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At least 1,063 records · Page 59Linked to original sources
USGS2020

Substantially greater carbon emissions estimated based on annual land-use transition data

Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km 2 , respectively, but developed lands gained 293 km 2 (29 km 2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr −1 ) and agricultural expansion (0.046 Tg C·yr −1 ); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

Delaware, Maryland, Virginia↗
USGS2011

Chapter 11: Management considerations

We conducted an ecoregional assessment of sagebrush ( Artemisia spp. ) ecosystems in the Wyoming Basins and surrounding regions (WBEA) to determine broad-scale species-environmental relationships. Our goal was to assess the potential influence from threats to the sagebrush ecosystem on associated wildlife through the use of spatially explicit occurrence and abundance models. These models were developed using information from field surveys conducted along gradients of vegetation productivity and human disturbance integrated with spatial datasets delineating land cover, topography, and human land use in the WBEA area. Our evaluation included all sagebrush-associated wildlife species across multiple taxa whose habitat requirements and distributions were appropriate for modeling and interpretation at the broad scales of this assessment. Dominant land uses were included in delineating the human footprint. Although overall levels of the cumulative human footprint were generally low across the WBEA area, oil and gas activities have decreased the amount of shrubland habitats and increased fragmentation within development regions over the last century. At the scale of this assessment, the influence of humans was primarily expressed as an indirect function through actions that altered or reduced available habitat. We identified 65 plant species of conservation concern; 28 of 40 vertebrate species associated with sagebrush were species of concern in at least one state. We modeled environmental relationships for 15 wildlife species from data collected from surveys conducted in 2005 and 2006 designed to sample multiple species and taxa along land cover and land use gradients across the WBEA area. Occurrence of 3 species was negatively influenced by human features; anthropogenic features were a positive influence for 3 species, 8 had a mixed response, and 1 had no measurable relationship. Sagebrush land cover, considered in all wildlife models, was important to most species but differed among species in the proportion of sagebrush required and at what spatial extent. For most species examined, the spatial extent at which sagebrush cover influenced the probability of occupancy was much larger than an individual’s home range size. Exotic plants were strongly associated with human features, particularly roads, which may function as linear vectors to facilitate spread of exotic plants across the WBEA area. We used coarse-grained spatial and thematic data because of the large spatial extent (350,000 km 2 ) of the WBEA area and the need for a consistent land cover map for the region. Distributions of species occurrence or abundance mapped in this assessment need to be corroborated with information on population demographics. In addition, our results should be interpreted relative to assumptions inherent in broad-scale ecoregional assessments. Our assessment provides managers with extensive and detailed maps of occurrence and abundance, allowing for status assessments of native species, diversity and richness, natural communities, and ecological systems present within the Wyoming Basins.

Wyoming↗
USGS2012

A water-budget model and estimates of groundwater recharge for Guam

On Guam, demand for groundwater tripled from the early 1970s to 2010. The demand for groundwater is anticipated to further increase in the near future because of population growth and a proposed military relocation to Guam. Uncertainty regarding the availability of groundwater resources to support the increased demand has prompted an investigation of groundwater recharge on Guam using the most current data and accepted methods. For this investigation, a daily water-budget model was developed and used to estimate mean recharge for various land-cover and rainfall conditions. Recharge was also estimated for part of the island using the chloride mass-balance method. Using the daily water-budget model, estimated mean annual recharge on Guam is 394.1 million gallons per day, which is 39 percent of mean annual rainfall (999.0 million gallons per day). Although minor in comparison to rainfall on the island, water inflows from water-main leakage, septic-system leachate, and stormwater runoff may be several times greater than rainfall at areas that receive these inflows. Recharge is highest in areas that are underlain by limestone, where recharge is typically between 40 and 60 percent of total water inflow. Recharge is relatively high in areas that receive stormwater runoff from storm-drain systems, but is relatively low in urbanized areas where stormwater runoff is routed to the ocean or to other areas. In most of the volcanic uplands in southern Guam where runoff is substantial, recharge is less than 30 percent of total water inflow. The water-budget model in this study differs from all previous water-budget investigations on Guam by directly accounting for canopy evaporation in forested areas, quantifying the evapotranspiration rate of each land-cover type, and accounting for evaporation from impervious areas. For the northern groundwater subbasins defined in Camp, Dresser & McKee Inc. (1982), mean annual baseline recharge computed in this study is 159.1 million gallons per day, which is 50 percent of mean annual rainfall, and is 42 percent greater than the recharge estimate of Camp, Dresser & McKee Inc. (1982). For the northern aquifer sectors defined in Mink (1991), which encompass most of the northern half of the island, mean annual baseline recharge computed in this study is 238.0 million gallons per day, which is 51 percent of mean annual rainfall, and is about 6 percent lower than the recharge estimate of Mink (1991). For the drought simulation performed in this study, recharge for the entire island is 259.3 million gallons per day, which is 34 percent lower than recharge computed for baseline conditions. For all aquifer sectors defined by Mink (1991), total recharge during drought conditions is 32 percent lower than mean baseline recharge. For the future land-cover water-budget simulation, which represents potential land-cover changes owing to the military relocation and population growth, estimated recharge for the entire island is nearly equal to the baseline recharge estimate that was based on 2004 land cover. Using the water-budget model, estimated recharge in the northern half of the island is most sensitive to crop coefficients and net precipitation rates—two of the water-budget parameters used in the estimation of total evapotranspiration. Estimated recharge in the southern half of the island is most sensitive to crop coefficients, net precipitation rate, and runoff-to-rainfall ratios. During March 2010 to May 2011, bulk-deposition samples from five rainfall stations on Guam were collected and analyzed for chloride. Additionally, samples from five groundwater sites were collected and analyzed for chloride. Results were used to estimate groundwater recharge using the chloride mass-balance method. Recharge estimates using this method at three bulk-deposition stations on the northern limestone plateau range from about 25 to 48 percent of rainfall. These recharge estimates are similar to the estimate of Ayers (1981) who also used this method. Recharge estimates at each bulk-deposition station, however, are lower than the baseline recharge estimate from the water-budget model used in this study. This may be because no large storms, such as tropical cyclones, passed near Guam during March 2010 to May 2011.

Scientific Investigations Report↗
USGS2007

Estimating soil erosion using the USPED model and consecutive remotely sensed land cover observations

Intensified soil erosion contributes to the degradation of ecosystems. Better estimation of soil erosion across landscapes is a necessary part of understanding ecosystem biogeochemical cycles and ecosystem sustainability. In this study, we used the Unit Stream Power-based Erosion Deposition (USPED) model to estimate the lateral movement of soils across Fort Benning, a military training installation in western Georgia, USA. A land cover weight factor was used in the calculation of surface flow accumulation. The simulation results were compared with observations of the total suspended sediments in stream water for ten watersheds, and showed a significant linear relationship (R 2 = 0.72). Erosion estimates of the ten watersheds are also related to the land disturbance index that is a measure of the intensity of military training disturbances. Results suggest that the USPED model is an effective tool to quantify erosion and deposition at military installations.

Georgia↗
USGS2020

Human-associated species dominate passerine communities across the United States

Aim Human development and agriculture can have transformative and homogenizing effects on natural systems, shifting the composition of ecological communities towards non-native and native species that tolerate or thrive under human-dominated conditions. These impacts cannot be fully captured by summarizing species presence, as they include dramatic changes to patterns of species abundance. However, how human land use patterns and species invasions intersect to shape patterns of abundance and dominance within ecological communities is poorly understood even in well-known taxa. Location Conterminous United States. Time period 2010–2012. Major taxa studied Passeriformes. Methods We analyse continental-scale monitoring data to study the proportional abundance of non-native and native synanthropic species within passerine bird communities. Synanthropic species are those that benefit from an association with humans. We estimate how the amount and configuration of human development and agriculture relate to the degree to which human-associated species dominate passerine communities across the continent. Results Human-associated species comprised the majority of detected passerine individuals across two-thirds of bird surveys. Non-native and synanthropic species responded differently to land cover and reached highest relative abundance in different portions of the continent. The proportional abundance of synanthropic birds increased rapidly with development, but was not related to the configuration of land cover. The proportion of non-native individuals was higher when intensively-used land cover was more aggregated. Main conclusions Even low amounts of intensively-used lands were associated with a dramatic reshaping of passerine communities, with consequences for patterns of relative abundance across the continent.

Global Ecology and Biogeography↗
USGS2016

Status and trends of land change in selected U.S. ecoregions - 2000 to 2011

U.S. Geological Survey scientists developed a dataset of 2006 and 2011 land-use and land-cover ( LULC ) information for selected 100-km 2 sample blocks within 29 U.S. Environmental Protection Agency ( EPA ) Level III ecoregions across the conterminous United States. The data can be used with the previously published Land Cover Trends Dataset: 1973 to 2000 to assess landuse/land-cover change across a 37-year study period. Results from analysis of these data include ecoregion-based statistical estimates of the amount of LULC change per time period, ranking of the most common types of conversions, rates of change, and percent composition. Overall estimated amount of change per ecoregion from 2001 to 2011 ranged from a low of 370 km 2 in the Northern Basin and Range Ecoregion to a high of 78,782 km 2 in the Southeastern Plains Ecoregion. The Southeastern Plains continues to encompass one of the most intense forest harvesting and regrowth regions in the country, with 16.6 percent of the ecoregion changing between 2001 and 2011. These LULC change statistics provide a new, valuable resource that complements other reference data and field-verified LULC data. Researchers can use this resource to independently validate other land change products or to conduct regional land change assessments.

Photogrammetric Engineering and Remote Sensing↗
USGS2017

Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).

Open-File Report↗
USGS2019

The driving forces of land change in the Northern Piedmont of the United States

Driving forces facilitate or inhibit land-use/land-cover change. Human driving forces include political, economic, cultural, and social attributes that often change across time and space. Remotely sensed imagery provides regional land-change data for the Northern Piedmont, an ecoregion of the United States that continued to urbanize after 1970 through conversion of agricultural and forest land covers to developed uses. Eight major driving forces facilitated most of the land conversion; other drivers inhibited or slowed change. A synergistic web of drivers may be more important in understanding land change than individual drivers by themselves.

Maryl;New York;Pennsylvania;Virginia↗
USGS2022

Operational assessment tool for forest carbon dynamics for the United States: A new spatially explicit approach linking the LUCAS and CBM-CFS3 models

Background Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Results We estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year −1 . Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source. Conclusions The new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.

Continental United States↗
USGS2017

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km 2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash–Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush management the most. Additionally, the reduced-parameterization model grossly underestimates uncertainty in the total volumetric ET difference compared to the full-parameterization model; total volumetric ET difference is a primary metric for evaluating the outcomes of brush management. The failure of the reduced-parameterization model to provide robust uncertainty estimates demonstrates the importance of parameterization when attempting to quantify uncertainty in land-cover change simulations.

Hydrology and Earth System Sciences↗
USGS2021

The effects of urban land cover dynamics on urban heat Island intensity and temporal trends

Assessments of surface urban heat island (UHI) have focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain time period by including land cover information. In this study, we implemented a prototype approach to characterize the spatiotemporal variations of UHI using time series of Landsat land surface temperature products and annual land change information. We analyzed UHI distribution and change in Sioux Falls, South Dakota, in the north-central United States and found that the mean UHI intensity in the region was as large as 2.2°C during the period 1986–2017 with an increasing trend of 0.02°C per year within the area with a 5-km non-urban extent. The UHI intensity associated with high intensity urban land cover usually is stronger than with low intensity urban land cover. We evaluated the impact of different non-urban reference extents on UHI variation using different non-urban buffers. The result also suggests that the overall temporal trends of UHI intensity are almost the same when using a 5-km or 10-km non-urban buffer surrounding the urban core. The prototype approach provides a framework to consistently quantify UHI and monitor its change to a large geographic extent.

South Dakota↗
USGS2016

A cellular automata downscaling based 1 km global land use datasets (2010–2100)

Global climate and environmental change studies require detailed land-use and land-cover(LULC) information about the past, present, and future. In this paper, we discuss a methodology for downscaling coarse-resolution (i.e., half-degree) future land use scenarios to finer (i.e., 1 km) resolutions at the global scale using a grid-based spatially explicit cellular automata (CA) model. We account for spatial heterogeneity from topography, climate, soils, and socioeconomic variables. The model uses a global 30 m land cover map (2010) as the base input, a variety of biogeographic and socioeconomic variables, and an empirical analysis to downscale coarse-resolution land use information (specifically urban, crop and pasture). The output of this model offers the most current and finest-scale future LULC dynamics from 2010 to 2100 (with four representative concentration pathway (RCP) scenarios—RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) at a 1 km resolution within a globally consistent framework. The data are freely available for download, and will enable researchers to study the impacts of LULC change at the local scale.

Science Bulletin↗
USGS2016

LANDFIRE 2010—Updates to the national dataset to support improved fire and natural resource management

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) 2010 data release provides updated and enhanced vegetation, fuel, and fire regime layers consistently across the United States. The data represent landscape conditions from approximately 2010 and are the latest release in a series of planned updates to maintain currency of LANDFIRE data products. Enhancements to the data products included refinement of urban areas by incorporating the National Land Cover Database 2006 land cover product, refinement of agricultural lands by integrating the National Agriculture Statistics Service 2011 cropland data layer, and improved wetlands delineations using the National Land Cover Database 2006 land cover and the U.S. Fish and Wildlife Service National Wetlands Inventory data. Disturbance layers were generated for years 2008 through 2010 using remotely sensed imagery, polygons representing disturbance events submitted by local organizations, and fire mapping program data such as the Monitoring Trends in Burn Severity perimeters produced by the U.S. Geological Survey and the U.S. Forest Service. Existing vegetation data were updated to account for transitions in disturbed areas and to account for vegetation growth and succession in undisturbed areas. Surface and canopy fuel data were computed from the updated vegetation type, cover, and height and occasionally from potential vegetation. Historical fire frequency and succession classes were also updated. Revised topographic layers were created based on updated elevation data from the National Elevation Dataset. The LANDFIRE program also released a new Web site offering updated content, enhanced usability, and more efficient navigation.

Open-File Report↗
USGS2018

Southern Rockies Landscape Conservation Cooperative unit watershed erosion potential prioritization for check-dam installation

Changes in land-use practices and the extirpation (local extinction) of beaver populations in the early 20th century during European settlement are believed to have resulted in many changes in how streams in the Western United States function. Some of the negative changes that have resulted include stream channelization, soil erosion, changing vegetation, water turbidity, and a loss of overland flow. Efforts to restore streams and reduce soil erosion by water have included reintroductions of beaver, incorporating Native American traditional knowledge of dry-land farming techniques, and the installation of rigid check-dams. Many of these efforts have been successful in improving both intermittent and perennial stream function. Therefore, stakeholders in the Southern Rockies Landscape Conservation Cooperative (SRLCC) have identified a need to prioritize streams within their region of interest for the installation of check-dams to continue restoration and conservation efforts and to improve sediment catchment. Using Natural Resource Conservation Service soil databases, topographic features derived from digital elevation models, stream networks, and regional climatic patterns, I developed a ranking system for watershed potential erosion rates and suitability for check-dam placement across the SRLCC. This ranking system serves as a first step for land managers to prioritize areas for check-dam installation based on relatively static factors (soil properties, topography, and hydrology) that can contribute to rates of soil erosion by water and the stability of check-dams. Many other relatively dynamic factors over time can contribute to rates of soil erosion by water, such as recent wildfire events, changes in weather patterns and extreme climate events, and changing land-use such as grazing, logging, mining, development, and cultivation. These factors that influence vegetative and biological soil crusts cover are also important elements to the potential erosion of soil by water. Because of this, SRLCC stakeholders might consider further evaluation of the watersheds identified here as high ranking. Final watershed prioritization among the high-ranking watersheds identified here should include current knowledge of land-use and land-cover estimates to identify areas at risk for soil erosion or degree of existing erosion problems.

Open-File Report↗
USGS2004

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Journal of Arid Environments↗
USGS1997

Applications of the U.S. Geological Survey's global land cover product

The U.S. Geological Survey (USGS), in partnership with several international agencies and universities, has produced a global land cover characteristics database. The land cover data were created using multitemporal analysis of advanced very high resolution radiometer satellite images in conjunction with other existing geographic data. A translation table permits the conversion of the land cover classes into several conventional land cover schemes that are used by ecosystem modelers, climate modelers, land management agencies, and other user groups. The alternative classification schemes include Global Ecosystems, the Biosphere Atmosphere Transfer Scheme, the Simple Biosphere, the USGS Anderson Level 2, and the International Geosphere Biosphere Programme. The distribution system for these data is through the World Wide Web (the web site address is: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html) or by magnetic media upon special request The availability of the data over the World Wide Web, in conjunction with the flexible database structure, allows easy data access to a wide range of users. The web site contains a user registration form that allows analysis of the diverse applications of large-area land cover data. Currently, applications are divided among mapping (20 percent), conservation (30 percent), and modeling (35 percent).

Acta Astronautica↗
USGS2010

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

International Journal of Remote Sensing↗
USGS2009

The potential of mid- and near-infrared diffuse reflectance spectroscopy for determining major- and trace-element concentrations in soils from a geochemical survey of North America

In 2004, soils were collected at 220 sites along two transects across the USA and Canada as a pilot study for a planned soil geochemical survey of North America (North American Soil Geochemical Landscapes Project). The objective of the current study was to examine the potential of diffuse reflectance (DR) Fourier Transform (FT) mid-infrared (mid-IR) and near-infrared (NIRS) spectroscopy to reduce the need for conventional analysis for the determination of major and trace elements in such continental-scale surveys. Soil samples (n = 720) were collected from two transects (east-west across the USA, and north-south from Manitoba, Canada to El Paso, Texas (USA), n = 453 and 267, respectively). The samples came from 19 USA states and the province of Manitoba in Canada. They represented 31 types of land use (e.g., national forest, rangeland, etc.), and 123 different land covers (e.g., soybeans, oak forest, etc.). The samples represented a combination of depth-based sampling (0-5 cm) and horizon-based sampling (O, A and C horizons) with 123 different depths identified. The set was very diverse with few samples similar in land use, land cover, etc. All samples were analyzed by conventional means for the near-total concentration of 49 analytes (C total , C carbonate and C organic , and 46 major and trace elements). Spectra were obtained using dried, ground samples using a Digilab FTS-7000 FT spectrometer in the mid- (4000-400 cm -1 ) and near-infrared (10,000-4000 cm -1 ) at 4 cm -1 resolution (64 co-added scans per spectrum) using a Pike AutoDIFF DR autosampler. Partial least squares calibrations were develop using: (1) all samples as a calibration set; (2) samples evenly divided into calibration and validation sets based on spectral diversity; and (3) samples divided to have matching analyte concentrations in calibration and validation sets. In general, results supported the conclusion that neither mid-IR nor NIRS would be particularly useful in reducing the need for conventional analysis of soils from this continental-scale geochemical survey. The extreme sample diversity, likely caused by the widely varied parent material, land use at the site of collection (e.g., grazing, recreation, agriculture, etc.), and climate resulted in poor calibrations even for C total , C organic and C carbonate . The results indicated potential for mid-IR and NIRS to differentiate soils containing high concentrations (>100 mg/kg) of some metals (e.g., Co, Cr, Ni) from low-level samples (<50 mg/kg). However, because of the small number of high-level samples, it is possible that differentiation was based on factors other than metal concentration. Results for Mg and Sr were good, but results for other metals examined were fair to poor, at best. In essence, it appears that the great variation in chemical and physical properties seen in soils from this continental-scale survey resulted in each sample being virtually unique. Thus, suitable spectroscopic calibrations were generally not possible.

Applied Geochemistry↗