Validation of the U.S. Geological Survey's Land Change Monitoring, Assessment and Projection (LCMAP) Collection 1.0 annual land cover products 1985–2017

Stehman, Stephen V.; Pengra, Bruce W.; Horton, Josephine A.; Wellington, Danika

doi:10.1016/j.rse.2021.112646

Cited by 46 publications

(50 citation statements)

References 37 publications

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“…These LCMAP product values were extracted for the plots corresponding to the reference sample locations. Data files containing these values are available online [36], and the results for an accuracy assessment of LCPRI and LCACHG are reported in [37].…”

Section: Methodsmentioning

confidence: 99%

“…The two strata for the post-stratified estimator of the overall footprint of change included one stratum defined as all map pixels that have a mapped change for any year in the time series (i.e., the total map footprint of change) and the other stratum defined as all other pixels (i.e., stable pixels with no change in any year of the times series). Post-stratified estimation was not used for annual area of change because of inadequate map accuracy [37], and because some change classes are so rare that very few or even no sample plots were found in the map stratum for that change class.…”

Section: Sample-based Estimatorsmentioning

confidence: 99%

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Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series

Auch

Wellington

Taylor

et al. 2022

Land

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Sample-based estimates augmented by complete coverage land-cover maps were used to estimate area and describe patterns of annual land-cover change across the conterminous United States (CONUS) between 1985 and 2016. Most of the CONUS land cover remained stable in terms of net class change over this time, but a substantial gross change dynamic was captured by the annual and cumulative time intervals. The dominant types of changes can be grouped into natural resource cycles, increases in urbanization, and surface-water dynamics. The annual estimates over the 30-year time series showed a reduction in the rate of urban expansion after 2006, new growth in cropland after 2007, but a net overall decline in cropland since 1985, and two eras of net tree cover loss, the first one early in the time series and the second starting in 2012. Our study provides a holistic assessment of the CONUS land-cover conversion (class) change and can serve as a new benchmark for future research.

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Section: Methodsmentioning

confidence: 99%

Section: Sample-based Estimatorsmentioning

confidence: 99%

Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series

Auch

Wellington

Taylor

et al. 2022

Land

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“…However, because good quality training data is essential to estimating highquality classification models and acquisition of training data is difficult and labor-intensive at global scale, training data provided by collaborators who have regional expertise in land cover and land cover change processes is extremely valuable. In North America, for example, we incorporated a data set that includes 17,476 randomly sampled reference sites distributed across the conterminous United States that were used to assess the accuracy of map products from the USGS LCMap program (Stehman et al, 2021), along with 9,073 sites from Canada and Alaska that were compiled as part of a separate project funded by NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) (Wang et al, 2020). Similarly, in South America, we are leveraging training sites distributed across the Northern half of South America (Brazil, Bolivia, Peru, Ecuador, Columbia Venezuela, French Guyana, and Suriname) provided by colleagues involved in the MapBiomas project (Souza et al, 2020).…”

Section: Name Descriptionmentioning

confidence: 99%

Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat

Friedl

Woodcock

Olofsson

et al. 2022

Front. Remote Sens.

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Land cover maps are essential for characterizing the biophysical properties of the Earth’s land areas. Because land cover information synthesizes a rich array of information related to both the ecological condition of land areas and their exploitation by humans, they are widely used for basic and applied research that requires information related to land surface properties (e.g., terrestrial carbon models, water balance models, weather, and climate models) and are core inputs to models and analyses used by natural resource scientists and land managers. As the Earth’s global population has grown over the last several decades rates of land cover change have increased dramatically, with enormous impacts on ecosystem services (e.g., biodiversity, water supply, carbon sequestration, etc.). Hence, accurate information related to land cover is essential for both managing natural resources and for understanding society’s ecological, biophysical, and resource management footprint. To address the need for high-quality land cover information we are using the global record of Landsat observations to compile annual maps of global land cover from 2001 to 2020 at 30 m spatial resolution. To create these maps we use features derived from time series of Landsat imagery in combination with ancillary geospatial data and a large database of training sites to classify land cover at annual time step. The algorithm that we apply uses temporal segmentation to identify periods with stable land cover that are separated by breakpoints in the time series. Here we provide an overview of the methods and data sets we are using to create global maps of land cover. We describe the algorithms used to create these maps and the core land cover data sets that we are creating through this effort, and we summarize our approach to accuracy assessment. We also present a synthesis of early results and discuss the strengths and weaknesses of our early map products and the challenges that we have encountered in creating global land cover data sets from Landsat. Initial accuracy assessment for North America shows good overall accuracy (77.0 ± 2.0% correctly classified) and 79.8% agreement with the European Space Agency (ESA) WorldCover product. The land cover mapping results we report provide the foundation for robust, repeatable, and accurate mapping of global land cover and land cover change across multiple decades at 30 m spatial resolution from Landsat.

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“…The observed streamflow data from the USGS are based on the stage-discharge relationship, and this method has an uncertainty of ±6% for ideal conditions [41], and may increase depending on the condition of flow control structure and channel stability [42]. The LCMAP land cover data have a pixel-level overall accuracy above 80% [43], and errors may exist at the pixel level. Potential changes in stormflow characteristics from urban stormwater management infrastructures [7,36] and non-urban areas, such as drainage systems in agricultural croplands [44] or silviculture in forest areas [45], are not quantified.…”

Section: Potential Uncertaintiesmentioning

confidence: 99%

Land Cover Change Effects on Stormflow Characteristics across Broad Hydroclimate Representative Urban Watersheds in the United States

Khand

Senay

2022

Water

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Urban development alters stormflow characteristics and is associated with increasing flood risks. The long-term evaluation of stormflow characteristics that exacerbate floods, such as peak stormflow and time-to-peak stormflow at varying levels of urbanization across different hydroclimates, is limited. This study investigated the long-term (1980s to 2010s) effects of increasing urbanization on key stormflow characteristics using observed 15 min streamflow data across six broad hydroclimate representative urban watersheds in the conterminous United States. The results indicate upward trends in peak stormflow and downward trends in time-to-peak stormflow at four out of six watersheds. The watershed in the Great Plains region had the largest annual increasing (decreasing) percent change in peak stormflow (time-to-peak stormflow). With the current change rates, peak stormflow in the Great Plains region watershed is expected to increase by 55.4% and have a 2.71 h faster time-to-peak stormflow in the next decade.

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Validation of the U.S. Geological Survey's Land Change Monitoring, Assessment and Projection (LCMAP) Collection 1.0 annual land cover products 1985–2017

Cited by 46 publications

References 37 publications

Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series

Conterminous United States Land-Cover Change (1985–2016): New Insights from Annual Time Series

Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat

Land Cover Change Effects on Stormflow Characteristics across Broad Hydroclimate Representative Urban Watersheds in the United States

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