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 …

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 …

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.

A Tale Of Two Working Landscapes, Sage C. Sutcliffe

Graduate Student Theses, Dissertations, & Professional Papers

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.

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.

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Urban Flood And Its Correlation With Built-Up Area In Semarang, Indonesia, Risty Khoirunisa, Bambang Darmo Yuwono

Smart City

The expansion of urban areas is closely related to environmental problems such as changes in land use, flooding, and land subsidence. Semarang is a city with reasonably rapid development and a high land change experiencing floods and land subsidence. This paper will discuss land transformation caused by urban growth and its implications. It uses a combination of geospatial techniques and cloud computing Google Earth Engine (GEE) to carry out mapping over a large area without being constrained by computer capabilities. This study found that the built-up area in 2010 occupied 36.27% of the city, and it went up to 59.79% …

Agricultural Groundcover Update October 2023, Justin Laycock

Natural resources published reports

Summary

• About 98% of the grainbelt had adequate vegetative groundcover (more than 50%) to prevent wind erosion in October 2023. This amount of groundcover is normal at the end of spring and pre-harvest in most areas.
• There was a larger than average area with 51–60% groundcover, and groundcover in these areas is expected to reduce over summer to below 50%.
• About 2% of the grainbelt (293,000 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 8% of this farmland had inadequate groundcover. …

Complex Impacts Of Wars On Global Sustainable Development In A Metacoupled World, Qutu Jiang, Zhenci Xu, Yuanzheng Cui, Jianguo Liu

I-GUIDE Forum

Wars and armed conflicts have had profound impacts on local and global sustainable development in an interconnected world. However, evidence on the impacts of wars is fragmented and little attention has been paid to the impacts on the 17 UN’s Sustainable Development Goals (SDGs), a unifying framework for achieving global sustainable development. This perspective synthesizes the scattered information to provide a holistic analysis and highlight the applications of remote sensing in assessing the impacts of wars on global sustainable development in a metacoupling world. Wars have complex impacts on all 17 SDGs, which cascade beyond conflict zones and spillover to …

The Challenge Of Misclassification Error In The European Union’S Deforestation Regulation, Caleb T. Gallemore

I-GUIDE Forum

The European Union’s Regulation 2023/1115, which requires firms to undertake significant due diligence efforts to minimize the import of deforestation-linked commodities into the Union, relies heavily on cutting-edge geospatial technologies. While several studies of zero-deforestation supply chain efforts have pointed to the political and logistical challenges such initiatives face, there has been less consideration of the role that the measurement errors that are unavoidable in geospatial technologies might affect emerging zero-deforestation governance systems. Using information on misclassification error rates for forest areas from 20 recent validation studies of global land-cover datasets, I simulate the misclassification risks we might expect from …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

Causes And Effects Of Shisper Glacial Lake Outburst Flood Event In Karakoram In 2022, Sandeep Kumar Mondal, Vatsal D. Patel, Rishikesh Bharti, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Karakoram Himalayas are vulnerable to glacial lake outburst floods (GLOFs), which cause catastrophic floods in the surrounding areas. The increasing natural and anthropogenic activities, especially in the Indo-Gangetic Plains at the southern flank of the towering Himalayas, could be the cause of climate change affecting the frequency of the natural hazards in the Himalayas. In the present study, a detailed analysis of the Shisper Lake breach of 7 May 2022 is carried out using satellite remote sensing. A decreasing trend in the glacial mass balance is observed between 2017 and 2021; in this period, frequent GLOF episodes occurred. A pronounced …

Analysis Of Normalized Difference Vegetation Index Change Of The West Bank, Palestine, Using Multitemporal Satellite Remote Sensing Data, Ahmed Ghodieh

An-Najah University Journal for Research - B (Humanities)

The West Bank is characterized by the diversity of its climate despite its small area. It includes four climatic regions:- a humid, semi-humid, arid, and semi-arid climate. This in turn affected the geographical distribution of vegetation cover seasonally and over the years. This study investigated changes in the West Bank, Palestine vegetation cover using multitemporal Landsat data. Four images were selected for this purpose – two corresponding to 2001 and the other two corresponding to 2021. Seasonal change of the Normalized Difference Vegetation Index (NDVI) was investigated for the acquired images. ArcGIS 10.8 software was used for image processing and …

Application Of Model-Based Time Series Prediction Of Infrared Long-Wave Radiation Data For Exploring The Precursory Patterns Associated With The 2021 Madoi Earthquake, Jingye Zhang, Ke Sun, Junqing Zhu, Ning Mao, Dimitar Ouzounov

Mathematics, Physics, and Computer Science Faculty Articles and Research

Taking the Madoi M_S 7.4 earthquake of 21 May 2021 as an example, this paper proposes using time series prediction models to predict the outgoing long-wave radiation (OLR) anomalies and study short-term pre-earthquake signals. Five time series prediction models, including autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM), were trained with the OLR time series data of the aseismic moments in the 5° × 5° spatial range around the epicenter. The model with the highest prediction accuracy was selected to retrospectively predict the OLR values during the aseismic period and before the earthquake in the area. It …

Structure-From-Motion Derived Snow Cover In Burned Forests Of The Western Oregon Cascades, Siobhan Ciafone

Dissertations and Theses

Forest fire occurrence in the western US has increased rapidly since the 1980s, and most western US fires occur in the seasonal snow zone. Burned forests influence snow accumulation and melt patterns for years following fire, and understanding drivers of variability in snow cover across a burned landscape at the basin-scale is necessary for accurate hazard prediction and water resource forecasting. Basin-scale surveys of snowpack are possible with remote sensing, but accurate sensing methods such as Light Detection and Ranging (LiDAR) are often cost-prohibitive. In the last decade, structure-from-motion (SfM), an optical remote sensing technique, has emerged as an affordable …

Demonstration Of Large Area Land Cover Classification With A One Dimensional Convolutional Neural Network Applied To Single Pixel Temporal Metric Percentiles, Hankui K. Zhang, David P. Roy, Dong Luo

GSCE Faculty Publications

Over large areas, land cover classification has conventionally been undertaken using satellite time series. Typically temporal metric percentiles derived from single pixel location time series have been used to take advantage of spectral differences among land cover classes over time and to minimize the impact of missing observations. Deep convolutional neural networks (CNNs) have demonstrated potential for land cover classification of single date images. However, over large areas and using time series their application is complicated because they are sensitive to missing observations and they may misclassify small and spatially fragmented surface features due to their spatial patch-based implementation. This …