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Geospatial Analyses Of Seismic Hazards And Risk Perception In Libya, Somaia Suwihli 2020 University of Arkansas, Fayetteville

Geospatial Analyses Of Seismic Hazards And Risk Perception In Libya, Somaia Suwihli

Theses and Dissertations

Libya is not considered a highly active seismic region. However, several earthquakes of magnitude >5.0 have occurred there. This dissertation analyzes the seismicity of Libya in order to better understand earthquake hazards, related geomorphic features, and the current evolution of Libyan perceptions of seismic risk. The first article developed a baseline of past and current seismic inventory in Libya, which represented an assessment of Libya seismic hazard by translating, analyzing, and compiling historical sources and archaeological data. This study shows that Libya has experienced earthquakes in varying degrees since ancient times. Through the spatial and temporal distribution of earthquakes ...


Earth Observation And Sustainable Development Goals, Ramesh P. Singh 2020 Chapman University

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 ...


How Globalization, Sustainability, And Human Impacts Are Affecting Two Major Mexican Cities: Mexico City And Guadalajara, Cristina Sedano 2020 California State University, San Bernardino

How Globalization, Sustainability, And Human Impacts Are Affecting Two Major Mexican Cities: Mexico City And Guadalajara, Cristina Sedano

Electronic Theses, Projects, and Dissertations

Mexico is one of the richest countries in the world, not in terms of economic stability but in terms of natural resources, culture, and atmosphere. When people think of Mexico, they usually think of the high-tension relationship with the United States, their neighboring country to the North. Although there are many diverse historical and present-day characteristics of Mexico, most associate the county with the high levels of crime due to narco and cartels, the high levels of poverty in regional areas, and to some just a party destination. Unbeknownst to many is the thousands year old culture that is passed ...


Synergistic Use Of Remote Sensing And Modeling For Estimating Net Primary Productivity In The Red Sea With Vgpm, Eppley-Vgpm, And Cbpm Models Intercomparison, Wenzhao Li, Surya Prakash Tiwari, Hesham el-Askary, Mohamed Ali Qurban, Vassilis Amiridis, K. P. Manikandan, Michael J. Garay, Olga V. Kalashnikova, Thomas C. Piechota, Daniele C. Struppa 2020 Chapman University

Synergistic Use Of Remote Sensing And Modeling For Estimating Net Primary Productivity In The Red Sea With Vgpm, Eppley-Vgpm, And Cbpm Models Intercomparison, Wenzhao Li, Surya Prakash Tiwari, Hesham El-Askary, Mohamed Ali Qurban, Vassilis Amiridis, K. P. Manikandan, Michael J. Garay, Olga V. Kalashnikova, Thomas C. Piechota, Daniele C. Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Primary productivity (PP) has been recently investigated using remote sensing-based models over quite limited geographical areas of the Red Sea. This work sheds light on how phytoplankton and primary production would react to the effects of global warming in the extreme environment of the Red Sea and, hence, illuminates how similar regions may behave in the context of climate variability. study focuses on using satellite observations to conduct an intercomparison of three net primary production (NPP) models--the vertically generalized production model (VGPM), the Eppley-VGPM, and the carbon-based production model (CbPM)--produced over the Red Sea domain for the 1998-2018 time ...


Samsts Satellite Time Series Gap Filling Source Codes - Landsat, Lin Yan, David P. Roy 2020 South Dakota State University

Samsts Satellite Time Series Gap Filling Source Codes - Landsat, Lin Yan, David P. Roy

SAMSTS Satellite Time Series Gap Filling Source Codes

  • SAMSTS is open-source software (coded in C) for gap filling of Landsat multispectral time series developed by Drs. Lin Yan and David Roy.
  • SAMSTS 1.1.1 release includes source codes, user manual and test data.
  • The test data are year-2013 time series of Landsat 7 ETM+ and Landsat 8 OLI ARD surface reflectance products (http://landsat.usgs.gov/ard) over Kansas and Iowa. Each ARD tile is composed of 5000 x 5000 30m pixels with six bands (blue, red, green, NIR, SWIR 1, SWIR 2).
  • Major Software functionality:
    • Automatic gap filling of Landsat multispectral time series caused by clouds ...


Changes In Land Use Land Cover (Lulc), Surface Water Quality And Modelling Surface Discharge In Beaver Creek Watershed, Northeast Tennessee And Southwest Virginia, Tosin James 2020 East Tennessee State University

Changes In Land Use Land Cover (Lulc), Surface Water Quality And Modelling Surface Discharge In Beaver Creek Watershed, Northeast Tennessee And Southwest Virginia, Tosin James

Electronic Theses and Dissertations

Beaver Creek is an impaired streams that is not supporting its designated use for recreation due to Escherichia coli (E.coli), and sediment. To address this problem, this thesis was divided into two studies.

The first study explored changes in Land Use Land Cover (LULC), and its impact on surface water quality. Changes in E.coli load between 1997-2001 and 2014-2018 were analyzed. Also, Landsat data of 2001, and 2018 were examined in Terrset 18.31. Mann-Whitney test only showed a significant reduction in E.coli for one site. Negative correlation was established between E.coli load, and Developed LULC ...


Learning About Learning With Deep Learning: Satellite Estimates Of School Test Scores, Heather M. Baier 2020 William & Mary

Learning About Learning With Deep Learning: Satellite Estimates Of School Test Scores, Heather M. Baier

Undergraduate Honors Theses

Convolutional neural networks are deep-learning models commonly applied when analyzing imagery. Convolutional neural networks and satellite imagery have shown potential for the global estimation of key factors driving socioeconomic ability to adapt to global change. Unlike more traditional approaches to data collection, such as surveys, approaches based on satellite data are low cost, timely, and allow replication by a wide range of parties. We illustrate the potential of this approach with a case study estimating school test scores based solely on publicly available imagery in both the Philippines (2010, 2014) and Brazil (2016), with predictive accuracy across years and regions ...


Characterizing The Impacts Of The Invasive Hemlock Woolly Adelgid On The Forest Structure Of New England, Peter Brehm Boucher 2020 University of Massachusetts Boston

Characterizing The Impacts Of The Invasive Hemlock Woolly Adelgid On The Forest Structure Of New England, Peter Brehm Boucher

Graduate Doctoral Dissertations

Climate change is raising winter temperatures in the Northeastern United States, both expanding the range of an invasive pest, the hemlock woolly adelgid (HWA; Adelges tsugae), and threatening the survival of its host species, eastern hemlock (Tsuga canadensis). As a foundation species, hemlock trees underlie a distinct network of ecological, biogeochemical, and structural systems that will likely disappear as the HWA infestation spreads northward. Remote sensing can offer new perspectives on this regional transition, recording the progressive loss of an ecological foundation species and the transition of evergreen hemlock forest to mixed deciduous forest over the course of the infestation ...


How Much Variation In Land Surface Phenology Can Climate Oscillation Modes Explain At The Scale Of Mountain Pastures In Kyrgyzstan?, Monika A. Tomaszewska, Geoffrey M. Henebry 2020 South Dakota State University

How Much Variation In Land Surface Phenology Can Climate Oscillation Modes Explain At The Scale Of Mountain Pastures In Kyrgyzstan?, Monika A. Tomaszewska, Geoffrey M. Henebry

NASA Land-Cover Land-Use Change Data Sets

Climate oscillation modes can shape weather across the globe due to atmospheric teleconnections. We built on the findings of a recent study to assess whether the impacts of teleconnections are detectable and significant in the early season dynamics of highland pastures across five rayons in Kyrgyzstan. Specifically, since land surface phenology (LSP) has already shown to be influenced by snow cover seasonality and terrain, we investigated here how much more explanatory and predictive power information about climatic oscillation modes might add to explain variation in LSP. We focused on seasonal values of five climate oscillation indices that influence vegetation dynamics ...


Earth Observation And Cloud Computing In Support Of Two Sustainable Development Goals For The River Nile Watershed Countries, Wenzhao Li, Hesham el-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa 2020 Chapman University

Earth Observation And Cloud Computing In Support Of Two Sustainable Development Goals For The River Nile Watershed Countries, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

In September 2015, the members of United Nations adopted the 2030 Agenda for Sustainable Development with universal applicability of 17 Sustainable Development Goals (SDGs) and 169 targets. The SDGs are consequential for the development of the countries in the Nile watershed, which are affected by water scarcity and experiencing rapid urbanization associated with population growth. Earth Observation (EO) has become an important tool to monitor the progress and implementation of specific SDG targets through its wide accessibility and global coverage. In addition, the advancement of algorithms and tools deployed in cloud computing platforms provide an equal opportunity to use EO ...


Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola 2020 Resonant Sciences

Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing, Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola

Faculty Publications

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed ...


A View From Above: Alternative Perspectives On Smallholder Livelihoods And Agrobiodiversity Conservation In Northern Ecuador, Chris Hair 2020 The University of Southern Mississippi

A View From Above: Alternative Perspectives On Smallholder Livelihoods And Agrobiodiversity Conservation In Northern Ecuador, Chris Hair

Dissertations

Food security and deintensification of agriculture are serious concerns in Latin America. Agriculture, especially at small-scale subsistence levels, is hard work, and comes with some economic and physical risk. Transitions from traditional multi-cropping to mono-cropping systems introduce two particular risks that are new to most smallholders: (1) the loss of agricultural diversity and (2) the potential for widespread failure when focusing on the cultivation of a single crop. This research explores how Small Unmanned Aerial Systems (sUAS), or drones, can be used for rapid inventories of crop diversity and to enhance crop management techniques on small-scale farms. In the community ...


Land Surface Phenology In The Highland Pastures Of Montane Central Asia: Interactions With Snow Cover Seasonality And Terrain Characteristics, Monika A. Tomaszewska, Lan H. Nguyen, Geoffrey Henebry 2020 South Dakota State University

Land Surface Phenology In The Highland Pastures Of Montane Central Asia: Interactions With Snow Cover Seasonality And Terrain Characteristics, Monika A. Tomaszewska, Lan H. Nguyen, Geoffrey Henebry

NASA Land-Cover Land-Use Change Data Sets

Many studies have shown that high elevation environments are among very sensitive to climatic changes and where impacts are exacerbated. Across Central Asia, which is especially vulnerable to climate change due to aridity, the ability of global climate projections to capture the complex dynamics of mountainous environments is particularly limited. Over montane Central Asia, agropastoralism constitutes a major portion of the rural economy. Extensive herbaceous vegetation forms the basis of rural economies in Kyrgyzstan. Here we focus on snow cover seasonality and the effects of terrain on phenology in highland pastures using remote sensing data for 2001–2017. First, we ...


Unveiling Shadows: How To Optimize Shadow Detection In Hsi Through Combination Of Lidar And Histogram Thresholding, Maritza Salinas 2020 University of Northern Iowa

Unveiling Shadows: How To Optimize Shadow Detection In Hsi Through Combination Of Lidar And Histogram Thresholding, Maritza Salinas

Research in the Capitol

From “multi-” to “hyper-” spectral, remote sensing capacities have improved tremendously in how we measure Earth’s unique signatures. Unfortunately, shadow detection and correction remain an issue in most images, especially those with high spatial resolution. Shadows result when direct sun light is obstructed and the spectral reflectance values for pixels in those regions decrease. Many successful approaches exist to correct this blue skew to shorter wavelengths, but it can be daunting to truly assess which approach to employ since each require different levels of priori knowledge. This research attempts to generate and cross-validate shadow masks using popular GIS software ...


Changes In Atmospheric, Meteorological, And Ocean Parameters Associated With The 12 January 2020 Taal Volcanic Eruption, Feng Jing, Akshansa Chauhan, Ramesh P. Singh, Prasanjit Dash 2020 China Earthquake Administration

Changes In Atmospheric, Meteorological, And Ocean Parameters Associated With The 12 January 2020 Taal Volcanic Eruption, Feng Jing, Akshansa Chauhan, Ramesh P. Singh, Prasanjit Dash

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The Taal volcano erupted on 12 January 2020, the first time since 1977. About 35 mild earthquakes (magnitude greater than 4.0) were observed on 12 January 2020 induced from the eruption. In the present paper, we analyzed optical properties of volcanic aerosols, volcanic gas emission, ocean parameters using multi-satellite sensors, namely, MODIS (Moderate Resolution Imaging Spectroradiometer), AIRS (Atmospheric Infrared Sounder), OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument) and ground observations, namely, Argo, and AERONET (AErosol RObotic NETwork) data. Our detailed analysis shows pronounced changes in all the parameters, which mainly occurred in the western and south-western regions because ...


Microwave Brightness Temperature Characteristics Of Three Strong Earthquakes In Sichuan Province, China, Feng Jing, Ramesh P. Singh, Yueju Cui, Ke Sun 2020 China Earthquake Administration

Microwave Brightness Temperature Characteristics Of Three Strong Earthquakes In Sichuan Province, China, Feng Jing, Ramesh P. Singh, Yueju Cui, Ke Sun

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Passive microwave remote sensing technology is an effective means to identify the thermal anomalies associated with earthquakes due to its penetrating capability through clouds compared with infrared sensors. However, observed microwave brightness temperature is strongly influenced by soil moisture and other surface parameters. In the present article, the segmented threshold method has been proposed to detect anomalous microwave brightness temperature associated with the strong earthquakes occurred in Sichuan province, China, an earthquake-prone area with high soil moisture. The index of microwave radiation anomaly (IMRA) computed by the proposed method is found to enhance prior to the three strong earthquakes, 2008 ...


Regional Forest Volume Estimation By Expanding Lidar Samples Using Multi-Sensor Satellite Data, Bo Xie, Chunxiang Cao, Min Xu, Barjeece Bashir, Ramesh P. Singh, Zhibin Huang, Xiaojuan Lin 2020 Chinese Academy of Sciences

Regional Forest Volume Estimation By Expanding Lidar Samples Using Multi-Sensor Satellite Data, Bo Xie, Chunxiang Cao, Min Xu, Barjeece Bashir, Ramesh P. Singh, Zhibin Huang, Xiaojuan Lin

Mathematics, Physics, and Computer Science Faculty Articles and Research

Accurate information regarding forest volume plays an important role in estimating afforestation, timber harvesting, and forest ecological services. Traditionally, operations on forest growing stock volume using field measurements are labor-intensive and time-consuming. Recently, remote sensing technology has emerged as a time-cost efficient method for forest inventory. In the present study, we have adopted three procedures, including samples expanding, feature selection, and results generation and evaluation. Extrapolating the samples from Light Detection and Ranging (LiDAR) scanning is the most important step in satisfying the requirement of sample size for nonparametric methods operation and result in accuracy improvement. Besides, mean decrease Gini ...


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 2020 Chinese Academy of Sciences

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 ...


Using Unmanned Aerial Systems (Drones) With A Thermal Sensor To Map And Count Deer Population, Maxwell C. Ott 2020 The University of Akron

Using Unmanned Aerial Systems (Drones) With A Thermal Sensor To Map And Count Deer Population, Maxwell C. Ott

Williams Honors College, Honors Research Projects

The number of deer in an area is an important statistic for land managers to know, as overabundance has many negative effects. There are many methods that have been used to count deer in the past, such as using manned helicopters and airplanes, walking on foot, and conducting controlled hunts. UAS (unmanned aerial systems) is a growing field that provides many benefits over traditional methods of counting deer, such as lower cost and missions being less time consuming. Using a thermal sensor attached to a UAS makes it simple to spot any deer during a flight. Two main methods of ...


Spectrally Derived Values Of Community Leaf Dry Matter Content Link Shifts In Grassland Composition With Change In Biomass Production, H. Wayne Polley, Chenghai Yang, Brian J. Wilsey, Philip A. Fay 2020 U.S. Department of Agriculture

Spectrally Derived Values Of Community Leaf Dry Matter Content Link Shifts In Grassland Composition With Change In Biomass Production, H. Wayne Polley, Chenghai Yang, Brian J. Wilsey, Philip A. Fay

Ecology, Evolution and Organismal Biology Publications

Leaf traits link environmental effects on plant species abundances to changes in ecosystem processes but are a challenge to measure regularly and over large areas. We used measurements of canopy reflectance from grassland communities to derive a regression model for one leaf trait, leaf dry matter content (LDMC). Partial least squares regression (PLSR) analysis was used to model community‐weighted (species abundance‐weighted) values of LDMC as a function of canopy reflectance in visible and near‐infrared (NIR) wavebands. The PLSR model then was applied to airborne measurements of canopy reflectance to determine how community LDMC interacts with inter‐annual ...


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