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USGS1992

Forum on land use and land Cover: Summary report

This report includes the agenda and abstracts of presentations from the Forum on Land Use and Land Cover Data, cohosted by the U. S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA), February 25-27,1992 at the USGS National Center in Reston, Virginia. The Forum was conducted under the auspices of the Federal Geographic Data Committee (FGDC) and was attended by Federal and State managers of programs that produce and use land use and land cover maps and data in support of environmental analysis, monitoring, and policy development. The goal was to improve opportunities for Federal and State coordination, information exchange, data sharing, and work sharing in land use and land cover mapping.

Book↗

USGS2025

Determination of provenance soil type using inductively coupled plasma mass spectrometry (ICP-MS) analyses of Pinus ponderosa ash

This study demonstrates the feasibility of determining soil provenance from tree ash composition using elemental analysis and chemometric techniques. To date, no published studies have applied chemometric approaches to classify ash for provenance determination following forest fires. In this work, Pinus ponderosa ash was analyzed to distinguish samples based on soil type and geographic location. Pinus ponderosa , a widely distributed pine species in the western United States where wildfires are prevalent, was selected as a model system. Needles were collected from trees grown in five distinct soil types across northern Arizona and Colorado, then dry-ashed under controlled conditions. Classification was performed using three preprocessing techniques and five machine learning algorithms, including hierarchical modeling structures to optimize separation. Partial least squares discriminant analysis (PLS-DA) following a Box-Cox transformation yielded the highest classification accuracy, achieving a prediction kappa value of 0.98 for soil type identification. However, classification performance decreased when distinguishing both soil type and geographic location, indicating that additional variability may influence predictive accuracy in broader applications. These findings highlight the potential of inductively coupled plasma mass spectrometry (ICP-MS) and machine learning for post-wildfire forensic analysis and environmental monitoring.

Applied Spectroscopy↗

USGS2008

Standards and specifications for the calibration and stability of amateur digital cameras for close-range mapping applications

Photogrammetry is concerned with the accurate derivation of spatial and descriptive information from imagery that can be used in several applications such as mapping, DEM generation, orthophoto production, construction planning, environmental monitoring, structural analysis, 3D visualization, and change detection. The type of cameras traditionally used for high accuracy projects were large format analogue cameras. In recent years, however, the use of digital cameras for photogrammetric purposes has become more prevalent. The switch by some users from analogue to digital cameras has been fuelled by the ease of use, decreasing cost, and increasing resolution of digital cameras. Digital photogrammetric cameras can be classified into several categories: line cameras (e.g., ADS40 from Leica Geosystems), large format frame cameras (e.g., DMC TM from Zeiss/Intergraph), and medium to small-format digital cameras. More recently, amateur medium-format digital cameras (MFDC) and small-format digital cameras (SFDC) are being used in photogrammetric activities (e.g., in conjunction with LiDAR systems, smaller flight blocks, and for close-range photogrammetric applications). The continuing development in the capabilities of digital photogrammetry coupled with users’ needs has spawned new markets in photogrammetric mapping with amateur digital cameras. With the wide spectrum of designs for amateur digital cameras, several issues have surfaced, including the method and quality of camera calibration, as well as long-term stability. This paper addresses these concerns and outlines possible solutions. First, we will start by introducing an automated methodology for an in-door camera calibration. The main objective of such a procedure is to provide mapping companies using these cameras with a simple calibration procedure that requires an easy-to-establish test field. The paper will then discuss the concept of how to evaluate camera stability, which will be followed by the introduction of a set of tools for its evaluation. Following the discussion on calibration and stability analysis, the paper will deal with several related questions: How to develop meaningful standards for evaluating the outcome from the calibration procedure; How to develop meaningful standards for evaluating the stability of the involved camera; Is there a flexibility in choosing the stability analysis tool based on the geo-referencing procedure; Can the stability analysis be used for evaluating the equivalency of different distortion models. Finally, experimental results are then provided for two small format digital cameras.

Conference Paper↗

USGS2008

U.S.-Mexico Border Geographic Information System

Geographic Information Systems (GIS) and the development of extensive geodatabases have become invaluable tools for addressing a variety of contemporary societal issues and for making predictions about the future. The United States-Mexico Geographic Information System (USMX-GIS) is based on fundamental datasets that are produced and/or approved by the national geography agencies of each country, the U.S. Geological Survey (USGS) and the Instituto Nacional de Estadistica Y Geografia (INEGI) of Mexico, and the International Boundary and Water Commission (IBWC). The data are available at various scales to allow both regional and local analysis. The USGS and the INEGI have an extensive history of collaboration for transboundary mapping including exchanging digital technology and developing methods for harmonizing seamless national level geospatial datasets for binational environmental monitoring, urban growth analysis, and other scientific applications.

Fact Sheet↗

USGS2010

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Open-File Report↗

USGS2021

Coastal wetland shoreline change monitoring: A comparison of shorelines from high-resolution WorldView satellite imagery, aerial imagery, and field surveys

Shoreline change analysis is an important environmental monitoring tool for evaluating coastal exposure to erosion hazards, particularly for vulnerable habitats such as coastal wetlands where habitat loss is problematic world-wide. The increasing availability of high-resolution satellite imagery and emerging developments in analysis techniques support the implementation of these data into shoreline monitoring. Geospatial shoreline data created from a semi-automated methodology using WorldView (WV) satellite data between 2013 and 2020 were compared to contemporaneous field-surveyed Global Position System (GPS) data. WV-derived shorelines were found to have a mean difference of 2 ± 0.08 m of GPS data, but accuracy decreased at high-wave energy shorelines that were unvegetated, bordered by sandy beach or semi-submergent sand bars. Shoreline change rates calculated from WV imagery were comparable to those calculated from GPS surveys and geospatial data derived from aerial remote sensing but tended to overestimate shoreline erosion at highly erosive locations (greater than 2 m yr −1 ). High-resolution satellite imagery can increase the spatial scale-range of shoreline change monitoring, provide rapid response to estimate impacts of coastal erosion, and reduce cost of labor-intensive practices.

Remote Sensing↗

USGS2003

Environmental water-quality zones for streams: A regional classification scheme

Various approaches have been used to classify large geographical areas into smaller regions of similar water quality or extrapolate water-quality data from a few streams to other unmonitored streams. A combination of some of the strengths of existing techniques is used to develop a new approach for these purposes. In this new approach, referred to here as SPARTA (SPAtial Regression-Tree Analysis), environmental characteristics for each monitored stream are first quantified using a Geographic Information System (GIS) and then regression-tree analysis is used to determine which characteristics are most statistically important in describing the distribution of a specific water-quality constituent. GIS coverages of only the most statistically significant environmental characteristics are then used to subdivide the area of interest into relatively homogeneous environmental water-quality zones. Results from the regression-tree analysis not only define the most important environmental characteristics, but also describe how to subdivide the coverage of the specific characteristic (for example, areas with <26% or ???26% soil clay content). The resulting regionalization scheme is customized for each water-quality constituent based on the environmental characteristics most statistically related to that constituent. SPARTA was used to delineate areas of similar phosphorus, nitrogen, and sediment concentrations (by including land-use characteristics) and areas of similar potential water quality (by excluding land-use characteristics). The SPARTA approach reduced the variability in water-quality concentrations (phosphorus, total nitrogen, Kjeldahl nitrogen, and suspended sediment) within similarly classified zones from that obtained using the US Environmental Protection Agency's nutrient ecoregions.

Environmental Management↗

USGS2014

Evaluating the efficiency of environmental monitoring programs

Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.

Ecological Indicators↗

USGS2021

Long-term monitoring of Vermont’s forest soils: Early trends and efforts to address innate variability

Long-term monitoring of forest soils is necessary to understand the effects of continued environmental change, including climate change, atmospheric deposition of metals, and, in many regions, recovery from acidic precipitation. A monitoring program was initiated in 2002 at five protected forest sites, primarily Spodosol soils, in Vermont, northeastern USA. Every 5 years, ten soil pits were sampled from random subplots in a 50 × 50-m plot at each site. Samples were taken by genetic horizon and, to reduce variability and improve comparability, from four specific layers: the combined Oi/Oe layer, the combined Oa/A layer, the top 10 cm of the B horizon, and 60–70 cm below the soil surface (usually the C horizon). The samples were archived and a subset analyzed for carbon, nitrogen, and exchangeable cations. After four sampling campaigns, the average coefficients of variation (CVs) at each site had a broad range, 10.7% for carbon in the Oa/A horizon to 84.3% for exchangeable Ca 2+ in the B horizon. An investigation of variability within the upper 10 cm of the B horizon across a 90-cm soil pit face showed similar CVs to the entire site, emphasizing the need for consistent and careful sampling. After 15 years, temporal trends were significant in the Oa/A and B horizons at two of the five sites, with one site showing an increase in carbon concentration in both layers along with increases in both exchangeable Ca 2+ and Al 3+ in the B horizon, perhaps linked to recovery from acidification. The monitoring program plans to continue at 5-year intervals for the next century.

Vermont↗

USGS2001

Seabird tissue archival and monitoring project: Protocol for collecting and banking seabird eggs

Archiving biological and environmental samples for retrospective analysis is a major component of systematic environmental monitoring. The long-term storage of carefully selected, representative samples in an environmental specimen bank is an important complement to the real-time monitoring of the environment. These archived samples permit: The use of subsequently developed innovative analytical technology that was not available at the time the samples were archived, for clear state-of-art identification an~ quantification of analytes of interest, The identification and quantification of analytes that are of subsequent interest but that were not of interest at the time the samples were archived, and The comparison of present and past analytical techniques and values, providing continued credibility of past analytical values, and allowing flexibility in environmental monitoring programs. Seabirds, including albatrosses, pelicans, cormorants, terns, kittiwakes, murres, guillemots, and puffins spend most of their lives at sea and have special adaptations for feeding in the marine environment, including the ability to excrete the excess salt obtained from ingesting seawater. Many species nest in dense groups (colonies) on steep, precipitous sea-cliffs and headlands. Seabirds are long-lived and slow to mature. They occupy high positions in the marine food web and are considered sensitive indicators for the marine environment (prey includes krill, small fish, and squid). Breeding success, timing of nesting, diets, and survival rates may provide early indications of changing environmental conditions (e.g., see Hatch et aI., 1993). Chemical analysis of seabird tissues, including egg contents, can be particularly useful in determining whether contaminants (and potential biological effects) associated with human industrial activities, such as offshore petroleum and mineral exploration and development, are accumulating in marine environments. The collection and archival of seabird tissues over a period of several years will be a resource for future analyses, providing samples that can be used to determine historical baseline contaminant levels.

Report↗

USGS2005

Environmental exposure modeling and monitoring of human pharmaceutical concentrations in the environment

Human pharmaceuticals are receiving increased attention as environmental contaminants. This is due to their biological activity and the number of monitoring programs focusing on analysis of these compounds in various environmental media and compartments. Risk assessments are needed to understand the implications of reported concentrations; a fundamental part of the risk assessment is an assessment of environmental exposures. The purpose of this chapter is to provide guidance on the use of predictive tools (e.g., models) and monitoring data in exposure assessments for pharmaceuticals in the environment. Methods to predict environmental concentrations from equations based on first principles are presented. These equations form the basis of existing GIS (geographic information systems)-based systems for understanding the spatial distribution of pharmaceuticals in the environment. The pharmaceutical assessment and transport (P h ATE), georeferenced regional exposure assessment tool for European rivers (GREAT-ER), and geographical information system (GIS)-ROUT models are reviewed and recommendations are provided concerning the design and execution of monitoring studies. Model predictions and monitoring data are compared to evaluate the relative utility of each approach in environmental exposure assessments. In summary, both models and monitoring data can be used to define representative exposure concentrations of pharmaceuticals in the environment in support of environmental risk assessments.

Book chapter↗

USGS1997

Matrix-enhanced degradation of p,p'-DDT during gas chromatographic analysis: A consideration

Analysis of p,p ‘-DDT in environmental samples requires monitoring the GC-derived breakdown of this insecticide, which produces p,p ‘-DDD and/or p,p ‘-DDE, both also primary environmental degradation products. A performance evaluation standard (PES) containing p,p ‘-DDT but not p,p ‘-DDD or p,p ‘-DDE can be injected at regular intervals throughout an analytical sequence to monitor GC degradation. Some U.S. EPA methods limit GC breakdown of DDT in the PES to ≤20%. GC/MS analysis of large-volume natural water samples fortified with deuterium- and 13 C-labeled p,p ‘-DDT exhibited up to 65% DDT breakdown by the GC inlet. These matrix-enhanced GC degradation amounts substantially exceeded the <20% breakdown levels indicated by bracketing injections of the PES containing unlabeled and labeled DDT. Substantial matrix-enhanced GC degradation was not observed during analysis of a limited number of fractionated bed-sediment extracts containing labeled DDT. Use of isotopically labeled DDT seems to provide an effective tool for monitoring sample-specific DDT breakdown during GC/MS analysis. However, analyte co-elutions render impractical their use in GC/ECD analysis. The oc currence of matrix-enhanced GC degradation might have important implications on data quality and the resultant interpretations of the environmental degradation of DDT and other thermolabile contaminants.

Environmental Science & Technology↗

USGS1995

Ecosystem trends in the Colorado Rockies

Biological conservation is increasingly moving toward an ecosystem and landscape approach, recognizing the prohibitive cost and difficulty of a species-by-species approach (LaRoe 1993). Also, statewide (e.g., Gap Analysis Program) and national surveys (e.g., Environmental Monitoring and Assessment Program or EMAP) are conducted at a scale and level of resolution that do not meet the needs of most small land-management units that require detailed information at the ecosystem and landscape scale (Stohlgren 1994). The Colorado Rockies are an ideal outdoor laboratory for ecosystem science and management. The escalating environmental threats described in this article compelled us to design a landscape-scale assessment of the status and trends of biotic resources.

Colorado↗

USGS2012

Sampling and analysis plan for the characterization of groundwater quality in two monitoring wells near Pavillion, Wyoming

In June 2010, the U.S. Environmental Protection Agency installed two deep monitoring wells (MW01 and MW02) near Pavillion, Wyoming to study groundwater quality. The U.S Geological Survey, in cooperation with the Wyoming Department of Environmental Quality, designed a plan to collect groundwater data from these monitoring wells. This sampling and analysis plan describes the sampling equipment that will be used, well purging strategy, purge water disposal, sample collection and processing, field and laboratory sample analysis, equipment decontamination, and quality-assurance and quality-control procedures.

Wyoming↗

USGS2020

Oases of the future? Evaluating springs as potential hydrologic refugia in drying climates

Springs in water-limited landscapes are biodiversity hotspots and keystone ecosystems, disproportionately influencing surrounding landscapes despite their often small areas. Some springs served as evolutionary refugia during previous climate drying, supporting relict species in isolated habitats. Understanding whether springs will provide hydrologic refugia from future climate change is important to biodiversity conservation but complicated by hydrologic variability among springs, data limitations, and multiple non-climate threats to groundwater-dependent ecosystems. Here, we present a conceptual framework for categorizing springs as potentially stable, relative, or transient hydrologic refugia in a drying climate. Clues about refugial capacity of springs can be assembled from diverse approaches, including citizen-science-powered ecohydrologic monitoring, remote sensing, landowner interviews, and environmental tracer analysis. Managers can integrate multiple lines of evidence to predict which springs may become future refugia for species of concern, strengthening the long-term effectiveness of springs conservation and restoration and informing climate adaptation for terrestrial and freshwater species.

Frontiers in Ecology and the Environment↗

USGS2006

Land-Cover Trends of the Central Basin and Range Ecoregion

The U.S. Geological Survey (USGS) Land Cover Trends research project is focused on understanding the amounts, rates, trends, causes, and implications of contemporary land-use and land-cover (LU/LC) change in the United States. This project is supported by the USGS Geographic Analysis and Monitoring Program in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). LU/LC change is a pervasive process that modifies landscape characteristics and affects a broad range of socioeconomic, biologic, and hydrologic systems. Understanding the impacts and feedbacks of LU/LC change on environmental systems requires an understanding of the rates, patterns, and driving forces of past, present, and future LU/LC change. The objectives of the Land Cover Trends project are to (1) determine and describe the amount, rates, and trends of contemporary LU/LC change by ecoregion for the period 1973-2000 for the conterminous United States, (2) document the causes, driving forces, and implications of change, and (3) synthesize individual ecoregion results into a national assessment of LU/LC change. The Land Cover Trends research team includes staff from the USGS National Center for Earth Resources Observation and Science (EROS), Rocky Mountain Geographic Science Center, Eastern Geographic Science Center, Mid-Continent Geographic Science Center, and the Western Geographic Science Center. Other partners include researchers at South Dakota State University, University of Southern Mississippi, and State University of New York College of Environmental Science and Forestry. This report presents an assessment of LU/LC change in the Central Basin and Range ecoregion for the period 1973-2000. The Central Basin and Range ecoregion is one of 84 Level-III ecoregions as defined by the Environmental Protection Agency. Ecoregions have served as a spatial framework for environmental resource management and to denote areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of LU/LC change using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.

Scientific Investigations Report↗

USGS2014

Demographic monitoring and population viability analysis of two rare beardtongues from the Uinta Basin

Energy development, in combination with other environmental stressors, poses a persistent threat to rare species endemic to energy-producing regions of the western United States. Demographic analyses of monitored populations can provide key information on the natural dynamics of threatened plant and animal populations and how these dynamics might be affected by present and future development. In the Uinta Basin in Utah and Colorado, Graham's beardtongue ( Penstemon grahamii ) and White River beardtongue ( Penstemon scariosus var. albifluvis ) are 2 rare endemic wildflowers that persist on oil shale habitats that are heavily impacted by current energy exploration and development and are slated for expanded traditional drilling and oil shale development. We described demographic characteristics and population viability for 2 populations of each species that have been monitored since 2004. First, we measured population size, survival rates, transitions between life stages, and recruitment by using individually marked plants at the 4 study areas. We then used matrix population models to determine stochastic population growth rates (λ) and the probability that each population would persist 50 years into the future, given current conditions. The 2 P. grahamii study plots had small populations, averaging 70 adult plants, and relatively constant and high survival in both vegetative and flowering plants. The 2 P. scariosus var. albifluvis study plots had populations that averaged 120 adult plants, with high and stable survival in flowering plants and variable survival in vegetative plants. Recruitment of new seedlings into all populations was low and variable, with most recruitment occurring in one or 2 years. Both P. grahamii populations had λ near 1.0 (stable). One P. scariosus var. albifluvis population appeared to be declining (λ = 0.97), whereas the other was increasing (λ = 1.16). Our analyses reveal populations that appear relatively stable, but that are susceptible to declines now and into the future. Increases in environmental variability, deterministic changes in habitat conditions or stressors, or a single catastrophic event could all have immediately deleterious impacts on the long-term growth trajectory of these populations.

Utah↗

USGS2026

Spatial ecology and recovery patterns of a translocated mammal community in southern Africa

Conservation translocations are an increasingly common tool to restore wildlife populations within protected areas. Along with identifying and mitigating threats, post-release monitoring allows managers to evaluate recovery effectiveness and improve success rates. Multispecies translocations present challenges in monitoring design, data processing, and analysis. Camera traps coupled with computer-vision-assisted workflows, environmental data, and spatially explicit occupancy models show promise for efficient multispecies monitoring over broad spatiotemporal scales. We applied this approach to a large translocation program in Nkhotakota Wildlife Reserve, Malawi, using a six-year camera-trap dataset to assess recovery patterns of nine large herbivore species. We fit spatial occupancy models to estimate species distributions and trends in landscape use while incorporating environmental covariates and accounting for spatial autocorrelation. African bush elephants ( Loxodonta africana ) and cape buffalo ( Syncerus caffer ) showed the strongest evidence of establishment and expansion, while common eland ( Taurotragus oryx ), greater kudu ( Tragelaphus strepsiceros ), plains zebra ( Equus quagga ), and impala ( Aepyceros melampus ) showed positive but weaker or uneven trends. Sable antelope ( Hippotragus niger ) showed evidence of establishment without expansion, whereas waterbuck ( Kobus ellipsiprymnus ) and warthog ( Phacochoerus africanus ) exhibited negative trends, although support for waterbuck declines was weak. Species exhibited variable and seasonally specific relationships with tree density, proximity to water, elevation, slope, and the reserve boundary, indicating that a range of environmental conditions support this mammal community. Our results demonstrate how spatial occupancy models can provide interpretable recovery indicators for multispecies translocations while highlighting how long-term monitoring can distinguish early recovery, behavioral shifts, and interannual variation from long-term population responses.

Nkhotakota Wildlife Reserve↗