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- Mathematics, Physics, and Computer Science Faculty Articles and Research (7)
- Electrical & Computer Engineering Faculty Publications (4)
- Biology, Chemistry, and Environmental Sciences Faculty Articles and Research (3)
- GSCE Faculty Publications (2)
- Geography (2)
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- Michigan Tech Publications (2)
- 2022 Symposium (1)
- Department of Geography: Dissertations, Theses, and Student Research (1)
- Electrical and Computer Engineering Faculty Publications and Presentations (1)
- Faculty Publications (1)
- Forestry and Natural Resources Faculty Publications (1)
- Institute for ECHO Articles and Research (1)
- KWRRI Research Reports (1)
- Land Cover Data for the Mississippi-Alabama Barrier Islands, 2010-2011 (1)
- Mathematics, Statistics, and Computer Science Honors Projects (1)
- OES Faculty Publications (1)
- School of Natural Resources: Dissertations, Theses, and Student Research (1)
- Student Scholar Symposium Abstracts and Posters (1)
- Supplementary Data and Tools (1)
Articles 1 - 30 of 33
Full-Text Articles in Physical Sciences and Mathematics
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
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 …
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
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 …
Utilizing Remote Sensing Technology To Relocate Lubra Village And Visualize Flood Damages, Ronan Wallace
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 …
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
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
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 …
Using Lidar To Estimate Carbon Sequestration Of Evergreen Trees At Eastern Washington University (Ewu) Campus, Cheney, Washington, Kristy A. Snyder
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 …
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 …
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …
Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li
Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li
Electrical & Computer Engineering Faculty Publications
Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t1 together with low-resolution images at a …
Earth Observation And Sustainable Development Goals, Ramesh P. Singh
Earth Observation And Sustainable Development Goals, Ramesh P. Singh
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
"Planet Earth is a dynamic body, which is home to 7.8 billion people, and strong interactions exist between the human population and the Earth’s different components (land, ocean, biosphere, cryosphere and atmosphere). The impacts of such interactions are observed from the day-to-day changes in weather, solar radiation, cloudy conditions, poor visibility, rainfall and frequency of natural hazards around the globe. The dynamic nature of the Earth is evident at the ocean coast through the ocean waves, the nature of these waves varies from day-to-day and also morning to evening. For example, the heights of waves can now be predicted through …
Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin
Remote Sensing Monitoring Of Vegetation Dynamic Changes After Fire In The Greater Hinggan Mountain Area: The Algorithm And Application For Eliminating Phenological Impacts, Zhibin Huang, Chunxiang Cao, Wei Chen, Min Xu, Yongfeng Dang, Ramesh P. Singh, Barjeece Bashir, Bo Xie, Xiaojuan Lin
Mathematics, Physics, and Computer Science Faculty Articles and Research
Fires are frequent in boreal forests affecting forest areas. The detection of forest disturbances and the monitoring of forest restoration are critical for forest management. Vegetation phenology information in remote sensing images may interfere with the monitoring of vegetation restoration, but little research has been done on this issue. Remote sensing and the geographic information system (GIS) have emerged as important tools in providing valuable information about vegetation phenology. Based on the MODIS and Landsat time-series images acquired from 2000 to 2018, this study uses the spatio-temporal data fusion method to construct reflectance images of vegetation with a relatively consistent …
A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee
A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee
Mathematics, Physics, and Computer Science Faculty Articles and Research
Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to …
Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell
Determining Remote Sensing Spatial Resolution Requirements For The Monitoring Of Harmful Algal Blooms In The Great Lakes, John Lekki, Eric Deutsch, Michael Sayers, Karl Bosse, Robert Anderson, Roger Tokars, Reid W. Sawtell
Michigan Tech Publications
Harmful algal blooms (HABs) have become a major health and environmental concern in the Great Lakes. In 2014, severe HABs prompted the State of Ohio to request NASA Glenn Research Center (GRC) to assist with monitoring algal blooms in Lake Erie. The most notable species of HAB is Microcystis aeruginosa, a hepatotoxin producing cyanobacteria that is responsible for liver complications for humans and other fauna that come in contact with these blooms. NASA GRC conducts semiweekly flights in order to gather up-to-date imagery regarding the blooms' spatial extents and concentrations. Airborne hyperspectral imagery is collected using two hyperspectral imagers, HSI-2 …
Impact Of Deadly Dust Storms (May 2018) On Air Quality, Meteorological, And Atmospheric Parameters Over The Northern Parts Of India, Sudipta Sarkar, Akshansa Chauhan, Rajesh Kumar, Ramesh P. Singh
Impact Of Deadly Dust Storms (May 2018) On Air Quality, Meteorological, And Atmospheric Parameters Over The Northern Parts Of India, Sudipta Sarkar, Akshansa Chauhan, Rajesh Kumar, Ramesh P. Singh
Mathematics, Physics, and Computer Science Faculty Articles and Research
The northern part of India, adjoining the Himalaya, is considered as one of the global hot spots of pollution because of various natural and anthropogenic factors. Throughout the year, the region is affected by pollution from various sources like dust, biomass burning, industrial and vehicular pollution, and myriad other anthropogenic emissions. These sources affect the air quality and health of millions of people who live in the Indo‐Gangetic Plains. The dust storms that occur during the premonsoon months of March–June every year are one of the principal sources of pollution and originate from the source region of Arabian Peninsula and …
Spatial-Temporal Variability Of In Situ Cyanobacteria Vertical Structure In Western Lake Erie: Implications For Remote Sensing Observations, Karl Bosse, Michael Sayers, Robert Shuchman, Gary L. Fahnenstiel, Steven A. Ruberg, David L. Fanslow, Dack G. Stuart, Thomas H. Johengen, Ashley M. Burtner
Spatial-Temporal Variability Of In Situ Cyanobacteria Vertical Structure In Western Lake Erie: Implications For Remote Sensing Observations, Karl Bosse, Michael Sayers, Robert Shuchman, Gary L. Fahnenstiel, Steven A. Ruberg, David L. Fanslow, Dack G. Stuart, Thomas H. Johengen, Ashley M. Burtner
Michigan Tech Publications
Remote sensing has provided expanded temporal and spatial range to the study of harmful algal blooms (cyanoHABs) in western Lake Erie, allowing for a greater understanding of bloom dynamics than is possible through in situ sampling. However, satellites are limited in their ability to specifically target cyanobacteria and can only observe the water within the first optical depth. This limits the ability of remote sensing to make conclusions about full water column cyanoHAB biomass if cyanobacteria are vertically stratified. FluoroProbe data were collected at nine stations across western Lake Erie in 2015 and 2016 and analyzed to characterize spatio-temporal variability …
Estimation Of The Relationship Between Satellite-Derived Vegetation Indices And Live Fuel Moisture Towards Wildfire Risk In Southern California, Kristen Whitney, Seung Hee Kim, Shenyue Jia, Menas Kafatos
Estimation Of The Relationship Between Satellite-Derived Vegetation Indices And Live Fuel Moisture Towards Wildfire Risk In Southern California, Kristen Whitney, Seung Hee Kim, Shenyue Jia, Menas Kafatos
Mathematics, Physics, and Computer Science Faculty Articles and Research
Southern California possesses a Mediterranean climate having semi-arid to arid characteristics and contains shrubland areas at high risk to wildfire. To assess wildfire danger, fire agencies have been monitoring the moisture of vegetation, called live fuel moisture (LFM), using field-based sampling. Unfortunately, spatial and temporal resolution of live fuel moisture data are significantly limited because sampling is labor intensive. Remote sensing satellite data has been used to monitor vegetation moisture content and health of shrublands. Therefore, a potential approach to overcome the limitations of manual measurements of live fuel moisture is to use vegetation indices (VIs) derived from satellite data. …
Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu
Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu
Forestry and Natural Resources Faculty Publications
Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability …
Utilizing A Consumer-Grade Camera System To Quantify Surface Reflectance, Joseph J. Lehnert
Utilizing A Consumer-Grade Camera System To Quantify Surface Reflectance, Joseph J. Lehnert
Department of Geography: Dissertations, Theses, and Student Research
Consumer-grade camera systems are often employed in aerial remote sensing to provide insight into patterns and processes of interest to science and industry, a trend that has largely been encouraged by the rapid growth of the small unmanned aircraft system (sUAS) industry. However, little research exists on the ability of these systems to accurately measure surface reflectance in specific wavebands, a crucial consideration for many remote sensing applications. This research was conducted on the premise that with proper equipment and calibration techniques consumer-grade cameras would be capable of accurately measuring surface reflectance in user-defined wavebands of interest. A stereo-pair, Fujifilm …
Subset Data From The Nauru 1999 And African Monsoon Multidisciplinary Analysis (Amma) 2006 Cruise And Matlab Code For Generating Plots For The Paper: Wong And Minnett (2017): The Response Of The Ocean Thermal Skin Layer To Variations In Incident Infrared Radiation., Elizabeth Wong
Supplementary Data and Tools
Data in this collection is largely comprised of subsetted data from two research cruises, the Nauru cruise held from June to July 1999 and the African Monsoon Multidisciplinary Analysis (AMMA) cruise held from May to July 2006. The data subset is limited to night conditions under low wind speeds of < 10 m/s and consists of the surface fluxes, radiance measurements from the Marine Atmospheric Emitted Radiance Interferometer (M-AERI), the retrievals of the skin sea surface temperatures and skin sea surface temperature profiles from the M-AERI's radiance spectral measurements. Also included are line-by-line-radiative transfer simulations provided by Dr. Goshka Szczodrak, transmission coefficient spectra obtained from the HITRAN database, and wind speed data from the Special Sensing Microwave Imager (SSM/I) version 6. provided by Dr. Chelle Gentemann. Matlab code is provided which reads the datafile (DATA.mat) and outputs the figures illustrated in the paper Wong and Minnett (2017) (https://doi.org/10.1002/2017JC013351).
Multi-Year Modis Active Fire Type Classification Over The Brazilian Tropical Moist Forest Biome, David P. Roy, S. S. Kumar
Multi-Year Modis Active Fire Type Classification Over The Brazilian Tropical Moist Forest Biome, David P. Roy, S. S. Kumar
GSCE Faculty Publications
The Brazilian Tropical Moist Forest Biome (BTMFB) spans almost 4 million km2 and is subject to extensive annual fires that have been categorized into deforestation, maintenance, and forest fire types. Information on fire types is important as they have different atmospheric emissions and ecological impacts. A supervised classification methodology is presented to classify the fire type of MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections using training data defined by consideration of Brazilian government forest monitoring program annual land cover maps, and using predictor variables concerned with fuel flammability, fuel load, fire behavior, fire seasonality, fire annual frequency, proximity …
Land Cover Data For The Mississippi-Alabama Barrier Islands, 2010-2011 Arcgis V10.3 Geodatabase, Gregory A. Carter, Carlton P. Anderson, Kelly L. Lucas, Nathan L. Hopper
Land Cover Data For The Mississippi-Alabama Barrier Islands, 2010-2011 Arcgis V10.3 Geodatabase, Gregory A. Carter, Carlton P. Anderson, Kelly L. Lucas, Nathan L. Hopper
Land Cover Data for the Mississippi-Alabama Barrier Islands, 2010-2011
Land cover on the Mississippi-Alabama barrier islands was surveyed in 2010-2011 as part of continuing research on island geomorphic and vegetation dynamics following the 2005 impact of Hurricane Katrina. Results of the survey include sub-meter GPS location, a listing of dominant vegetation species and field photographs recorded at 375 sampling locations distributed among Cat, West Ship, East Ship, Horn, Sand, Petit Bois and West Dauphin Islands. The survey was conducted in a period of intensive remote sensing data acquisition over the northern Gulf of Mexico by federal, state and commercial organizations in response to the 2010 Macondo Well (Deepwater Horizon) …
Remote Sensing And Modeling Of Atmospheric Dust And Studying Its Impact On Environment, Weather, And Climate, Hesham El-Askary, Seon K. Park, Slobodan Nickovic, Mian Chin
Remote Sensing And Modeling Of Atmospheric Dust And Studying Its Impact On Environment, Weather, And Climate, Hesham El-Askary, Seon K. Park, Slobodan Nickovic, Mian Chin
Mathematics, Physics, and Computer Science Faculty Articles and Research
An overview of the 2015 volume of Advances in Meteorology, which was co-edited by Chapman faculty member Dr. Hesham El-Askary.
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li
Electrical & Computer Engineering Faculty Publications
We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l1/lq regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …
How The Presence Of Plastic In The North Pacific Gyre Affects The Growth Of Thalassiosira Through Remote Sensing And Laboratory Replication, Jordynn Brennan, Hesham El-Askary
How The Presence Of Plastic In The North Pacific Gyre Affects The Growth Of Thalassiosira Through Remote Sensing And Laboratory Replication, Jordynn Brennan, Hesham El-Askary
Student Scholar Symposium Abstracts and Posters
Through the use of remote sensing, we are able to determine the approximate location of the garbage patch in the North Pacific Gyre. Though remote sensing does not penetrate the surface of the ocean, monthly satellite images can be analyzed to determine the rate of growth or rate of decrease of certain parameters, such as atmospheric gases, phytoplankton, and dissolved organic matter. Over the past decade, data from the Goddard Earth Sciences Data and Information Services Center (Giovanni program) has shown a significant increase in dissolved organic matter and chlorophyll a content in the area of the North Pacific Garbage …
Interannual Variations And Trends In Global Land Surface Phenology Derived From Enhanced Vegetation Index During 1982–2010, Xiaoyang Zhang, Bin Tan, Yunyue Yu
Interannual Variations And Trends In Global Land Surface Phenology Derived From Enhanced Vegetation Index During 1982–2010, Xiaoyang Zhang, Bin Tan, Yunyue Yu
GSCE Faculty Publications
Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel …
Numerical Simulation Of “An American Haboob”, A. Vukovic, M. Vujadinovic, G. Pejanovic, J. Andric, M. J. Kumjian, V. Djurdjevic, M. Dacic, Anup K. Prasad, Hesham El-Askary, B. C. Paris, S. Petkovic, W. Sprigg, S. Nickovic
Numerical Simulation Of “An American Haboob”, A. Vukovic, M. Vujadinovic, G. Pejanovic, J. Andric, M. J. Kumjian, V. Djurdjevic, M. Dacic, Anup K. Prasad, Hesham El-Askary, B. C. Paris, S. Petkovic, W. Sprigg, S. Nickovic
Mathematics, Physics, and Computer Science Faculty Articles and Research
A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land–atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert …
Satellite-Based Estimates Of Antarctic Surface Meltwater Fluxes, Luke D. Trusel, Karen E. Frey, Sarah B. Das, Peter Kuipers Munneke, Michiel R. Van Den Broeke
Satellite-Based Estimates Of Antarctic Surface Meltwater Fluxes, Luke D. Trusel, Karen E. Frey, Sarah B. Das, Peter Kuipers Munneke, Michiel R. Van Den Broeke
Geography
This study generates novel satellite-derived estimates of Antarctic-wide annual (1999-2009) surface meltwater production using an empirical relationship between radar backscatter from the QuikSCAT (QSCAT) satellite and melt calculated from in situ energy balance observations. The resulting QSCAT-derived melt fluxes significantly agree with output from the regional climate model RACMO2.1 and with independent ground-based observations. The high-resolution (4.45 km) QSCAT-based melt fluxes uniquely detect interannually persistent and intense melt (>400 mm water equivalent (w.e.) year-1) on interior Larsen C Ice Shelf that is not simulated by RACMO2.1. This supports a growing understanding of the importance of a föhn effect in …
Antarctic Surface Melting Dynamics: Enhanced Perspectives From Radar Scatterometer Data, L. D. Trusel, K. E. Frey, S. B. Das
Antarctic Surface Melting Dynamics: Enhanced Perspectives From Radar Scatterometer Data, L. D. Trusel, K. E. Frey, S. B. Das
Geography
Antarctic ice sheet surface melting can regionally influence ice shelf stability, mass balance, and glacier dynamics, in addition to modulating near-surface physical and chemical properties over wide areas. Here, we investigate variability in surface melting from 1999 to 2009 using radar backscatter time series from the SeaWinds scatterometer aboard the QuikSCAT satellite. These daily, continent-wide observations are explored in concert with in situ meteorological records to validate a threshold-based melt detection method. Radar backscatter decreases during melting are significantly correlated with in situ positive degree-days as well as meltwater production determined from energy balance modeling at Neumayer Station, East Antarctica. …
Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)
Sparse Coding For Hyperspectral Images Using Random Dictionary And Soft Thresholding, Ender Oguslu, Khan Iftekharuddin, Jiang Li, Mark Allen Neifeld (Ed.), Amit Ashok (Ed.)
Electrical & Computer Engineering Faculty Publications
Many techniques have been recently developed for classification of hyperspectral images (HSI) including support vector machines (SVMs), neural networks and graph-based methods. To achieve good performances for the classification, a good feature representation of the HSI is essential. A great deal of feature extraction algorithms have been developed such as principal component analysis (PCA) and independent component analysis (ICA). Sparse coding has recently shown state-of-the-art performances in many applications including image classification. In this paper, we present a feature extraction method for HSI data motivated by a recently developed sparse coding based image representation technique. Sparse coding consists of a …
Modeling Acoustic Scattering From The Seabed Using Transport Theory, Jorge Quijano, Lisa M. Zurk
Modeling Acoustic Scattering From The Seabed Using Transport Theory, Jorge Quijano, Lisa M. Zurk
Electrical and Computer Engineering Faculty Publications and Presentations
Radiative Transfer (RT) theory has established itself as an important tool for electromagnetic remote sensing in parallel plane geometries with random distributions of scatterers, and most recently it has also been proposed as a model for the propagation of elastic waves in layered ocean sediments. In this work the capabilities of this model are illustrated, as the RT method is used to predict backscattering strength from laboratory models of random media. The RT model is characterized by its flexibility on accommodating scatterers in a broad variety of sizes, shapes, and acoustic contrast relative to the background media. Additionally, this formulation …