) and Zero-Inflated Negative Binomial (ZINB) are commonly used for count data analysis, their application to flash flood modeling in the USA, including regions like Maryland, remains limited …

Lidar Remote Sensing And The Monitoring Of Brazilian Amazon Forest Structure: Tackling Issues And Finding New Possibilities, Pedro Valle De Carvalho E Oliveira

Electronic Theses and Dissertations

The Amazon is the largest tropical forest in the world and around 60% of it is in Brazil. The amount of carbon stored in the region uncertain, the impacts of land use and climate changes are unknown, and what drives the dynamic of the forest structure is still under a heated debate. Optical remote sensing has been used for a long time to assist the monitoring of the Brazilian Amazon. However, optical remote sensing only allows a comprehensive study from the top of the forest canopy. In contrast, lidar remote sensing of forests can produce robust information regarding the canopy …

A Tale Of Two Working Landscapes, Sage C. Sutcliffe

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

Road Extraction On Remote Sensing Imagery: Historical Mapping Of The Brazilian Amazon, Jonas Paiva Botelho Jr

Graduate Theses/Dissertations

This work proposes an artificial intelligence model based on U-Net architecture to map road networks in the Brazilian Amazon. Over the years, the Amazon region has been heavily exploited, leading to increased deforestation rates, contributing to CO2 emissions, amplifying global warming, and causing a disturbance in local fauna and flora. The expansion into the forest by illegal miners, loggers, and land grabbers can be tracked down by the construction of roads, which we can refer to as the arteries of deforestation. Previous works on the matter proposed algorithms that use high-resolution imagery to map roads precisely. However, this work approach …

Agricultural Groundcover Update December 2023, Justin Laycock

Natural resources published reports

Summary

• About 96% of the grainbelt had adequate vegetative groundcover (more than 50%) to prevent wind erosion in December 2023.
• In the northern half of the grainbelt, a larger-than-average area has 51–60% groundcover, which is expected to decrease to below 50% over the summer.
• Just under 4% of the grainbelt (553,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. West Midlands Ag Soil Zone had the highest risk of wind erosion and 11.4% of this farmland had inadequate groundcover.
• Less than 0.5% of the grainbelt had a high to very high risk of wind erosion …

A Review Of Emerging Sensor Technologies For Tank Inspection: A Focus On Lidar And Hyperspectral Imaging And Their Automation And Deployment, Sergio Pallas Enguita, Chung-Hao Chen, Samuel Kovacic

Electrical & Computer Engineering Faculty Publications

This paper reviews various sensor technologies for tank inspection, focusing on Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) as advanced solutions for corrosion detection. These technologies are evaluated alongside traditional methods such as ultrasonic, electromagnetic, and thermographic inspections. This review highlights their potential to enhance inspection accuracy, reduce the limitations of manual inspection, and support integrated data analysis for comprehensive asset management. Additionally, this paper proposes a pathway for automating these techniques to streamline inspection processes and improve implementation in practical applications.

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 …

Optimizing Remote Sensing Approaches For Dryland Carbon Flux Estimation, Kamal Nyaupane

Open Access Theses & Dissertations

Dryland ecosystems account for 40% of the global land surface area and play a vital role in the global carbon cycle. Gross Primary Productivity (GPP) is crucial for carbon exchange between ecosystems and the atmosphere, serving as a fundamental determinant of the carbon balance. However, precise modeling of GPP in terrestrial ecosystems, especially drylands, remains a complex challenge. This research utilizes a decade long spectral reflectance dataset acquired with a robotic tram system to estimate GPP using Random Forest model. The research exceled in capturing the complex spatio-temporal dynamics of the study site. Notably, the RF model exhibited best performance …

Sc-Fuse: A Feature Fusion Approach For Unpaved Road Detection From Remotely Sensed Images, Aniruddh Saxena

School of Computing: Dissertations, Theses, and Student Research

Road network extraction from remote sensing imagery is crucial for numerous applications, ranging from autonomous navigation to urban and rural planning. A particularly challenging aspect is the detection of unpaved roads, often underrepresented in research and data. These roads display variability in texture, width, shape, and surroundings, making their detection quite complex. This thesis addresses these challenges by creating a specialized dataset and introducing the SC-Fuse model.

Our custom dataset comprises high resolution remote sensing imagery which primarily targets unpaved roads of the American Midwest. To capture the diverse seasonal variation and their impact, the dataset includes images from different …

Unraveling Water Quality Issues In The Colorado River Basin: Utilizing Remote Sensing Satellite Images, Statistical, And Machine Learning For Improved Monitoring, Godson Ebenezer Adjovu

UNLV Theses, Dissertations, Professional Papers, and Capstones

This research was aimed at exploring innovative and cost-effective tools in understanding the spatiotemporal variability of water quality parameters in the Colorado River Basin (CRB), which includes the Colorado River and major reservoirs and lakes in the USA including Lake Mead. The river which arises in the state of Colorado and empties into the Republic of Mexico at the Gulf of California, is a source of water to seven US states and the Republic of Mexico and provides water to about 40 million people and million acres of farmlands in seven states in the western US and the Republic of …

Agricultural Groundcover Update November 2023, Justin Laycock

Natural resources published reports

Summary

• About 98% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in November 2023. This amount of groundcover is normal for the middle of harvest.
• In the northern half of the grainbelt, a larger-than-average area had 51–60% groundcover, which is expected to decrease to below 50% over summer.
• Just over 2% of the grainbelt (324,000 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion. Mullewa to Morawa Ag Soil Zone had the highest risk of wind erosion and 9.7% of this farmland had inadequate groundcover.
• Less than 0.5% of the …