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USGS2025

Resiliency of land change monitoring efforts to input data resampling

The geometric transformation of remotely sensed imagery from one map projection to another necessitates a data resampling operation which alters the recorded values. The global Landsat archive is made available in the Universal Transverse Mercator (UTM) projection system which preserves geographic shape across small area but introduces small errors in distance and area. As remote sensing-based studies develop from local scales to regional and global, they need to adopt more appropriate map projections from which accurate area measurements can be made. While effects of resampling on recorded values have been studied in the past, the impacts on higher-level results such as land cover have not been widely reported. This study investigates an approach for monitoring land cover and land change using two input datasets derived from identical source Landsat data, where one input dataset is transformed to an equal-area map projection and thereby resampled. Recorded surface reflectance values are changed through the reprojection/resampling process, and our study highlights observed differences in derived land cover from these two different input datasets throughout the various stages of deriving land cover and related characteristics. Our findings suggest that large-scale analyses of land cover will not be substantially impacted by reprojection of input data, but small-scale analyses should exercise caution when interpreting timing and magnitude of pixel-level change and classification dynamics.

Georgia↗
USGS2017

A land product characterization system for comparative analysis of satellite data and products

A Land Product Characterization System (LPCS) has been developed to provide land data and products to the community of individuals interested in validating space-based land products by comparing them with similar products available from other sensors or surface-based observations. The LPCS facilitates the application of global multi-satellite and in situ data for characterization and validation of higher-level, satellite-derived, land surface products (e.g., surface reflectance, normalized difference vegetation index, and land surface temperature). The LPCS includes data search, inventory, access, and analysis functions that will permit data to be easily identified, retrieved, co-registered, and compared statistically through a single interface. The system currently includes data and products available from Landsat 4 through 8, Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua, Suomi National Polar-Orbiting Partnership (S-NPP)/Joint Polar Satellite System (JPSS) Visible Infrared Imaging Radiometer Suite (VIIRS), and simulated data for the Geostationary Operational Environmental Satellite (GOES)-16 Advanced Baseline Imager (ABI). In addition to the future inclusion of in situ data, higher-level land products from the European Space Agency (ESA) Sentinel-2 and -3 series of satellites, and other high and medium resolution spatial sensors, will be included as available. When fully implemented, any of the sensor data or products included in the LPCS would be available for comparative analysis.

Remote Sensing↗
USGS2020

Methods for rapid quality assessment for national-scale land surface change monitoring

Providing rapid access to land surface change data and information is a goal of the U.S. Geological Survey. Through the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative, we have initiated a monitoring capability that involves generating a suite of ten annual land cover and land surface change datasets across the United States at a 30-m spatial resolution. During the LCMAP automated production on a tile-by-tile basis, erroneous data can occasionally be generated due to hardware or software failure. While crucial to assure the quality of the data, rapid evaluation of results at the pixel level during production is a substantial challenge because of the massive data volumes. Traditionally, product quality relies on the validation after production, which is inefficient to reproduce the whole product when an error occurs. This paper presents a method for automatically evaluating LCMAP results during the production phase based on fourteen indices to quickly find and flag erroneous tiles in the LCMAP products. The methods involved two types of comparisons: comparing LCMAP values across the temporal record to measure internal consistency and calculating agreement with multiple intervals of the National Land Cover Database (NLCD) data to measure the consistency with existing products. We developed indices on a tile-by-tile basis in order to quickly find and flag potential erroneous tiles by comparing with surrounding tiles using local outlier factor analysis. The analysis integrates all indices into a local outlier score (LOS) to detect erroneous tiles distinct from neighbor tiles. Our analysis showed that the methods were sensitive to partially erroneous tiles in the simulated data with a LOS higher than 2. The rapid quality assessment methods also successfully identified erroneous tiles during the LCMAP production, in which land surface change results were not properly saved to the products. The LOS map and indices for rapid quality assessment also point to directions for further investigations. A map of all LOS values by tile for the published LCMAP shows all LOS values are below 2. We also investigated tiles with high LOS to ensure the distinction with neighboring tiles was reasonable. An index in this study shows the overall agreement between LCMAP and NLCD on a tile basis is above 71.5% and has an average at 89.1% across the 422 tiles in the conterminous U.S. The workflow is suitable for other studies with a large volume of image products.

Remote Sensing↗
USGS2025

A review of the effects of climate change on visitor use in US public lands and waters

Climate change is affecting recreational visitor use in U.S. public lands and waters, causing changes to visitation levels, timing of trips, activity participation, and visitor safety. This report reviews the literature on how climate change is influencing visitor use in the United States and how visitor use may be affected in the future. Our goal is to provide the current state of the literature for managers of public lands and waters and provide foundational information for the development of a climate change vulnerability assessment methodology for visitor use within the National Park Service (that may be applicable to other federal lands and waters). Specifically, we investigate how seven different climate change factors may affect visitor use on public lands and waters. These factors consist of increasing temperatures; flooding, drought, and increased variability of precipitation; decreasing snowpack and earlier spring runoff; wildfires, smoke, and air quality; coastal hazards: hurricanes and sea level rise; harmful algal blooms (HABs); and zoonotic and vector-borne disease. The current research indicates that these factors are already affecting visitors to public lands and waters and continued effects in the future are likely as the climate warms. Additionally, we summarize existing research on how visitors to U.S. public lands and waters are adapting to climate change. Throughout the review, we note where there are substantial gaps in the literature and more research would help managers respond to the effects of climate change on visitor use.

Science Report↗
USGS2026

Morphometric properties of the CP-21 landing site on the Moon at Mons Gruithuisen Gamma

Characterizing terrain surface properties is an essential step in assessing the feasibility of landing successfully at a location on a planetary surface. Slopes and terrain ruggedness index (TRI) values derived from high-resolution (2 m pixel −1 ) digital terrain models provided important constraints in selecting the landing site for the upcoming Payloads and Research Investigations on the Surface of the Moon program as part of the Commercial Lunar Payload Services task order CP-21 mission. The selected landing site needed to balance safety requirements with the ability to achieve the science and exploration goals of the Lunar Vulkan Imaging and Spectroscopy Explorer payload. In this study, we compare several morphometric parameters in the context of the CP-21 landing site on Mons Gruithuisen Gamma, or the Gamma dome, and quantify the information they convey about lunar surface properties to assess their utility for future landing site evaluation. TRI was found to be a useful metric for assessing landing site safety. Metrics that better decouple slope and surface roughness, the vector ruggedness measure and the standard deviation of slope, provided additional information about surface characteristics and textures such as the degree to which roughness is isotropic.

Planetary Science Journal↗
USGS2026

Lunar-VISE landing site selection and characterization at Mons Gruithuisen Gamma

The Lunar Vulkan Imaging and Spectroscopy Explorer (Lunar-VISE) was selected for a Commercial Lunar Payload Services (CLPS) delivery to the Gruithuisen domes region of the Moon as part of NASA’s Payloads and Research Investigation on the Surface of the Moon (PRISM) program. The Gruithuisen domes are chemically and morphologically distinct from their surroundings with a thorium-rich, silicic composition. The Lunar-VISE instrument payload is designed to investigate the compositional and thermophysical properties of dome materials in order to understand how late-stage silicic volcanism occurred on the Moon. Selection of a landing site required balancing science and exploration goals with the safety requirements for landing and rover trafficability. Science required access to boulders, potential exposures of bedrock, and if possible, rover access to the dome edge to enable observations of the surrounding maria. Safety considerations included landing hazards, maintenance of line-of-sight communications between the lander and rover, and any early morning or late afternoon shadows that would limit the mission duration. After consideration of several candidate landing sites, a 100-meter diameter landing ellipse centered on 36.45715° N, 319.20398° E, was selected near the edge of a topographic step and blocky ejecta crater (recently named Mareta) near the summit of Mons Gruithuisen Gamma. This location enables access to a field of boulders excavated by a relatively fresh impact providing a diversity of boulders for investigations, as well as views to the surrounding mare and Mons Gruithuisen Delta dome off of the dome edge via only a short rover traverse outside the landing ellipse (traverse < 100 m) while meeting safety requirements in accord with the CLPS risk posture.

Planetary Science Journal↗
USGS2014

Characterization of intra-annual reflectance properties of land cover classes in southeastern South Dakota using Landsat TM and ETM+ data

Landsat-7 and Landsat-5 have orbits that are offset from each other by 8 days. During the time that the sensors on both satellites are operational, there is an opportunity for conducting analyses that incorporate multiple intra-annual high spatial resolution data sets for characterizing the Earth's land surface. In the current study, nine Landsat thematic mapper (TM) and enhanced thematic mapper plus (ETM+) data sets, covering the same path and row on different dates, were acquired during a 1-year time interval for a region in southeastern South Dakota and analyzed. Scenes were normalized using pseudoinvariant objects, and digital data from a series of test sites were extracted from the imagery and converted to surface reflectance. Sunphotometer data acquired on site were used to atmospherically correct the data. Ground observations that were made throughout the growing season by a large group of volunteers were used to help interpret spectroradiometric patterns and trends. Normalized images were found to be very effective in portraying the seasonal patterns of reflectance change that occurred throughout the region. Many of the radiometric patterns related to plant growth and development, but some also related to different background properties. The different kinds of land cover in the region were spectrally and radiometrically characterized and were found to have different seasonal patterns of reflectance. The degree to which the land cover classes could be separated spectrally and radiometrically, however, depended on the time of year during which the data sets were acquired, and no single data set appeared to be adequate for separating all types of land cover. This has practical implications for classification studies because known patterns of seasonal reflectance properties for the different types of land cover within a region will facilitate selection of the most appropriate data sets for producing land cover classifications.

Canadian Journal of Remote Sensing↗
USGS1999

Diatom (Bacillariophyta) community response to water quality and land use

Aquatic algal communities are sensitive to environmental stresses and are used as indicators of water quality. Diatoms were collected from three streams that drain the Great Marsh at Indiana Dunes National Lakeshore. Diatom communities, water chemistry, and land use were measured at each site to test the hypothesis that differences in land use indirectly affect diatom communities, through changes in water quality. Relationships among these variables were examined by correlation, cluster, and detrended correspondence analysis. Several water chemistry variables were correlated to several land-use categories. Diatom species diversity was most variable in disturbed areas with poorer water quality and was correlated with land use and total alkalinity, total hardness, and specific conductance. Sites within each stream were grouped in terms of their diatom assemblage by both cluster and detrended correspondence analysis with but two exceptions in Dunes Creek. Diatom communities in the three streams responded to land use through its effects on water quality. The results of this study demonstrate the use of diatom assemblages as indicators of water quality, which can be linked to land use in a watershed.

Indiana↗
USGS2011

Ecological influence and pathways of land use in sagebrush

Land use in sagebrush (Artemisia spp.) landscapes influences all sage-grouse (Centrocer-cus spp.) populations in western North America. Croplands and the network of irrigation canals cover 230,000 km2 and indirectly influence up to 77% of the Sage-Grouse Conservation Area and 73% of sagebrush land cover by subsidizing synanthropic predators on sage-grouse. Urbanization and the demands of human population growth have created an extensive network of con-necting infrastructure that is expanding its influence on sagebrush landscapes. Over 2,500 km 2 are now covered by interstate highways and paved roads; when secondary roads are included, 15% of the Sage-Grouse Conservation Area and 5% of existing sagebrush habitats are 2.5 km from roads. Density of secondary roads often exceeds 5 km/km 2 , resulting in widespread motorized access for recreation, creating extensive travel corridors for management actions and resource development, subsidizing predators adapted to human presence, and facilitating spread of exotic or invasive plants. Sagebrush lands also are being used for their wilderness and recreation values, including off highway vehicle use. Approximately 12,000,000 animal use months (AUM amount of forage to support one livestock unit per month) are permitted for grazing livestock on public lands in the western states. Direct effects of grazing on sage-grouse populations or sagebrush landscapes are not possible to assess from current data. However, management of lands grazed by livestock has influenced sagebrush ecosystems by vegetation treatments to increase forage and reduce sagebrush and other plant species unpalatable to livestock. Fences (2 km/km 2 in some regions), roads, and water developments to manage livestock movements further modify the landscape. Oil and gas development influences 8% of the sagebrush habitats with the highest intensities occurring in the eastern range of sage-grouse; 20% of the sagebrush distribution is indirectly influenced in the Great Plains, Wyoming Basin, and Colorado Plateau SMZs. Energy development physically removes habitat to construct well pads, roads, power lines, and pipelines; indirect effects include habitat fragmentation, soil disturbance, and facilitation of exotic plant and animal spread. More recent development of alternative energy, such as wind and geothermal, creates infrastructure in new regions of the sage-grouse distribution. Land use will continue to be a dominant stressor on sage-brush systems; its individual and cumulative effects will challenge long-term conservation of sage-grouse populations.

Book chapter↗
USGS2000

Accuracy assessment for the U.S. Geological Survey Regional Land-Cover Mapping Program: New York and New Jersey Region

The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific accuracies. In Region 2, consisting of New York and New Jersey, the accuracy assessment was completed for 15 land-cover and land-use classes, using interpreted 1:40,000-scale aerial photographs as reference data. The methodology used for Region 2 features a two-stage, geographically stratified approach, with a general sample of all classes (1,033 sample sites), and a separate sample for rare classes (294 sample sites). A confidence index was recorded for each land-cover interpretation on the 1:40,000-scale aerial photography The estimated overall accuracy for Region 2 was 63 percent (standard error 1.4 percent) using all sample sites, and 75.2 percent (standard error 1.5 percent) using only reference sites with a high-confidence index. User's and producer's accuracies for the general sample and user's accuracy for the sample of rare classes, as well as variance for the estimated accuracy parameters, were also reported. Narrowly defined land-use classes and heterogeneous conditions of land cover are the major causes of misclassification errors. Recommendations for modifying the accuracy assessment methodology for use in the other nine Federal regions are provided.

Photogrammetric Engineering and Remote Sensing↗
USGS2002

A strategy for estimating the rates of recent United States land-cover changes

Information on the rates of land-use and land-cover change is important in addressing issues ranging from the health of aquatic resources to climate change. Unfortunately, there is a paucity of information on land-use and land-cover change except at very local levels. We describe a strategy for estimating land-cover change across the conterminous United States over the past 30 years. Change rates are estimated for 84 ecoregions using a sampling procedure and five dates of Landsat imagery. We have applied this methodology to six eastern U.S. ecoregions. Results show very high rates of change in the Plains ecoregions, high to moderate rates in the Piedmont ecoregions, and moderate to low rates in the Appalachian ecoregions. This indicates that ecoregions are appropriate strata for capturing unique patterns of land-cover change. The results of the study are being applied as we undertake the mapping of the rest of the conterminous United States.

Photogrammetric Engineering and Remote Sensing↗
USGS2008

Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery

Satellite image-based mapping of tropical forests is vital to conservation planning. Standard methods for automated image classification, however, limit classification detail in complex tropical landscapes. In this study, we test an approach to Landsat image interpretation on four islands of the Lesser Antilles, including Grenada and St. Kitts, Nevis and St. Eustatius, testing a more detailed classification than earlier work in the latter three islands. Secondly, we estimate the extents of land cover and protected forest by formation for five islands and ask how land cover has changed over the second half of the 20th century. The image interpretation approach combines image mosaics and ancillary geographic data, classifying the resulting set of raster data with decision tree software. Cloud-free image mosaics for one or two seasons were created by applying regression tree normalization to scene dates that could fill cloudy areas in a base scene. Such mosaics are also known as cloud-filled, cloud-minimized or cloud-cleared imagery, mosaics, or composites. The approach accurately distinguished several classes that more standard methods would confuse; the seamless mosaics aided reference data collection; and the multiseason imagery allowed us to separate drought deciduous forests and woodlands from semi-deciduous ones. Cultivated land areas declined 60 to 100 percent from about 1945 to 2000 on several islands. Meanwhile, forest cover has increased 50 to 950%. This trend will likely continue where sugar cane cultivation has dominated. Like the island of Puerto Rico, most higher-elevation forest formations are protected in formal or informal reserves. Also similarly, lowland forests, which are drier forest types on these islands, are not well represented in reserves. Former cultivated lands in lowland areas could provide lands for new reserves of drier forest types. The land-use history of these islands may provide insight for planners in countries currently considering lowland forest clearing for agriculture. Copyright 2008 College of Arts and Sciences.

Caribbean Journal of Science↗
USGS2009

Monitoring land use on military installations

The US Geological Survey's Land Cover Trends is a research projects aimed to understand the rates, trends, causes, and consequences of contemporary US land use and land-cover change. The project is using the EPA Level III eco-regions as a geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The results are expected to be used for collaborative environmental change consequences research with various partners including the National Science Foundation, the National Oceanic and Atmospheric Administration, and the US Fish and Wildlife Service. The Land Cover project can provide geographic understanding of the state of the nation's ecosystems. The project is scheduled to be completed by 2010 and expected to provide an unbiased, national synthesis of land-cover changes.

Military Engineer↗
USGS2016

Regional land subsidence caused by the compaction of susceptible aquifer systems accompanying groundwater extraction

Land subsidence includes both gentle downwarping and sudden sinking of segments of the land surface. Major anthropogenic causes of land subsidence are extraction of fluids including water, oil, and gas. Measurement and detec- tion of land subsidence include both ground-based and remotely sensed air- borne and space-based methods. Methods for measurement of subsidence at points include differential leveling, global positioning system surveys, and extensometers. Satellite-borne differential interferometric synthetic aperture radar and airborne LiDAR techniques can detect land-surface movement over wide areas of interest. Aquifer-system compaction and subsidence owing to groundwater extraction typically occurs in areas of unconsolidated alluvial or basin-fill aquifer systems comprising aquifers and aquitards. Approaches to analyzing and modeling deformation of aquifer systems follow from the basic relations between head, stress, compressibility, and groundwater flow. Analysis and simulation of aquifer-system compaction have been addressed primarily using either an approach based on conventional groundwater flow theory or an approach based on linear poroelasticity theory. Both approaches rely on the principle of effective stress outlined by Karl Terzaghi in 1925. In the approach based on conventional groundwater flow theory, an aquitard drainage model explains the compaction of fine grained material using the principle of effective stress and theory of hydrodynamic lag. Packages for the widely-used MODFLOW groundwater model are available to simulate aqui- fer-system compaction and land subsidence using the aquitard-drainage approach. Poroelasticity theory describes the more fully coupled processes of groundwater flow and three-dimensional deformation of aquifer systems. The general theory accounts for compressible fluid, porous matrix and solid grains. Simulation codes using the poroelastic theory include some commer- cial software products and a few research codes.

Book chapter↗
USGS1995

History and use of remote sensing for conservation and management of federal lands in Alaska, USA

Remote sensing has been used to aid land use planning efforts for federal public lands in Alaska since the 1940s. Four federal land management agencies-the U.S. Fish and Wildlife Service, US. Bureau of Land Management, US. National Park Service, and U.S. Forest Service-have used aerial photography and satellite imagery to document the extent, type, and condition of Alaska's natural resources. Aerial photographs have been used to collect detailed information over small to medium-sized areas. This standard management tool is obtainable using equipment ranging from hand-held 35-mm cameras to precision metric mapping cameras. Satellite data, equally important, provide synoptic views of landscapes, are digitally manipulatable, and are easily merged with other digital databases. To date, over 109.2 million ha (72%) of Alaska's land cover have been mapped via remote sensing. This information has provided a base for conservation, management, and planning on federal public lands in Alaska.

Alaska↗
USGS2014

A new map of global ecological land units — An ecophysiographic stratification approach

In response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterized in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs. This subdivision of the Earth’s surface into relatively fine, ecological land areas is designed to be useful for various types of ecosystem research and management applications, including assessments of climate change impacts to ecosystems, economic and non-economic valuation of ecosystem services, and conservation planning.

Book↗
USGS2017

Understanding recurrent land use processes and long-term transitions in the dynamic south-central United States, c. 1800 to 2006

Forests have historically been under significant land use pressures that cause periods of degradation, clearance, and recovery. To understand these changes, studies are needed that place trends in a historical landscape context and also examine recent dynamics. Here, we use historical investigation (c. 1800) and an examination of land use and land cover change between 1973 and 2006 to establish a baseline trajectory of the forested system of the south-central United States (US) plains. The study culminates in a highly detailed accounting of the processes and causes of land change between 2001 and 2006. In the study region, the forest transitioned from early low-intensity use, to clearance for farming and timber, to widespread recovery from degradation beginning in the 1930s. By 1970, the region was transitioning from recovered woodlands to an intensive regime of recurrent timber harvest and replanting. The recurring cycle inherent in intensive silviculture has been the main cause of land change for the past several decades, accounting for more than 95% of the total extent of change between 2001 and 2006. The transition to forest recovery in the south-central US was an important historical occurrence. However, the dynamic post-transition landscape needs to be better understood.

Arkansas, Louisiana, Oklahoma, Texas↗
USGS2021

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability

Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite imagery and other ancillary spatial data. Different analysts interpreting the same spatial unit will not always agree on the land cover class label that should be assigned. Two approaches for accommodating interpreter variability when estimating the area are simple averaging (SA) and latent class modeling (LCM). This study compares agreement between area estimates obtained from SA and LCM using reference data obtained by seven trained, professional interpreters who independently interpreted an annual time series of land cover reference class labels for 300 sampled Landsat pixels. We also compare the variability of the LCM and SA area estimates over different numbers of interpreters and different subsets of interpreters within each interpreter group size, and examine area estimates of three land cover classes (forest, developed, and wetland) and three change types (forest gain, forest loss, and developed gain). Differences between the area estimates obtained from SA and LCM are most pronounced for the estimates of wetland and the three change types. The percent area estimates of these rare classes were usually greater for LCM compared to SA, with the differences between LCM and SA increasing as the number of interpreters providing the reference data increased. The LCM area estimates generally had larger standard deviations and greater ranges over different subsets of interpreters, indicating greater sensitivity to the selection of the individual interpreters who carried out the reference class labeling.

Washington↗