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At least 1,189 records · Page 66Linked to original sources
USGS2026

The influence of tree canopy cover data choices on urban ecosystem accounting

Because urban landscapes are heterogeneous, the methods and spatial resolution used to depict the land surface greatly influence the representation of urban features. Land cover products such as tree canopy cover (TCC) are particularly sensitive to the methodology and resolution used in their creation. Differences in TCC mapping have implications on the outcomes of ecosystem service (ES) models, including those underlying natural capital accounting. Here, we quantify the sensitivity of physical rainfall interception and local climate regulation ES models for 189 U.S. cities to TCC inputs from four TCC products: a) National Land Cover Database (NLCD), b) Enhanced NLCD TCC, c) aggregated city-specific composite, and d) global tree canopy height dataset. We find both city-level and aggregate differences in TCC estimates, from a 38% decrease to a 3% increase relative to an aggregated high-resolution product. These differences result in up to 3% overestimations and 27% underestimation of rainfall interception and 2–56% underestimation of local climate regulation ES. City size, population, and greenness in addition to climatic variation drove differences between TCC products, and this variation requires users to carefully consider the choice of input data for any planned analysis. Though high-resolution data can offer greater nuance and accuracy, more limited spatiotemporal availability can hinder their usefulness for long-term monitoring applications such as natural capital accounting. The differences found in this study provide valuable insights for making informed decisions on data inputs for use in urban ecosystem research and for contextualizing model outcomes.

Contiguous United States↗
USGS2012

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The area-weighted fractional tree cover for the study area was 1.85 %, corrected for a slight bias associated with the coarser sampling resolution. The pastures sampled for fractional tree cover were divided between ‘high’ and ‘low’ tree cover, which may be the result of intentional incorporation of arboreal species in pasture. Further research involving those ranchers that have a higher fractional tree cover may indicate ways to promote the practice on a broader scale in the region.

Urban Ecosystems↗
USGS2026

Moose indifferent to canopy loss from forest disturbance by bark beetles

Conifer forests have experienced widespread disturbance following the infestation of bark beetles ( Dendroctonus spp.). Tree mortality and resulting canopy loss have altered forest composition in ways that could affect moose ( Alces alces ), including potential benefits from increased understory forage and drawbacks through the loss of refuge from heat and deep snow. We examined the behavioral response of moose to beetle-killed forest, comparing resource selection before (2005–2006) and after (2015–2017) disturbance in southeast Wyoming, USA. To evaluate selection, we created a land cover classification layer at 0.5-m resolution using machine learning to delineate dead conifers, as well as aspen and willows that were underrepresented in existing land cover products. By measuring resource selection in a fractional cover framework, we found that moose showed strikingly similar resource selection before and after beetle disturbance. Moose during both periods selected willows and aspen while avoiding conifer forest and shrubs throughout the year. Moose in the post-beetle periods avoided conifer forest more strongly the more conifer forest made up their home range. The same pattern emerged for beetle-killed conifer: the more beetle-kill in a home range, the stronger the avoidance of beetle-kill. Our findings indicate that forest disturbance caused by bark beetles does not appreciably alter habitat quality for moose, and moose continue to employ similar patterns of resource selection regardless of forest changes in the early stages of the post-beetle infestation. Our work supports the importance of riparian and deciduous land cover in sustaining moose populations in the face of widespread forest disturbances.

Wyoming↗
USGS2015

Regional scale estimates of baseflow and factors influencing baseflow in the Upper Colorado River Basin

Study region The study region encompasses the Upper Colorado River Basin (UCRB), which provides water for 40 million people and is a vital part of the water supply in the western U.S. Study focus Groundwater and surface water can be considered a single water resource and thus it is important to understand groundwater contributions to streamflow, or baseflow, within a region. Previously, quantification of baseflow using chemical mass balance at large numbers of sites was not possible because of data limitations. A new method using regression-derived daily specific conductance values with conductivity mass balance hydrograph separation allows for baseflow estimation at sites across large regions. This method was applied to estimate baseflow discharge at 229 sites across the UCRB. Subsequently, climate, soil, topography, and land cover characteristics were statistically evaluated using principal component analysis (PCA) to determine their influence on baseflow discharge. New hydrological insights for the region Results suggest that approximately half of the streamflow in the UCRB is baseflow derived from groundwater discharge to streams. Higher baseflow yields typically occur in upper elevation areas of the UCRB. PCA identified precipitation, snow, sand content of soils, elevation, land surface slope, percent grasslands, and percent natural barren lands as being positively correlated with baseflow yield; whereas temperature, potential evapotranspiration, silt and clay content of soils, percent agriculture, and percent shrublands were negatively correlated with baseflow yield.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS2014

Identifying sources of aeolian mineral dust: Present and past

Aeolian mineral dust is an important component of the Earth’s environmental systems, playing roles in the planetary radiation balance, as a source of fertilizer for biota in both terrestrial and marine realms and as an archive for understanding atmospheric circulation and paleoclimate in the geologic past. Crucial to understanding all of these roles of dust is the identification of dust sources. Here we review the methods used to identify dust sources active at present and in the past. Contemporary dust sources, produced by both glaciogenic and non-glaciogenic processes, can be readily identified by the use of Earth-orbiting satellites. These data show that present dust sources are concentrated in a global dust belt that encompasses large topographic basins in low-latitude arid and semiarid regions. Geomorphic studies indicate that specific point sources for dust in this zone include dry or ephemeral lakes, intermittent stream courses, dune fields, and some bedrock surfaces. Back-trajectory analyses are also used to identify dust sources, through modeling of wind fields and the movement of air parcels over periods of several days. Identification of dust sources from the past requires novel approaches that are part of the geologic toolbox of provenance studies. Identification of most dust sources of the past requires the use of physical, mineralogical, geochemical, and isotopic analyses of dust deposits. Physical properties include systematic spatial changes in dust deposit thickness and particle size away from a source. Mineralogy and geochemistry can pinpoint dust sources by clay mineral ratios and Sc-Th-La abundances, respectively. The most commonly used isotopic methods utilize isotopes of Nd, Sr, and Pb and have been applied extensively in dust archives of deep-sea cores, ice cores, and loess. All these methods have shown that dust sources have changed over time, with far more abundant dust supplies existing during glacial periods. Greater dust supplies in glacial periods are likely due to greater production of glaciogenic dust particles from expanded ice sheets and mountain glaciers, but could also include dust inputs from exposed continental and insular shelves now submerged. Future dust sources are difficult to assess, but will likely differ from those of the present because of global warming. Global warming could bring about shifts in dust sources by changes in degree or type of vegetation cover, changes in wind strength, and increases or decreases in the size of water bodies. A major uncertainty in assessing dust sources of the future is related to changes inhuman land use, which could affect land surface cover, particularly due to increased agricultural endeavors and water usage.

Book chapter↗
USGS2008

Landsat continuity: Issues and opportunities for land cover monitoring

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.

Remote Sensing of Environment↗
USGS2024

Evaluating habitat use and relative abundance of Iowa's river otter with harvest data

The North American river otter ( Lontra canadensis ) was extirpated from much of the United States in the early 20th century due to habitat loss, pollution of waterways, and overharvesting. The Iowa Department of Natural Resources began a river otter reintroduction effort in 1985, which placed otters in 14 sites across the state. Otters have since been known to occur in every county in Iowa and appear to have successfully repopulated their former range throughout the state. Our objective was to relate land cover characteristics and otter abundance using harvest data. We used data collected by agency staff to map the locations of otter harvest in Iowa from 2006 to 2016. We mapped otter harvest locations at the subwatershed level (also called 12-digit Hydrologic Unit Code or HUC-12). We related otter harvest to land cover variables and predicted otter abundance by land cover type. We found that roads, forests, larger waterways, and Ictaluridae (catfish) presence were negatively correlated with otter harvest. Variables positively correlated with otter harvest were areas with greater land cover diversity, wetland patch density, average stream density, and waterway and wetland areas. The land cover model predicted otters in equal or greater numbers than the harvest data in 62.8% of HUC-12s. The areas of greatest otter abundance estimates were located near recreation areas and urban areas, indicating the underutilization of these heavy-trafficked areas by trappers. Areas of fewer predicted otters were not concentrated in a single area of the state but occurred along the Interstate 80 corridor.

Iowa↗
USGS2020

Numerical simulation of groundwater availability in central Moloka‘i, Hawai‘i

Since the 1990s, increased chloride concentrations of water pumped from wells (much of which is used for drinking water) and the effects of withdrawals on groundwater-dependent ecosystems have led to concerns over groundwater availability on the island of Molokaʻi, Hawaiʻi. An improved understanding of the hydrologic effects of proposed groundwater withdrawals is needed to ensure effective management of the groundwater resources of Molokaʻi, plan for possible growth, and accommodate cultural, social, and economic concerns. To address the information needs of managers and community stakeholders on Molokaʻi, the U.S. Geological Survey developed a numerical groundwater model capable of simulating salinity change and reduction in groundwater discharge in coastal areas of central and southern Molokaʻi. Estimates of groundwater recharge needed as input to the numerical groundwater model were made using a daily water budget for each decade during 1940−2012 (the period 2000−12 spanned 13 years) and the most current available data, including the distributions of monthly rainfall and potential evapotranspiration. Total island recharge during the decadal periods ranged from a low of about 189 Mgal/d during the 1970s to a high of 278 Mgal/d during the 1960s. These recharge estimates were used to develop an island-wide numerical groundwater model with simplifying assumptions (sharp interface between freshwater and saltwater; two-dimensional flow). The island-wide model provided estimates of groundwater inflows to the main area of interest simulated with a three-dimensional numerical groundwater model. Simulated withdrawal scenarios were selected in consultation with water managers and stakeholders and consisted of: (1) a baseline scenario using average recharge (1978−2007 rainfall and 2010 land cover) and average 2016−17 withdrawals; (2) a scenario using average recharge and withdrawals from existing wells at pending (as of January 2019) water-use permit rates; (3) six scenarios using average recharge and selected withdrawals from existing and proposed wells; and (4) a scenario using reduced recharge and selected withdrawals from existing and proposed wells. Results of the simulated withdrawal scenarios indicate that wells may be capable of producing groundwater with chloride concentrations below 250 mg/L at withdrawal rates exceeding average 2016−17 rates. However, the quality of water withdrawn from production wells is dependent on the rate and distribution of the withdrawals. For all nonbaseline scenarios, simulated groundwater discharge to the nearshore environment is reduced relative to the baseline scenario. Areas of discharge reduction may correspond to areas used for cultural or subsistence purposes. The three-dimensional numerical groundwater model developed for this study utilizes the latest available hydrologic and geologic information and is a useful tool for understanding the hydrologic effects of additional groundwater withdrawals in central Molokaʻi. The model has several limitations, including its nonuniqueness and inability to account for local-scale heterogeneities.

Hawaii↗
USGS2007

Effects of Impoundments and Land-Cover Changes on Streamflows and Selected Fish Habitat in the Upper Osage River Basin, Missouri and Kansas

A study was conducted by the U.S. Geological Survey in cooperation with the Missouri Department of Conservation to estimate the effects of existing and proposed impoundments, land-cover changes, and reported water uses on streamflows in the 5,410-square mile upper Osage River Basin. The hydrologic model Hydrologic Simulation Program-FORTRAN (HSPF) was calibrated and validated to current (1995?2004 water years) regulation and water-use conditions, and scenarios were developed to evaluate differences for the same 10-years of record under pre-settlement, and proposed impoundment conditions. Analyses included quantification of changes in the magnitude, frequency, timing, and duration of streamflows under each simulation scenario. Streamflows from the simulations were used in conjunction with known streamflow-fish habitat relations to quantify effects of altered flows on fish-habitat area at selected Marais des Cygnes and Marmaton River locations. The cumulative effects of impoundments and land-cover changes were determined to substantially alter streamflows in the upper Osage River Basin model simulations spanning pre-settlement to proposed future conditions. The degree of streamflow alteration varied between major subbasins. Streamflows in the Marais des Cygnes River Basin were altered between pre-settlement and current conditions, primarily by major impoundments, with smaller changes expected with proposed regulation. Streamflows in the Little Osage River Basin were relatively unchanged between pre-settlement and current conditions with land-cover changes (primarily the conversion of native prairies to cultivated land) affecting flows more than the few current impoundments in this basin. The current peak flows in the Marmaton River Basin generally were higher than pre-settlement or proposed scenario peak flows. Of the three major subbasins, the Marmaton River Basin is likely to be the most affected by proposed impoundments. Declines in monthly minimum streamflows under a proposed impoundment scenario at the Marais des Cygnes River near the Kansas-Missouri state line, Kansas, were greatest for the lowest 10 percent of corresponding observed flows and during the driest years (2000, 2001 water years); that is, the greatest percent declines in flows under proposed conditions generally occurred during the lowest current/observed flow periods. In a small headwater basin in the Marmaton River Basin, simulated declines in minimum flows were small (generally less than 6 cubic feet per second and less than 1 cubic foot per second for 1- and 3-day scenarios), but resulted in 10 to 18 additional zero flow days for the 10-year simulation for the proposed scenarios relative to current simulated conditions. Reductions in minimum monthly flows as a result of additional impoundments generally were less than 5 cubic feet per second at the Marmaton River near Marmaton, Kansas, and resulted in 6 additional zero flow days. The greatest declines between proposed and current flows at the Marmaton River near the Kansas-Missouri state line, Missouri, generally occurred in the lower 50 percentile of the distribution of current simulated flows and during the drier simulation years (2001?2003). Proposed conditions resulted in declines in the 0-10 percentile flow values for the 1-, 3-, and 7-day durations. July, August, and October had the largest declines in proposed low flows relative to current simulated low flows for the 10-year simulation at this site. The flood frequency for the Marais des Cygnes River near the Kansas-Missouri state line was unchanged between observed and proposed conditions for the 10-year simulation, but was 450 percent greater under the pre-settlement scenarios compared to observed conditions. Flood frequency generally was greatest for the current condition scenarios in the Marmaton River Basin and least for the proposed conditions, although the effects of regulation on flood frequency decreased downstream from the Kansas-

Scientific Investigations Report↗
USGS2018

Surrounding land cover types as predictors of palustrine wetland vegetation quality in conterminous USA

The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.

Science of the Total Environment↗
USGS2014

Influence of riparian and watershed alterations on sandbars in a Great Plains river

Anthropogenic alterations have caused sandbar habitats in rivers and the biota dependent on them to decline. Restoring large river sandbars may be needed as these habitats are important components of river ecosystems and provide essential habitat to terrestrial and aquatic organisms. We quantified factors within the riparian zone of the Kansas River, USA, and within its tributaries that influenced sandbar size and density using aerial photographs and land use/land cover (LULC) data. We developed, a priori , 16 linear regression models focused on LULC at the local, adjacent upstream river bend, and the segment (18–44 km upstream) scales and used an information theoretic approach to determine what alterations best predicted the size and density of sandbars. Variation in sandbar density was best explained by the LULC within contributing tributaries at the segment scale, which indicated reduced sandbar density with increased forest cover within tributary watersheds. Similarly, LULC within contributing tributary watersheds at the segment scale best explained variation in sandbar size. These models indicated that sandbar size increased with agriculture and forest and decreased with urban cover within tributary watersheds. Our findings suggest that sediment supply and delivery from upstream tributary watersheds may be influential on sandbars within the Kansas River and that preserving natural grassland and reducing woody encroachment within tributary watersheds in Great Plains rivers may help improve sediment delivery to help restore natural river function.

River Research and Applications↗
USGS2019

The ‘Ike Wai Hawai‘i groundwater recharge tool

This paper discusses the design and implementation of the ‘Ike Wai Hawai‘i Groundwater Recharge Tool, an application for providing data and analyses of the impacts of land-cover and climate modifications on groundwater-recharge rates for the island of O‘ahu. This application uses simulation data based on a set of 29 land-cover types and two rainfall scenarios to provide users with real-time recharge calculations for interactively defined land-cover modifications. Two visualizations, representing the land cover for the island and the resultant groundwater-recharge rates, and a set of metrics indicating the changes to groundwater recharge for relevant areas of the map are provided to present a set of easily interpreted outcomes based on the user-defined simulations. Tools are provided to give users varying degrees of control over the granularity of data input and output, allowing for the quick production of a roughly defined simulation, or more precise land-cover models that can be exported for further analysis. Heuristics are used to provide a responsive user interface and performant integration with the database containing the full set of simulation data. This tool is designed to provide user-friendly access to the information on the impacts of land-cover and climate changes on groundwater recharge rates needed to make data-driven decisions.

Hawaii↗
USGS2009

Sample project: establishing a global forest monitoring capability using multi-resolution and multi-temporal remotely sensed data sets

Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.

The NASA LCLUC Program: an interdisciplinary appro↗
USGS2013

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.

Remote Sensing of Environment↗
USGS2002

Classification of irrigated land using satellite imagery, the High Plains aquifer, nominal date 1992

Satellite imagery from the Landsat Thematic Mapper (nominal date 1992) was used to classify and map the location of irrigated land across the High Plains aquifer. The High Plains aquifer underlies 174,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. The U.S. Geological Survey is conducting a waterquality study of the High Plains aquifer as part of the National Water-Quality Assessment Program. To help interpret data and select sites for the study, it is helpful to know the location of irrigated land within the study area. To date, the only information available for the entire area is 20 years old. To update the data on irrigated land, 40 summer and 40 spring images (nominal date 1992) were acquired from the National Land Cover Data set and processed using a band-ratio method (Landsat Thematic Mapper band 4 divided by band 3) to enhance the vegetation signatures. The study area was divided into nine subregions with similar environmental characteristics, and a band-ratio threshold was selected from imagery in each subregion that differentiated the cutoff between irrigated and nonirrigated land. The classified images for each subregion were mosaicked to produce an irrigated land map for the study area. The total amount of irrigated land classified from the 1992 imagery was 13.1 million acres, or about 12 percent of the total land in the High Plains. This estimate is approximately 1.5 percent greater than the amount of irrigated land reported in the 1992 Census of Agriculture (12.8 millions acres). This information was also compared to a similar data set based on 1980 imagery. The 1980 data classified 13.7 million acres as irrigated. Although the change in the amount of irrigated land between the two times was not substantial, the location of the irrigated land did shift from areas where there were large ground-water-level declines to other areas where ground-water levels were static or rising.

Water-Resources Investigations Report↗
USGS2002

Location of irrigated land classified from satellite imagery - High Plains Area, nominal date 1992

Satellite imagery from the Landsat Thematic Mapper (nominal date 1992) was used to classify and map the location of irrigated land overlying the High Plains aquifer. The High Plains aquifer underlies 174,000 square miles in parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. The U.S. Geological Survey is conducting a water-quality study of the High Plains aquifer as part of the National Water-Quality Assessment Program. To help interpret data and select sites for the study, it is helpful to know the location of irrigated land within the study area. To date, the only information available for the entire area is 20 years old. To update the data on irrigated land, 40 summer and 40 spring images (nominal date 1992) were acquired from the National Land Cover Data set and processed using a band-ratio method (Landsat Thematic Mapper band 4 divided by band 3) to enhance the vegetation signatures. The study area was divided into nine subregions with similar environmental characteristics, and a band-ratio threshold was selected from imagery in each subregion that differentiated the cutoff between irrigated and nonirrigated land. The classified images for each subregion were mosaicked to produce an irrigated-land map for the study area. The total amount of irrigated land classified from the 1992 imagery was 13.1 million acres, or about 12 percent of the total land in the High Plains. This estimate is approximately 1.5 percent greater than the amount of irrigated land reported in the 1992 Census of Agriculture (12.8 millions acres).

Open-File Report↗
USGS2022

Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product

The increasing availability of high-quality remote sensing data and advanced technologies have spurred land cover mapping to characterize land change from local to global scales. However, most land change datasets either span multiple decades at a local scale or cover limited time over a larger geographic extent. Here, we present a new land cover and land surface change dataset created by the Land Change Monitoring, Assessment, and Projection (LCMAP) program over the conterminous United States (CONUS). The LCMAP land cover change dataset consists of annual land cover and land cover change products over the period 1985-2017 at 30-meter resolution using Landsat and other ancillary data via the Continuous Change Detection and Classification (CCDC) algorithm. In this paper, we describe our novel approach to implement the CCDC algorithm to produce the LCMAP product suite composed of five land cover and five land surface change related products. The LCMAP land cover products were validated using a collection of ~ 25,000 reference samples collected independently across CONUS. The overall agreement for all years of the LCMAP primary land cover product reached 82.5%. The LCMAP products are produced through the LCMAP Information Warehouse and Data Store (IW+DS) and Shared Mesos Cluster systems that can process, store, and deliver all datasets for public access. To our knowledge, this is the first set of published 30m annual land cover and land cover change datasets that span from the 1980s to the present for the United States. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems and the complex dynamics of the Earth system. The LCMAP system could be implemented to produce global land change products in the future.

Earth System Science Data↗
USGS1996

Spatial partitioning of environmental correlates of avian biodiversity in the conterminous United States

Classification and regression tree (CART) analysis was used to create hierarchically organized models of the distribution of bird species richness across the conterminous United States. Species richness data were taken from the Breeding Bird Survey and were related to climatic and land use data. We used a systematic spatial grid of approximately 12,500 hexagons, each approximately 640 square kilometres in area. Within each hexagon land use was characterized by the Loveland et al. land cover classification based on Advanced Very High Resolution Radiometer (AVHRR) data from NOAA polar orbiting meteorological satellites. These data were aggregated to yield fourteen land classes equivalent to an Anderson level II coverage; urban areas were added from the Digital Chart of the World. Each hexagon was characterized by climate data and landscape pattern metrics calculated from the land cover. A CART model then related the variation in species richness across the 1162 hexagons for which bird species richness data were available to the independent variables, yielding an R2-type goodness of fit metric of 47.5% deviance explained. The resulting model recognized eleven groups of hexagons, with species richness within each group determined by unique sequences of hierarchically constrained independent variables. Within the hierarchy, climate data accounted for more variability in the bird data, followed by land cover proportion, and then pattern metrics. The model was then used to predict species richness in all 12,500 hexagons of the conterminous United States yielding a map of the distribution of these eleven classes of bird species richness as determined by the environmental correlates. The potential for using this technique to interface biogeographic theory with the hierarchy theory of ecology is discussed. ?? 1996 Blackwell Science Ltd.

Biodiversity Letters↗