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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to be produced to guide national control programs. This study used an ecological niche modeling (ENM) and precision mapping approach to estimate environmental suitability and disease transmission risk. The results show that suitability for schistosomiasis is widespread and covers 264,781 km 2 (102,232 sq miles). Covariates of significance to the model were the accessibility to cities, distance to water, enhanced vegetation index (EVI), annual mean temperature, land surface temperature (LST), clay content, and annual precipitation. Disease transmission risk is greatest in the central highlands, tropical east coast, arid-southwest, and northwest. An estimated 14.9 million people could be at risk of schistosomiasis; 11.4 million reside in rural areas, while 3.5 million are in urban areas. This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations. Because of the focal nature of the disease, these maps can inform national surveillance programs while improving understanding of areas in need of medical interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States

While the market for medium- and heavy-duty battery-electric vehicles (MHD EVs) is still nascent, a growing number of these vehicles are being deployed across the U.S. This study used over 2.3 million miles of operational data from multiple types of MHD EVs across various regions and operating conditions to address knowledge gaps in total cost of ownership and operational range. First, real-world energy cost savings were determined: MHD fleets should experience energy cost savings each year from 2021 to 2035, regardless of vehicle platform, with the greatest savings seen in transit buses (up to USD 4459 annually) and HD trucks (up to USD 3284 annually). Second, to help fleets across various geographies throughout the U.S. assess the suitability of EVs for their year-round operating needs, operational range was modeled using the XGBoost algorithm (R2: 70%) given 22 input features relevant to vehicle efficiency. Finally, this paper recommends (1) that MHD fleets apply energy-saving practices to minimize the impacts of cold temperatures and high congestion levels on vehicle efficiency and range, and (2) that local hauling fleets select trucks with a nominal range nearly double the expected maximum daily range to account for range losses under local, urban driving conditions.

Qiu, Yin (ORCID:0009000900948794)↗
DOE OSTI2018

Local Variability in PV Soiling Rate

We explore local and hyper-local variability in PV soiling rate by examining the correlation between PV system soiling rates over a multi-year period within two groups of First Solar soiling stations in separate regions of California. The results demonstrate significant seasonal variations in monthly-averaged soiling rates, with soiling varying from near 0 to ~0.1%/day in different months and with seasonal patterns that differ between sites. Monthly patterns at nearby sites were more highly correlated, suggesting that soiling rates can be strongly affected by local geography and weather. For the two regions studied, soiling rate pattern correlation diminished beyond a distance on the order of 50 km. In addition, for selected sites we demonstrate within-site variation in soiling rate of up to ~1.5-2x, which may be correlated with proximity to nearby agricultural activity.

14 SOLAR ENERGY↗
DOE OSTI2023

Visualization and Decision Making Design Under Uncertainty

This report documents the program and the outcomes of Dagstuhl Seminar 22331 "Visualization and Decision Making Design Under Uncertainty". The seminar brought together 33 researchers and practitioners from different domains concerned with visualization and decision making under uncertainty including visualization, visual analytics, human-computer interaction, artificial intelligence, climate research, geography and geology. The programme was organized in two parts: In the first part which lasted two days, participants gave short talks where they discussed current practices and the uncertainty visualization challenges they encountered in their own research. At the end of day two, participants brainstormed collectively around the main uncertainty visualization research challenges across domains and applications. In the second part, participants voted for the following three main challenges they wished to discuss for the remainder of the seminar (one and a half days): applications, human-centered uncertainty visualization, a design process for uncertainty visualization. Thus three break-out groups were formed to discuss these challenges. Abstracts for the individual talks and the break-out group activities are included in this report.

decision making↗
DOE OSTI2018

Development of 80- and 100- Mile Work Day Cycles Representative of Commercial Pickup and Delivery Operation

When developing and designing new technology for integrated vehicle systems deployment, standard cycles have long existed for chassis dynamometer testing and tuning of the powertrain. However, to this day with recent developments and advancements in plug-in hybrid and battery electric vehicle technology, no true 'work day' cycles exist with which to tune and measure energy storage control and thermal management systems. To address these issues and in support of development of a range-extended pickup and delivery Class 6 commercial vehicle, researchers at the National Renewable Energy Laboratory in collaboration with Cummins analyzed 78,000 days of operational data captured from more than 260 vehicles operating across the United States to characterize the typical daily performance requirements associated with Class 6 commercial pickup and delivery operation. In total, over 2.5 million miles of real-world vehicle operation were condensed into a pair of duty cycles, an 80-mile cycle and a 100-mile cycle representative of the daily operation of U.S. class 3-6 commercial pickup and delivery trucks. Using novel machine learning clustering methods combined with mileage-based weighting, these composite representative cycles correspond to 90th and 95th percentiles for daily vehicle miles traveled by the vehicles observed. In addition to including vehicle speed vs time drive cycles, in an effort to better represent the environmental factors encountered by pickup and delivery vehicles operating across the United States, a nationally representative grade profile and key status information were also appended to the speed vs. time profiles to produce a 'work day' cycle that captures the effects of vehicle dynamics, geography, and driver behavior which can be used for future design, development, and validation of technology.

100 mile↗
DOE OSTI2023

Vehicle Powertrain Simulation Accuracy for Various Drive Cycle Frequencies and Upsampling Techniques

As connected and automated vehicle technologies emerge and proliferate, lower frequency vehicle trajectory data is becoming more widely available. In some cases, entire fleets are streaming position, speed, and telemetry at sample rates of less than 10 seconds. This presents opportunities to apply powertrain simulators such as the National Renewable Energy Laboratory's Future Automotive Systems Technology Simulator to model how advanced powertrain technologies would perform in the real world. However, connected vehicle data tends to be available at lower temporal frequencies than the 1-10 Hz trajectories that have typically been used for powertrain simulation. Higher frequency data, typically used for simulation, is costly to collect and store and therefore is often limited in density and geography. This paper explores the suitability of lower frequency, high availability, connected vehicle data for detailed powertrain simulation. A large data set of 1 Hz trajectories is used to quantify the accuracy loss when simulating energy consumption for conventional, hybrid, and battery electric powertrains using less than 1 Hz data. Techniques to upsample lower frequency drive cycle data in order to increase accuracy are also explored. Median energy consumption errors when simulating energy consumption for a 1/10 Hz trajectory are found to be 3-6% when compared to 1 Hz trajectories. Applying upsampling and interpolation techniques are shown to reduce the simulation errors by roughly 50%. The findings in this work can guide connected vehicle data collection specifications and processing techniques applied when using collected data for powertrain simulation.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Regional Analysis for an Economically and Environmentally Viable Transition to Heavy-Duty Vehicles with Alternative Powertrains

The transportation sector is responsible for a significant portion of greenhouse gas emissions. Within the sector, truck freight is responsible for a third of the associated emissions. Alternative powertrains are seen as a viable approach to significantly reduce these emissions. Prior to making a large-scale transition, it is important to consider the following questions: will the power grid support a transition to alternative powertrains?; will the transition truly reduce carbon emissions?; and will the transition impose an unnecessary economic burden on companies within the industry? The answer to these questions, however, can vary by geography, maturity/capacity of the energy distribution network or predicted vehicle load. We focus on the latter two questions, investigating the variation in estimated total cost of ownership and carbon emissions across the United States at the zip code level for both heavy-duty battery electric vehicles and heavy-duty fuel cell electric vehicles. As a benchmark, we compare estimated emissions and costs of alternative powertrain vehicles to that of conventional heavy-duty vehicles powered by diesel internal combustion engines. This work highlights areas with electric grids primed for a transition to alternative powertrain vehicles, such as the Pacific Northwest, and areas that require further infrastructure investment in renewables, such as many of the Mountain states, Missouri, and Florida. Additionally, this work illustrates the current advantages in carbon emissions of battery electric vehicles compared to fuel-cell electric vehicles, while providing insights into required regional investments for narrowing the gap.

Goulet, Nate [ORNL] (ORCID:0000000237314965)↗
DOE OSTI2025

LandScan Global 2024

The LandScan program is excited to share LandScan 2024, the latest annual update of a global gridded population dataset at 30 arc-second resolution that serves as foundational GEOINT Human Geography data. Substantial changes were continued from last year in the new ML methodological approach with the goal to retain the knowledge and expertise represented through improvements with each annual release over the past quarter century. Through these annual releases, Oak Ridge National Laboratory (ORNL) has consistently produced the most accurate global gridded population data, reflecting both ambient and unwarned population patterns that meet the United States Department of Defense (U.S. DoD) requirements. Additionally, the dataset is used widely across various U.S. government programs and is released publicly through an NGA and ORNL collaborative open portal (https://LandScan.ornl.gov) to expand its availability to researchers, humanitarian organizations, and the public at large.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2014

Assessment of the Effect of Air Pollution Controls on Trends in Shortwave Radiation over the United States from 1995 through 2010 from Multiple Observation Networks

Long term datasets of total (all-sky) and clear-sky downwelling shortwave (SW) radiation, cloud cover fraction (cloudiness) and aerosol optical depth (AOD) are analyzed together with aerosol concentration from several networks (e.g. SURFRAD, CASTNET, IMPROVE and ARM) in the United States (US). Seven states with varying climatology are selected to better understand the effect of aerosols and clouds on SW radiation. This analysis aims to test the hypothesis that the reductions in anthropogenic aerosol burden resulting from substantial reductions in emissions of sulfur dioxide and nitrogen oxides over the past 15 years across the US has caused an increase in surface SW radiation. We show that the total and clear-sky downwelling SW radiation from seven sites have increasing trends except Penn State which shows no tendency in clear-sky SW radiation. After investigating several confounding factors, the causes can be due to the geography of the site, aerosol distribution, heavy air traffic and increasing cloudiness. Moreover, we assess the relationship between total column AOD with surface aerosol concentration to test our hypothesis. In our findings, the trends of clear-sky SW radiation, AOD, and aerosol concentration from the sites in eastern US agree well with our hypothesis. However, the sites in western US demonstrate increasing AOD associated with mostly increasing trends in surface aerosol concentration. At these sites, the changes in aerosol burden and/or direct aerosol effects alone cannot explain the observed changes in SW radiation, but other factors need to be considered such as cloudiness, aerosol vertical profiles and elevated plumes.

1995-2010↗
DOE OSTI2018

A Suite of Mechanistic Epidemiological Decision Support Tools

Objective: We will demonstrate tools that allow mechanistic contraints on disease progression and epidemic spread to play off against interventions, mitigation, and control measures. The fundamental mechanisms of disease progression and epidemic spread provide important constraints on interpreting changing epidemic cases counts with time and geography in the context of on-going interventions, mitigations, and controls. Models such as these that account for the effects of human actions can also allow evaluation of the importance of categories of epidemic and disease controls. Introduction: We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs. late diagnosis, vaccination, etc. in outbreak control. A fine-grained hybrid-agent epidemic model (EpiCast) with diurnal agent travel and contagion allows the analysis of the importance of contact-networks, travel, and detailed intervention strategies for the control of outbreaks and epidemics. Methods: We use three types of methods for simulation and analysis. They are: (1) Bayesian and regression methods allowing estimation of the basic reproductive number from case-count data; (2) ordinary-differential equation integration with modifications to account for discreteness of disease spread when case counts are small (we include space- and time-dependent effects); and (3) methods that hybridize agent-based travel, mixing, and disease progression with nested-mass action contagion (i.e. not fully agent-based). From the perspective of decision support, the crucial feature of mechanistic infectious epidemiological models is a way to capture the human interventions that determine epidemic outcome. Categorizing types of mitigation into those that change the force of infection, and those that branch disease progression allows a common framework that can be extended from medium-grained models through fine-grained. Our canonical example is our EpiGrid tool which allows for the modulation of the force of infection (i.e. contagion) with time (and potentially space), the vaccination of a susceptible population in a geographically-targeted manner, movement controls, and branching our disease progression model to account for early- vs. late-intervention during host disease progression.ResultsWe will present analysis of diseases that exemplify the various aspects of analysis in support of outbreak and epidemic control. Human and animal diseases relevant to this demonstration include rinderpest, avian influenza, and measles. We will begin with EpiEarly’s estimate of epidemic potential using aggregated time-dependent case-count data. The key observation for EpiEarly is that under a wide range of situations a disease's reproductive number should be generalized to a distribution of possibilities to account for inherent randomness and other factors (including the variability of a disease contact network). We will then continue with a demonstration of EpiGrid’s capabilities for understanding and modelling the role of interventions including contagion control (the force of infection), treatment (changing disease progression and infectiousness depending on treatment), vaccination, culling, and movement controls. We will briefly touch on the capabilities of EpiCast for more detailed analysis of specific intervention strategies. Conclusions: We will demonstrate examples where modeling either contributed or plausibly would contribute to informing epidemic and outbreak control constrained by the possibilities of the underlying epidemic and disease dynamics.

Geospatial↗
DOE OSTI2023

HarDWR - Raw Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. In order to hold a water right in the western United States, an entity, (e.g., an individual, corporation, municipality, sovereign government, or non-profit) must register a physical document with the state's water regulatory agency. State water agencies each maintain their own database containing all registered water right documents within the state, along with relevant metadata such as the point of diversion and place of use of the water. All western U.S. states have digitized their individual water rights databases, along with the geospatial data describing the spatial units where water rights are managed. Each state maintains and provides their own water rights data in accordance with individual state regulations and standards. We collected water rights databases from 11 western United States states either by downloading them from publicly accessible web portals, or by contacting state water management representatives; detailed descriptions of where and when the data was collected is provided in the README.txt, as well as Lisk et al.(in review). This collection of data are those raw water rights. Each state formats their data differently, meaning that file types, field availability, and names vary from state to state. Note, the data provided here reflects the state of the water rights databases at the time we collected the data; updates have likely occurred in many states. Some pieces of information are common among all states. These are: priority date, volume or flow of water allowed by the right, stated water use of the right, and some means of identifying the geography and source of the water pertaining to the right - typically the coordinates of the Point of Diversion (PoD) of a waterbody or well. Arizona regulates water in a different way than the other 10 states. Outside of some relatively small critical agricultural areas called Active Management Areas (AMAs), Arizona does not maintain any water rights. However, the state does require registration of surface and groundwater pumping devices, which includes disclosing the mechanical specifics of the devices. We used these records as a proxy for water rights. Each state, and their respective water right authorities, have made their water right records available for non-commercial reference uses. In addition, the states make no guarantees as to the completeness, accuracy, or timeliness of their respective databases, let alone the modifications which we, the authors of this paper, have made to the collected records. None of the states should be held liable for using this data outside of its intended use. In addition, the following states have requested specifically worded disclaimers to be included with their data. Colorado: "The data made available here has been modified for use from its original source, which is the State of Colorado. THE STATE OF COLORADO MAKES NO REPRESENTATIONS OR WARRANTY AS TO THE COMPLETENESS, ACCURACY, TIMELINESS, OR CONTENT OF ANY DATA MADE AVAILABLE THROUGH THIS SITE. THE STATE OF COLORADO EXPRESSLY DISCLAIMS ALL WARRANTIES, WHETHER EXPRESS OR IMPLIED, INCLUDING ANY IMPLIED WARRANTIES OF MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. The data is subject to change as modifications and updates are complete. It is understood that the information contained in the Web feed is being used at one's own risk." Montana: "The Montana State Library provides this product/service for informational purposes only. The Library did not produce it for, nor is it suitable for legal, engineering, or surveying purposes. Consumers of this information should review or consult the primary data and information sources to ascertain the viability of the information for their purposes. The Library provides these data in good faith but does not represent or warrant its accuracy, adequacy, or completeness. In no event shall the Library be liable for any incorrect results or analysis; any direct, indirect, special, or consequential damages to any party; or any lost profits arising out of or in connection with the use or the inability to use the data or the services provided. The Library makes these data and services available as a convenience to the public, and for no other purpose. The Library reserves the right to change or revise published data and/or services at any time." Oregon: "This product is for informational purposes and may not have been prepared for, or be suitable for legal, engineering, or surveying purposes. Users of this information should review or consult the primary data and information sources to ascertain the usability of the information." The available data is provided as a series of compressed files, which each containing the full data collected from each state. Some of the files have been renamed, to more easily know which state the data belongs to. The file renaming was also required as some files from different states had the same name. In other cases, the data for a state has been placed in a folder indicating which state it belongs to - as the state organized its data by selected subregions. Below is a brief description of the format of the collected data from each state. ArizonaRights_StatementOfClaimants: A folder containing a database of interconnected CSV files. The soc_erd.pdf file contains a visual flowchart of how the various files are connected, beginning with SOC_MAIN.csv in the center of the page. ArizonaRights_SurfaceWaterRightsData: A folder containing a database of a single Shapefile and 10 associated CSVs. SurfaceWater.pdf contains a visual flowchart of how the various files are connected, beginning with ADWR_SW_APPL_REGRY.csv. ArizonaRights_Well55Registry: A folder containing a database of a single Shapefile and 59 associated CSVs. Wells55.pdf contains a visual flowchart of how the various files are connected, beginning with WellRegistry.shp. CaliforniaRights_eWRIMS_directDatabase: A folder containing a collection of four "series" Microsoft Excel files, as either XLS or XLSX. The four "series": byCounty, byEntity (what type of legal entity holds the right), byUse (stated water use), and byWatershed, are various methods by which the California water rights are organized within the state's database. However, it was observed that by only collecting a single series, not all water rights were being provided. So, essentially, the majority of records within each "series" are copies of each other, with each "series" containing some unique records. ColoradoRights_NetAmounts: A folder containing 78 CSV files, with one file per Colorado Water District. IdahoRights_PointOfDiversion: A Shapefile containing the Points of Diversion for the entire state of Idaho. IdahoRights_PlaceOfUse: A Shapefile containing the Place of Use polygons for the entire state of Idaho. MontanaRights_WaterRights: A Geodatabase file containing the Points of Diversion and Places of Use for the entire state of Montana. The name of the Points of Diversion Feature Layer within the Geodatabase is "WRDIV", and the name of the Places of Use Feature Layer is "WRPOU". NevadaRights_POD_Sites: A Shapefile containing the Points of Diversion for the entire state of Nevada. NewMexicoRights_Points_of_Diversion: A Shapefile containing the Points of Diversion for the entire state of New Mexico. OregonRights_state_shp: A folder containing 36 Shapefiles and are split between "pod" (Point of Diversion) and "pou" (Place of Use) for each water management basin within Oregon. In other words, each basin has one "pod" file and one "pou" file. The "pod" files are point shapes, and the "pou" files are polygons. UtahRights_Points_of_Diversion: A Shapefile containing the Points of Diversion for the entire state of Utah. WashingtonRights_WaterDiversions_ECY_NHD: A Geodatabase file containing both the Points of Diversion for the entire state of Washington. The name of the Feature Layer within the Geodatabase is "WaterDiversions_ECY_NHD". WyomingRights: A folder containing four subdirectories, one for each Wyoming Water Division. Each Division directory includes a varying number of subdirectories for each Wyoming Water District. Each District folder contains two copies of the Point of Diversion records for that area, with one copying being in CSV and one copy in Microsoft Excel XLS format.

Lisk, Matthew↗
DOE OSTI2026

Bioengineered algal lipids enriched in structured medium- and long-chain triacylglycerols, linoleate, and sn -2 palmitate for human milk fat substitutes

Human milk fat (HMF) contains triacylglycerol (TAG) as its primary component, providing over 50% of the calories for infant nutrition, along with structural and bioactive lipids that are important for immune and nervous system development. Palmitic acid, comprising 20-25% of the fatty acid complement of HMF, is predominantly esterified to the sn -2 position on the glycerol backbone. This regiospecific positioning facilitates absorption as 2-palmitoyl-monoacylglycerol after hydrolysis of the fatty acids at sn -1 and sn -2 by gut lipases. Other features of HMF include enrichment in structured medium- and long-chain triglycerides (MLCTs), and variation in the ratio of oleic acid to linoleic acid with maternal diet and geography. We have engineered Auxenochlorella, an oleaginous green alga, for biosynthesis of an MLCT- and sn -2 palmitate-enriched HMF substitute for infant formula, matching the regioisomeric composition and proportions of the most abundant fatty acids in HMF.

Lin, Jon Y-T [University of California, Berkeley;]↗
DOE OSTI2017

Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data

This research focused on accelerating solar photovoltaic (PV) diffusion by collecting new market data and developing predictive modeling frameworks to test and refine understandings of household level motivations for adopting solar. Three different household-level surveys were fielded: one for households who had installed PV on their current home or had signed a contract to do so (the Adopter survey), one for households that had seriously considered PV but had not installed it (the Considerer survey), and one for the general population who did not have PV on their current home (the general population survey or GPS). Survey respondents were from four U.S. states: New Jersey, New York, Arizona, and California. Details of recruiting and sampling are documented below. Research projects on residential PV adoption often collect data only from PV adopters or from the general population. One of the innovations of this project was the three-pronged household survey data collection. By collecting similar data from three fairly different "statuses" with respect to adoption, the surveys provide a basis for understanding how those who do not have rooftop PV differ from those who have, for how and why people do (or don't) transition from not having to having rooftop PV on their home, and for understanding the characteristics and viewpoints of households who have scarcely, or not at all, entered the "PV consideration" track. All three surveys covered single-family owner-occupied households in each of the four target states used in the project -- Arizona, California, New Jersey, and New York - allowing a comparative approach to understanding how the factors that affect PV adoption vary by geography and policy conditions. The General Population and Considerer surveys provide a basis for understanding opinions about and interest in solar, and how these relate to household demographics and other conditions. Paired with the Adopter survey, they also provide data for understanding how those who do not have rooftop PV differ from those who have, and for how and why people do (or don't) transition from not having to having rooftop PV on their home. The Adopter survey questions were designed to capture a broad range of information on what motivates and impedes households to install rooftop PV, as well as the details and timing of the decision and installation. Survey instrument development drew from existing PV adoption survey instruments, PV adoption literature, and research team experience, as well as from past work on household interest in energy efficiency, environmental attitudes, purchasing tendencies, and related knowledge. Early interviews and discussions with installers and others in the PV industry were also taken into consideration.

14 SOLAR ENERGY↗
NASA NTRS1971

Experiment S005: Synoptic terrain photography

Several tentative conclusions can be derived from the results of the synoptic terrain photography experiment, with particular reference to the results from the Gemini mission. The photographs are additional confirmation of the feasibility and value of orbital photographs for geology, geography, and oceanography. The photographs have proven to be of value in the study of the tectonic problems. Although vertical or near-vertical photography is superior to oblique photography, photographs from the Gemini 12 mission have proven that low oblique photographs, and even high oblique photographs, may be of value for certain situations. The oblique views of the Makran Range were useful substitutes for vertical photographs. Equivalent aerial coverage by vertical photographs would have necessitated a camera altitude of several hundred miles. The oblique views of the Sierra Madre Oriental have been used in the search for structures that are approximately normal to the horizon and are enhanced by the foreshortening because of the photograph.

Lowman, P. D., Jr.↗
NASA NTRS1971

Studies in remote sensing of Southern California and related environments

A summary is presented of the research activities in southern California to determine whether meaningful geographic information was obtainable by use of remote sensing in an area already well documented or if the techniques and methodology could be transferred to related environments. Several broad characteristics of the regional geography were investigated with regards to their feasibility to be studied by aircraft and spacecraft sensors to improve the inventory and understanding of resources and environmental circumstances and to serve as models for future geographic analysis of other regions when using remote sensing devices. Sample activities are described in detail and three experiments producing worthwhile results are highlighted: mapping montane vegetation with color IR imagery, analysis of urban residual environment using color IR aerial photography, and regional agricultural land use mapping tested against color IR photography.

Bowden, L. W.↗