- Dataset Availability
- 2016-01-01T00:00:00Z–2017-01-01T00:00:00Z
- Dataset Provider
- USDA Forest Service (USFS) Geospatial Technology and Applications Center (GTAC)
- Earth Engine Snippet
-
ee.ImageCollection("USFS/GTAC/TreeMap/v2016")
- Tags
Description
This product is part of the TreeMap data suite. It provides detailed spatial information on forest characteristics including number of live and dead trees, biomass, and carbon across the entire forested extent of the continental United States in 2016.
TreeMap v2016 contains one image, a 22-band 30 x 30m resolution gridded map of the forests of the continental United States circa 2016, with each band representing an attribute derived from select FIA data (and one band representing the TreeMap ID). Examples of attributes include forest type, canopy cover percent, live tree stocking, live/dead tree biomass, and carbon in live/dead trees.
TreeMap products are the output of a random forest machine learning algorithm that assigns the most similar Forest Inventory Analysis (FIA) plot to each pixel of gridded LANDFIRE input data. The objective is to combine the complimentary strengths of detailed-but-spatially-sparse FIA data with less-detailed-but-spatially-comprehensive LANDFIRE data to produce better estimations of forest characteristics at a variety of scales. TreeMap is being used in both the private and public sectors for projects including fuel treatment planning, snag hazard mapping, and estimation of terrestrial carbon resources.
TreeMap is distinct from other imputed forest vegetation products in that it provides an FIA plot identifier to each pixel whereas other datasets provide forest characteristics such as live basal area (e.g., Ohmann and Gregory 2002; Pierce Jr et al. 2009; Wilson, Lister, and Riemann 2012). The FIA plot identifier can be linked to the hundreds of variables and attributes recorded for each tree and plot in the FIA DataMart, FIA's public repository of plot information (Forest Inventory Analysis 2022a).
The 2016 methodology includes disturbance as a response variable, resulting in increased accuracy in mapping disturbed areas. Within-class accuracy was over 90% for forest cover, height, vegetation group, and disturbance code when compared to LANDFIRE maps. At least one pixel within the radius of validation plots matched the class of predicted values in 57.5% of cases for forest cover, 80.0% for height, 80.0% for tree species with highest basal area, and 87.4% for disturbance.
Additional Resources
Please see the TreeMap 2016 Publication for more detailed information regarding methods and accuracy assessment.
The TreeMap 2016 Data Explorer is a web-based application that provides users the ability to view and download TreeMap attribute data.
The TreeMap Research Data Archive for the full dataset download, metadata, and support documents.
TreeMap Raster Data Gateway for TreeMap attribute data downloads, metadata, and support documents.
FIA Database Manual version 8 for more detailed information on the attributes included in TreeMap 2016.
Contact sm.fs.treemaphelp@usda.gov with any questions or specific data requests.
Forest Inventory Analysis. 2022a. Forest Inventory Analysis DataMart. Forest Inventory Analysis DataMart FIADB_1.9.0. 2022. https://apps.fs.usda.gov/fia/datamart/datamart.html.
Ohmann, Janet L and Matthew J Gregory. 2002. Predictive Mapping of Forest Composition and Structure with Direct Gradient Analysis and Nearest- Neighbor Imputation in Coastal Oregon, USA. Can. J. For. Res. 32:725-741. doi: 10.1139/X02-011.
Pierce, Kenneth B Jr, Janet L Ohmann, Michael C Wimberly, Matthew J Gregory, and Jeremy S Fried. 2009. Mapping Wildland Fuels and Forest Structure for Land Management: A Comparison of Nearest Neighbor Imputation and Other Methods. Can. J. For. Res. 39: 1901-1916. doi:10.1139/X09-102.
Wilson, B Tyler, Andrew J Lister, and Rachel I Riemann. 2012. A Nearest-Neighbor Imputation Approach to Mapping Tree Species over Large Areas Using Forest Inventory Plots and Moderate Resolution Raster Data. Forest Ecol. Manag. 271:182-198. doi: 10.1016/j. foreco.2012.02.002.
Bands
Resolution
30 meters
Bands
Name | Units | Description |
---|---|---|
ALSTK |
% | All-Live-Tree Stocking. The sum of stocking percent values of all live trees on the condition. |
BALIVE |
ft^2/acre | Live Tree Basal Area. Basal area in square feet per acre of all live trees ≥1.0 inch d.b.h./d.r.c. sampled in the condition. |
CANOPYPCT |
% | Live Canopy Cover. Derived from the Forest Vegetation Simulator. |
CARBON_D |
tons/acre | Carbon, Standing Dead. Calculated via the following FIA query: Sum (DRYBIO_BOLE, DRYBIO_TOP, DRYBIO_STUMP, DRYBIO_SAPLING, DRYBIO_WDLD_SPP) / 2 /2000*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=2) AND ((TREE.DIA)>=5) AND ((TREE.STANDING_DEAD_CD)=1)) |
CARBON_DWN |
tons/acre | Carbon, Down Dead. Carbon (tons per acre) of woody material >3 inches in diameter on the ground, and stumps and their roots >3 inches in diameter. Estimated from models based on geographic area, forest type, and live tree carbon density (Smith and Heath 2008). |
CARBON_L |
tons/acre | Carbon, Live Above Ground. Calculated via the following FIA query: Sum (DRYBIO_BOLE, DRYBIO_TOP, DRYBIO_STUMP, DRYBIO_SAPLING, DRYBIO_WDLD_SPP) / 2 /2000*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=1)) |
DRYBIO_D |
tons/acre | Dry Standing Dead Tree Biomass, Above Ground. Calculated via the following FIA query: Sum (DRYBIO_BOLE, DRYBIO_TOP, DRYBIO_STUMP, DRYBIO_SAPLING, DRYBIO_WDLD_SPP) /2000*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=2) AND ((TREE.DIA)>=5) AND ((TREE.STANDING_DEAD_CD)=1)) |
DRYBIO_L |
tons/acre | Dry Live Tree Biomass, Above Ground. Calculated via the following FIA query: Sum (DRYBIO_BOLE, DRYBIO_TOP, DRYBIO_STUMP, DRYBIO_SAPLING, DRYBIO_WDLD_SPP) /2000*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=1)) |
FLDSZCD |
Field Stand-Size Class Code - Field-assigned classification of the predominant (based on stocking) diameter class of live trees within the condition. |
|
FLDTYPCD |
Field Forest Type Code - A code indicating the forest type, assigned by the field crew, based on the tree species or species groups forming a plurality of all live stocking. The field crew assesses the forest type based on the acre of forest land around the plot, in addition to the species sampled on the condition. |
|
FORTYPCD |
Algorithm Forest Type Code - This is the forest type used for reporting purposes. It is primarily derived using a computer algorithm, except when less than 25 percent of the plot samples a particular forest condition or in a few other cases. |
|
GSSTK |
% | Growing-Stock Stocking. The sum of stocking percent values of all growing-stock trees on the condition. |
QMD_RMRS |
in | Stand Quadratic Mean Diameter. Rocky Mountain Research Station. The quadratic mean diameter, or the diameter of the tree of average basal area, on the condition. Based on live trees ≥1.0 inch d.b.h./d.r.c. Only collected by certain FIA work units. |
SDIPCT_RMRS |
% | Stand Density Index. Rocky Mountain Research Station. A relative measure of stand density for live trees (≥1.0 inch d.b.h./d.r.c.) on the condition, expressed as a percentage of the maximum stand density index (SDI). Only collected by certain FIA work units. |
STANDHT |
ft | Height of dominant trees. Derived from the Forest Vegetation Simulator. |
STDSZCD |
Algorithm Stand-Size Class Code - A classification of the predominant (based on stocking) diameter class of live trees within the condition assigned using an algorithm. |
|
TPA_DEAD |
count/acre | Dead Trees Per Acre. Number of dead standing trees per acre (DIA >= 5”). Calculated via the following FIA query: Sum TREE.TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=2) AND ((TREE.DIA)>=5) AND ((TREE.STANDING_DEAD_CD)=1)) |
TPA_LIVE |
count/acre | Live Trees Per Acre. Number of live trees per acre (DIA > 1"). Calculated via the following FIA query: Sum TREE.TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=1) AND ((TREE.DIA)>=1)) |
Value |
Raw TreeMap identifier dataset values. This dataset is useful to see spatial groupings of individual modeled plot values. |
|
VOLBFNET_L |
sawlog-board-ft/acre | Volume, Live (log rule: Int’l ¼ inch). Calculated via the following FIA query: Sum VOLBFNET * TPA_UNADJ WHERE (((TREE.TREECLCD)=2) AND ((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=1)) |
VOLCFNET_D |
ft^3/acre | Volume, Standing Dead. Calculated via the following FIA query: Sum VOLCFNET*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=2) AND ((TREE.DIA)>=5) AND ((TREE.STANDING_DEAD_CD)=1)) |
VOLCFNET_L |
ft^3/acre | Volume, Live. Calculated via the following FIA query: Sum VOLCFNET*TPA_UNADJ WHERE (((COND.COND_STATUS_CD)=1) AND ((TREE.STATUSCD)=1)) |
FLDSZCD Class Table
Value | Color | Description |
---|---|---|
0 | #c62363 | Nonstocked - Meeting the definition of accessible land and one of the following applies (1) less than 10 percent stocked by trees, seedlings, and saplings and not classified as cover trees, or (2) for several woodland species where stocking standards are not available, less than 10 percent canopy cover of trees, seedlings, and saplings. |
1 | #feba12 | ≤4.9 inches (seedlings/saplings). At least 10 percent stocking (or 10 percent canopy cover if stocking standards are not available) in trees, seedlings, and saplings, and at least 2/3 of the canopy cover is in trees less than 5.0 inches d.b.h./d.r.c. |
2 | #ffff00 | 5.0-8.9 inches (softwoods)/ 5.0-10.9 inches (hardwoods). At least 10 percent stocking (or 10 percent canopy cover if stocking standards are not available) in trees, seedlings, and saplings; and at least one-third of the canopy cover is in trees greater than 5.0 inches d.b.h./d.r.c. and the plurality of the canopy cover is in softwoods 5.0-8.9 inches diameter and/or hardwoods 5.0-10.9 inches d.b.h., and/or woodland trees 5.0-8.9 inches d.r.c. |
3 | #38a800 | 9.0-19.9 inches (softwoods)/ 11.0-19.9 inches (hardwoods). At least 10 percent stocking (or 10 percent canopy cover if stocking standards are not available) in trees, seedlings, and sapling; and at least one-third of the canopy cover is in trees greater than 5.0 inches d.b.h./d.r.c. and the plurality of the canopy cover is in softwoods 9.0-19.9 inches diameter and/or hardwoods between 11.0-19.9 inches d.b.h., and/or woodland trees 9.0-19.9 inches d.r.c. |
4 | #73dfff | 20.0-39.9 inches. At least 10 percent stocking (or 10 percent canopy cover if stocking standards are not available) in trees, seedlings, and saplings; and at least one-third of the canopy cover is in trees greater than 5.0 inches d.b.h./d.r.c. and the plurality of the canopy cover is in trees 20.0-39.9 inches d.b.h. |
5 | #5c09fc | 40.0+ inches. At least 10 percent stocking (or 10 percent canopy cover if stocking standards are not available) in trees, seedlings, and saplings; and at least one-third of the canopy cover is in trees greater than 5.0 inches d.b.h./d.r.c. and the plurality of the canopy cover is in trees greater than or equal to 40.0 inches d.b.h. |
FLDTYPCD Class Table
Value | Color | Description |
---|---|---|
101 | #6e26ec | Jack pine |
102 | #c765ec | Red pine |
103 | #efdbcc | Eastern white pine |
104 | #a8a9f2 | Eastern white pine / eastern hemlock |
105 | #d0ce83 | Eastern hemlock |
121 | #47d0b6 | Balsam fir |
122 | #9d86a6 | White spruce |
123 | #a5f77a | Red spruce |
124 | #dcf4d9 | Red spruce / balsam fir |
125 | #64e1f7 | Black spruce |
126 | #afa9b0 | Tamarack |
127 | #f2c531 | Northern white-cedar |
128 | #87cc75 | Fraser fir |
141 | #84d7eb | Longleaf pine |
142 | #ef4677 | Slash pine |
161 | #97f2ad | Loblolly pine |
162 | #d45549 | Shortleaf pine |
163 | #63f3ac | Virginia pine |
164 | #f58de4 | Sand pine |
165 | #e9c991 | Table Mountain pine |
166 | #ddbef2 | Pond pine |
167 | #bba847 | Pitch pine |
171 | #95eacd | Eastern redcedar |
182 | #a6827b | Rocky Mountain juniper |
184 | #bca28a | Juniper woodland |
185 | #cff3f4 | Pinyon / juniper woodland |
201 | #c1ded5 | Douglas-fir |
202 | #948ee9 | Port-Orford-cedar |
221 | #d0ef5b | Ponderosa pine |
222 | #e29af0 | Incense-cedar |
224 | #c34bc3 | Sugar pine |
225 | #e6acb8 | Jeffrey pine |
226 | #ea3b34 | Coulter pine |
241 | #724353 | Western white pine |
261 | #f2c7a0 | White fir |
262 | #6ab27f | Red fir |
263 | #f1f3d3 | Noble fir |
264 | #ea5aba | Pacific silver fir |
265 | #edc7e1 | Engelmann spruce |
266 | #4965e2 | Engelmann spruce / subalpine fir |
267 | #a0f4c4 | Grand fir |
268 | #5697de | Subalpine fir |
269 | #5defc4 | Blue spruce |
270 | #e8f384 | Mountain hemlock |
271 | #cc63bd | Alaska-yellow-cedar |
281 | #e16f3d | Lodgepole pine |
301 | #f5da68 | Western hemlock |
304 | #a63bcf | Western redcedar |
305 | #51d0dd | Sitka spruce |
321 | #6bc5b6 | Western larch |
341 | #f2f4a5 | Redwood |
361 | #576abe | Knobcone pine |
362 | #b56f7c | Southwestern white pine |
365 | #dca5ca | Foxtail pine / bristlecone pine |
366 | #67eff4 | Limber pine |
367 | #ca5483 | Whitebark pine |
368 | #a8bf86 | Miscellaneous western softwoods |
369 | #aff6e9 | Western juniper |
371 | #a53394 | California mixed conifer |
381 | #e9e2eb | Scotch pine |
383 | #d0cfad | Other exotic softwoods |
384 | #eee1b3 | Norway spruce |
385 | #e4db79 | Introduced larch |
401 | #ec42f6 | Eastern white pine / northern red oak / white ash |
402 | #7e9f81 | Eastern redcedar / hardwood |
403 | #4a7196 | Longleaf pine / oak |
404 | #5cd76e | Shortleaf pine / oak |
405 | #37999a | Virginia pine / southern red oak |
406 | #ed54dd | Loblolly pine / hardwood |
407 | #6792f0 | Slash pine / hardwood |
409 | #82eb3e | Other pine / hardwood |
501 | #b8db98 | Post oak / blackjack oak |
502 | #bccc4b | Chestnut oak |
503 | #f22ab1 | White oak / red oak / hickory |
504 | #f6e095 | White oak |
505 | #77989d | Northern red oak |
506 | #718640 | Yellow-poplar / white oak / northern red oak |
507 | #9d4f8d | Sassafras / persimmon |
508 | #c376e4 | Sweetgum / yellow-poplar |
509 | #7cb133 | Bur oak |
510 | #5fa7cc | Scarlet oak |
511 | #9ae6e8 | Yellow-poplar |
512 | #def3b1 | Black walnut |
513 | #b88bf2 | Black locust |
514 | #a5f031 | Southern scrub oak |
515 | #eeafa3 | Chestnut oak / black oak / scarlet oak |
516 | #9bd763 | Cherry / white ash / yellow-poplar |
517 | #b838ee | Elm / ash / black locust |
519 | #e88fbb | Red maple / oak |
520 | #cce5b9 | Mixed upland hardwoods |
601 | #ed8a9c | Swamp chestnut oak / cherrybark oak |
602 | #c8ed2d | Sweetgum / Nuttall oak / willow oak |
605 | #f0bd53 | Overcup oak / water hickory |
606 | #60dad1 | Atlantic white-cedar |
607 | #c790c1 | Baldcypress / water tupelo |
608 | #54c7ef | Sweetbay / swamp tupelo / red maple |
609 | #8e6a31 | Baldcypress / pondcypress |
701 | #cecceb | Black ash / American elm / red maple |
702 | #b1bef2 | River birch / sycamore |
703 | #f077ef | Cottonwood |
704 | #969aca | Willow |
705 | #c4ec84 | Sycamore / pecan / American elm |
706 | #efadec | Sugarberry / hackberry / elm / green ash |
707 | #da23cf | Silver maple / American elm |
708 | #e4c3c0 | Red maple / lowland |
709 | #bf90e1 | Cottonwood / willow |
722 | #52f3eb | Oregon ash |
801 | #a2c9eb | Sugar maple / beech / yellow birch |
802 | #3ff451 | Black cherry |
805 | #6ab7f2 | Hard maple / basswood |
809 | #b3714c | Red maple / upland |
901 | #d28f25 | Aspen |
902 | #f59550 | Paper birch |
903 | #dd82c7 | Gray birch |
904 | #c5f2a0 | Balsam poplar |
905 | #e3f2e7 | Pin cherry |
911 | #b2c2b1 | Red alder |
912 | #4ff389 | Bigleaf maple |
921 | #8772e8 | Gray pine |
922 | #bb24a1 | California black oak |
923 | #c7f7cd | Oregon white oak |
924 | #8fc3c6 | Blue oak |
931 | #f13896 | Coast live oak |
933 | #efe92f | Canyon live oak |
934 | #6c48ae | Interior live oak |
935 | #b3e8cd | California white oak (valley oak) |
941 | #e8a882 | Tanoak |
942 | #b3e0f0 | California laurel |
943 | #6a48de | Giant chinkapin |
961 | #c3ab6e | Pacific madrone |
962 | #f5f169 | Other hardwoods |
971 | #f3c66f | Deciduous oak woodland |
972 | #4ecb89 | Evergreen oak woodland |
973 | #60b0c2 | Mesquite woodland |
974 | #76e45f | Cercocarpus (mountain brush) woodland |
975 | #b3c5ce | Intermountain maple woodland |
976 | #ee73af | Miscellaneous woodland hardwoods |
982 | #9473b4 | Mangrove |
983 | #80d9a8 | Palms |
995 | #e67774 | Other exotic hardwoods |
FORTYPCD Class Table
Value | Color | Description |
---|---|---|
101 | #6e26ec | Jack pine |
102 | #c765ec | Red pine |
103 | #efdbcc | Eastern white pine |
104 | #a8a9f2 | Eastern white pine / eastern hemlock |
105 | #d0ce83 | Eastern hemlock |
121 | #47d0b6 | Balsam fir |
122 | #9d86a6 | White spruce |
123 | #a5f77a | Red spruce |
124 | #dcf4d9 | Red spruce / balsam fir |
125 | #64e1f7 | Black spruce |
126 | #afa9b0 | Tamarack |
127 | #f2c531 | Northern white-cedar |
141 | #84d7eb | Longleaf pine |
142 | #ef4677 | Slash pine |
161 | #97f2ad | Loblolly pine |
162 | #d45549 | Shortleaf pine |
163 | #63f3ac | Virginia pine |
164 | #f58de4 | Sand pine |
165 | #e9c991 | Table Mountain pine |
166 | #ddbef2 | Pond pine |
167 | #bba847 | Pitch pine |
171 | #95eacd | Eastern redcedar |
182 | #a6827b | Rocky Mountain juniper |
184 | #bca28a | Juniper woodland |
185 | #cff3f4 | Pinyon / juniper woodland |
201 | #c1ded5 | Douglas-fir |
202 | #948ee9 | Port-Orford-cedar |
221 | #d0ef5b | Ponderosa pine |
222 | #e29af0 | Incense-cedar |
224 | #c34bc3 | Sugar pine |
225 | #e6acb8 | Jeffrey pine |
226 | #ea3b34 | Coulter pine |
241 | #724353 | Western white pine |
261 | #f2c7a0 | White fir |
262 | #6ab27f | Red fir |
263 | #f1f3d3 | Noble fir |
264 | #ea5aba | Pacific silver fir |
265 | #edc7e1 | Engelmann spruce |
266 | #4965e2 | Engelmann spruce / subalpine fir |
267 | #a0f4c4 | Grand fir |
268 | #5697de | Subalpine fir |
269 | #5defc4 | Blue spruce |
270 | #e8f384 | Mountain hemlock |
271 | #cc63bd | Alaska-yellow-cedar |
281 | #e16f3d | Lodgepole pine |
301 | #f5da68 | Western hemlock |
304 | #a63bcf | Western redcedar |
305 | #51d0dd | Sitka spruce |
321 | #6bc5b6 | Western larch |
341 | #f2f4a5 | Redwood |
361 | #576abe | Knobcone pine |
362 | #b56f7c | Southwestern white pine |
365 | #dca5ca | Foxtail pine / bristlecone pine |
366 | #67eff4 | Limber pine |
367 | #ca5483 | Whitebark pine |
368 | #a8bf86 | Miscellaneous western softwoods |
369 | #aff6e9 | Western juniper |
371 | #a53394 | California mixed conifer |
381 | #e9e2eb | Scotch pine |
383 | #d0cfad | Other exotic softwoods |
384 | #eee1b3 | Norway spruce |
385 | #e4db79 | Introduced larch |
401 | #ec42f6 | Eastern white pine / northern red oak / white ash |
402 | #7e9f81 | Eastern redcedar / hardwood |
403 | #4a7196 | Longleaf pine / oak |
404 | #5cd76e | Shortleaf pine / oak |
405 | #37999a | Virginia pine / southern red oak |
406 | #ed54dd | Loblolly pine / hardwood |
407 | #6792f0 | Slash pine / hardwood |
409 | #82eb3e | Other pine / hardwood |
501 | #b8db98 | Post oak / blackjack oak |
502 | #bccc4b | Chestnut oak |
503 | #f22ab1 | White oak / red oak / hickory |
504 | #f6e095 | White oak |
505 | #77989d | Northern red oak |
506 | #718640 | Yellow-poplar / white oak / northern red oak |
507 | #9d4f8d | Sassafras / persimmon |
508 | #c376e4 | Sweetgum / yellow-poplar |
509 | #7cb133 | Bur oak |
510 | #5fa7cc | Scarlet oak |
511 | #9ae6e8 | Yellow-poplar |
512 | #def3b1 | Black walnut |
513 | #b88bf2 | Black locust |
514 | #a5f031 | Southern scrub oak |
515 | #eeafa3 | Chestnut oak / black oak / scarlet oak |
516 | #9bd763 | Cherry / white ash / yellow-poplar |
517 | #b838ee | Elm / ash / black locust |
519 | #e88fbb | Red maple / oak |
520 | #cce5b9 | Mixed upland hardwoods |
601 | #ed8a9c | Swamp chestnut oak / cherrybark oak |
602 | #c8ed2d | Sweetgum / Nuttall oak / willow oak |
605 | #f0bd53 | Overcup oak / water hickory |
606 | #60dad1 | Atlantic white-cedar |
607 | #c790c1 | Baldcypress / water tupelo |
608 | #54c7ef | Sweetbay / swamp tupelo / red maple |
609 | #8e6a31 | Baldcypress / pondcypress |
701 | #cecceb | Black ash / American elm / red maple |
702 | #b1bef2 | River birch / sycamore |
703 | #f077ef | Cottonwood |
704 | #969aca | Willow |
705 | #c4ec84 | Sycamore / pecan / American elm |
706 | #efadec | Sugarberry / hackberry / elm / green ash |
707 | #da23cf | Silver maple / American elm |
708 | #e4c3c0 | Red maple / lowland |
709 | #bf90e1 | Cottonwood / willow |
722 | #52f3eb | Oregon ash |
801 | #a2c9eb | Sugar maple / beech / yellow birch |
802 | #3ff451 | Black cherry |
805 | #6ab7f2 | Hard maple / basswood |
809 | #b3714c | Red maple / upland |
901 | #d28f25 | Aspen |
902 | #f59550 | Paper birch |
903 | #dd82c7 | Gray birch |
904 | #c5f2a0 | Balsam poplar |
905 | #e3f2e7 | Pin cherry |
911 | #b2c2b1 | Red alder |
912 | #4ff389 | Bigleaf maple |
921 | #8772e8 | Gray pine |
922 | #bb24a1 | California black oak |
923 | #c7f7cd | Oregon white oak |
924 | #8fc3c6 | Blue oak |
931 | #f13896 | Coast live oak |
933 | #efe92f | Canyon live oak |
934 | #6c48ae | Interior live oak |
935 | #b3e8cd | California white oak (valley oak) |
941 | #e8a882 | Tanoak |
942 | #b3e0f0 | California laurel |
943 | #6a48de | Giant chinkapin |
961 | #c3ab6e | Pacific madrone |
962 | #f5f169 | Other hardwoods |
971 | #f3c66f | Deciduous oak woodland |
972 | #4ecb89 | Evergreen oak woodland |
973 | #60b0c2 | Mesquite woodland |
974 | #76e45f | Cercocarpus (mountain brush) woodland |
975 | #b3c5ce | Intermountain maple woodland |
976 | #ee73af | Miscellaneous woodland hardwoods |
982 | #9473b4 | Mangrove |
983 | #80d9a8 | Palms |
991 | #e6a25e | Paulownia |
992 | #f8f3b7 | Melaleuca |
995 | #e67774 | Other exotic hardwoods |
999 | #d5cc36 | Nonstocked |
STDSZCD Class Table
Value | Color | Description |
---|---|---|
1 | #38a800 | Large diameter - Stands with an all live stocking value of at least 10 (base 100); with more than 50 percent of the stocking in medium and large diameter trees; and with the stocking of large diameter trees equal to or greater than the stocking of medium diameter trees. |
2 | #ffff00 | Medium diameter - Stands with an all live stocking value of at least 10 (base 100); with more than 50 percent of the stocking in medium and large diameter trees; and with the stocking of large diameter trees less than the stocking of medium diameter trees. |
3 | #feba12 | Small diameter - Stands with an all live stocking value of at least 10 (base 100) on which at least 50 percent of the stocking is in small diameter trees. |
5 | #c62363 | Nonstocked - Forest land with all live stocking value less than 10. |
Image Properties
Image Properties
Name | Type | Description |
---|---|---|
year | INT | Year of the product. |
landfire_ver | STRING | Landfire version used as reference and target data for imputation. |
Terms of Use
Terms of Use
The USDA Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liability or responsibility for the accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphics are not legal documents and are not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may be in place on either public or private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. The user is responsible to verify the limitations of the geospatial data and to use the data accordingly.
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the appropriate citation.
Citations
Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Shaw, John D. 2021. TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2021-0074.
Explore with Earth Engine
Code Editor (JavaScript)
// Load the full dataset var dataset = ee.ImageCollection('USFS/GTAC/TreeMap/v2016'); // Get the 2016 image var tm2016 = dataset.filterDate('2016', '2017').first(); // 'Official' TreeMap 2016 palettes var bamako = ['00404d', '134b42', '265737', '3a652a', '52741c', '71870b', '969206', 'c5ae32', 'e7cd68', 'ffe599']; var bamako_r = JSON.parse(JSON.stringify(bamako)).reverse(); var lajolla = ['ffffcc','fbec9a','f4cc68','eca855','e48751','d2624d','a54742','73382f','422818','1a1a01']; var lajolla_r = JSON.parse(JSON.stringify(lajolla)).reverse(); var imola = ['1a33b3','2446a9','2e599f','396b94','497b85','60927b','7bae74','98cb6d','c4ea67','ffff66']; var imola_r = JSON.parse(JSON.stringify(imola)).reverse(); // Select all 22 attributes var alstk = tm2016.select('ALSTK'); var balive = tm2016.select('BALIVE'); var canopypct = tm2016.select('CANOPYPCT'); var carbon_d = tm2016.select('CARBON_D'); var carbon_dwn = tm2016.select('CARBON_DWN'); var carbon_l = tm2016.select('CARBON_L'); var drybio_d = tm2016.select('DRYBIO_D'); var drybio_l = tm2016.select('DRYBIO_L'); var fldszcd = tm2016.select('FLDSZCD'); var fldtypcd = tm2016.select('FLDTYPCD'); var fortypcd = tm2016.select('FORTYPCD'); var gsstk = tm2016.select('GSSTK'); var qmd_rmrs = tm2016.select('QMD_RMRS'); var sdipct_rmrs = tm2016.select('SDIPCT_RMRS'); var standht = tm2016.select('STANDHT'); var stdszcd = tm2016.select('STDSZCD'); var tpa_dead = tm2016.select('TPA_DEAD'); var tpa_live = tm2016.select('TPA_LIVE'); var value = tm2016.select('Value'); var volbfnet_l = tm2016.select('VOLBFNET_L'); var volcfnet_d = tm2016.select('VOLCFNET_D'); var volcfnet_l = tm2016.select('VOLCFNET_L'); // Add all attributes to the map with the 'official' visualization Map.addLayer(alstk, {'min': 0, 'max': 100, 'palette': bamako_r}, 'ALSTK: All-Live-Tree Stocking (percent)', false); Map.addLayer(balive, {'min': 24, 'max': 217, 'palette': bamako_r}, 'BALIVE: Live Tree Basal Area (ft²)', false); Map.addLayer(canopypct, {'min': 0, 'max': 100, 'palette': bamako_r}, 'CANOPYPCT: Live Canopy Cover (percent)', false); Map.addLayer(carbon_d, {'min': 0, 'max': 9, 'palette': lajolla}, 'CARBON_D: Carbon, Standing Dead (tons/acre)', false); Map.addLayer(carbon_dwn, {'min': 0, 'max': 7, 'palette': lajolla}, 'CARBON_DWN: Carbon, Down Dead (tons/acre)', false); Map.addLayer(carbon_l, {'min': 2, 'max': 59, 'palette': lajolla_r}, 'CARBON_L: Carbon, Live Above Ground (tons/acre)', false); Map.addLayer(drybio_d, {'min': 0, 'max': 10, 'palette': lajolla}, 'DRYBIO_D: Dry Standing Dead Tree Biomass, Above Ground (tons/acre)', false); Map.addLayer(drybio_l, {'min': 4, 'max': 118, 'palette': lajolla_r}, 'DRYBIO_L: Dry Live Tree Biomass, Above Ground (tons/acre)', false); Map.addLayer(fldszcd, {}, 'FLDSZCD: Field Stand-Size Class Code', false); Map.addLayer(fldtypcd, {}, 'FLDTYPCD: Field Forest Type Code'); Map.addLayer(fortypcd, {}, 'FORTYPCD: Algorithm Forest Type Code', false); Map.addLayer(gsstk, {'min': 0, 'max': 100, 'palette': bamako_r}, 'GSSTK: Growing-Stock Stocking (percent)', false); Map.addLayer(qmd_rmrs, {'min': 2, 'max': 25, 'palette': bamako_r}, 'QMD_RMRS: Stand Quadratic Mean Diameter (in)', false); Map.addLayer(sdipct_rmrs, {'min': 6, 'max': 99, 'palette': bamako_r}, 'SDIPCT_RMRS: Stand Density Index (percent of maximum)', false); Map.addLayer(standht, {'min': 23, 'max': 194, 'palette': bamako_r}, 'STANDHT: Height of Dominant Trees (ft)', false); Map.addLayer(stdszcd, {}, 'STDSZCD: Algorithm Stand-Size Class Code', false); Map.addLayer(tpa_dead, {'min': 38, 'max': 126, 'palette': bamako}, 'TPA_DEAD: Dead Trees Per Acre', false); Map.addLayer(tpa_live, {'min': 252, 'max': 1666, 'palette': bamako_r}, 'TPA_LIVE: Live Trees Per Acre', false); Map.addLayer(value.randomVisualizer(), {}, 'Value: TreeMap ID', false); Map.addLayer(volbfnet_l, {'min': 441, 'max': 36522, 'palette': imola_r}, 'VOLBFNET_L: Volume, Live (sawlog-board-ft/acre)', false); Map.addLayer(volcfnet_d, {'min': 5, 'max': 1326, 'palette': imola_r}, 'VOLCFNET_D: Volume, Standing Dead (ft³/acre)', false); Map.addLayer(volcfnet_l, {'min': 137, 'max': 5790, 'palette': imola_r}, 'VOLCFNET_L: Volume, Live (ft³/acre)', false); // Set basemap Map.setOptions('TERRAIN'); // Center map on CONUS Map.setCenter(-95.712891, 38, 5);