Remote Sensing Commons^™

Correlation Of Road Network Structure And Urban Mobility Intensity: An Exploratory Study Using Geo-Tagged Tweets, Li Geng, Ke Zhang

Publications and Research

Urban planners have been long interested in understanding how urban structure and activities are mutually influenced. Human mobility and economic activities naturally drive the formation of road network structure and the accessibility of the latter shapes the patterns of movement flow across urban space. In this paper, we perform an exploratory study on the relationship between the street network structure and the intensity of human movement in urban areas. We focus on two cities and we utilize a dataset of geo-tagged tweets that can form a proxy to urban mobility and the corresponding street networks as obtained from OpenStreetMap. We …

Relative Importance Of Radar Variables For Nowcasting Heavy Rainfall: A Machine Learning Approach, Yi Victor Wang, Seung Hee Kim, Geunsu Lyu, Choeng-Lyong Lee, Gyuwon Lee, Ki-Hong Min, Menas C. Kafatos

Institute for ECHO Articles and Research

Highly short-term forecasting, or nowcasting, of heavy rainfall due to rapidly evolving mesoscale convective systems (MCSs) is particularly challenging for traditional numerical weather prediction models. To overcome such a challenge, a growing number of studies have shown significant advantages of using machine learning (ML) modeling techniques with remote sensing data, especially weather radar data, for high-resolution rainfall nowcasting. To improve ML model performance, it is essential first and foremost to quantify the importance of radar variables and identify pertinent predictors of rainfall that can also be associated with domain knowledge. In this study, a set of MCS types consisting of …

Possible Overestimation Of Nitrogen Dioxide Outgassing During The Beirut 2020 Explosion, Ashraf Farahat, Nayla El-Kork, Ramesh P. Singh, Feng Jing

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

On 4 August 2020, a strong explosion occurred near the Beirut seaport, Lebanon and killed more than 200 people and damaged numerous buildings in the vicinity. As Amonium Nitrate (AN) caused the explosion, many studies claimed the release of large amounts of NO₂ in the atmosphere may have resulted in a health hazard in Beirut and the vicinity. In order to reasonably evaluate the significance of NO₂ amounts released in the atmosphere, it is important to investigate the spatio-temporal distribution of NO₂ during and after the blast and compare it to the average day-to-day background emissions from …

Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace

Mathematics, Statistics, and Computer Science Honors Projects

As weather patterns change worldwide, isolated communities impacted by climate change go unnoticed and we need community and habitat-conscious solutions. In Himalayan Mustang, Nepal, indigenous Lubra village faces threats of increasing flash flooding. After every flood, residual concrete-like sediment hardens across the riverbed, 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 village witnessed floods swallowing several fields and damaging two homes. One solution considers relocating the village to a new location entirely. However, relocation poses a challenging task, as eight centuries …

Studying Factors Of Environmental Injustice And Ways To Achieve Equity, Arham Hussain, Reginald Metellus

Publications and Research

In today's day of age, the biggest concern for current and future generations: the environment. The urban heat island (UHi) with its significant energy, health, and societal impacts is among the major environmental issues in urban regions, especially in historically underserved and socially vulnerable communities (HUSVCs). In the 1930s, the former federal agency, Homeowners' Loan Corporation (H0Lq, created ''Residential Security" maps of major cities, known today as "redlined" areas. These neighborhoods were often designated as "hazardous" due to the high percentages of people of color living there, leading to systematic disinvestment based on race. While the program ended in 1968, …

Systematic Review Of A Ramsar Wetland And Unesco Biosphere Reserve In A Climate Change Hotspot (Ichkeul Lake, Tunisia), Sabrine Sahbani, Béchir Béjaoui, Sihem Benabdalla, Rachid Toujani, Afef Fathalli, Noureddine Zaaboub, Jalel Aouissi, Zeineb Kassouk, Nabil Hamdi, Nabiha Ben Mbarek, Hechmi Missaoui, Leila Basti, Reginald Blake, Hamidreza Norouzi

Publications and Research

Tunisia's Ichkeul Lake is among the most productive ecosystems in the Mediterranean, with a great regional value thanks to its diversity of habitats. It is an important overwintering area for waterfowl species. It is a RAMSAR wetland, a National Park, a UNESCO World Heritage, and a Biosphere Reserve. This review paper provides a broad overview of the climatic, hydraulic, biogeochemical features, bio-resources, and bio-productivity of the Lake. The interconnectivity between the different environmental components of the lake is presented, highlighting the main characteristics of this vital ecosystem. Its ecosystem consists of a permanent lake bordered by temporary marshes. It is …

Meteor Radar Vertical Wind Observation Biases And Mathematical Debiasing Strategies Including The 3dvar+Div Algorithm, Alan Z. Liu, Zishun Qiao, Gunter Stober, Alexander Kozlovsky, Ales Kuchar, Christoph Jacobi, Chris Meek, Diego Janches, Guiping Liu, Masaki Tsutsumi, Njål Gulbrandsen, Satonori Nozawa, Mark Lester, Evgenia Belova, Johan Kero, Nicholas Mitchell

Publications

Meteor radars have become widely used instruments to study atmospheric dynamics, particularly in the 70 to 110 km altitude region. These systems have been proven to provide reliable and continuous measurements of horizontal winds in the mesosphere and lower thermosphere. Recently, there have been many attempts to utilize specular and/or transverse scatter meteor measurements to estimate vertical winds and vertical wind variability. In this study we investigate potential biases in vertical wind estimation that are intrinsic to the meteor radar observation geometry and scattering mechanism, and we introduce a mathematical debiasing process to mitigate them. This process makes use of …

Spatio-Temporal Changes In Vegetation In The Last Two Decades (2001–2020) In The Beijing–Tianjin–Hebei Region, Yuan Zou, Wei Chen, Siliang Li, Tiejun Wang, Le Yu, Min Xu, Ramesh P. Singh, Cong-Qiang Liu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In terrestrial ecosystems, vegetation is sensitive to climate change and human activities. Its spatial-temporal changes also affect the ecological and social environment. In this paper, we considered the Beijing–Tianjin–Hebei region to study the spatio-temporal vegetation patterns. The detailed analysis of a moderate-resolution imaging spectroradiometer (MODIS) data were carried out through the Google Earth Engine (GEE) platform. Our results show a slow and tortuous upward trend in the average leaf area index (LAI) in the study region for the periods 2001–2020. Specifically, Beijing had the highest LAI value, with an average of 1.64 over twenty years, followed by Hebei (1.30) and …

Titaniferous-Vanadiferous, Magnetite-Ilmenite Mineralization In A Mafic Suite Within The Chhotanagpur Gneissic Complex, Bihar, India, Ashmeer Mohammad, Anup K. Prasad, Kehe-U Wetsah, Mohammad Azad, Vivek Aryan, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Titanium or vanadium metals or their alloys are important industrial metals/alloys. Because these resources are in short supply, the investigation of potential titaniferous-vanadiferous deposits needs special attention to bridge the supply-demand gap. The study integrates geological, geochemical, remote sensing, and geophysical data for assessing the potentiality of titaniferous-vanadiferous, magnetite-ilmenite mineralization in and around the Sudamakund and Paharpur areas, Gaya and Jehanabad districts, Bihar, India, and delineation of specific targets for detailed exploration. Field visits for large scale mapping on (1:12,500 scale) were used to conduct a reconnaissance survey for magnetite-ilmenite mineralization in parts of toposheet number 72G/04 in the Gaya …

Response Of Surface And Atmospheric Parameters Associated With The Iran M 7.3 Earthquake, Feng Jing, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Multiparameter observed from satellite, including microwave brightness temperature, skin temperature, air temperature, and carbon monoxide, have been analyzed to identify the anomalous signals associated with the M 7.3 Iran earthquake of November 12, 2017. Besides removing the multiyear variability of parameters as background, the effect of surface and atmosphere of a dust storm event in Middle East region during October 29–November 1 is considered to distinguish the possible anomalies associated with the earthquake. The characteristic behaviors of surface and atmospheric parameters clearly show the signals associated with the M 7.3 earthquake and the dust storm event. The multiple parameters at …

Differentiating Fissure-Fed Lava Flow Types And Facies Using Radar And Lidar: An Example From The 2014–2015 Holuhraun Lava Flow-Field, Gavin Douglas Tolometti, Catherine D. Neish, Christopher W. Hamilton, Gordon R. Osinski, Antero Kukko, Joana R.C. Voigt

Earth Sciences Publications

Distinguishing between lava types and facies using remote sensing data is important for interpreting the emplacement history of lava flow-fields on Earth and other planetary bodies. Lava facies typically include a mixture of lava types and record the collective emplacement history of material preserved at a particular location. We seek to determine if lava facies in the 2014–2015 Holuhraun lava flow-field are discernible using radar roughness analysis. Furthermore, we also seek to distinguish between lava types using high resolution Light Detection and Ranging (LiDAR) data. We extracted circular polarization ratios (CPR) from the Uninhabited Aerial Vehicle Synthetic Aperture Radar and …

Machine Learning With Kay, Lasith Niroshan, James Carswell

Conference Papers

Computational power is very important when training Deep Learning (DL) models with large amounts of data (Wooldridge, 2021). Hence, High-Performance Computing (HPC) can be leveraged to reduce computational cost, and the Irish Centre for High-End Computing (ICHEC) provides significant infrastructure and services for research and development to both academia and industry. A portion of ICHEC's HPC system has been allocated for institutional access, and this paper presents a case study of how to use Kay (Ireland's national supercomputer) in the remote sensing domain. Specifically, this study uses clusters of Kay Graphics Processing Units (GPUs) for training DL models to extract …

Pronounced Changes In Thermal Signals Associated With The Madoi (China) M 7.3 Earthquake From Passive Microwave And Infrared Satellite Data, Feng Jing, Lu Zhang, Ramesh P. Singh

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Thermal variations in surface and atmosphere observed from multiple satellites prior to strong earthquakes have been widely reported ever since seismic thermal anomalies were discovered three decades ago. These thermal changes are related to stress accumulation caused by the tectonic activities in the final stage of earthquake preparation. In the present paper, we focused on the thermal changes associated with the 2021 Madoi M 7.3 earthquake in China and analyzed the temporal and spatial evolution of the Index of Microwave Radiation Anomaly (IMRA) and the Index of Longwave Radiation Anomaly (ILRA) based on 8-year microwave brightness temperature (MWBT) and 14-year …

Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder

2022 Symposium

EWU contains a variety of deciduous and evergreen trees across its campus, providing several benefits. However, no comprehensive record exists of the total number, location, species, or ages of these trees. This knowledge can inform facilities of proper care for individual trees and can be used to estimate carbon sequestration on campus. Traditional on-the-ground methods for assessing trees require tree cores or clinometers, making trees susceptible to pests or disease and leading to inaccurate results. Remote sensing using lidar data is a noninvasive, more precise method to measure tree height and subsequently assess tree age. This poster explores using point …

Remote Sensing & Land Surface Temperature From Satellite Observations, Isatu Jollah

Publications and Research

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is designed and developed in 1995. • It is a critical instrument aboard Terra and Aqua satellites. Terra's orbit around the Earth is timed so that it crosses the equator from north to south in the morning, while Aqua crosses the equator from south to north in the afternoon. • Every 1 to 2 days, Terra MODIS and Aqua MODIS scan the entire Earth's surface, collecting data in groups of wavelengths. • In this research, a whole month of MODIS Land Surface Temperature data from both Aqua and Terra were explored and investigated.

Lake Satellite Temperature Data Validation, Mamadou Balde, Pascal Kouogang

Publications and Research

In environmental remote sensing, satellite data isn't absolutely conclusive, for that reason, there is a natural need to verify the data acquired from the satellite. The most suitable tool to achieve such verification is on ground sensors that have the advantage of proximity. Addressing any possible discrepancies between the satellite data and the ground sensor data is sure to yield ways to come up with improvements of satellite band calibration and sensing capabilities. This research focused on correlating temperature data from the MODIS satellite with the data obtained from the In Situ sensor located in Lake Sunapee. Doing the latter …

Multi-Criteria Evaluation Model For Classifying Marginal Cropland In Nebraska Using Historical Crop Yield And Biophysical Characteristics, Andrew Laws

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

Marginal cropland is suboptimal due to historically low and variable productivity and limiting biophysical characteristics. To support future agricultural management and policy decisions in Nebraska, U.S.A, it is important to understand where cropland is marginal for its two most economically important crops: corn (Zea mays) and soybean (Glycine max). As corn and soybean are frequently planted in a crop rotation, it is important to consider if there is a relationship with cropland marginality. Based on the current literature, there exists a need for a flexible yet robust methodology for identifying marginal land at different scales, which …

Land And Water Resources For Irrigated Agriculture In The Pilbara, Paul Galloway, John A. Simons, Karen Holmes, Dennis Van Gool

Resource management technical reports

This report documents the procedures used to identify suitable locations for irrigation development in the Pilbara region. It is the first study to investigate the potential for irrigated agriculture across the Pilbara. We used a desktop analysis to ascertain water availability and spatial data modelling to determine the potential of the land and soil resource to support irrigated agriculture. This study was part of the Pilbara Hinterland Agricultural Development Initiative (PHADI).

We used existing rangeland land inventory information augmented with digital spatial environmental data, in a process known as map disaggregation, to create soil and landform maps that had a …

Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …

Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam

Faculty Publications

Lack of instrument sensitivity to low electron density (N_e) concentration makes it difficult to measure sharp N_e vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region N_e from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …

Accuracy Assessment, Comparative Performance, And Enhancement Of Public Domain Digital Elevation Models (Aster 30 M, Srtm 30 M, Cartosat 30 M, Srtm 90 M, Merit 90 M, And Tandem-X 90 M) Using Dgps, Kumari Preety, Anup K. Prasad, Atul K. Varma, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Publicly available Digital Elevation Models (DEM) derived from various space-based platforms (Satellite/Space Shuttle Endeavour) have had a tremendous impact on the quantification of landscape characteristics, and the related processes and products. The accuracy of elevation data from six major public domain satellite-derived Digital Elevation Models (a 30 m grid size—ASTER GDEM version 3 (Ast30), SRTM version 3 (Srt30), CartoDEM version V3R1 (Crt30)—and 90 m grid size—SRTM version 4.1 (Srt90), MERIT (MRT90), and TanDEM-X (TDX90)), as well as the improvement in accuracy achieved by applying a correction (linear fit) using Differential Global Positioning System (DGPS) estimates at Ground Control Points (GCPs) …

High Resolution, Annual Maps Of Field Boundaries For Smallholder-Dominated Croplands At National Scales, Lyndon D. Estes, Su Ye, Lei Song, Boka Luo, J. Ronald Eastman, Zhenhua Meng, Qi Zhang, Dennis Mcritchie, Stephanie R. Debats, Justus Muhando, Angeline H. Amukoa, Brian W. Kaloo, Jackson Makuru, Ben K. Mbatia, Isaac M. Muasa, Julius Mucha, Adelide M. Mugami, Judith M. Mugami, Francis W. Muinde, Fredrick M. Mwawaza, Jeff Ochieng, Charles J. Oduol, Purent Oduor, Thuo Wanjiku, Joseph G. Wanyoike, Ryan B. Avery, Kelly K. Caylor

Geography

Mapping the characteristics of Africa’s smallholder-dominated croplands, including the sizes and numbers of fields, can provide critical insights into food security and a range of other socioeconomic and environmental concerns. However, accurately mapping these systems is difficult because there is 1) a spatial and temporal mismatch between satellite sensors and smallholder fields, and 2) a lack of high-quality labels needed to train and assess machine learning classifiers. We developed an approach designed to address these two problems, and used it to map Ghana’s croplands. To overcome the spatio-temporal mismatch, we converted daily, high resolution imagery into two cloud-free composites (the …

Landslide Detection In The Himalayas Using Machine Learning Algorithms And U-Net, Sansar Raj Meena, Lucas Pedrosa Soares, Carlos H. Grohmann, Cees Van Westen, Kushanav Bhuyan, Ramesh P. Singh, Mario Floris, Filippo Catani

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Event-based landslide inventories are essential sources to broaden our understanding of the causal relationship between triggering events and the occurring landslides. Moreover, detailed inventories are crucial for the succeeding phases of landslide risk studies like susceptibility and hazard assessment. The openly available inventories differ in the quality and completeness levels. Event-based landslide inventories are created based on manual interpretation, and there can be significant differences in the mapping preferences among interpreters. To address this issue, we used two different datasets to analyze the potential of U-Net and machine learning approaches for automated landslide detection in the Himalayas. Dataset-1 is composed …

Spatial Downscaling Of Goes-R Land Surface Temperature Over Urban Regions: A Case Study For New York City, Abdou Bah, Hamidreza Norouzi, Satya Prakash, Reginald Blake, Reza Khanbilvardi, Cynthia Rosenzweig

Publications and Research

The surface urban heat island (SUHI) effect is among the major environmental issues encountered in urban regions. To better predict the dynamics of the SUHI and its impacts on extreme heat events, an accurate characterization of the surface energy balance in urban regions is needed. However, the ability to improve understanding of the surface energy balance is limited by the heterogeneity of surfaces in urban areas. This study aims to enhance the understanding of the urban surface energy budget through an innovation in the use of land surface temperature (LST) observations from remote sensing satellites. A LST database with 5–min …

Snow Cover Variability And Trend Over The Hindu Kush Himalayan Region Using Modis And Srtm Data, Nirasindhu Desinayak, Anup K. Prasad, Hesham El-Askary, Menas Kafatos, Ghassem R. Asrar

Mathematics, Physics, and Computer Science Faculty Articles and Research

Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic changes in the intra-annual (accumulating season and melting season) and interannual variations in …

A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

Sporadic-E (E_s) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques for detecting E_s formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate E_s occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site …

Editorial: Geospace Observation Of Natural Hazards, Dimitar Ouzounov, Jann-Yenq Liu, Patrick T. Taylor, Katsumi Hattori

Mathematics, Physics, and Computer Science Faculty Articles and Research

"This collection of technical papers aims to bring recent data from many sources into the study of natural hazards. They represent a multi-instrumental approach using both ground observations: Global Navigation Satellite System (GNSS); and Low Earth Orbiting Electromagnetic (LEO EM) satellites missions together with Earth Observations (EO), which could reveal new information. Results from latest satellite missions, [(NPP/NASA/NOAA(US), CENTINEL, Swarm/ESA (EU), HIMAWARI (JMA, Japan), FORMOSAT-5 (Taiwan, August 2017), CSES1 (China/Italy, Feb 2018), and FORMOSAT-7/COSMIC-2 (Taiwan/United States, May 2019)], are represented in this volume."

Catastrophic Ice-Debris Flow In The Rishiganga River, Chamoli, Uttarakhand (India), Vijendra Kumar Pandey, Rajesh Kumar, Rupendra Singh, Rajesh Kumar, Suresh Chand Rai, Ramesh P. Singh, Arun Kumar Tripathi, Vijay Kumar Soni, S. Nawaz Ali, Dakshina Tamang, Syed Umer Latief

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

A catastrophic flood occurred on 7 February 2021 around 10:30 AM (local time) in the Rishiganga River, which has been attributed to a rockslide in the upper reach of the Raunthi River. The Resourcesat 2 LISS IV (8 February 2021) and CNES Airbus satellite imagery (9 February 2021) clearly show the location of displaced materials. The solar radiation observed was higher than normal by 10% and 25% on 6 and 7 February 2021, respectively, however, the temperature shows up to 34% changes. These conditions are responsible for the sudden change in instability in glacier blocks causing deadly rock-ice slides that …

Probabilistic Tracking Of Annual Cropland Changes Over Large, Complex Agricultural Landscapes Using Google Earth Engine, Sitian Xiong, Priscilla Baltezar, Morgan A. Crowley, Michael Cecil, Stefano C. Crema, Eli Baldwin, Jeffrey A. Cardille, Lyndon Estes

Geography

Cropland expansion is expected to increase across sub-Saharan African (SSA) countries in the next thirty years to meet growing food needs across the continent. These land transformations will have cascading social and ecological impacts that can be monitored using novel Earth observation techniques that produce datasets complementary to national cropland surveys. In this study, we present a flexible Bayesian data synthesis workflow on Google Earth Engine (GEE) that can be used to fuse optical and synthetic aperture radar data and demonstrate its ability to track agricultural change at national scales. We adapted the previously developed Bayesian Updating of Land Cover …

Forging Ahead And Adapting To Change: A Review Of The Initiatives Of The Isprs Student Consortium, Sheryl Rose C. Reyes, Charmaine A. Cruz

SOSE Affiliate: Manila Observatory

The International Society for Photogrammetry and Remote Sensing Student Consortium (ISPRS SC) is an international organization that represents a constituency of the students and the young professionals with common interests and goals within ISPRS in the areas of photogrammetry, remote sensing and spatial information science. The ISPRS SC Board of Directors strengthened the organization’s foundations and increased its engagement in the Society from 2016 to 2022. Given the current global health crisis, selected members of the Board of Directors continued to serve in the ISPRS SC for a two-year extension and developed creative strategies in navigating the new normal. Building …