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Climatic Controls On The Kinematics Of The Hooskanaden Landslide, Curry County, Oregon, Kara Kingen 2021 Portland State University

Climatic Controls On The Kinematics Of The Hooskanaden Landslide, Curry County, Oregon, Kara Kingen

Dissertations and Theses

Slow-moving earthflows represent major sources of sediment transport and erosion and are problematic for the management of critical infrastructure. The Hooskanaden Landslide -- a slow-moving earthflow on the southwest coast of Oregon -- crosses US Highway 101 and has been a site of continued interest to the Oregon Department of Transportation (ODOT) due to the weak lithology, erosive environment, and recurrent surge behavior (every ~15 years). Past surges, including the most recent (2019), have occurred during the winter, suggesting that velocity changes are predominantly controlled by climatic inputs. To examine the response of the Hooskanaden Landslide to seasonal and other …


Understanding The Effect Of Internal Climate Variability On 20th Century Indian Ocean Sea Level: Results From Newly Reconstructed Sea Level Data, Praveen Kumar 2021 Old Dominion University

Understanding The Effect Of Internal Climate Variability On 20th Century Indian Ocean Sea Level: Results From Newly Reconstructed Sea Level Data, Praveen Kumar

OES Theses and Dissertations

Densely populated low-lying coastal zones of countries that border the Indian Ocean are at risk due to sea level rise. However, sea level change in the Indian Ocean is poorly understood primarily due to short and sparse tide gauge observations. Although satellite altimetry provides accurate basin-wide sea level measurements, trends computed from its relatively short (~27-year) data record are heavily influenced by interannual to multi-decadal variability. To accurately project future Indian Ocean sea level trends using altimeter data it is imperative that trends associated with fluctuating internal variability (interannual-decadal) be identified and extracted, which in turn requires long (~100-year) data. …


Participatory Mapping With High-Resolution Satellite Imagery: A Mixed Method Assessment Of Land Degradation And Rehabilitation In Northern Burkina Faso, Colin Thor West, Elisabeth Kago Ilboudo Nébié, Aaron J. Moody 2021 University of North Carolina, Chapel Hill

Participatory Mapping With High-Resolution Satellite Imagery: A Mixed Method Assessment Of Land Degradation And Rehabilitation In Northern Burkina Faso, Colin Thor West, Elisabeth Kago Ilboudo Nébié, Aaron J. Moody

Journal of Ecological Anthropology

Sahelian West Africa is a region that has high population densities and that has frequent severe droughts and enormous pressure on natural resources. Because of these challenges, it is the place where the term desertification was originally coined. Recently, however, experts have identified large zones of greening where the amount of vegetation exceeds what one would expect based on rainfall alone. This pattern is well documented, but its mechanisms remain poorly understood. This research employs participatory mapping linked with high-resolution satellite imagery to better understand the human role behind regional vegetation trends. Through a case study of three communities in …


Investigating Decadal Changes Of Multiple Hydrological Products And Land-Cover Changes In The Mediterranean Region For 2009–2018, Wenzhao Li, Sachi Perera, Erik Linstead, Rejoice Thomas, Hesham el-Askary, Thomas Piechota, Daniele Struppa 2021 Chapman University

Investigating Decadal Changes Of Multiple Hydrological Products And Land-Cover Changes In The Mediterranean Region For 2009–2018, Wenzhao Li, Sachi Perera, Erik Linstead, Rejoice Thomas, Hesham El-Askary, Thomas Piechota, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Land-cover change is a critical concern due to its climatic, ecological, and socioeconomic consequences. In this study, we used multiple variables including precipitation, vegetation index, surface soil moisture, and evapotranspiration obtained from different satellite sources to study their association with land-cover changes in the Mediterranean region. Both observational and modeling data were used for climatology and correlation analysis. Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) and Global Land Data Assimilation System (GLDAS) were used to extract surface soil moisture and evapotranspiration data. Intercomparing the results of FLDAS and GLDAS suggested that FLDAS data had better …


Evaluation Of Manual And Semi-Automated Deep-Seated Landslide Inventory Processes: Willapa Hills, Washington, Tiffany E. Justice 2021 Portland State University

Evaluation Of Manual And Semi-Automated Deep-Seated Landslide Inventory Processes: Willapa Hills, Washington, Tiffany E. Justice

Dissertations and Theses

Recent advances in remote sensing data and technology have allowed for computational models to be designed that successfully extract landforms from the landscape. The goal of this work is to create one such semi-automated model to extract deep-seated landslides located in complex geomorphic terrain. This is accomplished using geographic object-based image analysis (GEOBIA) techniques, considered by leaders in the field of image analysis to have an advantage over traditional automated classification methods. GEOBIA methods can mimic human visual interpretation by including more characteristic features used to assess the relationship between image data and the ground surface such as color reflectance …


Diurnal Cycle Of Passive Microwave Brightness Temperatures Over Land At A Global Scale, Zahra Sharifnezhad, Hamid Norouzi, Satya Prakash, Reginald Blake, Reze Khanbilvard 2021 CUNY City College

Diurnal Cycle Of Passive Microwave Brightness Temperatures Over Land At A Global Scale, Zahra Sharifnezhad, Hamid Norouzi, Satya Prakash, Reginald Blake, Reze Khanbilvard

Publications and Research

Satellite-borne passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range which includes a number of frequency channels and generally two polarizations: horizontal and vertical. These TBs are widely used to retrieve several atmospheric and surface variables and parameters such as precipitation, soil moisture, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments and at various incidence angles, spatial resolutions, and radiometric characteristics, a mere direct integration of them from different microwave sensors would not necessarily provide consistency. However, when appropriately harmonized, they can provide a …


An Assessment Of The Filling Process Of The Grand Ethiopian Renaissance Dam And Its Impact On The Downstream Countries, Prakrut Kansara, Wenzhao Li, Hesham el-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed 2021 University of Virginia

An Assessment Of The Filling Process Of The Grand Ethiopian Renaissance Dam And Its Impact On The Downstream Countries, Prakrut Kansara, Wenzhao Li, Hesham El-Askary, Venkat Lakshmi, Thomas Piechota, Daniele Struppa, Mohamed Abdelaty Sayed

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Grand Ethiopian Renaissance Dam (GERD), formerly known as the Millennium Dam, has been filling at a fast rate. This project has created issues for the Nile Basin countries of Egypt, Sudan, and Ethiopia. The filling of GERD has an impact on the Nile Basin hydrology and specifically the water storages (lakes/reservoirs) and flow downstream. In this study, through the analysis of multi-source satellite imagery, we study the filling of the GERD reservoir. The time-series generated using Sentinel-1 SAR imagery displays the number of classified water pixels in the dam from early June 2017 to September 2020, indicating a contrasting …


Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez 2021 Michigan Technological University

Multi-Source Eo For Dynamic Wetland Mapping And Monitoring In The Great Lakes Basin, Michael Battaglia, Sarah Banks, Amir Behnamian, Laura Bourgeau-Chavez

Michigan Tech Publications

Wetland managers, citizens and government leaders are observing rapid changes in coastal wetlands and associated habitats around the Great Lakes Basin due to human activity and climate variability. SAR and optical satellite sensors offer cost effective management tools that can be used to monitor wetlands over time, covering large areas like the Great Lakes and providing information to those making management and policy decisions. In this paper we describe ongoing efforts to monitor dynamic changes in wetland vegetation, surface water extent, and water level change. Included are assessments of simulated Radarsat Constellation Mission data to determine feasibility of continued monitoring …


Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Mohammed Alqawba, Norou Diawara, Kwasi G. Afrifa, Mohamed I. Elbakary, Mecit Cetin, Khan Iftekharuddin 2021 Old Dominion University

Statistical Analysis And Comparison Of Optical Classification Of Atmospheric Aerosol Lidar Data, Mohammed Alqawba, Norou Diawara, Kwasi G. Afrifa, Mohamed I. Elbakary, Mecit Cetin, Khan Iftekharuddin

Mathematics & Statistics Faculty Publications

In this article, we present a new study for the analysis and classification of atmospheric aerosols in remote sensing LIDAR data. Information on particle size and associated properties are extracted from these remote sensing atmospheric data which are collected by a ground-based LIDAR system. This study first considers optical LIDAR parameter-based classification methods for clustering and classification of different types of harmful aerosol particles in the atmosphere. Since accurate methods for aerosol prediction behaviors are based upon observed data, computational approaches must overcome design limitations, and consider appropriate calibration and estimation accuracy. Consequently, two statistical methods based on generalized linear …


Towards Advancing The Earthquake Forecasting By Machine Learning Of Satellite Data, Pan Xiong, Lei Tong, Kun Zhang, Xuhui Shen, Roberto Battiston, Dimitar Ouzounov, Roberto Iuppa, Danny Crookes, Cheng Long, Huyui Zhou 2021 China Earthquake Administration

Towards Advancing The Earthquake Forecasting By Machine Learning Of Satellite Data, Pan Xiong, Lei Tong, Kun Zhang, Xuhui Shen, Roberto Battiston, Dimitar Ouzounov, Roberto Iuppa, Danny Crookes, Cheng Long, Huyui Zhou

Mathematics, Physics, and Computer Science Faculty Articles and Research

Earthquakes have become one of the leading causes of death from natural hazards in the last fifty years. Continuous efforts have been made to understand the physical characteristics of earthquakes and the interaction between the physical hazards and the environments so that appropriate warnings may be generated before earthquakes strike. However, earthquake forecasting is not trivial at all. Reliable forecastings should include the analysis and the signals indicating the coming of a significant quake. Unfortunately, these signals are rarely evident before earthquakes occur, and therefore it is challenging to detect such precursors in seismic analysis. Among the available technologies for …


Fine-Grained, Spatiotemporal Datasets Measuring 200 Years Of Land Development In The United States, Johannes H. Uhl, Stefan Leyk, Caitlin M. McShane, Anna E. Braswell, Dylan S. Connor, Deborah Balk 2021 University of Colorado, Boulder

Fine-Grained, Spatiotemporal Datasets Measuring 200 Years Of Land Development In The United States, Johannes H. Uhl, Stefan Leyk, Caitlin M. Mcshane, Anna E. Braswell, Dylan S. Connor, Deborah Balk

Publications and Research

The collection, processing, and analysis of remote sensing data since the early 1970s has rapidly improved our understanding of change on the Earth’s surface. While satellite-based Earth observation has proven to be of vast scientific value, these data are typically confined to recent decades of observation and often lack important thematic detail. Here, we advance in this arena by constructing new spatially explicit settlement data for the United States that extend back to the early 19th century and are consistently enumerated at fine spatial and temporal granularity (i.e. 250m spatial and 5-year temporal resolution). We create these time series using …


Viability And Application Of Mounting Personal Pid Voc Sensors To Small Unmanned Aircraft Systems, Cheryl Lynn Marcham, Scott Burgess, Joseph Cerreta, Patti J. Clark, James P. Solti, Brandon Breault, Joshua G. Marcham 2021 Embry-Riddle Aeronautical University

Viability And Application Of Mounting Personal Pid Voc Sensors To Small Unmanned Aircraft Systems, Cheryl Lynn Marcham, Scott Burgess, Joseph Cerreta, Patti J. Clark, James P. Solti, Brandon Breault, Joshua G. Marcham

Publications

Using a UAS-mounted sensor to allow for a rapid response to areas that may be difficult to reach or potentially dangerous to human health can increase the situational awareness of first responders of an aircraft crash site through the remote detection, identification, and quantification of airborne hazardous materials. The primary purpose of this research was to evaluate the remote sensing viability and application of integrating existing commercial-off-the-shelf (COTS) sensors with small unmanned aircraft system (UAS) technology to detect potentially hazardous airborne contaminants in emergency leak or spill response situations. By mounting the personal photoionization detector (PID) with volatile organic compound …


Rapid Mapping Of Landslides In The Western Ghats (India) Triggered By 2018 Extreme Monsoon Rainfall Using A Deep Learning Approach, Sansar Raj Meena, Omid Ghorbanzadeh, Cees J. van Westen, Thimmaiah Gudiyangada Nachappa, Thomas Blaschke, Ramesh P. Singh, Raju Sarkar 2021 University of Salzburg

Rapid Mapping Of Landslides In The Western Ghats (India) Triggered By 2018 Extreme Monsoon Rainfall Using A Deep Learning Approach, Sansar Raj Meena, Omid Ghorbanzadeh, Cees J. Van Westen, Thimmaiah Gudiyangada Nachappa, Thomas Blaschke, Ramesh P. Singh, Raju Sarkar

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Rainfall-induced landslide inventories can be compiled using remote sensing and topographical data, gathered using either traditional or semi-automatic supervised methods. In this study, we used the PlanetScope imagery and deep learning convolution neural networks (CNNs) to map the 2018 rainfall-induced landslides in the Kodagu district of Karnataka state in theWestern Ghats of India.We used a fourfold cross-validation (CV) to select the training and testing data to remove any random results of the model. Topographic slope data was used as auxiliary information to increase the performance of the model. The resulting landslide inventory map, created using the slope data with the …


The Feasibility Of Over-Summer Snow Storage At The Craftsbury Outdoor Center, Craftsbury Vt, Hannah Sarah Weiss 2021 University of Vermont

The Feasibility Of Over-Summer Snow Storage At The Craftsbury Outdoor Center, Craftsbury Vt, Hannah Sarah Weiss

Graduate College Dissertations and Theses

Climate change increases the unpredictability of winter weather and threatens the future of nordic skiing. Ski centers at high elevation and high latitude have employed over-summer snow storage, a climate change adaptation strategy, to ensure a consistent start-date to their winter ski season. Over-summer snow storage involves making a large pile of snow during winter and storing the snow beneath protective layers, such as wood chips or foam panels, to impede melt throughout the summer and fall. When ready to open the ski season, the ski center uncovers the pile and spreads the snow to create trails. Though many nordic …


A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali 2021 University of Nebraska-Lincoln

A 3d Point Cloud Deep Learning Approach Using Lidar To Identify Ancient Maya Archaeological Sites, Heather Richards-Rissetto, David Newton, Aziza Al Zadjali

Department of Anthropology: Faculty Publications

Airborne light detection and ranging (LIDAR) systems allow archaeologists to capture 3D data of anthropogenic landscapes with a level of precision that permits the identification of archaeological sites in difficult to reach and inaccessible regions. These benefits have come with a deluge of LIDAR data that requires significant and costly manual labor to interpret and analyze. In order to address this challenge, researchers have explored the use of state-of-the-art automated object recognition algorithms from the field of deep learning with success. This previous research, however, has been limited to the exploration of deep learning processes that work with only 2D …


Modelling Acoustics In Ancient Maya Cities: Moving Towards A Synesthetic Experience Using Gis & 3d Simulation, Graham Goodwin, Heather Richards-Rissetto 2021 University of California, Merced

Modelling Acoustics In Ancient Maya Cities: Moving Towards A Synesthetic Experience Using Gis & 3d Simulation, Graham Goodwin, Heather Richards-Rissetto

Department of Anthropology: Faculty Publications

Archaeological analyses have successfully employed 2D and 3D tools to measure vision and movement within cityscapes; however, built environments are often designed to invoke synesthetic experiences. GIS and Virtual Reality (VR) now enable archaeologists to also measure the acoustics of ancient spaces. To move toward an understanding of synesthetic experience in ancient Maya cities, we employ GIS and 3D modelling to measure sound propagation and reverberation using the main civic-ceremonial complex in ancient Copán as a case study. For the ancient Maya, sight and sound worked in concert to create ritually-charged atmospheres and architecture served to shape these experiences. Together …


Classification And Evaluation Of Extended Pics (Epics) On A Global Scale For Calibration And Stability Monitoring Of Optical Satellite Sensors, Juliana Maria Fajardo Rueda 2021 South Dakota State University

Classification And Evaluation Of Extended Pics (Epics) On A Global Scale For Calibration And Stability Monitoring Of Optical Satellite Sensors, Juliana Maria Fajardo Rueda

Electronic Theses and Dissertations

As targets for the calibration and monitoring of optical satellite sensors, historically stable areas across North Africa have been used, known as Pseudo Invariant Calibration Sites PICS. However, two major drawbacks exist for these sites; first is the dependency on a single location to be always invariant, and second is the limited amount of observation achieved using these sites. As a result, longer time periods are needed to construct a dense data set to assess the radiometric performance of on-orbit optical sensors, and be convinced that the change detected is sensor-specific rather than site-specific. This work presents a global land …


Detection Of Change Points In Pseudo-Invariant Calibration Sites Time Series Using Multi-Sensor Satellite Imagery, Neha Khadka 2021 South Dakota State University

Detection Of Change Points In Pseudo-Invariant Calibration Sites Time Series Using Multi-Sensor Satellite Imagery, Neha Khadka

Electronic Theses and Dissertations

The remote sensing community has extensively used Pseudo-Invariant Calibration Sites (PICS) to monitor the long-term in-flight radiometric calibration of Earth-observing satellites. The use of the PICS has an underlying assumption that these sites are invariant over time. However, the site’s temporal stability has not been assured in the past. This work evaluates the temporal stability of PICS by not only detecting the trend but also locating significant shifts (change points) lying behind the time series. A single time series was formed using the virtual constellation approach in which multiple sensors data were combined for each site to achieve denser temporal …


Using New And Long-Term Multi-Scale Remotely Sensed Data To Detect Recurrent Fires And Quantify Their Relationship To Land Cover/Use In Indonesian Peatlands, Yenni Vetrita 2021 South Dakota State University

Using New And Long-Term Multi-Scale Remotely Sensed Data To Detect Recurrent Fires And Quantify Their Relationship To Land Cover/Use In Indonesian Peatlands, Yenni Vetrita

Electronic Theses and Dissertations

Indonesia has committed to reducing its greenhouse gases emissions by 29% (potentially up to 41% with international assistance) by 2030. Achieving those targets requires many efforts but, in particular, controlling the fire problem in Indonesia’s peatlands is paramount, since it is unlikely to diminish on its own in the coming decades. This study was conducted in Sumatra and Kalimantan peatlands in Indonesia. Four MODIS-derived products (MCD45A1 collection 5.1, MCD64A1 (collection 5.1 and 6), FireCCI51) were initially assessed to explore long-term fire frequency and land use/cover change relationships. The results indicated the product(s) could only detect half of the fires accurately. …


Quantifying The Impacts Of Land Use, Management And Climate Change On Water Resources In Missouri River Basin, Arun Bawa 2021 South Dakota State University

Quantifying The Impacts Of Land Use, Management And Climate Change On Water Resources In Missouri River Basin, Arun Bawa

Electronic Theses and Dissertations

A location-specific evaluation of hydrological landscape responses concerning past and projected climate and land use land cover (LULC) changes can provide a powerful intellectual basis for developing efficient and profitable agroecosystems, and overcoming uncertain and detrimental consequences of LULC and climate shifts. This dissertation assessed the impacts of land use, management, and climate change on water resources in the Missouri River Basin (MRB) through four specific studies that included: (i) to study the responses of leached nutrient concentrations and soil health to winter rye cover crop (CC) under no-till corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotation, (ii) to …


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