Engineering Commons^™

Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R² = 0.72) to physical chlorophyll-a …

Using Remote Sensing Technologies In Relocating Lubrak Village And Visualizing Flood Damages, Ronan Wallace

Independent Study Project (ISP) Collection

As weather patterns change across the world, there are communities impacted by climate change that are left unnoticed. In the Himalayan mountain range, communities have suffered, experiencing an increase in flash flooding and droughts. For Lubrak Village in Lower Mustang, the community faces the threats of flash flooding. Over the last ten years, the amount of flash flooding has increased, occurring more than once each monsoon season. After every flood, concrete-like sediment is left behind, hardening across the riverbed and increasing its elevation. As the riverbed elevation increases, this sediment encroaches on Lu-brak Village’s agricultural fields and ancient mud buildings, …

Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li

Electrical & Computer Engineering Faculty Publications

Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t₁ together with low-resolution images at a …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

Characterizing Soil Stiffness Using Thermal Remote Sensing And Machine Learning, Jordan Ewing, T. Oommen, Paramsothy Jayakumar, Russell Alger

Michigan Tech Publications

Soil strength characterization is essential for any problem that deals with geomechanics, including terramechanics/terrain mobility. Presently, the primary method of collecting soil strength parameters through in situ measurements but sending a team of people out to a site to collect data this has significant cost implications and accessing the location with the necessary equipment can be difficult. Remote sensing provides an alternate approach to in situ measurements. In this lab study, we compare the use of Apparent Thermal Inertia (ATI) against a GeoGauge for the direct testing of soil stiffness. ATI correlates with stiffness, so it allows one to predict …

Rapid Quantification Of Biofouling With An Inexpensive, Underwater Camera And Image Analysis, Matthew R. First, Scott C. Riley, Kazi Aminul Islam, Victoria Hill, Jiang Li, Richard C. Zimmerman, Lisa A. Drake

Electrical & Computer Engineering Faculty Publications

To reduce the transport of potentially invasive species on ships' submerged surfaces, rapid-and accurate-estimates of biofouling are needed so shipowners and regulators can effectively assess and manage biofouling. This pilot study developed a model approach for that task. First, photographic images were collected in situ with a submersible, inexpensive pocket camera. These images were used to develop image processing algorithms and train machine learning models to classify images containing natural assemblages of fouling organisms. All of the algorithms and models were implemented in a widely available software package (MATLAB^©). Initially, an unsupervised clustering model was used, and three …

Remote Sensing And Three-Dimensional Photogrammetric Analysis Of Glaciofluvial Sand And Gravel Deposits For Aggregate Resource Assessment In Mchenry County, Illinois, Usa, Xiaodong Miao, Christopher J. Stohr, Paul R. Hanson, Qiansuo Wang

School of Natural Resources: Faculty Publications

Sand and gravel deposits, one of the most common natural resources, are used as aggregates mostly by the construction industry, and their extraction contributes significantly to a region's economy. Thus, it is critical to locate sand and gravel deposits, and evaluate their quantity and quality safely and quickly. However, information on aggregate resources is generally only available from conventional two-dimensional (2-D) geologic maps, and direct field measurements for quality analysis at outcrops are time consuming and are often not possible due to safety concerns, or simply because exposures are too difficult to access. In this study, we presented a methodology …

Performance Across Worldview-2 And Rapideye For Reproducible Seagrass Mapping, Megan M. Coffer, Blake A. Schaeffer, Richard C. Zimmerman, Victoria Hill, Jiang Li, Kazi A. Islam, Peter J. Whitman

OES Faculty Publications

Satellite remote sensing offers an effective remedy to challenges in ground-based and aerial mapping that have previously impeded quantitative assessments of global seagrass extent. Commercial satellite platforms offer fine spatial resolution, an important consideration in patchy seagrass ecosystems. Currently, no consistent protocol exists for image processing of commercial data, limiting reproducibility and comparison across space and time. Additionally, the radiometric performance of commercial satellite sensors has not been assessed against the dark and variable targets characteristic of coastal waters. This study compared data products derived from two commercial satellites: DigitalGlobe's WorldView-2 and Planet's RapidEye. A single scene from each platform …

Disaster Damage Categorization Applying Satellite Images And Machine Learning Algorithm, Farinaz Sabz Ali Pour, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Special information has a significant role in disaster management. Land cover mapping can detect short- and long-term changes and monitor the vulnerable habitats. It is an effective evaluation to be included in the disaster management system to protect the conservation areas. The critical visual and statistical information presented to the decision-makers can help in mitigation or adaption before crossing a threshold. This paper aims to contribute in the academic and the practice aspects by offering a potential solution to enhance the disaster data source effectiveness. The key research question that the authors try to answer in this paper is how …

Remote Sensing Of Water Use Efficiency And Terrestrial Drought Recovery Across The Contiguous United States, Behzad Ahmadi, Ali Ahmadalipour, Glenn Tootle

Civil and Environmental Engineering Faculty Publications and Presentations

Ecosystem water-use efficiency (WUE) is defined as the ratio of carbon gain (i.e., gross primary productivity; GPP) to water consumption (i.e., evapotranspiration; ET). WUE is markedly influential on carbon and water cycles, both of which are fundamental for ecosystem state, climate and the environment. Drought can affect WUE, subsequently disturbing the composition and functionality of terrestrial ecosystems. In this study, the impacts of drought on WUE and its components (i.e., GPP and ET) are assessed across the Contiguous US (CONUS) at fine spatial and temporal resolutions. Soil moisture simulations from land surface modeling are utilized to detect and characterize agricultural …

Uas Flight Operations In Complex Terrain: Assessing The Agricultural Impact From Hurricane Maria In The Central Mountainous Region Of Puerto Rico, Kevin Adkins

Publications

Hurricane Maria struck Puerto Rico in September 2017 as a Category 4 storm causing major damage to infrastructure, agriculture and natural ecosystems, as well as the loss of many lives. Among the crops hardest hit was coffee, one of the most important crops in Puerto Rico. As a perennial system, coffee takes various production forms along a gradient from high shade/biodiversity coffee farms to low shade coffee monocultures and therefore offers an ideal means for the study of resistance and resilience of an agroecosystem to weather and climate disturbance. During the summer of 2018, 14 impacted farms across the production …

Unmanned Aerial Systems For Monitoring Trace Tropospheric Gases, Travis J. Schuyler, Marcelo I. Guzman

Chemistry Faculty Publications

The emission of greenhouse gases (GHGs) has changed the composition of the atmosphere during the Anthropocene. Accurately documenting the sources and magnitude of GHGs emission is an important undertaking for discriminating the contributions of different processes to radiative forcing. Currently there is no mobile platform that is able to quantify trace gases at altitudes(UASs) can be deployed on-site in minutes and can support the payloads necessary to quantify trace gases. Therefore, current efforts combine the use of UASs available on the civilian market with inexpensively designed analytical systems for monitoring atmospheric trace gases. In this context, this perspective introduces the …

Development Of Geospatial And Temporal Characteristics For Hispaniola’S Lake Azuei And Enriquillo Using Landsat Imagery, Mahrokh Moknatian, Michael Piasecki, Jorge Gonzalez

Publications and Research

In this paper, we used Landsat imagery for water body identification to create a novel 36-year surface area extent time series for lakes Azuei (Haiti) and Enriquillo (Dominican Republic) aimed at illuminating the dramatic temporal changes of these two lakes not just at yearly but at monthly or even sub-monthly scales. We used the Normalized Difference Water Index (NDWI) to extract water features and we also used spatial differentiation and thresholding techniques to remove clouds and associated shadows from the scene that were then passed through gap filling algorithms to complete and extract the lake extent polygons. We also explored …

A Method For Reflectance Index Wavelength Selection From Moisture-Controlled Soil And Crop Residue Samples, Ali Hamidisepehr, Michael P. Sama, Aaron P. Turner, Ole O. Wendroth

Biosystems and Agricultural Engineering Faculty Publications

Reflectance indices are a method for reducing the dimensionality of spectral measurements used to quantify material properties. Choosing the optimal wavelengths for developing an index based on a given material and property of interest is made difficult by the large number of wavelengths typically available to choose from and the lack of homogeneity when remotely sensing agricultural materials. This study aimed to determine the feasibility of using a low-cost method for sensing the moisture content of background materials in traditional crop remote sensing. Moisture-controlled soil and wheat stalk residue samples were measured at varying heights using a reflectance probe connected …

Utilizing Vegetation Indices As A Proxy To Characterize The Stability Of A Railway Embankment In A Permafrost Region, Priscilla Addison, Pasi T. Lautala, Thomas Oommen

Michigan Tech Publications

Degrading permafrost conditions around the world are posing stability issues for infrastructure constructed on them. Railway lines have exceptionally low tolerances for differential settlements associated with permafrost degradation due to the potential for train derailments. Railway owners with tracks in permafrost regions therefore make it a priority to identify potential settlement locations so that proper maintenance or embankment stabilization measures can be applied to ensure smooth and safe operations. The extensive discontinuous permafrost zone along the Hudson Bay Railway (HBR) in Northern Manitoba, Canada, has been experiencing accelerated deterioration, resulting in differential settlements that necessitate continuous annual maintenance to avoid …

Estimating The Probability Of Vegetation To Be Groundwater Dependent Based On The Evaluation Of Tree Models, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi

Publications and Research

Groundwater Dependent Ecosystems (GDEs) are increasingly threatened by humans’ rising demand for water resources. Consequently, it is imperative to identify the location of GDEs to protect them. This paper develops a methodology to identify the probability of an ecosystem to be groundwater dependent. Probabilities are obtained by modeling the relationship between the known locations of GDEs and factors influencing groundwater dependence, namely water table depth and climatic aridity index. Probabilities are derived for the state of Nevada, USA, using modeled water table depth and aridity index values obtained from the Global Aridity database. The model selected results from the performance …

A Review Of Advances In The Identification And Characterization Of Groundwater Dependent Ecosystems Using Geospatial Technologies, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi, Roy A. Armstrong

Publications and Research

Groundwater Dependent Ecosystem (GDE) protection is increasingly being recognized as essential for the sustainable management and allocation of water resources. GDE services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in remote sensing technologies and their integration with Geographic Information Systems (GIS) has provided alternative ways to map GDEs at a much larger spatial extent. This paper presents a review …

Informative Spectral Bands For Remote Green Lai Estimation In C3 And C4 Crops, Oz Kira, Anthony L. Nguy-Robertson, Timothy J. Arkebauer, Raphael Linker, Anatoly A. Gitelson

School of Natural Resources: Faculty Publications

Green leaf area index (LAI) provides insight into the productivity, physiological and phenological status of vegetation. Measurement of spectral reflectance offers a fast and nondestructive estimation of green LAI. A number of methods have been used for the estimation of green LAI; however, the specific spectral bands employed varied widely among the methods and data used. Our objectives were (i) to find informative spectral bands retained in three types of methods, neural network (NN), partial least squares (PLS) regression and vegetation indices (VI), for estimating green LAI in maize (a C4 species) and soybean (a C3 species); (ii) to assess …

Slides: Food Production: Technical Challenges In Agricultural Water Conservation, Perry Cabot

Innovations in Managing Western Water: New Approaches for Balancing Environmental, Social and Economic Outcomes (Martz Summer Conference, June 11-12)

Presenter: Dr. Perry Cabot, Research Scientist and Extension Specialist, Colorado Water Institute, Colorado State University

35 slides

Sparse Coding Based Dense Feature Representation Model For Hyperspectral Image Classification, Ender Oguslu, Guoqing Zhou, Zezhong Zheng, Khan Iftekharuddin, Jiang Li

Electrical & Computer Engineering Faculty Publications

We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l₁/l_q regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear …

Daily Area Of Snow Melt Onset On Arctic Sea Ice From Passive Microwave Satellite Observations 1979–2012, Angela C. Bliss, Mark R. Anderson

Department of Earth and Atmospheric Sciences: Faculty Publications

Variability in snow melt onset (MO) on Arctic sea ice since 1979 is examined by determining the area of sea ice experiencing the onset of melting during the melt season on a daily basis. The daily MO area of the snow and ice surface is determined from passive microwave satellite-derived MO dates for the Arctic Ocean and sub-regions. Annual accumulations of MO area are determined by summing the time series of daily MO area through the melt season. Daily areas and annual accumulations of MO area highlight inter-annual and regional variability in the timing of MO area, which is sensitive …

Assessing The Performance Of A Northern Gulf Of Mexico Tidal Model Using Satellite Imagery, Stephen C. Medeiros, Scott C. Hagen, Naira Chaouch, Jesse Feyen, Marouane Temimi, John F. Weishampel, Yuji Funakoshi, Reza Khanbilvardi

Publications and Research

Tidal harmonic analysis simulations along with simulations spanning four specific historical time periods in 2003 and 2004 were conducted to test the performance of a northern Gulf of Mexico tidal model. A recently developed method for detecting inundated areas based on integrated remotely sensed data (i.e., Radarsat-1, aerial imagery, LiDAR, Landsat 7 ETM+) was applied to assess the performance of the tidal model. The analysis demonstrates the applicability of the method and its agreement with traditional performance assessment techniques such as harmonic resynthesis and water level time series analysis. Based on the flooded/non-flooded coastal areas estimated by the integrated remotely …

Slides: Air Monitoring And Litigation Update, John Jacus

Air Quality Impacts from Oil and Gas Development (January 27)

Presenter: John Jacus, Partner, Davis Graham & Stubbs LLP, reviews recent litigation aimed at oil and gas development activities with respect to air emissions impacts, and also several recent and ongoing studies and ambient monitoring efforts focused upon air emissions from oil and gas activities

23 slides

Use Of Remote Sensing To Support Forest And Wetlands Policies In The Usa, Audrey L. Mayer, Ricardo D. Lopez

College of Forest Resources and Environmental Science Publications

The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the “Roadless Rule” and “Travel Management Rules” as enforced by the US Department of Agriculture Forest Service …

Modeling Acoustic Scattering From The Seabed Using Transport Theory, Jorge Quijano, Lisa M. Zurk

Electrical and Computer Engineering Faculty Publications and Presentations

Radiative Transfer (RT) theory has established itself as an important tool for electromagnetic remote sensing in parallel plane geometries with random distributions of scatterers, and most recently it has also been proposed as a model for the propagation of elastic waves in layered ocean sediments. In this work the capabilities of this model are illustrated, as the RT method is used to predict backscattering strength from laboratory models of random media. The RT model is characterized by its flexibility on accommodating scatterers in a broad variety of sizes, shapes, and acoustic contrast relative to the background media. Additionally, this formulation …

Volcanic Activity: Processing Of Observation And Remote Sensing Data (Vapor), Mark Wylie

Reports

The World Bank makes a very clear distinction between disasters and natural phenomena. Natural phenomena are events like volcanic eruptions. A disaster only occurs when the ability of the community to cope with natural phenomenon has been surpassed, causing widespread human, material, economic or environmental losses. By these definitions, volcanic eruptions do not have to lead to disasters. On November 13, 1985, the second most deadly eruption of the twentieth century occurred in Colombia. Within a few hours of the eruption of the Nevado del Ruiz volcano, 23,000 people were dead because no infrastructure existed to respond to such an …

Vegetation Identification Based On Satellite Imagery, Vamsi K.R. Mantena, Ramu Pedada, Srinivas Jakkula, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)

Electrical & Computer Engineering Faculty Publications

Automatic vegetation identification plays an important role in many applications including remote sensing and high performance flight simulations. This paper presents a method to automatically identify vegetation based upon satellite imagery. First, we utilize the ISODATA algorithm to cluster pixels in the images where the number of clusters is determined by the algorithm. We then apply morphological operations to the clustered images to smooth the boundaries between clusters and to fill holes inside clusters. After that, we compute six features for each cluster. These six features then go through a feature selection algorithm and three of them are determined to …

Investigation Of Image Feature Extraction By A Genetic Algorithm, Steven P. Brumby, James P. Theiler, Simon J. Perkins, Neal R. Harvey, John J. Szymanski, Jeffrey J. Bloch, Melanie Mitchell

Computer Science Faculty Publications and Presentations

We describe the implementation and performance of a genetic algorithm which generates image feature extraction algorithms for remote sensing applications. We describe our basis set of primitive image operators and present our chromosomal representation of a complete algorithm. Our initial application has been geospatial feature extraction using publicly available multi-spectral aerial-photography data sets. We present the preliminary results of our analysis of the efficiency of the classic genetic operations of crossover and mutation for our application, and discuss our choice of evolutionary control parameters. We exhibit some of our evolved algorithms, and discuss possible avenues for future progress.