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James Wickham

Publications and source records attributed to James Wickham.

14 recordsLinked to original sources
USGS2026

Thematic accuracy assessment of the National Land Cover Database (NLCD2021) for the conterminous United States

The MultiResolution Land Characteristics (MRLC) consortium’s National Land Cover Database (NLCD) was established as an operational, stakeholder-oriented land cover monitoring program with the release of the NLCD2001 database. Both land cover and land cover change data became available with the release of NLCD2006. Here, we report the land cover and land cover change accuracies for NLCD2021, documenting Level II and I accuracies for the 2016, 2019, and 2021 land cover datasets and 2016–2021 land cover change. An additional objective, not addressed in previous NLCD assessments, is the estimation of the total variance of area estimates, where total variance includes sampling variance and variability in reference label assignment. We estimate the total variance of the area estimates for the stable and change classes targeted by the strata used in the sampling design. For the 16 Level II classes, the overall accuracy (OA) was 73% ± 1% when agreement was defined using only the primary reference class label and 89% ± 0.7% when agreement was defined as a match between the map label and either the primary or alternate reference label (± standard error, SE). For the eight Level I classes, the corresponding OA estimates were 81% ± 0.9% and 89% ± 0.7%. Level II and Level I OA tended to be higher for 2016 land cover and lower and more similar for 2019 and 2021 land cover. Land cover change user and producer accuracies (UA and PA) tended to be <50%. When the alternate reference label was included in the definition of agreement, exceptions of high class-specific accuracies (≥75%) were more prevalent for PA than UA. The consistency of reference label interpretations was greater for no-change classes than for change classes. The estimates of the total variance incorporating interpreter variability were often smaller than the standard variance estimates, indicating the possibility that the total variance estimator is highly unstable. Further study is needed to improve the utility of this total variance estimator for practical applications.

conterminous United States↗
USGS2025

Thirty years of the U.S. National Land Cover Database: Impacts and future direction

The National Land Cover Database (NLCD), developed through the Multi-Resolution Land Characteristics Consortium, was initiated 30 years ago and has continually provided critical, Landsat-based landcover and land-change information for the United States. Originally launched to address the lack of national-scale, moderate-resolution land-cover data, NLCD has evolved from the pioneering 1992 dataset into a comprehensive, annually updated product suite. Key innovations include the introduction of impervious surface mapping, forest canopy mapping, standardized Landsat mosaics, national-scale accuracy assessments, continual evolution of deep learning and artificial intelligence methodologies, and a transition toward operational, change-focused monitoring. The NLCD has become an essential resource for scientific research, land management, and policy development, with extensive adoption across federal, state, and local agencies; academia; and the private sector. The NLCD data underpin a wide array of applications, including biodiversity conservation, urban planning, hydrology, human health studies, and natural hazard assessment. As new global and high-resolution commercial land-cover products emerge, the NLCD continues to distinguish itself through its temporal depth, federal backing, and thematic consistency. Moving forward, the NLCD will maintain its niche as the leading, moderate-resolution, long-term land-cover and land-change dataset for the United States, ensuring continued support for broad national applications while complementing higher-resolution and global-mapping efforts.

Photogrammetric Engineering & Remote Sensing↗
USGS2025

An interagency perspective on improving consistency and transparency of land use and land cover mapping

Executive Summary Geospatial products of land use and land cover are broadly used in many applications. For example, the annual national greenhouse gas inventory uses the National Land Cover Database, the Coastal Change Analysis Program, Landscape Fire and Resource Management Planning Tools, the Forest Inventory and Analysis, and the National Resources Inventory to represent the land use and management base of the United States and attribute sources and sinks of greenhouse gas emissions. Federally produced land use and land cover datasets for the United States, including those from the Multi-Resolution Land Characteristics Consortium, set the foundation for developing and informing applications such as land change, conservation, greenhouse gas monitoring, urban planning, agricultural production, ecosystem functions, and water quantity and use. No single land use and land cover product is optimal for all land use and land cover applications. Approaches for defining and mapping land use and land cover classes differ across Federal map products, reflecting the tailoring of product specifications to match specific agency needs. These differing approaches present a challenge when attempting to integrate and harmonize multiple land use and land cover products into single analysis or application frameworks. Nuanced understanding of how these products are designed and produced may not be immediately evident to users; however, the availability of a diverse suite of products also represents an opportunity, providing multiple approaches for observing landscape change. In response to the National Strategy to Advance an Integrated U.S. Greenhouse Gas Measurement, Monitoring, and Information System, this Multi-Resolution Land Characteristics Consortium-led interagency report presents (1) the current status of U.S. Federal land use and land cover products (as of May 2024), (2) existing synergies and integration among these federally produced land use and land cover products, (3) inherent challenges of creating a single consistent framework, and (4) strategies for collectively tackling these challenges to improve coordination and collaboration among data producers and facilitate the adoption of land use and land cover products for greenhouse gas monitoring and a variety of other applications.

Circular↗
USGS2023

Where forest may not return in the western United States

Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response to these changing disturbance regimes. Meta-analyses of these studies provide broad guidelines on the biotic and abiotic factors that hinder forest recovery, but study-to-study differences in methods and objectives do not support estimation of the total extent of potentially impaired forest succession. In this research, we provide an estimate of the area of potentially impaired forest succession. The estimate was derived from modeling of an 18-year land cover and Normalized Difference Vegetation Index (NDVI) time series supported by an extensive ancillary dataset. We estimate an upper bound of approximately 3470 km 2 of disturbed forest that may not return or reattain prior composition and structure. Based on the data used, fire appears to be the main disturbance agent of impaired forest succession, although climatic factors cannot be discounted. The numerous field studies routinely cite distal seed sources as a factor that hinders forest recovery, and we estimate that 20 % of the upper bound estimate has no forest cover within a 4.4-ha neighborhood. Our upper bound estimate is about 0.5 % of the 2001 mapped extent of western United States forests. The estimate is cognizant of measurement and modeling uncertainties (i.e., upper bound) and uncertainties related to successional rates and trajectories (i.e., potential).

Ecological Indicators↗
USGS2023

Thematic accuracy assessment of the NLCD 2019 land cover for the conterminous United States

The National Land Cover Database (NLCD), a product suite produced through the MultiResolution Land Characteristics (MRLC) consortium, is an operational land cover monitoring program. Starting from a base year of 2001, NLCD releases a land cover database every 2–3-years. The recent release of NLCD2019 extends the database to 18 years. We implemented a stratified random sample to collect land cover reference data for the 2016 and 2019 components of the NLCD2019 database at Level II and Level I of the classification hierarchy. For both dates, Level II land cover overall accuracies (OA) were 77.5% ± 1% (± value is the standard error) when agreement was defined as a match between the map label and primary reference label only, and increased to 87.1% ± 0.7% when agreement was defined as a match between the map label and either the primary or alternate reference label. At Level I of the classification hierarchy, land cover OA was 83.1% ± 0.9% for both 2016 and 2019 when agreement was defined as a match between the map label and primary reference label only, and increased to 90.3% ± 0.7% when agreement also included the alternate reference label. The Level II and Level I OA for the 2016 land cover in the NLCD2019 database were 5% higher compared to the 2016 land cover component of the NLCD2016 database when agreement was defined as a match between the map label and primary reference label only. No improvement was realized by the NLCD2019 database when agreement also included the alternate reference label. User’s accuracies (UA) for forest loss and grass gain were>70% when agreement included either the primary or alternate label, and UA was generally<50% for all other change themes. Producer’s accuracies (PA) were>70% for grass loss and gain and water gain and generally<50% for the other change themes. We conducted a post-analysis review for map-reference agreement to identify patterns of disagreement, and these findings are discussed in the context of potential adjustments to mapping and reference data collection procedures that may lead to improved map accuracy going forward.

conterminous United States↗
USGS2020

Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001-2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001-2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this time. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4,778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001-2006 at twice the rate of 2011-2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2018

Accuracy assessment of NLCD 2011 impervious cover data for the Chesapeake Bay region, USA

The National Land Cover Database (NLCD) contains three eras (2001, 2006, 2011) of percentage urban impervious cover (%IC) at the native pixel size (30 m-x-30 m) of the Landsat Thematic Mapper satellite. These data are potentially valuable to environmental managers and stakeholders because of the utility of %IC as an indicator of watershed and aquatic condition, but lack an accuracy assessment because of the absence of suitable reference data. Recently developed 1 m2 land cover data for the Chesapeake Bay region makes it possible to assess NLCD %IC accuracy for a 262,000 km2 region based on a census rather than a sample of reference data. We report agreement between the two %IC datasets for watersheds and the riparian zones within watersheds and four additional square units. The areas of the six assessment units were 40 ha cell, 433 ha (riparian unit average), 2,756 ha cell, 5,626 ha cell, 8,569 ha (watershed unit average) and 22,500 ha cell. Mean Absolute Deviation (MAD) was ≤ 1.6% for each of the six assessment units and Mean Deviation (MD) was only slightly less, indicating NLCD reliably reproduced %IC from the 1 m2 data with a small (≤ 1.6%) and consistent tendency for underestimation. Results were sensitive to assessment unit choice. The results for the four largest assessment units had very similar regression parameters, R2 values, and patterns of bias. Results for the riparian assessment were different from those for the watershed unit and the other three larger units. MAD was about 50% less for the riparian zones than it was for the watersheds, the direction of bias was less consistent, and NLCD %IC was uniformly higher than 1 m2 %IC in urbanized riparian zones. For the smallest unit, bias patterns were more similar to the riparian unit and regression results were more similar to the four larger units. MAD and MD were also sensitive to the amount of urbanization, increasing as NLCD %IC increased. The low overall bias and positive relationship between bias and level of urbanization suggest that the benefits of obtaining 1 m2 IC data outside of urban areas may not outweigh the costs of obtaining such data.

Delaware, Maryland, New York, Pennsylvania, Virgin↗
USGS2018

Land cover and land use change

Climate can affect and be affected by changes in land cover (the physical features that cover the land such as trees or pavement) and land use (human management and activities on land, such as mining or recreation). A forest, for instance, would likely include tree cover but could also include areas of recent tree removals currently covered by open grass areas. Land cover and use are inherently coupled: changes in land-use practices can change land cover, and land cover enables specific land uses. Understanding how land cover, use, condition, and management vary in space and time is challenging. Changes in land cover can occur in response to both human and climate drivers. For example, demand for new settlements often results in the permanent loss of natural and working lands, which can result in localized changes in weather patterns, temperature, and precipitation. Aggregated over large areas, these changes have the potential to influence Earth’s climate by altering regional and global circulation patterns, changing the albedo (reflectivity) of Earth’s surface, and changing the amount of carbon dioxide (CO 2 ) in the atmosphere. Conversely, climate change can also influence land cover, resulting in a loss of forest cover from climate-related increases in disturbances, the expansion of woody vegetation into grasslands, and the loss of beaches due to coastal erosion amplified by rises in sea level. Land use is also changed by both human and climate drivers. Land-use decisions are traditionally based on short-term economic factors. Land-use changes are increasingly being influenced by distant forces due to the globalization of many markets. Land use can also change due to local, state, and national policies, such as programs designed to remove cultivation from highly erodible land to mitigate degradation, legislation to address sea level rise in local comprehensive plans, or policies that reduce the rate of timber harvest on federal lands. Technological innovation has also influenced land-use change, with the expansion of cultivated lands from the development of irrigation technologies and, more recently, decreases in demand for agricultural land due to increases in crop productivity. The recent expansion of oil and gas extraction activities throughout large areas of the United States demonstrates how policy, economics, and technology can collectively influence and change land use and land cover. Decisions about land use, cover, and management can help determine society’s ability to mitigate and adapt to climate change.

Report↗
USGS2017

Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)

Accuracy assessment is a standard protocol of National Land Cover Database (NLCD) mapping. Here we report agreement statistics between map and reference labels for NLCD 2011, which includes land cover for ca. 2001, ca. 2006, and ca. 2011. The two main objectives were assessment of agreement between map and reference labels for the three, single-date NLCD land cover products at Level II and Level I of the classification hierarchy, and agreement for 17 land cover change reporting themes based on Level I classes (e.g., forest loss; forest gain; forest, no change) for three change periods (2001–2006, 2006–2011, and 2001–2011). The single-date overall accuracies were 82%, 83%, and 83% at Level II and 88%, 89%, and 89% at Level I for 2011, 2006, and 2001, respectively. Many class-specific user's accuracies met or exceeded a previously established nominal accuracy benchmark of 85%. Overall accuracies for 2006 and 2001 land cover components of NLCD 2011 were approximately 4% higher (at Level II and Level I) than the overall accuracies for the same components of NLCD 2006. The high Level I overall, user's, and producer's accuracies for the single-date eras in NLCD 2011 did not translate into high class-specific user's and producer's accuracies for many of the 17 change reporting themes. User's accuracies were high for the no change reporting themes, commonly exceeding 85%, but were typically much lower for the reporting themes that represented change. Only forest loss, forest gain, and urban gain had user's accuracies that exceeded 70%. Lower user's accuracies for the other change reporting themes may be attributable to the difficulty in determining the context of grass (e.g., open urban, grassland, agriculture) and between the components of the forest-shrubland-grassland gradient at either the mapping phase, reference label assignment phase, or both. NLCD 2011 user's accuracies for forest loss, forest gain, and urban gain compare favorably with results from other land cover change accuracy assessments.

Remote Sensing of Environment↗
USGS2015

Completion of the 2011 National Land Cover Database for the conterminous United States – Representing a decade of land cover change information

The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associated changes. The recent release of NLCD 2011 products now represents a decade of consistently produced land cover and impervious surface for the Nation across three periods: 2001, 2006, and 2011 (Homer et al., 2007; Fry et al., 2011). Tree canopy cover has also been produced for 2011 (Coluston et al., 2012; Coluston et al., 2013). With the release of NLCD 2011, the database provides the ability to move beyond simple change detection to monitoring and trend assessments. NLCD 2011 represents the latest evolution of NLCD products, continuing its focus on consistency, production, efficiency, and product accuracy. NLCD products are designed for widespread application in biology, climate, education, land management, hydrology, environmental planning, risk and disease analysis, telecommunications and visualization, and are available for no cost at http://www.mrlc.gov. NLCD is produced by a Federal agency consortium called the Multi-Resolution Land Characteristics Consortium (MRLC) (Wickham et al., 2014). In the consortium arrangement, the U.S. Geological Survey (USGS) leads NLCD land cover and imperviousness production for the bulk of the Nation; the National Oceanic and Atmospheric Administration (NOAA) completes NLCD land cover for the conterminous U.S. (CONUS) coastal zones; and the U.S. Forest Service (USFS) designs and produces the NLCD tree canopy cover product. Other MRLC partners collaborate through resource or data contribution to ensure NLCD products meet their respective program needs (Wickham et al., 2014).

Conterminous United States↗
USGS2013

The overlooked terrestrial impacts of mountaintop mining

Ecological research on mountaintop mining has been focused on aquatic impacts because the overburden (i.e., the mountaintop) is disposed of in nearby valleys, which leads to a wide range of water-quality impacts on streams. There are also numerous impacts on the terrestrial environment from mountaintop mining that have been largely overlooked, even though they are no less wide ranging, severe, and multifaceted. We review the impacts of mountaintop mining on the terrestrial environment by exploring six broad themes: (1) the loss of topographic complexity, (2) forest loss and fragmentation, (3) forest succession and soil loss, (4) forest loss and carbon sequestration, (5) biodiversity, and (6) human health and well-being.

BioScience↗
USGS2008

Detecting changes in riparian habitat conditions based on patterns of greenness change: A case study from the Upper San Pedro River Basin, USA

Healthy riparian ecosystems in arid and semi-arid regions exhibit shifting patterns of vegetation in response to periodic flooding. Their conditions also depend upon the amount of grazing and other human uses. Taking advantage of these system properties, we developed and tested an approach that utilizes historical Landsat data to track changes in the patterns of greenness (Normalized Difference Vegetation Index) within riparian zones. We tested the approach in the Upper San Pedro River of southeastern Arizona of the US, an unimpounded river system that flows north into the US from northern Mexico. We evaluated changes in the pattern of greenness in the San Pedro River National Conservation Area (SPRNCA), an area protected from grazing and development since 1988, and in a relatively unprotected area north of the SPRNCA (NA). The SPRNCA exhibited greater positive changes in greenness than did the NA. The SPRNCA also exhibited larger, more continuous patches of positive change than did the NA. These pattern differences may reflect greater pressures from grazing and urban sprawl in the NA than in the SPRNCA, as well as differences in floodplain width, depth to ground water, and base geology. The SPRNCA has greater amounts of ground and surface water available to support a riparian gallery forest than does the NA, and this may have influenced changes during the study period. Estimates of the direction of greenness change (positive or negative) from satellite imagery were similar to estimates derived from aerial photography , except in areas where changes were from one type of shrub community to another, and in areas with agriculture. Change estimates in these areas may be more difficult because of relatively low greenness values, and because of differences in soil moisture, sun-angle, and crop rotations among the dates of data collection. The potential for applying a satellite-based, greenness change approach to evaluate riparian ecosystem condition over broad geographic areas is also discussed.

Arizona↗
USGS2000

Global-scale patterns of forest fragmentation

We report an analysis of forest fragmentation based on 1-km resolution land-cover maps for the globe. Measurements in analysis windows from 81 km 2 (9 x 9 pixels, “small” scale) to 59,049 km 2 (243 x 243 pixels, “large” scale) were used to characterize the fragmentation around each forested pixel. We identified six categories of fragmentation (interior, perforated, edge, transitional, patch, and undetermined) from the amount of forest and its occurrence as adjacent forest pixels. Interior forest exists only at relatively small scales; at larger scales, forests are dominated by edge and patch conditions. At the smallest scale, there were significant differences in fragmentation among continents; within continents, there were significant differences among individual forest types. Tropical rain forest fragmentation was most severe in North America and least severe in Europe–Asia. Forest types with a high percentage of perforated conditions were mainly in North America (five types) and Europe–Asia (four types), in both temperate and subtropical regions. Transitional and patch conditions were most common in 11 forest types, of which only a few would be considered as “naturally patchy” (e.g., dry woodland). The five forest types with the highest percentage of interior conditions were in North America; in decreasing order, they were cool rain forest, coniferous, conifer boreal, cool mixed, and cool broadleaf.

Conservation Ecology↗