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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 1,027 records · Page 57Linked to original sources

USGS1988

Use of airborne imaging spectrometer data to map minerals associated with hydrothermally altered rocks in the northern Grapevine Mountains, Nevada, and California

Three flightlines of Airborne Imaging Spectrometer (AIS) data, acquired over the northern Grapevine Mountains, Nevada, and California, were used to map minerals associated with hydrothermally altered rocks. The data were processed to remove vertical striping, normalized using an equal area normalization, and reduced to reflectance relative to an average spectrum derived from the data. An algorithm was developed to automatically calculate the absorption band parameters band position, band depth, and band width for the strongest absorption feature in each pixel. These parameters were mapped into an intensity, hue, saturation (IHS) color system to produce a single color image that summarized the absorption band information, This image was used to map areas of potential alteration based upon the predicted relationships between the color image and mineral absorption band. Individual AIS spectra for these areas were then examined to identify specific minerals. Two types of alteration were mapped with the AIS data. Areas of quartz-sericite-pyrite alteration were identified based upon a strong absorption feature near 2.21 μm, a weak shoulder near 2.25 μm, and a weak absorption band near 2.35 μm caused by sericite (fine-grained muscovite). Areas of argillic alteration were defined based on the presence of montmorillonite, identified by a weak to moderate absorption feature near 2.21 μm and the absence of the 2.35 μm band. Montmorillonite could not be identified in mineral mixtures. Calcite and dolomite were identified based on sharp absorption features near 2.34 and 2.32 μm, respectively. Areas of alteration identified using the AIS data corresponded well with areas mapped using field mapping, field reflectance spectra, and laboratory spectral measurements.

California, Nevada↗

USGS1987

Higher resolution satellite remote sensing and the impact on image mapping

Recent advances in spatial, spectral, and temporal resolution of civil land remote sensing satellite data are presenting new opportunities for image mapping applications. The U.S. Geological Survey's experimental satellite image mapping program is evolving toward larger scale image map products with increased information content as a result of improved image processing techniques and increased resolution. Thematic mapper data are being used to produce experimental image maps at 1:100,000 scale that meet established U.S. and European map accuracy standards. Availability of high quality, cloud-free, 30-meter ground resolution multispectral data from the Landsat thematic mapper sensor, along with 10-meter ground resolution panchromatic and 20-meter ground resolution multispectral data from the recently launched French SPOT satellite, present new cartographic and image processing challenges. The need to fully exploit these higher resolution data increases the complexity of processing the images into large-scale image maps. The removal of radiometric artifacts and noise prior to geometric correction can be accomplished by using a variety of image processing filters and transforms. Sensor modeling and image restoration techniques allow maximum retention of spatial and radiometric information. An optimum combination of spectral information and spatial resolution can be obtained by merging different sensor types. These processing techniques are discussed and examples are presented.

Acta Astronautica↗

USGS2011

A GIS application for assessing, mapping, and quantifying the social values of ecosystem services

As human pressures on ecosystems continue to increase, research involving the effective incorporation of social values information into the context of comprehensive ecosystem services assessments is becoming more important. Including quantified, spatially explicit social value metrics in such assessments will improve the analysis of relative tradeoffs among ecosystem services. This paper describes a GIS application, So cia l V alues for E cosystem S ervices (SolVES), developed to assess, map, and quantify the perceived social values of ecosystem services by deriving a non-monetary Value Index from responses to a public attitude and preference survey. SolVES calculates and maps the Value Index for social values held by various survey subgroups, as distinguished by their attitudes regarding ecosystem use. Index values can be compared within and among survey subgroups to explore the effect of social contexts on the valuation of ecosystem services. Index values can also be correlated and regressed against landscape metrics SolVES calculates from various environmental data layers. Coefficients derived through these analyses were applied to their corresponding data layers to generate a predicted social value map. This map compared favorably with other SolVES output and led to the addition of a predictive mapping function to SolVES for value transfer to areas where survey data are unavailable. A more robust application is being developed as a public domain tool for decision makers and researchers to map social values of ecosystem services and to facilitate discussions among diverse stakeholders involving relative tradeoffs among different ecosystem services in a variety of physical and social contexts.

Applied Geography↗

USGS2022

How do accuracy and model agreement vary with versioning, scale, and landscape heterogeneity for satellite-derived vegetation maps in sagebrush steppe?

Maps of the distribution and abundance of dominant plants derived from satellite data are essential for ecological research and management, particularly in the vast semiarid shrub-steppe. Appropriate application of these maps requires an understanding of model accuracy and precision, and how it might vary across space, time, and different vegetation types. For a 113 k Ha burn area, we compared modeled maps of different vegetation cover types created from satellite data to ‘benchmark” models based on intensive field sampling (~1500-2000 plots resampled annually for 5 years) for three new satellite-derived models: USDA Rangeland Analysis Platform (RAP), the USGS Rangeland Condition Monitoring Assessment and Projection (RCMAP), and USGS fractional estimate of exotic annual grass cover (USGS-fractional-EAG). We assessed out-of-sample point accuracy and asked if and how accuracy changed each year due to vegetation shifts, new images, and model improvements (i.e. model versions). We also assessed how map agreement between satellite-based and field-based models changed with scale of application, topography, and time since fire. Accuracy and map agreement varied considerably among the vegetation types and across time and space (r 2 ranging from 0 to 0.53), and some of the variability was predictable. All models tended to over or underestimate cover when field-measured cover was relatively low or high, respectively, i.e. a “false moderating effect”. Accuracy was greater and improved with newer versions of RAP (+0.05 to 0.29 r 2 ) compared to RCMAP and USGS fractional model estimates, and in some cases was greater than field-based models. Variability in map agreement tended to decrease with larger areas sampled (particularly in areas >12 km), and this scale dependency was more evident in RAP and USGS-fractional-EAG models. Creating a “fair” basis for comparison of spatial models of low-statured semiarid vegetation derived from satellite compared to field data is not trivial because scaling the field data to the scale of large satellite pixels (or downscaling satellite-based models to field scale) requires modeling and associated model uncertainty. Accuracy can vary considerably and understanding the variation can help guide application of the models to the appropriate time, place, and variables.

Idaho, Oregon↗

USGS2025

Favorability mapping for hydrothermal power resource assessments of the Great Basin, USA

The U.S. Geological Survey (USGS) is updating the 2008 assessment of conventional hydrothermal resources for the Great Basin in the western United States. As part of this work, the workflow for hydrothermal resource favorability maps is being modified to integrate modern data-driven machine learning (ML) methods. Improvements include: [1] using new and refined evidence layers (features); [2] using an order of magnitude more training sites (labeled examples); [3] utilizing simple but non-linear supervised ML algorithms; [4] representing positive training sites (wells with measured heat flow) with their ordinal value proportional to the magnitude of convective upflow (i.e., low, high, or very high convective signals instead of past strategies using positive-negative labels); [5] supplementing training sites with additional sites with low convective signals to represent diverse under-sampled areas where hydrothermal systems are unlikely to exist; [6] comparing with competing approaches; and [7] utilizing Monte Carlo cross-validation to estimate and evaluate prediction uncertainty. For the new favorability map, over half of the power-producing systems (i.e., 15 of 28) are predicted in the 99th percentile of most favorable locations (i.e., the highest 1 % of favorability, corresponding to 1 % of the map area), exceeding the performance of past models that have explicitly used power plants as training sites. Previous favorability maps predicted approximately half of the power-producing hydrothermal systems above the 80th percentile (i.e., 20 % of the map area). For the new favorability map, 93 % of power-producing systems (i.e., 26 of 28) are above the 80th percentile. The power-producing systems for which the new model does not perform well are either comparatively small, low-temperature systems or systems also not predicted well by prior modeling approaches, suggesting that these few systems are unusual when compared with most power-producing systems. Focusing research on these known, seemingly different systems may yield new insights and subsequent discovery of new prospects.

California, Idaho, Nevada, Oregon, Utah↗

USGS2005

The Zamama-Thor region of Io: Insights from a synthesis of mapping, topography, and Galileo spacecraft data

We have studied data from the Galileo spacecraft's three remote sensing instruments (Solid-State Imager (SSI), Near-Infrared Mapping Spectrometer (NIMS), and Photopolarimeter-Radiometer (PPR)) covering the Zamama–Thor region of Io's antijovian hemisphere, and produced a geomorphological map of this region. This is the third of three regional maps we are producing from the Galileo spacecraft data. Our goal is to assess the variety of volcanic and tectonic materials and their interrelationships on Io using planetary mapping techniques, supplemented with all available Galileo remote sensing data. Based on the Galileo data analysis and our mapping, we have determined that the most recent geologic activity in the Zamama–Thor region has been dominated by two sites of large-scale volcanic surface changes. The Zamama Eruptive Center is a site of both explosive and effusive eruptions, which emanate from two relatively steep edifices (Zamama Tholi A and B) that appear to be built by both silicate and sulfur volcanism. A ∼100-km long flow field formed sometime after the 1979 Voyager flybys, which appears to be a site of promethean-style compound flows, flow-front SO 2 plumes, and adjacent sulfur flows. Larger, possibly stealthy, plumes have on at least one occasion during the Galileo mission tapped a source that probably includes S and/or Cl to produce a red pyroclastic deposit from the same vent from which silicate lavas were erupted. The Thor Eruptive Center, which may have been active prior to Voyager , became active again during the Galileo mission between May and August 2001. A pillanian-style eruption at Thor included the tallest plume observed to date on Io (at least 500 km high) and new dark lava flows. The plume produced a central dark pyroclastic deposit (probably silicate-rich) and an outlying white diffuse ring that is SO 2 -rich. Mapping shows that several of the new dark lava flows around the plume vent have reoccupied sites of earlier flows. Unlike most of the other pillanian eruptions observed during the Galileo mission, the 2001 Thor eruption did not produce a large red ring deposit, indicating a relative lack of S and/or Cl gases interacting with the magma during that eruption. Between these two eruptive centers are two paterae, Thomagata and Reshef. Thomagata Patera is located on a large shield-like mesa and shows no signs of activity. In contrast, Reshef Patera is located on a large, irregular mesa that is apparently undergoing degradation through erosion (perhaps from SO 2 -sapping or chemical decomposition of sulfur-rich material) from multiple secondary volcanic centers.

Icarus↗

USGS2011

Volcanism on Io: New insights from global geologic mapping

We produced the first complete, 1:15 M-scale global geologic map of Jupiter’s moon Io, based on a set of monochrome and color Galileo – Voyager image mosaics produced at a spatial resolution of 1 km/pixel. The surface of Io was mapped into 19 units based on albedo, color and surface morphology, and is subdivided as follows: plains (65.8% of surface), lava flow fields (28.5%), mountains (3.2%), and patera floors (2.5%). Diffuse deposits (DD) that mantle the other units cover ∼18% of Io’s surface, and are distributed as follows: red (8.6% of surface), white (6.9%), yellow (2.1%), black (0.6%), and green (∼0.01%). Analyses of the geographical and areal distribution of these units yield a number of results, summarized below. (1) The distribution of plains units of different colors is generally geographically constrained: Red–brown plains occur >±30° latitude, and are thought to result from enhanced alteration of other units induced by radiation coming in from the poles. White plains (possibly dominated by SO 2 + contaminants) occur mostly in the equatorial antijovian region (±30°, 90–230°W), possibly indicative of a regional cold trap. Outliers of white, yellow, and red–brown plains in other regions may result from long-term accumulation of white, yellow, and red diffuse deposits, respectively. (2) Bright (possibly sulfur-rich) flow fields make up 30% more lava flow fields than dark (presumably silicate) flows (56.5% vs. 43.5%), and only 18% of bright flow fields occur within 10 km of dark flow fields. These results suggest that secondary sulfurous volcanism (where a bright-dark association is expected) could be responsible for only a fraction of Io’s recent bright flows, and that primary sulfur-rich effusions could be an important component of Io’s recent volcanism. An unusual concentration of bright flows at ∼45–75°N, ∼60–120°W could be indicative of more extensive primary sulfurous volcanism in the recent past. However, it remains unclear whether most bright flows are bright because they are sulfur flows, or because they are cold silicate flows covered in sulfur-rich particles from plume fallout. (3) We mapped 425 paterae (volcano-tectonic depressions), up from 417 previously identified by Radebaugh et al. (Radebaugh, J., Keszthelyi, L.P., McEwen, A.S., Turtle, E.P., Jaeger, W., Milazzo, M. [2001]. J. Geophys. Res. 106, 33005–33020). Although these features cover only 2.5% of Io’s surface, they correspond to 64% of all detected hot spots; 45% of all hot spots are associated with the freshest dark patera floors, reflecting the importance of active silicate volcanism to Io’s heat flow. (4) Mountains cover only ∼3% of the surface, although the transition from mountains to plains is gradational with the available imagery. 49% of all mountains are lineated and presumably layered, showing evidence of linear structures supportive of a tectonic origin. In contrast, only 6% of visible mountains are mottled (showing hummocks indicative of mass wasting) and 4% are tholi (domes or shields), consistent with a volcanic origin. (5) Initial analyses of the geographic distributions of map units show no significant longitudinal variation in the quantity of Io’s mountains or paterae, in contrast to earlier studies. This is because we use the area of mountain and patera materials as opposed to the number of structures, and our result suggests that the previously proposed anti-correlation of mountains and paterae (Schenk, P., Hargitai, H., Wilson, R., McEwen, A., Thomas, P. [2001]. J. Geophys. Res. 106, 33201–33222; Kirchoff, M.R., McKinnon, W.B., Schenk, P.M. [2011]. Earth Planet. Sci. Lett. 301, 22–30) is more complex than previously thought. There is also a slight decrease in surface area of lava flows toward the poles of Io, perhaps indicative of variations in volcanic activity. (6) The freshest bright and dark flows make up about 29% of all of Io’s flow fields, suggesting active emplacement is occurring in less than a third of Io’s visible lava fields. (7) About 47% of Io’s diffuse deposits (by area) are red, presumably deriving their color from condensed sulfur gas, and ∼38% are white, presumably dominated by condensed SO 2 . The much greater areal extent of gas-derived diffuse deposits (red + white, 85%) compared to presumably pyroclast-bearing diffuse deposits (dark (silicate tephra) + yellow (sulfur-rich tephra), 15%) indicates that there is effective separation between the transport of tephra and gas in many Ionian explosive eruptions. Future improvements in the geologic mapping of Io can be obtained via (a) investigating the relationships between different color/material units that are geographically and temporally associated, (b) better analysis of the temporal variations in the map units, and (c) additional high-resolution images (spatial resolutions ∼200 m/pixel or better). These improvements would be greatly facilitated by new data, which could be obtained by future missions.

Icarus↗

USGS2004

Land cover mapping of North and Central America—Global Land Cover 2000

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

Remote Sensing of Environment↗

USGS2013

Challenges in making a seismic hazard map for Alaska and the Aleutians

We present a summary of the data and analyses leading to the revision of the time-independent probabilistic seismic hazard maps of Alaska and the Aleutians. These maps represent a revision of existing maps based on newly obtained data, and reflect best current judgments about methodology and approach. They have been prepared following the procedures and assumptions made in the preparation of the 2002 National Seismic Hazard Maps for the lower 48 States, and will be proposed for adoption in future revisions to the International Building Code. We present example maps for peak ground acceleration, 0.2 s spectral amplitude (SA), and 1.0 s SA at a probability level of 2% in 50 years (annual probability of 0.000404). In this summary, we emphasize issues encountered in preparation of the maps that motivate or require future investigation and research.

Alaska↗

USGS2001

Moss and lichen cover mapping at local and regional scales in the boreal forest ecosystem of central Canada

Mosses and lichens are important components of boreal landscapes [Vitt et al., 1994; Bubier et al., 1997]. They affect plant productivity and belowground carbon sequestration and alter the surface runoff and energy balance. We report the use of multiresolution satellite data to map moss and lichens over the BOREAS region at a 10 m, 30 m, and 1 km scales. Our moss and lichen classification at the 10 m scale is based on ground observations of associations among soil drainage classes, overstory composition, and cover type among four broad classes of ground cover (feather, sphagnum, and brown mosses and lichens). For our 30 m map, we used field observations of ground cover-overstory associations to map mosses and lichens in the BOREAS southern study area (SSA). To scale up to a 1 km (AVHRR) moss map of the BOREAS region, we used the TM SSA mosaics plus regional field data to identify AVHRR overstory-ground cover associations. We found that: 1) ground cover, overstory composition and density are highly correlated, permitting inference of moss and lichen cover from satellite-based land cover classifications; 2) our 1 km moss map reveals that mosses dominate the boreal landscape of central Canada, thereby a significant factor for water, energy, and carbon modeling; 3) TM and AVHRR moss cover maps are comparable; 4) satellite data resolution is important; particularly in detecting the smaller wetland features, lakes, and upland jack pine sites; and 5) distinct regional patterns of moss and lichen cover correspond to latitudinal and elevational gradients. Copyright 2001 by the American Geophysical Union.

Journal of Geophysical Research D: Atmospheres↗

USGS2020

Probabilistic categorical groundwater salinity mapping from airborne electromagnetic data adjacent to California’s Lost Hills and Belridge oil fields

Growing water stress has led to emerging interest in protecting fresh and brackish groundwater as a potential supplement to water supplies and raised questions about factors that could affect the future quality of fresh and brackish aquifers. Limited well infrastructure, particularly in regions where elevated salinity has led to limited historical groundwater development, hinders traditional mapping of salinity distributions through groundwater sampling. This paper presents a quantitative salinity mapping approach of the upper 300 m using high‐resolution, regionally comprehensive resistivity models derived from Bayesian inversion of an airborne electromagnetic survey adjacent to the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley of California. Using local water quality observations as an interpretational foundation, a probabilistic approach yields maps of fresh, saline, and brackish groundwater while quantifying joint uncertainty inherited from the geophysical data and interpretational relations. Saline and fresh regions are mapped with relatively high confidence in many locations, while areas of lower confidence, particularly at depth, can be mapped as their most probable salinity category while reflecting the relative uncertainty in the interpretation. These maps identify a stratified salinity structure, where saline water commonly occurs in the surficial aquifer overlying fresher groundwater in the Tulare aquifer, separated by regional confining clay layers. Downgradient of unlined surface water diversions, recharge of imported surface water results in relatively fresh groundwater throughout the depth of investigation.

California↗

USGS1998

Analysis of simulated advanced spaceborne thermal emission and reflection (ASTER) radiometer data of the Iron Hill, Colorado, study area for mapping lithologies

The advanced spaceborne thermal emission and reflection (ASTER) radiometer was designed to record reflected energy in nine channels with 15 or 30 m resolution, including stereoscopic images, and emitted energy in five channels with 90 m resolution from the NASA Earth Observing System AMI platform. A simulated ASTER data set was produced for the Iron Hill, Colorado, study area by resampling calibrated, registered airborne visible/infrared imaging spectrometer (AVIRIS) data, and thermal infrared multispectral scanner (TIMS) data to the appropriate spatial and spectral parameters. A digital elevation model was obtained to simulate ASTER-derived topographic data. The main lithologic units in the area are granitic rocks and felsite into which a carbonatite stock and associated alkalic igneous rocks were intruded; these rocks are locally covered by Jurassic sandstone, Tertiary rhyolitic tuff, and colluvial deposits. Several methods were evaluated for mapping the main lithologic units, including the unsupervised classification and spectral curve-matching techniques. In the five thermalinfrared (TIR) channels, comparison of the results of linear spectral unmixing and unsupervised classification with published geologic maps showed that the main lithologic units were mapped, but large areas with moderate to dense tree cover were not mapped in the TIR data. Compared to TIMS data, simulated ASTER data permitted slightly less discrimination in the mafic alkalic rock series, and carbonatite was not mapped in the TIMS nor in the simulated ASTER TIR data. In the nine visible and near-infrared channels, unsupervised classification did not yield useful results, but both the spectral linear unmixing and the matched filter techniques produced useful results, including mapping calcitic and dolomitic carbonatite exposures, travertine in hot spring deposits, kaolinite in argillized sandstone and tuff, and muscovite in sericitized granite and felsite, as well as commonly occurring illite/muscovite. However, the distinction made in AVIRIS data between calcite and dolomite was not consistently feasible in the simulated ASTER data. Comparison of the lithologie information produced by spectral analysis of the simulated ASTER data to a photogeologic interpretation of a simulated ASTER color image illustrates the high potential of spectral analysis of ASTER data to geologic interpretation.

Journal of Geophysical Research D: Atmospheres↗

USGS2025

Evaluating a simulation-based wildfire burn probability map for the conterminous US

Background Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography and ignition locations, and BP maps are key components of wildfire risk assessments. Aims Few studies have compared BP maps with real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous US based on the large fire simulation model FSim. Methods We compared BP with observed wildfires from 2016 to 2022 across 128 regions representing similar fire regimes (‘pyromes’). We evaluated the distribution of burned areas across BP values, and compared burned area distributions among fire size classes. Key results Across all pyromes, mean BP was moderately correlated with observed burned area. An average of 71% of burned area occurred in higher-BP classes, vs 79% expected. BP underpredicted burned area in the Mountain West, especially for extremely large fires. Conclusions The FSim BP map was useful for estimating subsequent wildfire hazard, but may have underestimated burned areas where input data did not reflect recent climate change, vegetation change or human ignition patterns. Implications Our evaluations indicate that caution is needed when relying on simulation-based BP maps to inform management decisions. Our results also highlight potential opportunities to improve model estimates.

Conterminous United States↗

USGS2008

Use of landsat ETM+ SLC-off segment-based gap-filled imagery for crop type mapping

Failure of the Scan Line Corrector (SLC) on the Landsat ETM+ sensor has had a major impact on many applications that rely on continuous medium resolution imagery to meet their objectives. The United States Department of Agriculture (USDA) Cropland Data Layer (CDL) program uses Landsat imagery as the primary source of data to produce crop-specific maps for 20 states in the USA. A new method has been developed to fill the image gaps resulting from the SLC failure to support the needs of Landsat users who require coincident spectral data, such as for crop type mapping and monitoring. We tested the new gap-filled method for a CDL crop type mapping project in eastern Nebraska. Scan line gaps were simulated on two Landsat 5 images (spring and late summer 2003) and then gap-filled using landscape boundary models, or segment models, that were derived from 1992 and 2002 Landsat images (used in the gap-fill process). Various date combinations of original and gap-filled images were used to derive crop maps using a supervised classification process. Overall kappa values were slightly higher for crop maps derived from SLC-off gap-filled images compared to crop maps derived from the original imagery (0.3–1.3% higher). Although the age of the segment model used to derive the SLC-off gap-filled product did not negatively impact the overall agreement, differences in individual cover type agreement did increase (−0.8%–1.6% using the 2002 segment model to −5.0–5.1% using the 1992 segment model). Classification agreement also decreased for most of the classes as the size of the segment used in the gap-fill process increased.

Geocarto International↗

USGS2022

Tree regrowth duration map from LCMAP collection 1.0 land cover products in the conterminous United States, 1985–2017

Forest covers about one-third of the land area of the conterminous United States (CONUS) and plays an important role in offsetting carbon emissions and supporting local economies. Growing interest in forests as relatively cost-effective nature-based climate solutions, particularly restoration and reforestation activities, has increased the demand for information on forest regrowth and recovery following natural and anthropogenic disturbances (e.g., fire, harvest, or thinning). However, a wall-to-wall mapping of the CONUS tree regrowth duration at an annual time interval and 30-m resolution is still challenging. In this study, we utilized the annual land cover products to develop a dataset to quantify forest regrowth duration for CONUS over 1985–2017. The land cover data used to derive the tree regrowth duration map is from the primary land cover product in the U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) collection. The LCMAP product used all available Landsat images to detect disturbances over forest and classify Grass/Shrub to Tree Cover transitions on an annual basis. The average regrowth duration was then calculated for each pixel. The regrowth duration map was validated using human interpreted annual reference data that were collected independently. The validation results show one-year of underestimation and 6-year standard deviation of error between the reference data and regrowth duration map. In southeastern CONUS, where major tree regrowth activities have been observed, our map showed higher accuracy with less than one-year bias and 3.6 years standard deviation of error. Forest in the southeast took around 5 years to recover, which was faster than other regions of CONUS. Many pixels had multiple disturbances during the 33-year study period in the region. The spatial pattern of the tree regrowth indicated intense harvesting activities in this region. The Pacific Northwest coast region was the second main area of tree regrowth, but this region often took multiple decades to recover. Given increasing interest in forests as nature-based climate solutions, the tree regrowth duration map can be used to assess reforestation activities as well as forest recovery following natural disturbance and harvesting.

Conterminous United States↗

USGS2025

Mapping ecological states in the upper Colorado River basin: Implications for fire management

Spatially explicit information on ecosystem dynamics that offers a mechanistic understanding of ecological processes can benefit environmental management. Broad-scale maps based on state-and-transition models provide valuable insight into transitions among ecological states resulting from specific drivers within areas sharing similar climatic and edaphic characteristics ecological sites (ES). We aimed to quantify ecological dynamics of two ES groups in the Upper Colorado River Basin from 1986 to 2022 through annual maps of ecological states and assess potential drivers of observed state change. This region comprises important sagebrush shrublands and pinyon-juniper woodlands affected by non-native annual grass invasion, wildfires, and drought-induced tree mortality. Using field-based and remote sensing data, we modeled vegetation states using random forest models and mapped the states annually from 1986 to 2022. To demonstrate the utility of the state maps for monitoring and management, we used this time series of maps to investigate the influences of fire and drought on state occurrence. Our findings revealed a statistically significant increase in states invaded by non-native annual species (Invaded state), which replaced Grassland and Shrubland states, while Shrubland states decreased significantly, transitioning to invaded and Woodland states. Invaded states had the highest likelihood of burning, followed by Woodlands. Drought was associated with increased area of Grassland and Bare states, but with decreased area of invaded and Shrubland states. These results indicate an accelerating fire cycle is potentially leading to ongoing regional environmental degradation. Despite increasing drought conditions during the study period, the invaded states continued to increase in area, indicating additional underlying mechanisms. Our reproducible, broad-scale, ecologically-driven state mapping process enhances understanding of how drought, fire, and invasion by non-native plants can transform semiarid landscapes of the western USA.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2006

The design and use of hydrogeologic maps

A map should treat the critical problems in a way understandable to the intended reader. Some maps appropriately show only one or two pertinent hydrogeologic parameters. Point‐data maps make little or no interpretation of the data. Four‐dimensional maps ‐those that include an elapsed span of time or projection of hydrogeologic variables into the future‐represent a high degree of interpretation of data; they are most useful to the map reader. The hydro‐geologist has an obligation to his reader to design maps that are as useful as possible.

Groundwater↗

USGS2011

Mapping rice areas of South Asia using MODIS multitemporal data

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R 2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.

South Asia↗