Geography Commons^™

Community Conservation In Madagascar: Aligning Local Livelihoods And Biodiversity Protection, Jane Slentz-Kesler

Geography Honors Projects

The management of natural resources in developing countries is of utmost importance as both high levels of biodiversity and local livelihoods often hang in the balance. The debate in conservation spheres often centers on 'fortress' versus 'community-based' conservation approaches, one emphasizing nature preservation and the other emphasizing the needs and empowerment of local communities in resource management. This study evaluates the management approach of a rainforest in northeast Madagascar, asking: how effectively does the COMATSA Sud protected area management system both preserve critical forest cover and provide for the local community? This research employs a mixed-methods approach, using interviews and …

Net Fluxes Of Broadband Shortwave And Photosynthetically Active Radiation Complement Ndvi And Near Infrared Reflectance Of Vegetation To Explain Gross Photosynthesis Variability Across Ecosystems And Climate, Kanishka Mallick, Joseph Verfaillie, Tianxin Wang, Ariane Arias Ortiz, Daphne Szutu, Koong Yi, Yanghui Kang, Robert Shortt, Tian Hu, Mauro Sulis, Zoltan Szantoi, Gilles Boulet, Joshua B. Fisher, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A significant challenge in global change research is understanding how vegetation interacts with the environment to influence ecosystem gross primary productivity (GPP) through carbon assimilation. One emerging objective is to consistently predict GPP fluctuations worldwide by establishing a robust scaling relationship between GPP measured at flux towers and satellite spectral reflectance data. However, a major hurdle in achieving this goal is the discrepancy in spatial resolution between early satellite measurements and eddy flux measurements. By using a large set of growing season data covering 100 site-years in North and Central America, we explored the potential of transforming incident and reflected …

Characteristic Of Dual Polarization Sentinel-1 For Estimation Of Seawater Intrusion On Kalianda Coast, South Lampung: A Preliminary Study, Choirunnisa Salsabila, Mochamad Firman Ghazali, Ananda Dermawan, Lauditta Zahra, Ni Made Mega Melliana, Mila Aulia

Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)

Seawater intrusion can increase soil salinity, which occurs due to flooding, evaporation, and land cover changes in coastal areas. This research aims to map and observe the characteristics of seawater intrusion in Way Urang, Kalianda, South Lampung, using Dual-polarization of Sentinel-1 SAR imagery with VV, VH, VV+VH, and (VV+VH)/2 polarization. There were 28 samples used in this research which were divided into two types, GCP (ground control point) and ICP (independent check point). GCP samples are used to create a seawater intrusion estimation model using the regression method, while ICP samples are used to test the validation model using the …

Changes In Chili Value Chain In Gunungkidul Regency Due To Covid-19 Pandemic, Muhammad Vitra Ramadhan, Widyawati Sumadio

Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)

This study explored the changes in the chili value chain in Gunungkidul Regency due to the COVID-19 pandemic. This study used a qualitative approach by conducting in-depth interviews with chili farmers, collectors, traders, and buyers in Gunungkidul Regency. The research results show that the COVID-19 pandemic has affected all stages of the chili value chain in Gunungkidul Regency. The actors in the chili value chain in Gunungkidul Regency have successfully adapted to face disruptions due to the COVID-19 pandemic by using information technology to communicate between actors and obtain market price information. Before the pandemic, Gunungkidul Regency was one of …

Assessment Site Attraction In Gunung Mas Agrotourism, Bogor Regency, West Java, Sarah Putri Fitriani, Masita Dwi Mandini Manessa, Mangapul Parlindungan Tambunan, Rudy Parluhutan Tambunan

Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)

Gunung Mas Agrotourism is a sub-unit managed by PT Perkebunan Nusantara VIII (PTPN VIII) under the management of Agrotourism and is the largest contributor to PTPN VIII's revenue, which is 70% and most of it comes from the tourism sector. The facilities and activities offered by Gunung Mas Agrotourism also vary, from lodging, restaurants, tourist attractions, and supporting facilities to meet the tourists' needs. To find out the magnitude of tourist interest in tourist attractions, an analysis of the attractiveness of tourist attractions is needed. This study aims to assess tourist attractions based on tourist preferences as well as the …

Kinematic And Dynamic Structure Of The 18 May 2020 Squall Line Over South Korea, Wishnu Agum Swastiko, Chia-Lun Tsai, Seung Hee Kim, Gyuwon Lee

Institute for ECHO Articles and Research

The diagonal squall line that passed through the Korean Peninsula on the 18 May 2020 was examined using wind data retrieved from multiple Doppler radar synthesis focusing on its kinematic and dynamic aspects. The low-level jet, along with warm and moist air in the lower level, served as the primary source of moisture supply during the initiation and formation process. The presence of a cold pool accompanying the squall line played a role in retaining moisture at the surface. As the squall line approached the Korean Peninsula, the convective bands in the northern segment (NS) and southern segment (SS) of …

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 …

Remote, Rugged Field Scenarios For Archaeology And The Field Sciences: Object Avoidance And 3d Flight Planning With Suas Photogrammetry, Carla Klehm, Malcolm D. Williamson, Leland C. Bement, Brandi Bethke

Center for Advanced Spatial Technologies Publications and Presentations

Advances built into recent sUASs (drones) offer a compelling possibility for field-based data collection in logistically challenging and GPS-denied environments. sUASs-based photogrammetry generates 3D models of features and landscapes, used extensively in archaeology as well as other field sciences. Until recently, navigation has been limited by the expertise of the pilot, as objects, like trees, and vertical or complex environments, such as cliffs, create significant risks to successful documentation. This article assesses sUASs’ capability for autonomous obstacle avoidance and 3D flight planning using data collection scenarios carried out in Black Mesa, Oklahoma. Imagery processed using commercial software confirmed that the …

Agricultural Groundcover Update February 2024, Justin Laycock

Natural resources published reports

• About 92% of the grainbelt had adequate (more than 50%) vegetative groundcover to prevent wind erosion in February 2024.

• Nearly 8% of the grainbelt (1,193,400 ha) had less than 50% groundcover, which is inadequate to prevent wind erosion.

• The northern grainbelt had the highest risk of wind erosion and 16.5% of this farmland had inadequate groundcover.

• Less than 0.7% of the grainbelt had a high to very high risk of wind erosion because groundcover was less than 30%.

Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang

Electrical & Computer Engineering Theses & Dissertations

The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …

Spatiotemporal Changes Of Urban Growth And Particulate Matter2.5 Concentrations: A Regional Study Using Gis-Remote Sensing Techniques, Mizanur Rahman

Masters Theses

Rapid urbanization and its environmental repercussions present profound challenges for developing countries. This study investigates the spatiotemporal relationship between urban growth and airborne particulate matter (PM_2.5) concentrations in four upazilas of Bangladesh from 2001 to 2019. Utilizing GIS and remote sensing techniques, this research explores the transitions in land cover and their impact on air quality, focusing on the escalating levels of PM_2.5 — a critical pollutant associated with numerous health risks. The study delineated land cover changes using satellite imagery; PM_2.5 concentration levels were derived from NASA's Socioeconomic Data and Applications Center while ground-truthing validated …

Ground Electric Field, Atmospheric Weather And Electric Grid Variations In Northeast Greece Influenced By The March 2012 Solar Activity And The Moderate To Intense Geomagnetic Storms, Georgios Anagnostopoulos, Anastasios Karkanis, Athanasios Kampatagis, Panagiotis Marhavilas, Sofia-Anna Menesidou, Dimitrios Efthymiadis, Stefanos Keskinis, Dimitar Ouzounov, Nick Hatzigeorgiu, Michael Danakis

Mathematics, Physics, and Computer Science Faculty Articles and Research

In a recent paper, we extended a previous study on the solar solar influence to the generation of the March 2012 heatwave in the northeastern USA. In the present study we check the possible relationship of solar activity with the early March 2012 bad weather in northeast Thrace, Greece. To this end, we examined data from various remote sensing instrumentation monitoring the Sun (SDO satellite), Interplanetary space (ACE satellite), the Earth’s magnetosphere (Earth-based measurements, NOAA-19 satellite), the top of the clouds (Terra and Aqua satellites), and the near ground atmosphere. Our comparative data analysis suggests that: (i) the winter-like weather …

Utilizing Hyperspectral Remote Sensing For Saline Soil Assessment In The Emirate Of Abu Dhabi, United Arab Emirates, Alya Hassan Aldhaheri

Theses

This study presents the application of hyperspectral remote sensing techniques to measure soil salinity. Soil salinity is a major concern in many arid and semi-arid regions, affecting crop productivity and ecosystem health. In most arid and semi-arid areas various levels of salinity can be encountered including sabkhas. Sabkha (salt flat) is a geological feature composed of saline and salt marshes that typically occur in shallow or coastal environments within arid and semi-arid climates. Traditional methods of measuring soil salinity are time-consuming and labor-intensive, making remote sensing techniques an attractive alternative. This study employed a hyperspectral sensor specifically the SVC-XHR-1024i to …

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 …

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 …

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 …

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 …

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 …

A Tale Of Two Working Landscapes, Sage C. Sutcliffe

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

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 …

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 …