Methods For Real-Time Prediction Of The Mode Of Travel Using Smartphone-Based Gps And Accelerometer Data,
2017
University of Washington - Seattle Campus
Methods For Real-Time Prediction Of The Mode Of Travel Using Smartphone-Based Gps And Accelerometer Data, Bryan D. Martin, Vittorio Addona, Julian Wolfson, Gediminas Adomavicius, Yingling Fan
Faculty Publications
We propose and compare combinations of several methods for classifying transportation activity data from smartphone GPS and accelerometer sensors. We have two main objectives. First, we aim to classify our data as accurately as possible. Second, we aim to reduce the dimensionality of the data as much as possible in order to reduce the computational burden of the classification. We combine dimension reduction and classification algorithms and compare them with a metric that balances accuracy and dimensionality. In doing so, we develop a classification algorithm that accurately classifies five different modes of transportation (i.e., walking, biking, car, bus and rail) …
Land Surface Phenology And Seasonality Using Cool Earthlight In Croplands Of Eastern Africa And The Linkages To Crop Production,
2017
South Dakota State University
Land Surface Phenology And Seasonality Using Cool Earthlight In Croplands Of Eastern Africa And The Linkages To Crop Production, Woubet G. Alemu, Geoffrey M. Henebry
GSCE Faculty Publications
Across Eastern Africa, croplands cover 45 million ha. The regional economy is heavily dependent on small holder traditional rain-fed peasant agriculture (up to 90%), which is vulnerable to extreme weather events such as drought and floods that leads to food insecurity. Agricultural production in the region is moisture limited. Weather station data are scarce and access is limited, while optical satellite data are obscured by heavy clouds limiting their value to study cropland dynamics. Here, we characterized cropland dynamics in Eastern Africa for 2003–2015 using precipitation data from Tropical Rainfall Measuring Mission (TRMM) and a passive microwave dataset of land …
Thermal Radiation Anomalies Associated With Major Earthquakes,
2017
Chapman University
Thermal Radiation Anomalies Associated With Major Earthquakes, Dimitar Ouzounov, Sergey Pulinets, Menas Kafatos, Patrick Taylor
Mathematics, Physics, and Computer Science Faculty Articles and Research
Recent developments of remote sensing methods for Earth satellite data analysis contribute to our understanding of earthquake related thermal anomalies. It was realized that the thermal heat fluxes over areas of earthquake preparation is a result of air ionization by radon (and other gases) and consequent water vapor condensation on newly formed ions. Latent heat (LH) is released as a result of this process and leads to the formation of local thermal radiation anomalies (TRA) known as OLR (outgoing Longwave radiation, Ouzounov et al, 2007). We compare the LH energy, obtained by integrating surface latent heat flux (SLHF) over the …
Acoustic Signatures Of Habitat Types In The Miombo Woodlands Of Western Tanzania,
2017
Universidad de Los Andes - Colombia
Acoustic Signatures Of Habitat Types In The Miombo Woodlands Of Western Tanzania, Sheryl Vanessa Amorocho, Dante Francomano, Kristen M. Bellisario, Ben Gottesman, Bryan C. Pijanowski
The Summer Undergraduate Research Fellowship (SURF) Symposium
The Miombo Woodlands of Tanzania comprise several habitat types that are home to a great number of flora and fauna. Understanding their responses to increasing human disturbance is important for conservation, especially in places where people depend so directly on their local ecosystem services to survive. Soundscapes are a powerful approach to study complex biomes undergoing change. The sounds emitted by soniferous fauna characterize the acoustic profile of the landscapes they inhabit such that habitats with the highest acoustic abundance are considered as the most diverse and possibly more ecologically resilient. However, acoustic variability within similar habitat types may pose …
Utilizing A Consumer-Grade Camera System To Quantify Surface Reflectance,
2017
University of Nebraska-Lincoln
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 …
Using The 500 M Modis Land Cover Product To Derive A Consistent Continental Scale 30 M Landsat Land Cover Classification,
2017
South Dakota State University
Using The 500 M Modis Land Cover Product To Derive A Consistent Continental Scale 30 M Landsat Land Cover Classification, Hankui Zhang, David P. Roy
GSCE Faculty Publications
Classification is a fundamental process in remote sensing used to relate pixel values to land cover classes present on the surface. Over large areas land cover classification is challenging particularly due to the cost and difficulty of collecting representative training data that enable classifiers to be consistent and locally reliable. A novel methodology to classify large volume Landsat data using high quality training data derived from the 500 m MODIS land cover product is demonstrated and used to generate a 30 m land cover classification for all of North America between 20°N and 50°N. Publically available 30 m global monthly …
A Global Analysis Of Sentinel-2a, Sentinel-2b And Landsat-8 Data Revisit Intervals And Implications For Terrestrial Monitoring,
2017
South Dakota State University
A Global Analysis Of Sentinel-2a, Sentinel-2b And Landsat-8 Data Revisit Intervals And Implications For Terrestrial Monitoring, Jian Li, David P. Roy
GSCE Faculty Publications
Combination of different satellite data will provide increased opportunities for more frequent cloud-free surface observations due to variable cloud cover at the different satellite overpass times and dates. Satellite data from the polar-orbiting Landsat-8 (launched 2013), Sentinel-2A (launched 2015) and Sentinel-2B (launched 2017) sensors offer 10 m to 30 m multi-spectral global coverage. Together, they advance the virtual constellation paradigm for mid-resolution land imaging. In this study, a global analysis of Landsat-8, Sentinel-2A and Sentinel-2B metadata obtained from the committee on Earth Observation Satellite (CEOS) Visualization Environment (COVE) tool for 2016 is presented. A global equal area projection grid defined …
Textural Analysis Of Historical Aerial Photography To Determine Change In Coastal Marsh Extent: Site Of The Present-Day Grand Bay National Estuarine Research Reserve (Gbnerr), Mississippi, 1955-2014,
2017
University of Southern Mississippi
Textural Analysis Of Historical Aerial Photography To Determine Change In Coastal Marsh Extent: Site Of The Present-Day Grand Bay National Estuarine Research Reserve (Gbnerr), Mississippi, 1955-2014, Heather Michelle Nicholson
Master's Theses
Coastal marshlands are among the world’s most highly productive ecosystems but they have diminished greatly in the past several decades owing to sea-level rise and direct anthropogenic influences. An effective means of quantifying loss or gain in marsh area is through the use of aerial image data, which offers synoptic views of the landscape at decadal-scale sampling frequencies. However, a potential problem with older panchromatic, or black-and-white, imagery is the absence of multispectral information that might be used otherwise in remote identification of vegetation types. Nevertheless, the analysis of horizontal variability in image brightness values, or image texture, can be …
Landscape-Scale Geophysics At Tel Shimron, Jezreel Valley, Israel,
2017
East Tennessee State University
Landscape-Scale Geophysics At Tel Shimron, Jezreel Valley, Israel, Rachel Grap
Electronic Theses and Dissertations
Ground-penetrating radar (GPR) and magnetometry were used at Tel Shimron, an archaeological site in Israel’s Jezreel Valley. GPR primarily measures electric properties while magnetometry measures magnetic properties, making them complementary methods for subsurface prospection. Magnetometry can be collected and processed quickly, making it an ideal landscape-scale reconnaissance tool. It takes more time to collect, process, and interpret GPR data, but the result is a higher resolution dataset. In addition, GPR often works better than magnetometry in desert environments such as the Jezreel Valley. Conventional wisdom suggests that GPR should not be used as a landscape-scale reconnaissance tool unless there is …
Uas As An Inventory Tool: A Photogrammetric Approach To Volume Estimation,
2017
University of Arkansas, Fayetteville
Uas As An Inventory Tool: A Photogrammetric Approach To Volume Estimation, Richard Kramer Rhodes
Graduate Theses and Dissertations
Unmanned aircraft systems (UAS), also referred to as unmanned aerial vehicles (UAV) or remotely piloted vehicles (RPV), are associated with unmanned aircraft either controlled by a pilot on the ground or pre-programmed with specific flight paths. Small UASs have seen a massive increase in public interest in recent years as hobbyist platforms; they are, however, a potentially powerful tool in remote sensing and geospatial applications. Due to the increased availability of low-cost UAS, this technology could soon revolutionize many industries, including those that require volumetric estimation. Traditionally volumetric inventories have been performed with tape measurements, and in some instances where …
Remote Sensing Of The Environmental Impacts Of Utility-Scale Solar Energy Plants,
2017
University of Nevada, Las Vegas
Remote Sensing Of The Environmental Impacts Of Utility-Scale Solar Energy Plants, Mohammad Masih Edalat
UNLV Theses, Dissertations, Professional Papers, and Capstones
Solar energy has many environmental benefits compared with fossil fuels but solar farming can have environmental impacts especially during construction and development. Thus, in order to enhance environmental sustainability, it is imperative to understand the environmental impacts of utility-scale solar energy (USSE) plants. During recent decades, remote sensing techniques and geographic information systems have become standard techniques in environmental applications. In this study, the environmental impacts of USSE plants are investigated by analyzing changes to land surface characteristics using remote sensing. The surface characteristics studied include land cover, land surface temperature, and hydrological response whereas changes are mapped by comparing …
Synergistic Use Of Remote Sensing And Modeling To Assess An Anomalously High Chlorophyll-A Event During Summer 2015 In The South Central Red Sea,
2017
Chapman University
Synergistic Use Of Remote Sensing And Modeling To Assess An Anomalously High Chlorophyll-A Event During Summer 2015 In The South Central Red Sea, Wenzhao Li, Hesham El-Askary, K. P. Manikandan, Mohamed A. Qurban, Michael J. Garay, Olga V. Kalishnikova
Mathematics, Physics, and Computer Science Faculty Articles and Research
An anomalously high chlorophyll-a (Chl-a) event (>2 mg/m3) during June 2015 in the South Central Red Sea (17.5° to 22°N, 37° to 42°E) was observed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellite platforms. This differs from the low Chl-a values (<0.5 mg/m3) usually encountered over the same region during summertime. To assess this anomaly and possible causes, we used a wide range of oceanographical and meteorological datasets, including Chl-a concentrations, sea surface temperature (SST), sea surface height (SSH), mixed layer depth (MLD), ocean current velocity and aerosol optical depth (AOD) obtained from different sensors and models. Findings confirmed this anomalous behavior in the spatial domain using Hovmöller data analysis techniques, while a time series analysis addressed monthly and daily variability. Our analysis suggests that a combination of factors controlling nutrient supply contributed to the anomalous phytoplankton growth. These factors include horizontal transfer of upwelling water through eddy circulation and possible mineral fertilization from atmospheric dust deposition. Coral reefs might have provided extra nutrient supply, yet this is out of the scope of our analysis. We thought that dust deposition from a coastal dust jet event in late June, coinciding with the phytoplankton blooms in the area under investigation, might have also contributed as shown by our AOD findings. However, a lag cross correlation showed a two- month lag between strong dust outbreak and the high Chl-a anomaly. The high Chl-a concentration at the edge of the eddy emphasizes the importance of horizontal advection in fertilizing oligotrophic (nutrient poor) Red Sea waters.
Landsat 15-M Panchromatic-Assisted Downscaling (Lpad) Of The 30-M Reflective Wavelength Bands To Sentinel-2 20-M Resolution,
2017
South Dakota State University
Landsat 15-M Panchromatic-Assisted Downscaling (Lpad) Of The 30-M Reflective Wavelength Bands To Sentinel-2 20-M Resolution, Zhongbin Li, Hankui K. Zhang, David P. Roy, Lin Yan, Haiyan Huang, Jian Li
GSCE Faculty Publications
The Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) method to downscale Landsat-8 Operational Land Imager (OLI) 30-m data to Sentinel-2 multi-spectral instrument (MSI) 20-m resolution is presented. The method first downscales the Landsat-8 30-m OLI bands to 15-m using the spatial detail provided by the Landsat-8 15-m panchromatic band and then reprojects and resamples the downscaled 15-m data into registration with Sentinel-2A 20-m data. The LPAD method is demonstrated using pairs of contemporaneous Landsat-8 OLI and Sentinel-2A MSI images sensed less than 19 min apart over diverse geographic environments. The LPAD method is shown to introduce less spectral and spatial distortion and …
High Resolution Spectra Of Carbon Monoxide, Propane And Ammonia For Atmospheric Remote Sensing,
2017
Old Dominion University
High Resolution Spectra Of Carbon Monoxide, Propane And Ammonia For Atmospheric Remote Sensing, Christopher Andrew Beale
OES Theses and Dissertations
Spectroscopy is a critical tool for analyzing atmospheric data. Identification of atmospheric parameters such as temperature, pressure and the existence and concentrations of constituent gases via remote sensing techniques are only possible with spectroscopic data. These form the basis of model atmospheres which may be compared to observations to determine such parameters. To this end, this dissertation explores the spectroscopy of three molecules: ammonia, propane and carbon monoxide.
Infrared spectra have been recorded for ammonia in the region 2400-9000 cm-1. These spectra were recorded at elevated temperatures (from 293-973 K) using a Fourier Transform Spectrometer (FTS). Comparison between …
Sustainable Recommendation Domains For Scaling Agricultural Technologies In Tanzania,
2017
International Institute of Tropical Agriculture (IITA)
Sustainable Recommendation Domains For Scaling Agricultural Technologies In Tanzania, Francis K. Muthoni, Zhe Guo, Mateete Bekunda, Haroon Sseguya, Fred Kizito, Frederick Baijukya, Irmgard Hoeschle-Zeledon
All Peer-Reviewed Publications
Low adoption of sustainable intensification technologies hinders achievement of their potential impacts on increasing agricultural productivity. Proper targeting of locations to scale-out particular technologies is a key determinant of the rate of adoption. Targeting locations with similar biophysical and socio-economic characteristics significantly increases the probability of adoption. Areas with similar biophysical and socio-economic characteristics are referred to as recommendation domains (RDs). This study used geospatial analysis to delineate sustainable recommendation domains (SRDs) for scaling improved crop varieties and good agronomic practices in Tanzania. The study uses K-means clustering to identify relatively similar clusters from grid raster's representing biophysical and socio-economic …
Application Of Iterative Noise-Adding Procedures For Evaluation Of Moment Distance Index For Lidar Waveforms,
2017
New Mexico State University
Application Of Iterative Noise-Adding Procedures For Evaluation Of Moment Distance Index For Lidar Waveforms, Eric Ariel L. Salas, Sadichya Amatya, Geoffrey Henebry
GSCE Faculty Publications
The new Moment Distance (MD) framework uses the backscattering profile captured in waveform LiDAR data to characterize the complicated waveform shape and highlight specific regions within the waveform extent. To assess the strength of the new metric for LiDAR application, we use the full-waveform LVIS data acquired over La Selva, Costa Rica in 1998 and 2005. We illustrate how the Moment Distance Index (MDI) responds to waveform shape changes due to variations in signal noise levels. Our results show that the MDI is robust in the face of three different types of noise—additive, uniform additive, and impulse. In effect, the …
Income Shocks And The Acceptance Of Intimate Partner Violence In Indonesia,
2017
University of San Francisco
Income Shocks And The Acceptance Of Intimate Partner Violence In Indonesia, Matthew N. Krupoff
Master's Theses
Intimate partner violence (IPV) is a pervasive issue affecting 1 in 3 women worldwide. Despite the negative welfare impacts, it is still seen as acceptable in some parts of the world, even amongst women. This paper examines how elastic these accepting attitudes towards IPV are to changing economic conditions. Specifically, this paper focuses on changes in intra-household resources from negative shocks to male-sourced income. The setting and context takes place in coastal communities in Indonesia, where fishing is a main source ofincome generated primarily by men. This paper uses satellite-derived fishing conditions to measure how women's attitudes towards IPV change …
Comparisons Of Global Land Surface Seasonality And Phenology Derived From Avhrr, Modis And Viirs Data,
2017
South Dakota State University
Comparisons Of Global Land Surface Seasonality And Phenology Derived From Avhrr, Modis And Viirs Data, Xiaoyang Zhang
Global Land Surface Season Data Sets
The data set in this collection is for the paper Comparisons of Global Land Surface Seasonality and Phenology Derived from AVHRR, MODIS and VIIRS Data which will be published in the "Journal of Geophysical Research: Biogeosciences."
Pavement Surface Distress Detection, Assessment, And Modeling Using Geospatial Techniques,
2017
University of New Mexico - Main Campus
Pavement Surface Distress Detection, Assessment, And Modeling Using Geospatial Techniques, Su Zhang
Civil Engineering ETDs
Roadway pavement surface distress information is essential for effective pavement asset management, and subsequently, transportation agencies at all levels dedicate a large amount of time and money to routinely collect data on pavement surface distress conditions as the core of their asset management programs. These data are used by these agencies to make maintenance and repair decisions. Current methods for pavement surface distress evaluation are time-consuming and expensive. Geospatial technologies provide new methods for evaluating pavement surface distress condition that can supplement or substitute for currently-adopted evaluation methods. However, few previous studies have explored the utility of geospatial technologies for …
An Operational Drought Prediction Framework With Application Of Vine Copula Functions,
2017
Portland State University
An Operational Drought Prediction Framework With Application Of Vine Copula Functions, Mahkameh Zarekarizi
Student Research Symposium
Early and accurate drought predictions can benefit water resources and emergency managers by enhancing drought preparedness. Soil moisture memory is shown to contain helpful information for prediction of future values. This study uses the soil moisture memory to predict their future states via multivariate statistical modeling. We present a drought forecasting framework which issues monthly and seasonal drought forecasts. This framework estimates droughts with different lead times and updates the forecasts when more data become available. Forecasts are generated by conditioning future soil moisture values on antecedent drought status. The statistical model is initialized by soil moisture simulations retrieved from …
