Assessing the Accuracy of National Land Cover Dataset Area Estimates at Multiple Spatial Extents

Hollister, Jeffrey W.; González, Marta; Paul, John F.; August, Peter V.; Copeland, Jane

doi:10.14358/pers.70.4.405

Cited by 35 publications

(13 citation statements)

References 10 publications

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“…Lastly, we used linear regression (estimate vs. true) to assess accuracy (Hollister et al 2004). As a measure of accuracy, 2 values would be in perfect agreement when the regression of those 2 values have a an R 2 equal to one, a slope (β 1 ) equal to one, and an intercept (β 0 ) equal to zero.…”

Section: Assessment Data and Methodsmentioning

confidence: 99%

Using GIS to estimate lake volume from limited data

Hollister

Milstead

2010

Lake and Reservoir Management

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Section: Assessment Data and Methodsmentioning

confidence: 99%

Using GIS to estimate lake volume from limited data

Hollister

Milstead

2010

Lake and Reservoir Management

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“…Thus, some pixels near the waterbody were classified as wetland in LCMAP but forest in NLCD. Rhode Island's forests are overestimated by almost 8%, and most misclassifications occur in the NLCD forest category, which is actually developed for agricultural land [35]. Because of the impacts of LULC on environmental processes, such as carbon dynamics and the hydrologic cycle, high-frequency land-cover mapping products are important for reducing model uncertainties [36][37][38].…”

Section: Discussionmentioning

confidence: 99%

Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

et al. 2020

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Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km2, respectively, but developed lands gained 293 km2 (29 km2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr−1) and agricultural expansion (0.046 Tg C·yr−1); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics.

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“…In neither case were these land cover classes included in our investigation. The issue here is not the difference between including forested wetlands within an Anderson I wetland classification or keeping them separate as an Anderson II class but that forested wetlands are notoriously hard to classify with high accuracy [39]. Some of the results from ecoregions from the above-listed larger regions may indicate classification confusion between what LC Trends called "upland" forest and what NLCD classified as "upland" forest compared to what was classified as "wetlands" and not included in the study.…”

Section: Limitationsmentioning

confidence: 99%

Regional Differences in Upland Forest to Developed (Urban) Land Cover Conversions in the Conterminous U.S., 1973–2011

Auch

Drummond

Xian

et al. 2016

Forests

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In this U.S. Geological Survey study of forest land cover across the conterminous U.S. (CONUS), specific proportions and rates of forest conversion to developed (urban) land were assessed on an ecoregional basis. The study period was divided into six time intervals between 1973 and 2011. Forest land cover was the source of 40% or more of the new urban land in 35 of the 84 ecoregions located within the CONUS. In 11 of these ecoregions this threshold exceeded in every time interval. When the percent of change, forest to urban, was compared to the percent of forest in each ecoregion, 58 ecoregions had a greater percent of change and, in six of those, change occurred in every time interval. Annual rates of forest to urban land cover change of 0.2% or higher occurred in 12 ecoregions at least once and in one ecoregion in all intervals. There were three ecoregions where the above conditions were met for nearly every time interval. Even though only a small number of the ecoregions were heavily impacted by forest loss to urban development within the CONUS, the ecosystem services provided by undeveloped forest land cover need to be quantified more completely to better inform future regional land management.

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Assessing the Accuracy of National Land Cover Dataset Area Estimates at Multiple Spatial Extents

Cited by 35 publications

References 10 publications

Using GIS to estimate lake volume from limited data

Using GIS to estimate lake volume from limited data

Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

Regional Differences in Upland Forest to Developed (Urban) Land Cover Conversions in the Conterminous U.S., 1973–2011

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