- Dataset Availability
- 1985-01-01T00:00:00Z–2022-01-01T00:00:00Z
- Dataset Provider
- United States Geological Survey and Bureau of Land Management
- Earth Engine Snippet
-
ee.ImageCollection("USGS/NLCD_RELEASES/2019_REL/RCMAP/V5/TRENDS_YEAR") - Tags
Description
This collection includes RCMAP yearly products from 1985 through 2021. The RCMAP product suite includes nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree. It also includes rule-based error maps and the temporal trends of each component. Data characterize the percentage of each 30-meter pixel in the Western United States covered by each component for each year from 1985-2021, providing change information for 36 years.
The temporal patterns in each RCMAP component are assessed with two approaches: 1) linear trends and 2) a breaks and stable states method with an 8-year temporal moving window based on structural change at the pixel level. Linear trend products include slope and p-value calculated from least squares linear regression. The slope represents the average percent cover change per year over the time series and the p-value reflects the confidence of change in each pixel. The structural change method partitions the time series into segments of similar slope values, with statistically significant break-points indicating perturbations to the prior trajectory. The break point trends analysis suite relies on structural break methods, resulting in the identification of the number and timing of breaks in the following statistics are produced: 1) for each component, each year, the presence/absence of breaks, 2) the slope, p-value, and standard error of the segment occurring in each year, 3) the overall model R2 (quality of model fit to the temporal profile), and 4) an index, Total Change Intensity. This index reflects the total amount of change occurring across components in that pixel. The linear and structural change methods generally agreed on patterns of change, but the latter found breaks more often, with at least one break point in most pixels. The structural change model provides more robust statistics on the significant minority of pixels with non-monotonic trends, while detrending some interannual signal potentially superfluous from a long-term perspective.
Bands
Resolution
30 meters
Bands
| Name | Units | Min | Max | Scale | Description |
|---|---|---|---|---|---|
annual_herbaceous_break_point |
count | 0 | 1 | Annual structural breaks in each component of annual herbaceous present or absent |
|
bare_ground_break_point |
count | 0 | 1 | Annual structural breaks in each component of bare ground present or absent |
|
herbaceous_break_point |
count | 0 | 1 | Annual structural breaks in each component of herbaceous present or absent |
|
litter_break_point |
count | 0 | 1 | Annual structural breaks in each component of litter present or absent |
|
sagebrush_break_point |
count | 0 | 1 | Annual structural breaks in each component of sagebrush present or absent |
|
shrub_break_point |
count | 0 | 1 | Annual structural breaks in each component of shrub present or absent |
|
non_sagebrush_shrub_break_point |
count | 0 | 1 | Annual structural breaks in each component of non sagebrush shrub present or absent |
|
perennial_herbaceous_break_point |
count | 0 | 1 | Annual structural breaks in each component of perennial herbaceous present or absent |
|
tree_break_point |
count | 0 | 1 | Annual structural breaks in each component of tree present or absent |
|
annual_herbaceous_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of annual herbaceous per year |
bare_ground_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of bare ground per year |
herbaceous_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of herbaceous per year |
litter_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of litter per year |
sagebrush_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of sagebrush per year |
shrub_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of shrub per year |
non_sagebrush_shrub_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of non sagebrush shrub per year |
perennial_herbaceous_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of perennial herbaceous per year |
tree_segment_pvalue |
P-value | 0 | 100 | 0.01 | P-values of structural break segments within each component of tree per year |
annual_herbaceous_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of annual herbaceous |
bare_ground_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of bare ground |
herbaceous_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of herbaceous |
litter_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of litter |
sagebrush_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of sagebrush |
shrub_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of shrub |
non_sagebrush_shrub_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of non sagebrush shrub |
perennial_herbaceous_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of perennial herbaceous |
tree_segment_slope |
% change/y | -99999 | 99999 | 0.01 | Annual slope of structural break segments within each component of tree |
Terms of Use
Terms of Use
This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law. This is an Open Access article that has been identified as being free of known restrictions under copyright law, including all related and neighboring rights (https://creativecommons.org/publicdomain/mark/1.0/). You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.
Citations
Rigge, M.B., Bunde, B., Postma, K., Shi, H., 2022, Rangeland Condition Monitoring Assessment and Projection (RCMAP) Fractional Component Time-Series Across the Western U.S. 1985-2021: U.S. Geological Survey data release. doi:10.5066/P9ODAZHC
Rigge, M., C. Homer, L. Cleeves, D. K. Meyer, B. Bunde, H. Shi, G. Xian, S. Schell, and M. Bobo. 2020. Quantifying western U.S. rangelands as fractional components with multi-resolution remote sensing and in situ data. Remote Sensing 12. doi:10.3390/rs12030412
Rigge, M., C. Homer, H. Shi, D. Meyer, B. Bunde, B. Granneman, K. Postma, P. Danielson, A. Case, and G. Xian. 2021. Rangeland Fractional Components Across the Western United States from 1985 to 2018. Remote Sensing 13:813. doi:10.3390/rs13040813
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
// Import the NLCD RCMAP TRENDS YEAR collection.
var image = ee.ImageCollection(
'USGS/NLCD_RELEASES/2019_REL/RCMAP/V5/TRENDS_YEAR'
).select('annual_herbaceous_segment_pvalue');
var vis = {
min: [0],
max: [100],
palette: [
'000000', 'f9e8b7', 'f7e3ac', 'f0dfa3', 'eedf9c', 'eada91', 'e8d687',
'e0d281', 'ddd077', 'd6cc6d', 'd3c667', 'd0c55e', 'cfc555', 'c6bd4f',
'c4ba46', 'bdb83a', 'bbb534', 'b7b02c', 'b0ad1f', 'adac17', 'aaaa0a',
'a3a700', '9fa700', '9aa700', '92a700', '8fa700', '87a700', '85a700',
'82aa00', '7aaa00', '77aa00', '70aa00', '6caa00', '67aa00', '5fa700',
'57a700', '52a700', '4fa700', '4aa700', '42a700', '3ca700', '37a700',
'37a300', '36a000', '369f00', '349d00', '339900', '339900', '2f9200',
'2d9100', '2d8f00', '2c8a00', '2c8800', '2c8500', '2c8400', '2b8200',
'297d00', '297a00', '297900', '277700', '247400', '247000', '29700f',
'2c6d1c', '2d6d24', '336d2d', '366c39', '376c44', '396a4a', '396a55',
'3a6a5f', '3a696a', '396774', '3a6782', '39668a', '376292', '34629f',
'2f62ac', '2c5fb7', '245ec4', '1e5ed0', '115cdd', '005ae0', '0057dd',
'0152d6', '0151d0', '014fcc', '014ac4', '0147bd', '0144b8', '0142b0',
'0141ac', '013da7', '013aa0', '01399d', '013693', '013491', '012f8a',
'012d85', '012c82', '01297a'
]
};
// Display the image on the map.
Map.setCenter(-114, 38, 6);
Map.addLayer(image, vis, 'Annual herbaceous segment pvalue');