Remote Sensing Commons^™

Spatiotemporal Observations Of Water Stress In Kansas Winter Wheat And Corn From Remotely Sensed Evapotranspiration And Ndwi, Lindi Diane Oyler

Masters Theses

"Optimizing water use is a growing concern, especially in agricultural communities where water use is high. An important challenge in agricultural water optimization is knowing when and where crop water stress is occurring, particularly on large scales where in-situ measurements are no longer practical to obtain. In an effort to combat this challenge, this study utilizes remotely sensed evapotranspiration (ET) and Normalized Difference Water Index (NDWI) to evaluate the responses of integrated satellite datasets to water-stressed conditions over fields of irrigated corn, irrigated winter wheat, and rainfed winter wheat from 2007 to 2017 in southwestern Kansas. Using two different ET …

Synergies Among Environmental Science Research And Monitoring Networks: A Research Agenda, J. A. Jones, Peter M. Groffman, J. Blair, F. W. Davis, H. Dugan, E. E. Euskirchen, S. D. Frey, T. K. Harms, E. Hinckley, M. Kosmala, S. Loberg, S. Malone, K. Novick, S. Record, A. V. Rocha, B. L. Ruddell, E. H. Stanley, C. Sturtevant, A. Thorpe, T. White, W. R. Wieder, L. Zhai, K. Zhu

Advanced Science Research Center

Many research and monitoring networks in recent decades have provided publicly available data documenting environmental and ecological change, but little is known about the status of efforts to synthesize this information across networks. We convened a working group to assess ongoing and potential cross-network synthesis research and outline opportunities and challenges for the future, focusing on the US-based research network (the US Long-Term Ecological Research network, LTER) and monitoring network (the National Ecological Observatory Network, NEON). LTER-NEON cross-network research synergies arise from the potentials for LTER measurements, experiments, models, and observational studies to provide context and mechanisms for interpreting NEON …

Multidecadal Analysis Of Beach Loss At The Major Offshore Sea Turtle Nesting Islands In The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Rejoice Thomas, Hesham El-Askary, Sachi Perera, Ace Vincent B. Flandez, Abdullajid U. Basali, Joselito Francis A. Alcaria, Jinoy Gopalan, Surya Prakash Tiwari, Mubarak Al-Jedani, Perdana K. Prihartato, Ronald A. Loughlan, Ali Qasem, Mohamed A. Qurban, Wail Falath, Daniele Struppa

Mathematics, Physics, and Computer Science Faculty Articles and Research

Undocumented historical losses of sea turtle nesting beaches worldwide could overestimate the successes of conservation measures and misrepresent the actual status of the sea turtle population. In addition, the suitability of many sea turtle nesting sites continues to decline even without in-depth scientific studies of the extent of losses and impacts to the population. In this study, multidecadal changes in the outlines and area of Jana and Karan islands, major sea turtle nesting sites in the Arabian Gulf, were compared using available Kodak aerographic images, USGS EROS Declassified satellite imagery, and ESRI satellite images. A decrease of 5.1% and 1.7% …

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

Potential Of Resampled Multispectral Data For Detecting Desmodium-Brachiaria Intercropped With Maize In A 'Push-Pull' System, B. T. Mudereri, E. M. Abdel-Rahman, T. Dube, T. Landmann, S. Niassy, H. E.Z. Tonnang, Z. R. Khan

All Peer-Reviewed Publications

Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds, unfavourable climatic conditions and degraded soils. Weed and pest control, based on the climate-adapted g'push-pull' system, has become an important target for sustainable intensification of food production adopted by many small-holder farmers. However, essential baseline information using remotely sensed data is missing, specifically for the g'push-pull' companion crops. In this study, we investigated the spectral uniqueness of two of the most commonly used g'companion' crops (i.e. greenleaf Desmodium (i Desmodium intortum/i) and Brachiaria (i Brachiaria/i cv Mulato) …

Pre-Emptive Detection Of Mature Pine Drought Stress Using Multispectral Aerial Imagery, Nancy Grulke, Jason Maxfield, Phillip Riggan, Charlie Schrader-Patton

Biology Faculty Publications and Presentations

Drought, ozone (O₃), and nitrogen deposition (N) alter foliar pigments and tree crown structure that may be remotely detectable. Remote sensing tools are needed that pre-emptively identify trees susceptible to environmental stresses could inform forest managers in advance of tree mortality risk. Jeffrey pine, a component of the economically important and widespread western yellow pine in North America was investigated in the southern Sierra Nevada. Transpiration of mature trees differed by 20% between microsites with adequate (mesic (M)) vs. limited (xeric (X)) water availability as described in a previous study. In this study, in-the-crown morphological traits (needle chlorosis, …

Long-Term Ndvi And Recent Vegetation Cover Profiles Of Major Offshore Island Nesting Sites Of Sea Turtles In Saudi Waters Of The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Hesham El-Askary, Ace Vincent B. Flandez, Joshua J. Dagoy, Joselito Francis A. Alcaria, Abdullajid U. Basali, Khaled A. Al-Abdulkader, Ronald A. Loughland, Mohamed A. Qurban

Mathematics, Physics, and Computer Science Faculty Articles and Research

Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the …

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. …

An Evaluation Of Unmanned Aircraft Systems' Ability To Assess Stripe Rust In Large Wheat Breeding Nursies, Jamison T. Murry

Graduate Theses and Dissertations

Stripe Rust (Puccinia striiformis f. sp. tritici) is a foliar disease that significantly impacts global wheat production, and resistant cultivars provide the most efficient method of control. High-throughput phenotyping using unmanned aircraft systems (UAS) offers a potentially more efficient method for field-based phenotyping compared to visual assessment. Here we tested the ability of remote sensing to predict stripe rust severity in a diverse population of 594 soft red winter wheat lines, planted in single-rows, and evaluated them by visually rating stripe rust intensity and remotely using the dark green color index (DGCI), normalized difference vegetation index (NDVI) and blue NDVI. …

Is It Possible To Discern Striga Weed (Striga Hermonthica) Infestation Levels In Maize Agro-Ecological Systems Using In-Situ Spectroscopy?, Bester Tawona Mudereri, Timothy Dube, Saliou Niassy, Emily Kimathi, Tobias Landmann, Zeyaur Khan, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

The invasion by Striga in most cereal crop fields in Africa has posed a significant threat to food security and has caused substantial socioeconomic losses. Hyperspectral remote sensing is an effective means to discriminate plant species, providing possibilities to track such weed invasions and improve precision agriculture. However, essential baseline information using remotely sensed data is missing, specifically for the Striga weed in Africa. In this study, we investigated the spectral uniqueness of Striga compared to other co-occurring maize crops and weeds. We used the in-situ FieldSpec® Handheld 2™ analytical spectral device (ASD), hyperspectral data and their respective narrow-band indices …

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

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 Aircraft Systems To Identify Invasive Species, Tithe Ahmed

Mahurin Honors College Capstone Experience/Thesis Projects

Invasive species serve as a threat to native biodiversity and ecosystem sustainability. Combatting the spread of invasive species requires long-term physical and monetary commitments. In Balule Nature Reserve of Greater Kruger National Park, South Africa, Opuntia ficus-inidica (the common prickly pear) has been a relentless invader, displacing the local flora and fauna. The goal of this project is to battle invasive species such as prickly pear using efficient and inexpensive technology: unmanned aerial vehicles (UAVs or drones) and multispectral sensors.

Using a 4-bandwidth Parrot Sequoia multispectral sensor in tandem with the DJI Phantom Pro 3^TM UAV, images of land …

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 …

Remote Sensing Approaches To Predict Forest Characteristics In Northwest Montana, Ryan P. Rock

Graduate Student Theses, Dissertations, & Professional Papers

Remote sensing can be utilized by land management organizations to save money and time. Mapping vegetation using either aerial photographs or satellite imagery and the applications for forest management are of particular interest to the Montana Department of Natural Resources. In 2018, the organization began a pilot program to test the incorporation of raster analysis of remotely sensed data into their inventory program and had limited success. This analysis identified two areas of improvement: the selection method of inventory plots and the imagery used for classification and metrics. This study found that selecting inventory plots using a generalized random tessellation …

Geographic And Climatic Attributions Of Autumn Land Surface Phenology Spatial Patterns In The Temperate Deciduous Broadleaf Forest Of China, Weiguang Lang, Xiaoqiu Chen, Liang Liang, Shilong Ren, Siwei Qian

Geography Faculty Publications

Autumn vegetation phenology plays a critical role in identifying the end of the growing season and its response to climate change. Using the six vegetation indices retrieved from moderate resolution imaging spectroradiometer data, we extracted an end date of the growing season (EOS) in the temperate deciduous broadleaf forest (TDBF) area of China. Then, we validated EOS with the ground-observed leaf fall date (LF) of dominant tree species at 27 sites and selected the best vegetation index. Moreover, we analyzed the spatial pattern of EOS based on the best vegetation index and its dependency on geo-location indicators and seasonal temperature/precipitation. …

Coral Reef Change Detection In Remote Pacific Islands Using Support Vector Machine Classifiers, Justin J. Gapper, Hesham El-Askary, Erik Linstead, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

Despite the abundance of research on coral reef change detection, few studies have been conducted to assess the spatial generalization principles of a live coral cover classifier trained using remote sensing data from multiple locations. The aim of this study is to develop a machine learning classifier for coral dominated benthic cover-type class (CDBCTC) based on ground truth observations and Landsat images, evaluate the performance of this classifier when tested against new data, then deploy the classifier to perform CDBCTC change analysis of multiple locations. The proposed framework includes image calibration, support vector machine (SVM) training and tuning, statistical assessment …

A Comparative Analysis Of Planetscope And Sentinel Sentinel-2 Space-Borne Sensors In Mapping Striga Weed Using Guided Regularised Random Forest Classification Ensemble, B. T. Mudereri, T. Dube, E. M. Adel-Rahman, S. Niassy, E. Kimathi, Z. Khan, T. Landmann

All Peer-Reviewed Publications

Weeds are one of the major restrictions to sustaining crop productivity. Weeds often outcompete crops for nutrients, soil moisture, solar radiation, space and provide platforms for breeding of pests and diseases. The ever-growing global food insecurity triggers the need for spatially explicit innovative geospatial technologies that can deliver timely detection of weeds within agro-ecological systems. This will help pinpoint maize fields to be prioritized for weed control. Satellite remote sensing offers incomparable opportunities for precision agriculture, ecological applications and vegetation characterisation, with vast socioeconomic benefits. This work compares and evaluates the strength of Sentinel-2 (S2) satellite with the constellation of …

The Use Of Geospatial Modeling And Novel Diagnostics To Detect And Map Risk Factors Of Soil-Transmitted Helminths In Feira De Santana, Brazil, Ryan Harry Avery

LSU Doctoral Dissertations

Soil-transmitted helminth (STH) infections impact billions of people worldwide. The traditional STH control approach is a morbidity control strategy implementing mass drug administration (MDA) programs targeting school-aged children (SAC). In Brazil, this control strategy has decreased STH prevalence to less than 20% in most of the country and providing an opportunity to transition from the morbidity control program and towards a surveillance and response system geared towards STH elimination. Surveillance and response systems geared towards elimination require the implementation higher accuracy diagnostics to detect infection in low-transmission communities, surveillance of entire households, high-resolution modeling at the household-habitat scale, and targeted …

Augmenting Land Cover/Land Use Classification By Incorporating Information From Land Surface Phenology: An Application To Quantify Recent Cropland Expansion In South Dakota, Lan Hoang Nguyen

Electronic Theses and Dissertations

Understanding rapid land change in the U.S. NGP region is not only critical for management and conservation of prairie habitats and ecosystem services, but also for projecting production of crops and biofuels and the impacts of land conversion on water quality and rural transportation infrastructure. Hence, it raises the need for an LCLU dataset with good spatiotemporal coverage as well as consistent accuracy through time to enable change analysis. This dissertation aims (1) to develop a novel classification method, which utilizes time series images from comparable sensors, from the perspective of land surface phenology, and (2) to apply the land …

Characterizing Spatiotemporal Patterns Of White Mold In Soybean Across South Dakota Using Remote Sensing, Confiance L. Mfuka

Electronic Theses and Dissertations

Soybean is among the most important crops, cultivated primarily for beans, which are used for food, feed, and biofuel. According to FAO, the United States was the biggest soybeans producer in 2016. The main soybean producing regions in the United States are the Corn Belt and the lower Mississippi Valley. Despite its importance, soybean production is reduced by several diseases, among which Sclerotinia stem rot, also known as white mold, a fungal disease that is caused by the fungus Sclerotinia sclerotiorum is among the top 10 soybean diseases. The disease may attack several plants and considerably reduce yield. According to …

Unmanned Aerial-Vehicle-Based Measurement Of Urban Forests, Earle W. Isibue

Graduate Research Theses & Dissertations

Human and natural forces continually act on urban forests to producing changes that leading to trees being removed or replanted. Therefore, to manage the urban forest effectively, periodic inventories are needed to ensure that information about the urban forest is current and comprehensive. This task has traditionally been accomplished by manual ground-based field surveys, or more recently by lidar; however, these methods are expensive, either in terms of time, labor, or cost. This project proposes a novel method of using Unmanned Aerial Vehicles (UAVs) to more accurately measure urban tree height and trunk diameter than is currently possible using conventional …

Utilizing Large Scale Datasets To Evaluate Aspects Of A Sustainable Bioeconomy, Gwanseon Kim

Theses and Dissertations--Agricultural Economics

This dissertation combines large scale datasets to evaluate crop prediction, land values, and consumption of a crop being considered to advance a sustainable bioeconomy. In chapter 2, we propose a novel application of the multinomial logit (MNL) model to estimate the conditional transition probabilities of crop choice for the state of Kentucky. Utilizing the recovered transition probabilities the forecast distributions of total acreages for alfalfa, corn, soybeans, tobacco, and wheat produced in the state from 2010 to 2015 can be recovered. The Cropland Data Layer is merged with the Common Land Unit dataset to allow for the identification of crop …

Crown-Level Mapping Of Tree Species And Health From Remote Sensing Of Rural And Urban Forests, Fang Fang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Tree species composition and health are key attributes for rural and urban forest biodiversity, and ecosystem services preservation. Remote sensing has facilitated extraordinary advances in estimating and mapping tree species composition and health. Yet previous sensors and algorithms were largely unable to resolve individual tree crowns and discriminate tree species or health classes at this essential spatial scale due to the low image spectral and spatial resolution. However, current available very high spatial resolution (VHR) remote sensing data can begin to resolve individual tree crowns and measure their spectral and structural qualities with unprecedented precision. Moreover, various machine learning algorithms …

[Introduction To] Collateral Values: The Natural Capital Created By Landscapes Of War., Todd R. Lookingbill, Peter D. Smallwood

Bookshelf

This book explores the unanticipated benefits that may arise after wars and conflicts, showing how the preservation of battlefields and the establishment of borderlands can create natural capital in the former landscapes of war. The editors call this Collateral Value, in contrast to the collateral damage that war inflicts upon infrastructure, natural capital, and human capital. The book includes case studies recounting successes and failures, opportunities and risks, and ambitious proposals.

The book is organized in two sections. The first visits U.S., English, and French battlefield sites dating from medieval England to World War I. The second explores borderlands located …

Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek

Graduate Student Theses, Dissertations, & Professional Papers

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, …

Spatio-Temporal Reconstruction Of Remote Sensing Observations, Kamrul Khan

Graduate Theses and Dissertations

The USDA Forest Service aims to use satellite imagery for monitoring and predicting changes in forest conditions over time within the country. We specifically focus on a 230, 400 hectares region in north-central Wisconsin between 2003 - 2012. The auxiliary data collected from the satellite imagery of this region are relatively dense in space and time and can be used to efficiently predict how the forest condition changed over that decade. However, these records have a significant proportion of missing values due to weather conditions and system failures. To fill in these missing values, we build spaciotemporal models based on …

Evaluation Of Spatial Generalization Characteristics Of A Robust Classifier As Applied To Coral Reef Habitats In Remote Islands Of The Pacific Ocean, Justin J. Gapper, Hesham El-Askary, Erik J. Linstead, Thomas Piechota

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study was an evaluation of the spectral signature generalization properties of coral across four remote Pacific Ocean reefs. The sites under consideration have not been the subject of previous studies for coral classification using remote sensing data. Previous research regarding using remote sensing to identify reefs has been limited to in-situ assessment, with some researchers also performing temporal analysis of a selected area of interest. This study expanded the previous in-situ analyses by evaluating the ability of a basic predictor, Linear Discriminant Analysis (LDA), trained on Depth Invariant Indices calculated from the spectral signature of coral in one location …

Uas-Based Remote Sensing For Weed Identification And Cover Crop Termination Determination, Shailaja Vemula

Student Theses and Dissertations

This project aimed at demonstrating the utility of using unmanned aerial system (UAS) based remote sensing to assess percentage weed coverage and cash crop vegetative coverage development corresponding to cover crop (cereal rye) termination at different growth stages. A UAS equipped with an RGB (visible bands) camera was used to acquire aerial imagery of cover crop integrated soybean plots. The specific objectives were: 1) to discriminate crop and weed vegetation based on (a) spectral information and (b) location relative to the crop rows; (2) to verify optimum timing for cover crop termination using vegetative cover development based on visible spectroscopy …

Predicting Potential Fire Severity Using Vegetation, Topography And Surface Moisture Availability In A Eurasian Boreal Forest Landscape, Lei Fang, Jian Yang, Megan White, Zhihua Liu

Forestry and Natural Resources Faculty Publications

Severity of wildfires is a critical component of the fire regime and plays an important role in determining forest ecosystem response to fire disturbance. Predicting spatial distribution of potential fire severity can be valuable in guiding fire and fuel management planning. Spatial controls on fire severity patterns have attracted growing interest, but few studies have attempted to predict potential fire severity in fire-prone Eurasian boreal forests. Furthermore, the influences of fire weather variation on spatial heterogeneity of fire severity remain poorly understood at fine scales. We assessed the relative importance and influence of pre-fire vegetation, topography, and surface moisture availability …