Remote Sensing Commons^™

Climatological Trends And Effects Of Aerosols And Clouds On Large Solar Parks: Application Examples In Benban (Egypt) And Al Dhafrah (Uae), Harshal Dhake, Panagiotis Kosmopoulos, Antonis Mantakas, Yashwant Kashyap, Hesham El-Askary, Omar Elbadawy

Mathematics, Physics, and Computer Science Faculty Articles and Research

Solar energy production is vastly affected by climatological factors. This study examines the impact of two primary climatological factors, aerosols and clouds, on solar energy production at two of the world’s largest solar parks, Benban and Al Dhafrah Solar Parks, by using Earth observation data. Cloud microphysics were obtained from EUMETSAT, and aerosol data were obtained from the CAMS and assimilated with MODIS data for higher accuracy. The impact of both factors was analysed by computing their trends over the past 20 years. These climatological trends indicated the variations in the change in each of the factors and their resulting …

Coupling Between Evapotranspiration, Water Use Efficiency, And Evaporative Stress Index Strengthens After Wildfires In New Mexico, Usa, Ryan C. Joshi, Annalise Jensen, Madeleine Pascolini-Campbell, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

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Challenges And Future Directions In Quantifying Terrestrial Evapotranspiration, Koong Yi, Gabriel B. Senay, Joshua B. Fisher, Lixin Wang, Kosana Suvočarev, Housen Chu, Georgianne W. Moore, Kimberly A. Novick, Mallory L. Barnes, Trevor F. Keenan, Kanishka Mallick, Xiangzhong Luo, Justine E. C. Missik, Kyle B. Delwiche, Jacob A. Nelson, Stephen P. Good, Xiangming Xiao, Steven A. Kannenberg, Arman Ahmadi, Tianxin Wang, Gil Bohrer, Marcy E. Litvak, David E. Reed, A. Christopher Oishi, Margaret S. Torn, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Terrestrial evapotranspiration is the second-largest component of the land water cycle, linking the water, energy, and carbon cycles and influencing the productivity and health of ecosystems. The dynamics of ET across a spectrum of spatiotemporal scales and their controls remain an active focus of research across different science disciplines. Here, we provide an overview of the current state of ET science across in situ measurements, partitioning of ET, and remote sensing, and discuss how different approaches complement one another based on their advantages and shortcomings. We aim to facilitate collaboration among a cross-disciplinary group of ET scientists to overcome the …

Challenges Of Using More Precise Temporal And Spatial Resolution Of Remote Sensing Data For Surface Water Quality Monitoring, Ivan Rykin

Dartmouth College Master’s Theses

Monitoring river suspended sediment concentration (SSC) is critical for environmental challenges such as understanding the fate of thawed permafrost sediment and its impact on global carbon cycling. However, traditional SSC monitoring using Landsat imagery is limited by spatial and temporal constraints, particularly for narrow rivers in cloudy and/or snowy regions.

This study investigates the use of higher spatial (3 m) and temporal (daily) resolution satellite imagery from the PlanetScope constellation to estimate SSC in remote rivers such as those in the Arctic. I compare the performance of PlanetScope’s spectral resolution (4 and 8 bands) with Landsat 7. Merging data from …

Conducting Structure-From-Motion (Sfm) Modeling Of Freshwater Environments Using Unpiloted Aerial Systems (Uas): Challenges And Lessons Learned, Benjamin T. Fraser, Christine L. Bunyon, Russell G. Congalton

Faculty Publications

The pairing of Unpiloted Aerial Systems (UAS) and Structure from Motion (SfM) has provided new capabilities for modeling freshwater environments. Applications of UAS-SfM range from water quality monitoring to the mapping of aquatic vegetation. The models produced provide users with the ability to analyze features at ultra-high-resolutions and across scales not easily achieved through in situ sampling. Despite the demonstrated benefits of UAS-SfM in freshwater and other natural resource disciplines, there remain fundamental technical challenges in the modeling of environments with homogenous surfaces (e.g., water). In this research, the effectiveness of several image collection and processing approaches for the modelling …

Seasonal Dynamics In Land Surface Temperature In Response To Land Use Land Cover Changes Using Google Earth Engine, Lei Feng, Sajjad Hussain, Narcisa G. Pricope, Sana Arshad, Aqil Tariq, Li Feng, Muhammad Mubeen, Rana Waqar Aslam, Mohammed S. Fnais, Wenzhao Li, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Changes in land use and land cover (LULC) are critical for evaluating global spatiotemporal trends, especially regarding climate change and urbanization. This study investigates the dynamics of Landsat surface temperature (LST) in response to LULC changes and their effects on the seasonal microclimate in Kasur District, Pakistan. Using the Google Earth Engine platform, we employed a random forest algorithm to detect LULC changes (cropland, forest, built-up, fallow, barren, and water) and analyze seasonal spectral indices from Landsat imagery for 1988, 2002, and 2022. Significant LULC changes were observed, including a 9.8% increase in built-up areas, a 4.2% decrease in cropland, …

An Automated Machine Learning Approach To The Retrieval Of Daily Soil Moisture In South Korea Using Satellite Images, Meteorological Data, And Digital Elevation Model, Nari Kim, Soo-Jin Lee, Eunha Sohn, Mija Kim, Seonkyeong Seong, Seung Hee Kim, Yangwon Lee

Institute for ECHO Articles and Research

Soil moisture is a critical parameter that significantly impacts the global energy balance, including the hydrologic cycle, land–atmosphere interactions, soil evaporation, and plant growth. Currently, soil moisture is typically measured by installing sensors in the ground or through satellite remote sensing, with data retrieval facilitated by reanalysis models such as the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and the Global Land Data Assimilation System (GLDAS). However, the suitability of these methods for capturing local-scale variabilities is insufficiently validated, particularly in regions like South Korea, where land surfaces are highly complex and heterogeneous. In contrast, artificial intelligence …

Key Largo Mangrove Population Monitoring: A Remote Sensing Analysis And Classification Methodology Review, David Lackajs

Geography and the Environment: Graduate Student Capstones

Mangrove forests are some of the world's most bio-diverse habitats, providing essential services to the surrounding coasts. Removal of these habitats has a devastating impact on the ecosystems within them. The Florida Keys are some of the last areas in the United States with extensive mangrove populations. One specific area, John Pennekamp Coral Reef State Park in Key Largo, has been under state protection since 1959. For that reason, mangrove forest habitats there are less fragmented. This study uses remotely sensed imagery to quantify and analyze mangrove populations in this area using two methods: sub-pixel analysis and supervised classification. The …

Aerialformer: Multi-Resolution Transformer For Aerial Image Segmentation, Taisei Hanyu, Kashu Yamazaki, Minh Tran, Roy A. Mccann, Haitao Liao, Chase Rainwater, Meredith Adkins, Jackson Cothren, Hoang Le

Industrial Engineering Faculty Publications and Presentations

When performing remote sensing image segmentation, practitioners often encounter various challenges, such as a strong imbalance in the foreground–background, the presence of tiny objects, high object density, intra-class heterogeneity, and inter-class homogeneity. To overcome these challenges, this paper introduces AerialFormer, a hybrid model that strategically combines the strengths of Transformers and Convolutional Neural Networks (CNNs). AerialFormer features a CNN Stem module integrated to preserve low-level and high-resolution features, enhancing the model’s capability to process details of aerial imagery. The proposed AerialFormer is designed with a hierarchical structure, in which a Transformer encoder generates multi-scale features and a multi-dilated CNN (MDC) …

Remotely Sensed Early Warning Of Algal Blooms In An Eastern Nebraska Reservoir: A Comparison Of Temporal And Spatial Indicators, Mercy Kipenda

School of Natural Resources: Dissertations, Theses, and Student Research

Cyanobacterial harmful algal blooms (CyanoHABs) detrimentally affect human, animal, and ecosystem health. Remotely sensed early warning systems for cyanoHABs in inland lakes could contribute to more proactive water quality monitoring and help mitigate negative impacts. Advances in freely available remote sensing imagery, with finer spatial, temporal, and spectral resolutions, present new opportunities for the development and comparative analysis of methods to detect sudden deterioration in lake water quality. In this thesis, I compared and tested for temporal and spatial early warning signals of cyanoHABs in field-based and remotely sensed datasets from 2019 to 2023 in Pawnee Lake in southeast Nebraska, …

A Comparative Analysis Of Openet For Evaluating Evapotranspiration In California Almond Orchards, Kyle Knipper, Martha Anderson, Nicholas Bambach, Forrest Melton, Zac Ellis, Yun Yang, John Volk, Andrew J. Mcelrone, William Kustas, Matthew Roby, Will Carrara, Sebastian Castro, Ayse Kilic, Joshua B. Fisher, Anderson Ruhoff, Gabriel B. Senay, Charles Morton, Sebastian Saa, Richard G. Allen

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in …

Agricultural Groundcover Update May 2024, Justin Laycock

Natural resources published reports

• In May, over 9% (1,410,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.3% (208,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%. Half of this land was in the West Midlands Ag Soil Zone.

Agricultural Groundcover Update April 2024, Justin Laycock

Natural resources published reports

• In April, over 12% (1,876,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.
• Northern grainbelt had the highest risk of wind erosion and over 26% of this farmland had inadequate groundcover, predominantly found on landscapes known for sandy soils.
• About 1.5% (238,900 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

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 …

Evaluation Of The Extent Of Floods In 2022 In Different Land Cover And Land Use Classes In Sindh Province, Pakistan Using Sentinel-1 And Sentinel-2 Imageries, Alina Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

Floods are one of the most frequent and most devastating natural disasters, which cause widespread destruction and pose significant risks to human life, infrastructure, and the environment. Advancement in remote sensing technologies and methodologies have demonstrated their efficacy in disaster-related applications, such as the detection, monitoring, and analysis of floods. This study explores the utilization of Synthetic Aperture Radar (SAR) and optical imagery for flood extent mapping and studying the extent of flood over various land cover and land use classes in Pakistan's Sindh province, utilizing the cloud computing power of Google Earth Engine. The change detection method identified extensive …

Agricultural Groundcover Update March 2024, Justin Laycock

Natural resources published reports

• In March, over 10% (1,577,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.

• The northern grainbelt had the highest risk of wind erosion and over 20% of this farmland had inadequate groundcover.

• About 1.3% (191,000 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

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 …

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%.

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 …

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 …

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.

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 …