Remote Sensing Commons^™

Creating A Field-Wide Forage Canopy Model Using Uavs And Photogrammetry Processing, Cameron Minch, Joseph S. Dvorak, Joshua J. Jackson, Stuart Tucker Sheffield

Biosystems and Agricultural Engineering Faculty Publications

Alfalfa canopy structure reveals useful information for managing this forage crop, but manual measurements are impractical at field-scale. Photogrammetry processing with images from Unmanned Aerial Vehicles (UAVs) can create a field-wide three-dimensional model of the crop canopy. The goal of this study was to determine the appropriate flight parameters for the UAV that would enable reliable generation of canopy models at all stages of alfalfa growth. Flights were conducted over two separate fields on four different dates using three different flight parameters. This provided a total of 24 flights. The flight parameters considered were the following: 30 m altitude with …

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

Monitoring War Destruction From Space Using Machine Learning, Hannes Mueller, Andre Groeger, Jonathan Hersh, Andrea Matranga, Joan Serrat

Economics Faculty Articles and Research

Satellite imagery is becoming ubiquitous. Research has demonstrated that artificial intelligence applied to satellite imagery holds promise for automated detection of war-related building destruction. While these results are promising, monitoring in real-world applications requires high precision, especially when destruction is sparse and detecting destroyed buildings is equivalent to looking for a needle in a haystack. We demonstrate that exploiting the persistent nature of building destruction can substantially improve the training of automated destruction monitoring. We also propose an additional machine-learning stage that leverages images of surrounding areas and multiple successive images of the same area, which further improves detection significantly. …

Mapping The Suitability Of Cal Poly's Insulated Solar Electric Cookers (Isec) In Ghana, Togo, And Jamaica, Julia G. Kraatz

Social Sciences

The World Health Organization estimates that 3 billion people depend on biomass fuels for cooking, heating, and other day-to-day activities, which causes approximately 4.3 million people annually to die from illnesses attributable to indoor air pollution. The issue is especially pressing for women and children in developing countries, because women care for the home and are consequently responsible for attaining household fuels and cooking. In 2015, ISECs (Insulated Solar Electric Cookers) were developed at California Polytechnic State University, San Luis Obispo, as a technology that utilizes solar electricity to directly cook food in a well-insulated chamber. They are capable of …

Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals

Faculty Publications

Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …

El Atlas De Las Carreteras Propuestas En La Zona Transfronteriza Ucayali, Perú-Acre, Brasil, David S. Salisbury, Stephanie A. Spera, Elspeth Collard*, Anna Frisbie*, M. R. Place*, Yunuen Reygadas Langarica, Elizabeth Zizzamia

Multimedia

El Atlas de las Carreteras Propuestas en la Zona Transfronteriza Ucayali, Perú-Acre, Brasil incluye una serie de 15 mapas de dos carreteras propuestas: 1) Pucallpa, Perú-Cruzeiro do Sul, Brasil; 2) Nuevo Italia-Puerto Breu, Perú. El objetivo del atlas es presentar los mapas, posters, e información geográfica para dar una perspectiva geográfica de las propuestas de carreteras y entender mejor los posibles impactos socio-ambientales en estas áreas fronterizas con altos índices en diversidad ambiental y cultural. Los mapas y posters son de acceso público.

Using Uncrewed Aerial Vehicles For Identifying The Extent Of Invasive Phragmites Australis In Treatment Areas Enrolled In An Adaptive Management Program, Colin Brooks, Charlotte Weinstein, Andrew Poley, Amanda Grimm, Nicholas Marion, Laura Bourgeau-Chavez, Dana Hansen, Kurt Kowalski

Michigan Tech Publications, Part 1

Higher spatial and temporal resolutions of remote sensing data are likely to be useful for ecological monitoring efforts. There are many different treatment approaches for the introduced European genotype of Phragmites australis, and adaptive management principles are being integrated in at least some long-term monitoring efforts. In this paper, we investigated how natural color and a smaller set of near-infrared (NIR) images collected with low-cost uncrewed aerial vehicles (UAVs) could help quantify the aboveground effects of management efforts at 20 sites enrolled in the Phragmites Adaptive Management Framework (PAMF) spanning the coastal Laurentian Great Lakes region. We used object-based image …

Digital Earth: The Impact Of Geographic Technology Through The Ages, Mishka Vance Huq

Theses and Dissertations

Geographic technology encompasses a wide range of geographic knowledge, concepts, processes, and artifacts. Because of its interdisciplinarity and integration with other technologies, the paper examines the diffuse impacts of geographic technology within the evolving relationship between technological and societal developments over time.

Investigating Water Usage Patterns Tied To California State Water Project, Xiaoqing Wu

Publications and Research

California (USA) is the largest agricultural producer and one of the populous states in the United State. As the population and agriculture grows, water consumption patterns become crucial to keep track of especially surface water. In this research project, we studied possible changes in water consumption patterns in different counties and water rights holders who obtain surface water supply from the State Water Project (SWP) in California. We conducted a time series analysis on the California Monthly Diverted Surface Water dataset through two different time series forecasting models. Our analysis indicates that the total diverted surface water presents a periodic …

Downscaling Methodology For Satellite Land Surface Temperatures Over Urban Environments, Naved Khan, Ruben Vecino

Publications and Research

The objective of this study is to develop high spatial and temporal resolution Land Surface Temperature (LST) data using a combination of Landsat 8, infrared satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellite-R Series (GOES-16). The Landsat 8 Thermal Infrared Sensor (TIRS) provides higher spatial resolution (30 m) estimates of skin temperature every 16 days. MODIS makes daytime and nighttime observations of the Earth’s thermal emission at a coarser spatial resolution (1000 m), while GOES-16, which has lower spatial resolution (2 km), measures the skin temperature at a much higher temporal resolution …

No More Shade: Deforestation And Rural-Urban Migration In Nigeria, Kambre Sims

Master's Theses

Some of the most well-documented motivating factors of migration in Nigeria include education, employment opportunities, and cultural conflicts. However, as the deforestation crisis has not improved and Nigeria has maintained its spot as the country with the most deforestation on Earth, access to critical forest resources may be in danger. In light of this crisis, this paper attempts to determine if deforestation has become a new motivating factor for migration as those in rural communities seek other avenues of obtaining those vital resources. Subsequently, Nigeria is also experiencing a housing crisis within its rapidly growing urban centers; obtaining and keeping …

The Role Of Elevation As A Control On Salt Marsh-Upland Ecotones Along The Mississippi Gulf Coast, Carlton P. Anderson

Dissertations

Salt marshes are critical ecological gems that serve as habitat for many specialized species of flora and fauna, while providing a natural buffer to human populations from tropical cyclone impacts. However, rises growth of coastal populations has led to greater strain on the natural services these ecosystems provide. To better understand and project the future of coastal evolution, the physical, mechanical, and biological feedbacks between the natural and human coupled systems need to be more defined and thoroughly understood. Human encroachment towards naturally retreating shorelines will lead to coastal communities being more susceptible to nuisance tidal flooding and minor tropical …

Assessment Of Normalized Water-Leaving Radiance Derived From Goci Using Aeronet-Oc Data, Mingjun He, Shuangyan He, Xiaodong Zhang, Feng Zhou, Peiliang Li

Faculty Publications

The geostationary ocean color imager (GOCI), as the world’s first operational geostationary ocean color sensor, is aiming at monitoring short-term and small-scale changes of waters over the northwestern Pacific Ocean. Before assessing its capability of detecting subdiurnal changes of seawater properties, a fundamental understanding of the uncertainties of normalized water-leaving radiance (nLw) products introduced by atmospheric correction algorithms is necessarily required. This paper presents the uncertainties by accessing GOCI-derived nLw products generated by two commonly used operational atmospheric algorithms, the Korea Ocean Satellite Center (KOSC) standard atmospheric algorithm adopted in GOCI Data Processing System (GDPS) and the NASA standard atmospheric …

Monitoring White-Tailed Deer Abundance And Habitat Selection In The Albany Pine Bush Preserve Using Unmanned Aerial Systems, Christopher Plummer

Legacy Theses & Dissertations (2009 - 2024)

Unmanned aerial systems (UAS) have seen recent advancements in technology that gave rise to their increasing use in recreational and commercial application, including wildlife conservation. Adaptive management is a must for wildlife conservation, with the goal of learning from management decisions to improve future management strategies, especially in the face of growing human related stressors such as climate change and habitat loss. Monitoring is a critical step for adaptive management, as it allows the manger to learn about the ecology of the natural system and quantify the impacts of management strategies. Species and habitats are frequently monitored for wildlife conservation …

Estimation Of Spatial Change In Cropland Area And Evaluation Of Irrigation Performance In Imperial Valley Using Remotely Sensed Data, Usha Poudel

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Imperial Valley (IV) in the US is an extensively irrigated agricultural region, which includes multiple crops changing on an annual and semiannual basis. The valley is facing grave concerns about water management due to its semi-arid environment, water intensive crops, and limited water supply. A simple, inexpensive, and repeatable method to detect changes in cropping patterns may assist irrigation managers to understand crop diversification and associated consumptive use. In addition, a spatial assessment of existing water irrigation system performance and productivity is crucial to benchmark and improve current water management strategies. This thesis estimates the spatial pattern of change …

Spatiotemporal Distributions Of Sargassum On Grand Cayman, Graeme Timmeney

Masters Theses

This mixed methods research examines individual perceptions of Sargassum on Grand Cayman’s beaches in 2020 using participant mapping, and semi – structured interviews. Results from the participant mapping are compared to satellite detection of sargassum. Sargassum poses health risks to both humans and the natural environment. Decaying Sargassum produces sulfuric gas and prevents young turtle hatchlings from reaching the ocean. Since 2011, Sargassum has diffused beyond the Sargasso Sea into entirely novel locations, spanning from the west African Coast to the Gulf of Mexico. Increased biomass has proven to be overwhelming for many Caribbean Islands, including Grand Cayman where hundreds …

Spatial Assessment Of Urban Growth In Cities Of The Decapolis; And The Implications For Modern Cities, Wade A. Pierson

Graduate Theses and Dissertations

The Levant’s Decapolis was a network of ten cities in Greco-Roman Israel, Jordan, and Syria that established a thriving economic community. The Decapolis was home to ancient and modern cities like Damascus (Dammásq) and Amman (Philadelphia). Despite the various origins of these cities, Roman administration and their city planners oversaw the implementation of idealized Roman city form throughout the region. Three Decapolis cities represent intriguing examples of the larger confederation. Philadelphia (Amman), Gerasa (Jerash), and Gadara (Umm Qais) represent cities of common original urban form which developed drastically diverse urban morphologies over time.

Spatial analyses of these cities required working …

Kaleidoscope Of Urban Evapotranspiration: Exploring The Science And Modeling Approaches, Rubab Saher

UNLV Theses, Dissertations, Professional Papers, and Capstones

Urban evapotranspiration is a complex physical process. It depends on various critical drivers, including the land surface temperature (LST), surface albedo, landscape types, and building orientations. All of these factors create difficulties in the estimation of evapotranspiration (ET) by changing the microclimate conditions. The literature has oversimplified microclimate conditions by considering temperature difference as the only variable defining climate. The physical process depends on land-use changes, building proximities, and landscape types. This study devised three objectives to understand the microclimate effects on ET.

In the first objective, land-use change effects on LST, surface albedo, and ET were analyzed over a …

Detecting Recent Crop Phenology Dynamics In Corn And Soybean Cropping Systems Of Kentucky, Yanjun Yang, Bo Tao, Liang Liang, Yawen Huang, Christopher J. Matocha, Chad D. Lee, Michael Sama, Bassil El Masri, Wei Ren

Geography Faculty Publications

Accurate phenological information is essential for monitoring crop development, predicting crop yield, and enhancing resilience to cope with climate change. This study employed a curve-change-based dynamic threshold approach on NDVI (Normalized Differential Vegetation Index) time series to detect the planting and harvesting dates for corn and soybean in Kentucky, a typical climatic transition zone, from 2000 to 2018. We compared satellite-based estimates with ground observations and performed trend analyses of crop phenological stages over the study period to analyze their relationships with climate change and crop yields. Our results showed that corn and soybean planting dates were delayed by 0.01 …

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

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

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

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

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

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

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

Michigan Tech Publications, Part 1

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

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

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

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 …