AI-generated Key Takeaways
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The OpenLandMap dataset provides global predictions of USDA soil great groups at a 250-meter resolution, excluding Antarctica.
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This dataset, available from 1950-01-01 to 2018-01-01, utilizes machine learning and a global soil profile compilation for its predictions.
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Users can access the data through Google Earth Engine using the provided code snippet (
ee.Image("OpenLandMap/SOL/SOL_GRTGROUP_USDA-SOILTAX_C/v01")) or visualize it via OpenGeoHub. -
A comprehensive class table offers detailed information on each soil great group, including values, colors, and descriptions, facilitating interpretation and analysis.
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Support for technical issues and general questions is available through dedicated links to GitLab and Disqus forums, respectively.
- Dataset Availability
- 1950-01-01T00:00:00Z–2018-01-01T00:00:00Z
- Dataset Provider
- EnvirometriX Ltd
- Tags
Description
Predicted USDA soil great group probabilities at 250m.
Distribution of the USDA soil great groups based on machine learning predictions from global compilation of soil profiles. To learn more about soil great groups please refer to the Illustrated Guide to Soil Taxonomy - NRCS - USDA.
- Processing steps are described in detail here
- Antarctica is not included.
To access and visualize maps outside of Earth Engine, use this page.
If you discover a bug, artifact or inconsistency in the LandGIS maps or if you have a question please use the following channels:
Bands
Pixel Size
250 meters
Bands
| Name | Pixel Size | Description |
|---|---|---|
grtgroup |
meters | USDA soil taxonomy great groups |
grtgroup Class Table
| Value | Color | Description |
|---|---|---|
| 0 | #ffffff | NODATA |
| 1 | #adff2d | Albaqualfs |
| 2 | #adff22 | Cryaqualfs |
| 4 | #a5ff2f | Durixeralfs |
| 6 | #87ff37 | Endoaqualfs |
| 7 | #baf019 | Epiaqualfs |
| 9 | #87ff19 | Fragiaqualfs |
| 10 | #96f03d | Fragiudalfs |
| 11 | #a3f52f | Fragixeralfs |
| 12 | #aff319 | Fraglossudalfs |
| 13 | #91ff37 | Glossaqualfs |
| 14 | #9cf319 | Glossocryalfs |
| 15 | #9bff37 | Glossudalfs |
| 16 | #91ff19 | Haplocryalfs |
| 17 | #71ff37 | Haploxeralfs |
| 18 | #86ff19 | Hapludalfs |
| 19 | #a9d42d | Haplustalfs |
| 25 | #aff519 | Natraqualfs |
| 26 | #9bff19 | Natrixeralfs |
| 27 | #9af024 | Natrudalfs |
| 28 | #a5fd2f | Natrustalfs |
| 29 | #88ff37 | Palecryalfs |
| 30 | #afed19 | Paleudalfs |
| 31 | #71ff19 | Paleustalfs |
| 32 | #aff026 | Palexeralfs |
| 38 | #8cf537 | Rhodustalfs |
| 39 | #b7ff19 | Vermaqualfs |
| 41 | #7177c0 | Eutroboralfs |
| 42 | #9a85ec | Ochraqualfs |
| 43 | #f5f5e1 | Glossoboralfs |
| 44 | #52cf5a | Cryoboralfs |
| 45 | #e42777 | Natriboralfs |
| 46 | #4ef76d | Paleboralfs |
| 50 | #ff00fb | Cryaquands |
| 58 | #eb05eb | Fulvicryands |
| 59 | #fa04fa | Fulvudands |
| 61 | #fc04f5 | Haplocryands |
| 63 | #f50df0 | Haploxerands |
| 64 | #f118f1 | Hapludands |
| 74 | #fa0cfa | Udivitrands |
| 75 | #fc05e1 | Ustivitrands |
| 76 | #f100d5 | Vitraquands |
| 77 | #eb09e6 | Vitricryands |
| 80 | #fa22fa | Vitrixerands |
| 82 | #ffdab9 | Aquicambids |
| 83 | #f5d2bb | Aquisalids |
| 85 | #e8c9b8 | Argidurids |
| 86 | #ffddc4 | Argigypsids |
| 87 | #e7cbc0 | Calciargids |
| 89 | #ffd2c3 | Calcigypsids |
| 90 | #f5d6bb | Gypsiargids |
| 92 | #d5d3b9 | Haplargids |
| 93 | #e8d4b8 | Haplocalcids |
| 94 | #e7cdc0 | Haplocambids |
| 96 | #f3eac8 | Haplodurids |
| 97 | #a0c4ba | Haplogypsids |
| 98 | #ffd2b9 | Haplosalids |
| 99 | #f5dabb | Natrargids |
| 100 | #f5d5b9 | Natridurids |
| 101 | #e8ebb8 | Natrigypsids |
| 102 | #ffddc2 | Paleargids |
| 103 | #e7ffc0 | Petroargids |
| 104 | #f3e6c8 | Petrocalcids |
| 105 | #ffdab9 | Petrocambids |
| 107 | #f5cdb9 | Petrogypsids |
| 110 | #a91d30 | Calciorthids |
| 111 | #796578 | Camborthids |
| 112 | #d8ff6e | Paleorthids |
| 113 | #177548 | Durorthids |
| 114 | #43efd6 | Durargids |
| 115 | #8496a9 | Gypsiorthids |
| 116 | #296819 | Nadurargids |
| 118 | #73ffd4 | Cryaquents |
| 119 | #6fffc8 | Cryofluvents |
| 120 | #75fbc9 | Cryopsamments |
| 121 | #86f5d1 | Cryorthents |
| 122 | #82ffd2 | Endoaquents |
| 123 | #88eec8 | Epiaquents |
| 124 | #80ffd4 | Fluvaquents |
| 126 | #6bffc9 | Frasiwassents |
| 131 | #88eec8 | Hydraquents |
| 133 | #7fffc8 | Psammaquents |
| 134 | #81ffd2 | Psammowassents |
| 135 | #86f0d4 | Quartzipsamments |
| 136 | #67ffc8 | Sulfaquents |
| 137 | #88eec8 | Sulfiwassents |
| 138 | #7ffbcb | Torrifluvents |
| 139 | #87ffd2 | Torriorthents |
| 140 | #8af5ce | Torripsamments |
| 141 | #6bfad2 | Udifluvents |
| 142 | #78f0d4 | Udipsamments |
| 143 | #88eec8 | Udorthents |
| 144 | #7ffbd4 | Ustifluvents |
| 145 | #73f5cd | Ustipsamments |
| 146 | #88c8d2 | Ustorthents |
| 147 | #91f0cd | Xerofluvents |
| 148 | #73cdd2 | Xeropsamments |
| 149 | #88eec8 | Xerorthents |
| 153 | #fb849b | Udarents |
| 154 | #dd4479 | Torriarents |
| 155 | #61388b | Xerarents |
| 179 | #a52a30 | Cryofibrists |
| 180 | #722328 | Cryofolists |
| 181 | #d81419 | Cryohemists |
| 182 | #a42828 | Cryosaprists |
| 183 | #82f5cd | Frasiwassists |
| 184 | #a54c2e | Haplofibrists |
| 185 | #c11919 | Haplohemists |
| 186 | #b91419 | Haplosaprists |
| 189 | #21b199 | Sphagnofibrists |
| 190 | #702028 | Sulfihemists |
| 191 | #b41919 | Sulfisaprists |
| 196 | #b22328 | Udifolists |
| 201 | #a2c7eb | Borosaprists |
| 202 | #36ba79 | Medisaprists |
| 203 | #806797 | Borohemists |
| 206 | #cb5b5f | Calcicryepts |
| 207 | #cd5c5c | Calciustepts |
| 208 | #d94335 | Calcixerepts |
| 209 | #d35740 | Cryaquepts |
| 210 | #e05a5d | Durixerepts |
| 212 | #cf5b5c | Durustepts |
| 213 | #ca5964 | Dystrocryepts |
| 215 | #ca5d5f | Dystroxerepts |
| 216 | #cd5e5a | Dystrudepts |
| 217 | #ca5969 | Dystrustepts |
| 218 | #d95a35 | Endoaquepts |
| 219 | #d36240 | Epiaquepts |
| 220 | #e05c43 | Eutrudepts |
| 221 | #d64755 | Fragiaquepts |
| 222 | #cf595c | Fragiudepts |
| 225 | #ff5f5f | Halaquepts |
| 226 | #cd6058 | Haplocryepts |
| 228 | #d95f35 | Haploxerepts |
| 229 | #d35140 | Haplustepts |
| 230 | #d65a55 | Humaquepts |
| 231 | #e05c59 | Humicryepts |
| 233 | #cf525e | Humixerepts |
| 234 | #c65978 | Humudepts |
| 235 | #f5615f | Humustepts |
| 245 | #826f9a | Ustochrepts |
| 246 | #cff41a | Eutrochrepts |
| 247 | #4a6f31 | Dystrochrepts |
| 248 | #a96989 | Eutrocryepts |
| 249 | #e16438 | Haplaquepts |
| 250 | #24f640 | Xerochrepts |
| 251 | #88c1f9 | Cryochrepts |
| 252 | #f5d25c | Fragiochrepts |
| 253 | #d74322 | Haplumbrepts |
| 254 | #7f939e | Cryumbrepts |
| 255 | #41a545 | Dystropepts |
| 256 | #8f8340 | Vitrandepts |
| 268 | #09fe03 | Argialbolls |
| 269 | #0aff00 | Argiaquolls |
| 270 | #0ff30f | Argicryolls |
| 271 | #02f00a | Argiudolls |
| 272 | #0fc903 | Argiustolls |
| 273 | #17f000 | Argixerolls |
| 274 | #0cff00 | Calciaquolls |
| 275 | #0ac814 | Calcicryolls |
| 276 | #0cfe00 | Calciudolls |
| 277 | #0aff0a | Calciustolls |
| 278 | #03ff05 | Calcixerolls |
| 279 | #1cf31c | Cryaquolls |
| 280 | #24f000 | Cryrendolls |
| 283 | #00ff0c | Durixerolls |
| 284 | #14c814 | Durustolls |
| 285 | #00fe4c | Endoaquolls |
| 286 | #14ff96 | Epiaquolls |
| 287 | #44d205 | Haplocryolls |
| 289 | #05f305 | Haploxerolls |
| 290 | #62f00a | Hapludolls |
| 291 | #0fcd03 | Haplustolls |
| 292 | #00d20f | Haprendolls |
| 294 | #1add11 | Natraquolls |
| 296 | #09ff0c | Natrixerolls |
| 297 | #03ff05 | Natrudolls |
| 298 | #05e700 | Natrustolls |
| 299 | #02f00a | Palecryolls |
| 300 | #0fea03 | Paleudolls |
| 301 | #00f000 | Paleustolls |
| 302 | #0ccb0c | Palexerolls |
| 303 | #14dd14 | Vermudolls |
| 306 | #6a685d | Haploborolls |
| 307 | #fae6b9 | Argiborolls |
| 308 | #769a34 | Haplaquolls |
| 309 | #6ff2df | Cryoborolls |
| 310 | #ca7fc6 | Natriborolls |
| 311 | #d8228f | Calciborolls |
| 312 | #c01bf0 | Paleborolls |
| 342 | #d2bad3 | Alaquods |
| 343 | #d8c3cb | Alorthods |
| 345 | #d4c6d4 | Duraquods |
| 348 | #d5bed5 | Durorthods |
| 349 | #ddb9dd | Endoaquods |
| 350 | #d8d2d8 | Epiaquods |
| 351 | #d4c9d4 | Fragiaquods |
| 353 | #d2bad5 | Fragiorthods |
| 354 | #d5bad5 | Haplocryods |
| 356 | #d5b2d5 | Haplohumods |
| 357 | #d8c8d2 | Haplorthods |
| 358 | #d4cbd4 | Humicryods |
| 367 | #552638 | Haplaquods |
| 368 | #2571eb | Cryorthods |
| 370 | #ffa514 | Albaquults |
| 371 | #f3a502 | Endoaquults |
| 372 | #fb7b00 | Epiaquults |
| 373 | #f0b405 | Fragiaquults |
| 374 | #f7a80f | Fragiudults |
| 375 | #fb9113 | Haplohumults |
| 376 | #ffa519 | Haploxerults |
| 377 | #f3a702 | Hapludults |
| 378 | #fbba07 | Haplustults |
| 381 | #f7970f | Kandiudults |
| 385 | #f3a702 | Kanhapludults |
| 387 | #fb5a00 | Paleaquults |
| 388 | #f0c005 | Palehumults |
| 389 | #f7810f | Paleudults |
| 390 | #ff9c00 | Paleustults |
| 391 | #f3b002 | Palexerults |
| 396 | #f0b005 | Rhodudults |
| 399 | #f7980f | Umbraquults |
| 401 | #4d7cfc | Ochraquults |
| 403 | #ffff00 | Calciaquerts |
| 405 | #fafa05 | Calciusterts |
| 406 | #ebeb22 | Calcixererts |
| 409 | #ffff14 | Dystraquerts |
| 410 | #f1f10a | Dystruderts |
| 412 | #fafa05 | Endoaquerts |
| 413 | #ebeb1e | Epiaquerts |
| 414 | #f5eb0c | Gypsitorrerts |
| 415 | #eef506 | Gypsiusterts |
| 417 | #f1f129 | Haplotorrerts |
| 418 | #fafa05 | Haploxererts |
| 419 | #ebeb0c | Hapluderts |
| 420 | #f5d202 | Haplusterts |
| 422 | #ffd700 | Natraquerts |
| 424 | #f1f12b | Salitorrerts |
| 429 | #a91fac | Chromusterts |
| 430 | #2da468 | Pellusterts |
| 431 | #9a8b71 | Chromoxererts |
| 432 | #76b989 | Pelluderts |
| 433 | #713959 | Torrerts |
Terms of Use
Terms of Use
Citations
Tomislav Hengl, & Travis Nauman. (2018). Predicted USDA soil great groups at 250 m (probabilities) (Version v01) [Data set]. Zenodo. 10.5281/zenodo.1476844
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.Image('OpenLandMap/SOL/SOL_GRTGROUP_USDA-SOILTAX_C/v01'); var visualization = { bands: ['grtgroup'], min: 0, max: 433, palette: [ 'ffffff', 'adff2d', 'adff22', 'a5ff2f', '87ff37', 'baf019', '87ff19', '96f03d', 'a3f52f', 'aff319', '91ff37', '9cf319', '9bff37', '91ff19', '71ff37', '86ff19', 'a9d42d', 'aff519', '9bff19', '9af024', 'a5fd2f', '88ff37', 'afed19', '71ff19', 'aff026', '8cf537', 'b7ff19', '7177c0', '9a85ec', 'f5f5e1', '52cf5a', 'e42777', '4ef76d', 'ff00fb', 'eb05eb', 'fa04fa', 'fc04f5', 'f50df0', 'f118f1', 'fa0cfa', 'fc05e1', 'f100d5', 'eb09e6', 'fa22fa', 'ffdab9', 'f5d2bb', 'e8c9b8', 'ffddc4', 'e7cbc0', 'ffd2c3', 'f5d6bb', 'd5d3b9', 'e8d4b8', 'e7cdc0', 'f3eac8', 'a0c4ba', 'ffd2b9', 'f5dabb', 'f5d5b9', 'e8ebb8', 'ffddc2', 'e7ffc0', 'f3e6c8', 'ffdab9', 'f5cdb9', 'a91d30', '796578', 'd8ff6e', '177548', '43efd6', '8496a9', '296819', '73ffd4', '6fffc8', '75fbc9', '86f5d1', '82ffd2', '88eec8', '80ffd4', '6bffc9', '88eec8', '7fffc8', '81ffd2', '86f0d4', '67ffc8', '88eec8', '7ffbcb', '87ffd2', '8af5ce', '6bfad2', '78f0d4', '88eec8', '7ffbd4', '73f5cd', '88c8d2', '91f0cd', '73cdd2', '88eec8', 'fb849b', 'dd4479', '61388b', 'a52a30', '722328', 'd81419', 'a42828', '82f5cd', 'a54c2e', 'c11919', 'b91419', '21b199', '702028', 'b41919', 'b22328', 'a2c7eb', '36ba79', '806797', 'cb5b5f', 'cd5c5c', 'd94335', 'd35740', 'e05a5d', 'cf5b5c', 'ca5964', 'ca5d5f', 'cd5e5a', 'ca5969', 'd95a35', 'd36240', 'e05c43', 'd64755', 'cf595c', 'ff5f5f', 'cd6058', 'd95f35', 'd35140', 'd65a55', 'e05c59', 'cf525e', 'c65978', 'f5615f', '826f9a', 'cff41a', '4a6f31', 'a96989', 'e16438', '24f640', '88c1f9', 'f5d25c', 'd74322', '7f939e', '41a545', '8f8340', '09fe03', '0aff00', '0ff30f', '02f00a', '0fc903', '17f000', '0cff00', '0ac814', '0cfe00', '0aff0a', '03ff05', '1cf31c', '24f000', '00ff0c', '14c814', '00fe4c', '14ff96', '44d205', '05f305', '62f00a', '0fcd03', '00d20f', '1add11', '09ff0c', '03ff05', '05e700', '02f00a', '0fea03', '00f000', '0ccb0c', '14dd14', '6a685d', 'fae6b9', '769a34', '6ff2df', 'ca7fc6', 'd8228f', 'c01bf0', 'd2bad3', 'd8c3cb', 'd4c6d4', 'd5bed5', 'ddb9dd', 'd8d2d8', 'd4c9d4', 'd2bad5', 'd5bad5', 'd5b2d5', 'd8c8d2', 'd4cbd4', '552638', '2571eb', 'ffa514', 'f3a502', 'fb7b00', 'f0b405', 'f7a80f', 'fb9113', 'ffa519', 'f3a702', 'fbba07', 'f7970f', 'f3a702', 'fb5a00', 'f0c005', 'f7810f', 'ff9c00', 'f3b002', 'f0b005', 'f7980f', '4d7cfc', 'ffff00', 'fafa05', 'ebeb22', 'ffff14', 'f1f10a', 'fafa05', 'ebeb1e', 'f5eb0c', 'eef506', 'f1f129', 'fafa05', 'ebeb0c', 'f5d202', 'ffd700', 'f1f12b', 'a91fac', '2da468', '9a8b71', '76b989', '713959', ] }; Map.centerObject(dataset); Map.addLayer(dataset, visualization, 'USDA soil taxonomy great groups');