Articles | Volume 14, issue 1
https://doi.org/10.5194/essd-14-143-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-143-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
19 Jan 2022
Data description paper |
| 19 Jan 2022
| 19 Jan 2022
Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product
United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
Kelcy Smith
KBR, contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
Danika Wellington
KBR, contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
Josephine Horton
KBR, contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
Qiang Zhou
ASRC Federal Data Solutions (AFDS), contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
Congcong Li
ASRC Federal Data Solutions (AFDS), contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
Roger Auch
United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
Jesslyn F. Brown
United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA
Zhe Zhu
Department of Natural Resources and the Environment, University of
Connecticut, Storrs, CT 06269, USA
Ryan R. Reker
KBR, contractor to the USGS EROS Center, Sioux Falls, SD 57198, USA
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- SSEBop Evapotranspiration Estimates Using Synthetically Derived Landsat Data from the Continuous Change Detection and Classification Algorithm M. Hiestand et al. 10.3390/rs16071297
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- Characterizing annual dynamics of urban form at the horizontal and vertical dimensions using long-term Landsat time series data Y. Wang et al. 10.1016/j.isprsjprs.2023.07.025
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- Understanding hurricane effects on forestlands: Land cover changes and salvage logging I. Sartorio et al. 10.1016/j.foreco.2024.122132
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- A global time series dataset to facilitate forest greenhouse gas reporting N. Gorelick et al. 10.1088/1748-9326/ace2da
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- Assessment of public and private land cover change in the United States from 1985–2018 N. Healey et al. 10.1088/2515-7620/acd3d8
- A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform J. Zhou et al. 10.1080/17538947.2023.2192004
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- Tracking land use trajectory to map abandoned farmland in mountainous area D. Yang & W. Song 10.1016/j.ecoinf.2023.102103
- Characterization of Change in Tree Cover State and Condition over the Conterminous United States F. Dwomoh & R. Auch 10.3390/f15030470
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- Trends in tree cover change over three decades related to interannual climate variability and wildfire in California F. Dwomoh et al. 10.1088/1748-9326/acad15
26 citations as recorded by crossref.
- Tree regrowth duration map from LCMAP collection 1.0 land cover products in the conterminous United States, 1985–2017 Q. Zhou et al. 10.1080/15481603.2022.2083790
- SSEBop Evapotranspiration Estimates Using Synthetically Derived Landsat Data from the Continuous Change Detection and Classification Algorithm M. Hiestand et al. 10.3390/rs16071297
- Object-based continuous monitoring of land disturbances from dense Landsat time series S. Ye et al. 10.1016/j.rse.2023.113462
- Characterizing annual dynamics of urban form at the horizontal and vertical dimensions using long-term Landsat time series data Y. Wang et al. 10.1016/j.isprsjprs.2023.07.025
- MLC30: A New 30 m Land Cover Dataset for Myanmar From 1990 to 2020 Using Training Sample Migration Framework H. Xing et al. 10.1109/JSTARS.2023.3328309
- Interannual changes of urban wetlands in China’s major cities from 1985 to 2022 M. Wang et al. 10.1016/j.isprsjprs.2024.02.011
- Annual time-series 1 km maps of crop area and types in the conterminous US (CropAT-US): cropping diversity changes during 1850–2021 S. Ye et al. 10.5194/essd-16-3453-2024
- Leveraging past information and machine learning to accelerate land disturbance monitoring S. Ye et al. 10.1016/j.rse.2024.114071
- Spatiotemporal disturbances and attribution analysis of mangrove in southern China from 1986 to 2020 based on time-series Landsat imagery K. Long et al. 10.1016/j.scitotenv.2023.169157
- Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges S. Liang et al. 10.1016/j.srs.2024.100152
- GLC_FCS30D: the first global 30 m land-cover dynamics monitoring product with a fine classification system for the period from 1985 to 2022 generated using dense-time-series Landsat imagery and the continuous change-detection method X. Zhang et al. 10.5194/essd-16-1353-2024
- Understanding hurricane effects on forestlands: Land cover changes and salvage logging I. Sartorio et al. 10.1016/j.foreco.2024.122132
- Reconstruction of seamless harmonized Landsat Sentinel-2 (HLS) time series via self-supervised learning H. Liu et al. 10.1016/j.rse.2024.114191
- Accuracy Assessment of Eleven Medium Resolution Global and Regional Land Cover Land Use Products: A Case Study over the Conterminous United States Z. Wang & G. Mountrakis 10.3390/rs15123186
- A global time series dataset to facilitate forest greenhouse gas reporting N. Gorelick et al. 10.1088/1748-9326/ace2da
- Toward consistent change detection across irregular remote sensing time series observations H. Tollerud et al. 10.1016/j.rse.2022.113372
- Assessment of public and private land cover change in the United States from 1985–2018 N. Healey et al. 10.1088/2515-7620/acd3d8
- A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform J. Zhou et al. 10.1080/17538947.2023.2192004
- Remote sensing of land change: A multifaceted perspective Z. Zhu et al. 10.1016/j.rse.2022.113266
- Tracking land use trajectory to map abandoned farmland in mountainous area D. Yang & W. Song 10.1016/j.ecoinf.2023.102103
- Characterization of Change in Tree Cover State and Condition over the Conterminous United States F. Dwomoh & R. Auch 10.3390/f15030470
- Integrating an abandoned farmland simulation model (AFSM) using system dynamics and CLUE-S for sustainable agriculture W. Song et al. 10.1016/j.agsy.2024.104063
- Continuous forest loss monitoring in a dynamic landscape of Central Portugal with Sentinel-2 data D. Moraes et al. 10.1016/j.jag.2024.103913
- An ensemble method for monitoring land cover changes in urban areas using dense Landsat time series data B. Chai & P. Li 10.1016/j.isprsjprs.2022.11.002
- Nationwide remote sensing framework for forest resource assessment in war-affected Ukraine V. Myroniuk et al. 10.1016/j.foreco.2024.122156
- Trends in tree cover change over three decades related to interannual climate variability and wildfire in California F. Dwomoh et al. 10.1088/1748-9326/acad15
Latest update: 19 Sep 2024
Short summary
Continuous change detection algorithms were implemented with time series satellite records to produce annual land surface change products for the conterminous United States. The land change products are in 30 m spatial resolution and represent land cover and change from 1985 to 2017 across the country. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems.
Continuous change detection algorithms were implemented with time series satellite records to...
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