The USGS Land Change Monitoring, Assessment and Projection (LCMAP) initiative strives to keep data products up-to-date and to make those updated products available quickly for the user community.
LCMAP Research and Development is working to meet that goal by updating the product suite on an annual basis using newly acquired Landsat observations and additional time series modeling. The Continuous Change Detection and Classification (CCDC) method used to produce LCMAP products is an excellent method for this goal as it allows additional data to be folded into the product suite in an automated fashion.
The initial science products that are being released as LCMAP Collection 1 are based on a time series of USGS Landsat data that runs from the earliest Landsat 4 acquisitions in 1982 through Landsat 7 and 8 acquisitions collected up until December 31, 2017. The input data is from Landsat Collection 1. Initial updates to the product suite will incorporate observations from 2018 and 2019.
It’s important for users to understand that there will be pixel-level impacts to the product suite with each new LCMAP production run. Spectral changes depicted in the five LCMAP Collection 1 spectral change products will remain constant earlier in the record (that is, closer to 1985), but spectral changes detected near the end of the initial period and during each additional year will appear. Land cover classification results in the five LCMAP land cover products may be slightly different across the full time range of the product suite with the addition of new data, although differences in the early part of the time period are limited.
This distinction is the result of CCDC’s two-step process, which includes change detection and classification. In the initial step – continuous change detection – the time series is scanned for spectral change (see above). The change detection method only uses current and previous data in change detection. A few parameters are calculated at the beginning of a change detection run, based on the full time series, and these parameters could be modified when additional data is added to the end of the time series. For LCMAP updating, however, these parameters are held constant based on the 1982-2017 period. Additional data, therefore, will not affect changes already present in the five spectral products from 1985-2017.
The second step in the CCDC process – “classification” – predicts a land cover type for the time between land cover changes. The classification method uses data from the entire “segment” of Landsat acquisitions between those changes – e.g. 2000-2010 - to classify each pixel, so each new run with additional data does have the potential to alter land cover classifications for previous years. Classification and product generation use the same methods as LCMAP Collection 1, with no changes.
Differences in land cover classifications are minimal early in the time series, but those differences do have the potential to alter results for LCMAP users. To address this issue and minimize the impact on users, annual LCMAP updates will include a re-release of all products for all years. LCMAP Updates will be titled “Collection 1.1,” “Collection 1.2,” and so on, to distinguish each release from Collection 1 data while acknowledging a substantial continuity with Collection 1. Users should note that products from Collection 1 and Collection 1.1 should not be used together in science studies, as there is some potential for inconsistencies across the temporal record.
Below are other science projects associated with this project.
Below are publications associated with this project.
Lessons learned implementing an operational continuous U.S. national land change monitoring capability: The LCMAP approach
Remote sensing as the foundation for high-resolution United States landscape projections – The Land Change Monitoring, assessment, and projection (LCMAP) initiative
Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative
- Overview
The USGS Land Change Monitoring, Assessment and Projection (LCMAP) initiative strives to keep data products up-to-date and to make those updated products available quickly for the user community.
LCMAP Research and Development is working to meet that goal by updating the product suite on an annual basis using newly acquired Landsat observations and additional time series modeling. The Continuous Change Detection and Classification (CCDC) method used to produce LCMAP products is an excellent method for this goal as it allows additional data to be folded into the product suite in an automated fashion.
The initial science products that are being released as LCMAP Collection 1 are based on a time series of USGS Landsat data that runs from the earliest Landsat 4 acquisitions in 1982 through Landsat 7 and 8 acquisitions collected up until December 31, 2017. The input data is from Landsat Collection 1. Initial updates to the product suite will incorporate observations from 2018 and 2019.
It’s important for users to understand that there will be pixel-level impacts to the product suite with each new LCMAP production run. Spectral changes depicted in the five LCMAP Collection 1 spectral change products will remain constant earlier in the record (that is, closer to 1985), but spectral changes detected near the end of the initial period and during each additional year will appear. Land cover classification results in the five LCMAP land cover products may be slightly different across the full time range of the product suite with the addition of new data, although differences in the early part of the time period are limited.
LCMAP Base Period This distinction is the result of CCDC’s two-step process, which includes change detection and classification. In the initial step – continuous change detection – the time series is scanned for spectral change (see above). The change detection method only uses current and previous data in change detection. A few parameters are calculated at the beginning of a change detection run, based on the full time series, and these parameters could be modified when additional data is added to the end of the time series. For LCMAP updating, however, these parameters are held constant based on the 1982-2017 period. Additional data, therefore, will not affect changes already present in the five spectral products from 1985-2017.
Collection 1 classification: Tree Cover; Collection 1.1 classification: Grass/Shrub The second step in the CCDC process – “classification” – predicts a land cover type for the time between land cover changes. The classification method uses data from the entire “segment” of Landsat acquisitions between those changes – e.g. 2000-2010 - to classify each pixel, so each new run with additional data does have the potential to alter land cover classifications for previous years. Classification and product generation use the same methods as LCMAP Collection 1, with no changes.
Differences in land cover classifications are minimal early in the time series, but those differences do have the potential to alter results for LCMAP users. To address this issue and minimize the impact on users, annual LCMAP updates will include a re-release of all products for all years. LCMAP Updates will be titled “Collection 1.1,” “Collection 1.2,” and so on, to distinguish each release from Collection 1 data while acknowledging a substantial continuity with Collection 1. Users should note that products from Collection 1 and Collection 1.1 should not be used together in science studies, as there is some potential for inconsistencies across the temporal record.
- Science
Below are other science projects associated with this project.
- Publications
Below are publications associated with this project.
Lessons learned implementing an operational continuous U.S. national land change monitoring capability: The LCMAP approach
Growing demands for temporally specific information on land surface change are fueling a new generation of maps and statistics that can contribute to understanding geographic and temporal patterns of change across large regions, provide input into a wide range of environmental modeling studies, clarify the drivers of change, and provide more timely information for land managers. To meet these needRemote sensing as the foundation for high-resolution United States landscape projections – The Land Change Monitoring, assessment, and projection (LCMAP) initiative
The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatiaOptimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative
The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the