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Landscape Change Monitoring System (LCMS) Conterminous United States Annual Change

Metadata Updated: October 2, 2025

This product is part of the Landscape Change Monitoring System (LCMS) data suite. It supplies LCMS Change classes for each year that are a refinement of the modeled LCMS Change classes (Slow Loss, Fast Loss, and Gain) and provide information on the cause of landscape change. See additional information about Change in the Entity_and_Attribute_Information or Fields section below.LCMS is a remote sensing-based system for mapping and monitoring landscape change across the United States. Its objective is to develop a consistent approach using the latest technology and advancements in change detection to produce a "best available" map of landscape change. Because no algorithm performs best in all situations, LCMS uses an ensemble of models as predictors, which improves map accuracy across a range of ecosystems and change processes (Healey et al., 2018). The resulting suite of LCMS Change, Land Cover, and Land Use maps offer a holistic depiction of landscape change across the United States over the past four decades.Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). To produce annual composites, the cFmask (Zhu and Woodcock, 2012), cloudScore, Cloud Score + (Pasquarella et al., 2023), and TDOM (Chastain et al., 2019) cloud and cloud shadow masking methods are applied to Landsat Tier 1 and Sentinel 2a and 2b Level-1C top of atmosphere reflectance data. The annual medoid is then computed to summarize each year into a single composite. The composite time series is temporally segmented using LandTrendr (Kennedy et al., 2010; Kennedy et al., 2018; Cohen et al., 2018). All cloud and cloud shadow free values are also temporally segmented using the CCDC algorithm (Zhu and Woodcock, 2014). LandTrendr, CCDC and terrain predictors can be used as independent predictor variables in a Random Forest (Breiman, 2001) model. LandTrendr predictor variables include fitted values, pair-wise differences, segment duration, change magnitude, and slope. CCDC predictor variables include CCDC sine and cosine coefficients (first 3 harmonics), fitted values, and pairwise differences from the Julian Day of each pixel used in the annual composites and LandTrendr. Terrain predictor variables include elevation, slope, sine of aspect, cosine of aspect, and topographic position indices (Weiss, 2001) from the USGS 3D Elevation Program (3DEP) (U.S. Geological Survey, 2019). Reference data are collected using TimeSync, a web-based tool that helps analysts visualize and interpret the Landsat data record from 1984-present (Cohen et al., 2010).Outputs fall into three categories: Change, Land Cover, and Land Use. At its foundation, Change maps areas of Disturbance, Vegetation Successional Growth, and Stable landscape. More detailed levels of Change products are available and are intended to address needs centered around monitoring causes and types of variations in vegetation cover, water extent, or snow/ice extent that may or may not result in a transition of land cover and/or land use. Change, Land Cover, and Land Use are predicted for each year of the time series and serve as the foundational products for LCMS.

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons Attribution

Downloads & Resources

Dates

Metadata Created Date November 3, 2022
Metadata Updated Date October 2, 2025

Metadata Source

Harvested from USDA JSON

Additional Metadata

Resource Type Dataset
Metadata Created Date November 3, 2022
Metadata Updated Date October 2, 2025
Publisher U.S. Forest Service
Maintainer
Identifier https://www.arcgis.com/home/item.html?id=a6f47897259f4c0b9c07986da724fc4c
Data First Published 2021-02-18
Data Last Modified 2025-09-19
Category geospatial
Public Access Level public
Bureau Code 005:96
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 1e98d4b2-8d9d-407d-a3d4-a49befb14f5e
Harvest Source Id d3fafa34-0cb9-48f1-ab1d-5b5fdc783806
Harvest Source Title USDA JSON
Homepage URL https://data-usfs.hub.arcgis.com/datasets/usfs::landscape-change-monitoring-system-lcms-conterminous-united-states-annual-change
License https://creativecommons.org/licenses/by/4.0/
Metadata Type geospatial
Old Spatial -127.9772,22.7686,-65.2542,51.6484
Program Code 005:059
Progresscode onGoing
Source Datajson Identifier True
Source Hash c58d0b7adefb950dcda6e73c3fbe5f2402957403bc1369ac87b7768835d0da49
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -127.9772, 22.7686, -127.9772, 51.6484, -65.2542, 51.6484, -65.2542, 22.7686, -127.9772, 22.7686}

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