Rigge, M.，H. Shi, C. Homer, P. Danielson 和 B. Granneman。2019 年。
美国北部大盆地分数分量变化的长期轨迹。Ecosphere 10(6):e02762.
doi:10.1002/ecs2.2762
Rigge, M.，C. Homer, L. Cleeves, D. K. Meyer, B. Bunde, H. Shi, G. Xian,
S. Schell 和 M. Bobo。2020 年。利用多分辨率遥感和原位数据，将美国西部牧区量化为分数分量。Remote Sensing 12.
doi:10.3390/rs12030412
Rigge, M.，C. Homer, H. Shi, D. Meyer, B.
Bunde, B. Granneman, K. Postma, P. Danielson, A. 案例，以及 G. 西安。2021 年。
1985 年至 2018 年美国西部各地的草地分数分量。Remote Sensing 13:813.
doi:10.3390/rs13040813。'
Rigge, M.B.，Bunde, B.，Postma, K. 和 Shi, H.，2024 年，“Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2023”（美国西部 1985-2023 年的草原状况监测评估和预测 (RCMAP) 分数分量时间序列）：美国地质调查局数据发布，doi:10.5066/P9SJXUI1。
[null,null,[],[[["\u003cp\u003eThe RCMAP dataset provides annual percent cover of 10 rangeland components across western North America from 1985 to 2023.\u003c/p\u003e\n"],["\u003cp\u003eIt utilizes Landsat imagery and an improved classification approach for enhanced accuracy and coverage.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes fractional components like annual herbaceous, bare ground, and shrub height, allowing for detailed rangeland analysis.\u003c/p\u003e\n"],["\u003cp\u003eRCMAP data can be used to assess the impact of climate change and management practices on rangeland ecosystems.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset is available through the USGS and is freely accessible for research and non-profit use.\u003c/p\u003e\n"]]],["The RCMAP dataset, provided by the USGS and BLM, uses Landsat imagery from 1985 to 2023 to quantify rangeland component cover across western North America. It includes ten fractional components like annual herbaceous, bare ground, and tree cover. Key actions involve revising training with a neural-net classifier, enhancing Landsat compositing, and expanding the study area to include Canadian regions. This data, updated yearly, helps analyze climate change and management practice effects.\n"],null,["# RCMAP Rangeland Component Timeseries (1985-2023), v06\n\nDataset Availability\n: 1985-01-01T00:00:00Z--2023-12-31T00:00:00Z\n\nDataset Provider\n:\n\n\n [United States Geological Survey and Bureau of Land Management](https://www.mrlc.gov/)\n\nCadence\n: 1 Year\n\nTags\n:\n[climate-change](/earth-engine/datasets/tags/climate-change) [disturbance](/earth-engine/datasets/tags/disturbance) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [landuse-landcover](/earth-engine/datasets/tags/landuse-landcover) [nlcd](/earth-engine/datasets/tags/nlcd) [rangeland](/earth-engine/datasets/tags/rangeland) [trends](/earth-engine/datasets/tags/trends) \n\n#### Description\n\n'The RCMAP (Rangeland Condition Monitoring Assessment and Projection)\ndataset quantifies the percent cover of rangeland components across\nwestern North America using Landsat imagery from 1985-2023. The RCMAP\nproduct suite consists of ten fractional components: annual herbaceous,\nbare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous,\nsagebrush, shrub, tree, and shrub height in addition to the temporal\ntrends of each component. Several enhancements were made to the RCMAP\nprocess relative to prior generations. First, high-resolution training\nwas revised using an improved neural-net classifier and modelling approach.\nThese data serve as foundation to the RCMAP approach. The training\ndatabase was further improved by incorporating additional datasets. Next,\nthe Landsat compositing approach was improved to better capture the range\nof conditions from across each year and through time. These composites are\nbased on Collection 2 Landsat data with improved geolocation accuracy and\ndynamic range. Finally, the Canadian portion of the sagebrush biome was\nincluded, which expanded the study area by 29,199 km2.\n\nProcessing efficiency has been increased using open-source software and\nUSGS High-Performance Computing (HPC) resources. The mapping area included\neight regions which were subsequently mosaicked. These data can be used to\nanswer critical questions regarding the influence of climate change and\nthe suitability of management practices. Component products can be\ndownloaded at\n[Multi-Resolution Land Characteristics Consortium](https://www.mrlc.gov/data).\n\nSee also:\n\n- Rigge, M., H. Shi, C. Homer, P. Danielson, and B. Granneman. 2019.\n Long-term trajectories of fractional component change in the Northern\n Great Basin, USA. Ecosphere 10(6):e02762.\n [doi:10.1002/ecs2.2762](https://doi.org/10.1002/ecs2.2762)\n\n- Rigge, M., C. Homer, L. Cleeves, D. K. Meyer, B. Bunde, H. Shi, G. Xian,\n S. Schell, and M. Bobo. 2020. Quantifying western U.S. rangelands as\n fractional components with multi-resolution remote sensing and in situ\n data. Remote Sensing 12.\n [doi:10.3390/rs12030412](https://doi.org/10.3390/rs12030412)\n\n- Rigge, M., C. Homer, H. Shi, D. Meyer, B.\n Bunde, B. Granneman, K. Postma, P. Danielson, A. Case, and G. Xian. 2021.\n Rangeland Fractional Components Across the Western United States\n from 1985 to 2018. Remote Sensing 13:813.\n [doi:10.3390/rs13040813](https://doi.org/10.3390/rs13040813).',\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|----------------------------------|-------|-----|-----|------------|------------------------------------------------------------------|\n| `rangeland_annual_herbaceous` | % | 0 | 100 | meters | Percent of the pixel covered by annual herbaceous vegetation. |\n| `rangeland_bare_ground` | % | 0 | 100 | meters | Percent of the pixel covered by bare ground. |\n| `rangeland_non_sagebrush_shrub` | % | 0 | 100 | meters | Percent of the pixel covered by non-sagebrush shrubs. |\n| `rangeland_herbaceous` | % | 0 | 100 | meters | Percent of the pixel covered by herbaceous vegetation. |\n| `rangeland_litter` | % | 0 | 100 | meters | Percent of the pixel covered by litter. |\n| `rangeland_sagebrush` | % | 0 | 100 | meters | Percent of the pixel covered by sagebrush (*Artemisia* spp). |\n| `rangeland_shrub` | % | 0 | 100 | meters | Percent of the pixel covered by shrub. |\n| `rangeland_shrub_height` | cm | 0 | 500 | meters | Average height of shrubs in centimeters. |\n| `rangeland_perennial_herbaceous` | % | 0 | 100 | meters | Percent of the pixel covered by perennial herbaceous vegetation. |\n| `rangeland_tree` | % | 0 | 100 | meters | Percent of the pixel covered by tree. |\n\n### Terms of Use\n\n**Terms of Use**\n\nThis work was authored as part of the Contributor's official duties as an\nEmployee of the United States Government and is therefore a work of the\nUnited States Government. In accordance with 17 U.S.C. 105, no copyright\nprotection is available for such works under U.S. Law. This is an Open\nAccess article that has been identified as being free of known restrictions\nunder copyright law, including all related and neighboring rights\n(https://creativecommons.org/publicdomain/mark/1.0/). You can copy, modify,\ndistribute and perform the work, even for commercial purposes, all without\nasking permission.\n\n### Citations\n\nCitations:\n\n- Rigge, M.B., Bunde, B., Postma, K., and Shi, H., 2024,\n Rangeland Condition Monitoring Assessment and Projection (RCMAP)\n Fractional Component Time-Series Across the Western U.S. 1985-2023:\n U.S. Geological Survey data release,\n [doi:10.5066/P9SJXUI1](https://doi.org/10.5066/P9SJXUI1).\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\n// Import the NLCD RCMAP collection.\nvar dataset = ee.ImageCollection('USGS/NLCD_RELEASES/2023_REL/RCMAP/V6/COVER');\n\n// Filter the collection to the 2021 product.\nvar nlcd2021 = dataset.filter(ee.Filter.eq('system:index', '2021')).first();\n\n// Each product has multiple bands for different rangeland categories.\nprint('Bands:', nlcd2021.bandNames());\n\n// Select the rangeland_annual_herbaceous band.\nvar percentCover = nlcd2021.select('rangeland_annual_herbaceous');\n\nvar vis = {\n // Map 0..100.\n 'palette': [\n '000000', 'f9e8b7', 'f7e3ac', 'f0dfa3', 'eedf9c', 'eada91', 'e8d687',\n 'e0d281', 'ddd077', 'd6cc6d', 'd3c667', 'd0c55e', 'cfc555', 'c6bd4f',\n 'c4ba46', 'bdb83a', 'bbb534', 'b7b02c', 'b0ad1f', 'adac17', 'aaaa0a',\n 'a3a700', '9fa700', '9aa700', '92a700', '8fa700', '87a700', '85a700',\n '82aa00', '7aaa00', '77aa00', '70aa00', '6caa00', '67aa00', '5fa700',\n '57a700', '52a700', '4fa700', '4aa700', '42a700', '3ca700', '37a700',\n '37a300', '36a000', '369f00', '349d00', '339900', '339900', '2f9200',\n '2d9100', '2d8f00', '2c8a00', '2c8800', '2c8500', '2c8400', '2b8200',\n '297d00', '297a00', '297900', '277700', '247400', '247000', '29700f',\n '2c6d1c', '2d6d24', '336d2d', '366c39', '376c44', '396a4a', '396a55',\n '3a6a5f', '3a696a', '396774', '3a6782', '39668a', '376292', '34629f',\n '2f62ac', '2c5fb7', '245ec4', '1e5ed0', '115cdd', '005ae0', '0057dd',\n '0152d6', '0151d0', '014fcc', '014ac4', '0147bd', '0144b8', '0142b0',\n '0141ac', '013da7', '013aa0', '01399d', '013693', '013491', '012f8a',\n '012d85', '012c82', '01297a'\n ]\n};\n\n// Display the image on the map.\nMap.setCenter(-114, 38, 6);\nMap.addLayer(percentCover, vis, 'Rangeland Annual Herbaceous %');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/USGS/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER) \n[RCMAP Rangeland Component Timeseries (1985-2023), v06](/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER) \n'The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height ... \nUSGS/NLCD_RELEASES/2023_REL/RCMAP/V6/COVER, climate-change,disturbance,landsat-derived,landuse-landcover,nlcd,rangeland,trends \n1985-01-01T00:00:00Z/2023-12-31T00:00:00Z \n26.5157 -128.0026 51.5761 -99.6758 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/https://www.mrlc.gov/)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/USGS_NLCD_RELEASES_2023_REL_RCMAP_V6_COVER)"]]
