全球土壤剖面汇编数据

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此星光明 发表于 2023/08/11 19:28:54 2023/08/11
【摘要】 ​OpenLandMap USDA Soil Taxonomy Great Groups 简介与Notebook示例¶该数据集为USDA根据全球土壤剖面汇编数据经机器学习方法进行预测生成的土壤分类数据产品。美国农业部土壤大类的分布,基于全球土壤剖面汇编(>350,000 个训练点)的机器学习预测。要了解有关土壤大类的更多信息,请参阅《土壤分类图解指南》(Illustrated Guide t...

OpenLandMap USDA Soil Taxonomy Great Groups 简介与Notebook示例

该数据集为USDA根据全球土壤剖面汇编数据经机器学习方法进行预测生成的土壤分类数据产品。

美国农业部土壤大类的分布,基于全球土壤剖面汇编(>350,000 个训练点)的机器学习预测。要了解有关土壤大类的更多信息,请参阅《土壤分类图解指南》(Illustrated Guide to Soil Taxonomy)- NRCS - USDA。此处详细介绍了处理步骤。不包括南极洲。https://www.cbedai.net/xg

要访问和可视化地图,请使用OpenLandMap.org

所有预测的备份副本(>65GB)可从以下网址下载: http://gofile.me/6J25n/mQ3cHOOMr

如果您发现地图中的错误、人工痕迹或不一致之处,或者您有任何疑问,请使用以下渠道:

有关代码的技术问题和疑问: https://gitlab.com/openlandmap/global-layers/issues
一般问题和评论: https://disqus.com/home/forums/landgis/
所有文件均使用 GDAL 中的 "COMPRESS=DEFLATE "创建选项进行内部压缩。文件命名约定:

sol = 主题:土壤、
grtgroup = 变量:USDA great group、
usda.argiustolls = 确定方法:USDA 土壤分类等级 Argiustolls、
p = 概率、
250m = 空间分辨率/区块支持:250 m,
s0..0cm = 垂直参考:土壤表面、
1950..2017 = 时间基准:1950-2017 年、
v0.2 = 版本号:0.2、

分辨率

250

波段

名称 描述
grtgroup USDA soil taxonomy great group

grtgroup Class Table

数值 类型
0 NODATA
1 Albaqualfs
2 Cryaqualfs
4 Durixeralfs
6 Endoaqualfs
7 Epiaqualfs
9 Fragiaqualfs
10 Fragiudalfs
11 Fragixeralfs
12 Fraglossudalfs
13 Glossaqualfs
14 Glossocryalfs
15 Glossudalfs
16 Haplocryalfs
17 Haploxeralfs
18 Hapludalfs
19 Haplustalfs
25 Natraqualfs
26 Natrixeralfs
27 Natrudalfs
28 Natrustalfs
29 Palecryalfs
30 Paleudalfs
31 Paleustalfs
32 Palexeralfs
38 Rhodustalfs
39 Vermaqualfs
41 Eutroboralfs
42 Ochraqualfs
43 Glossoboralfs
44 Cryoboralfs
45 Natriboralfs
46 Paleboralfs
50 Cryaquands
58 Fulvicryands
59 Fulvudands
61 Haplocryands
63 Haploxerands
64 Hapludands
74 Udivitrands
75 Ustivitrands
76 Vitraquands
77 Vitricryands
80 Vitrixerands
82 Aquicambids
83 Aquisalids
85 Argidurids
86 Argigypsids
87 Calciargids
89 Calcigypsids
90 Gypsiargids
92 Haplargids
93 Haplocalcids
94 Haplocambids
96 Haplodurids
97 Haplogypsids
98 Haplosalids
99 Natrargids
100 Natridurids
101 Natrigypsids
102 Paleargids
103 Petroargids
104 Petrocalcids
105 Petrocambids
107 Petrogypsids
110 Calciorthids
111 Camborthids
112 Paleorthids
113 Durorthids
114 Durargids
115 Gypsiorthids
116 Nadurargids
118 Cryaquents
119 Cryofluvents
120 Cryopsamments
121 Cryorthents
122 Endoaquents
123 Epiaquents
124 Fluvaquents
126 Frasiwassents
131 Hydraquents
133 Psammaquents
134 Psammowassents
135 Quartzipsamments
136 Sulfaquents
137 Sulfiwassents
138 Torrifluvents
139 Torriorthents
140 Torripsamments
141 Udifluvents
142 Udipsamments
143 Udorthents
144 Ustifluvents
145 Ustipsamments
146 Ustorthents
147 Xerofluvents
148 Xeropsamments
149 Xerorthents
153 Udarents
154 Torriarents
155 Xerarents
179 Cryofibrists
180 Cryofolists
181 Cryohemists
182 Cryosaprists
183 Frasiwassists
184 Haplofibrists
185 Haplohemists
186 Haplosaprists
189 Sphagnofibrists
190 Sulfihemists
191 Sulfisaprists
196 Udifolists
201 Borosaprists
202 Medisaprists
203 Borohemists
206 Calcicryepts
207 Calciustepts
208 Calcixerepts
209 Cryaquepts
210 Durixerepts
212 Durustepts
213 Dystrocryepts
215 Dystroxerepts
216 Dystrudepts
217 Dystrustepts
218 Endoaquepts
219 Epiaquepts
220 Eutrudepts
221 Fragiaquepts
222 Fragiudepts
225 Halaquepts
226 Haplocryepts
228 Haploxerepts
229 Haplustepts
230 Humaquepts
231 Humicryepts
233 Humixerepts
234 Humudepts
235 Humustepts
245 Ustochrepts
246 Eutrochrepts
247 Dystrochrepts
248 Eutrocryepts
249 Haplaquepts
250 Xerochrepts
251 Cryochrepts
252 Fragiochrepts
253 Haplumbrepts
254 Cryumbrepts
255 Dystropepts
256 Vitrandepts
268 Argialbolls
269 Argiaquolls
270 Argicryolls
271 Argiudolls
272 Argiustolls
273 Argixerolls
274 Calciaquolls
275 Calcicryolls
276 Calciudolls
277 Calciustolls
278 Calcixerolls
279 Cryaquolls
280 Cryrendolls
283 Durixerolls
284 Durustolls
285 Endoaquolls
286 Epiaquolls
287 Haplocryolls
289 Haploxerolls
290 Hapludolls
291 Haplustolls
292 Haprendolls
294 Natraquolls
296 Natrixerolls
297 Natrudolls
298 Natrustolls
299 Palecryolls
300 Paleudolls
301 Paleustolls
302 Palexerolls
303 Vermudolls
306 Haploborolls
307 Argiborolls
308 Haplaquolls
309 Cryoborolls
310 Natriborolls
311 Calciborolls
312 Paleborolls
342 Alaquods
343 Alorthods
345 Duraquods
348 Durorthods
349 Endoaquods
350 Epiaquods
351 Fragiaquods
353 Fragiorthods
354 Haplocryods
356 Haplohumods
357 Haplorthods
358 Humicryods
367 Haplaquods
368 Cryorthods
370 Albaquults
371 Endoaquults
372 Epiaquults
373 Fragiaquults
374 Fragiudults
375 Haplohumults
376 Haploxerults
377 Hapludults
378 Haplustults
381 Kandiudults
385 Kanhapludults
387 Paleaquults
388 Palehumults
389 Paleudults
390 Paleustults
391 Palexerults
396 Rhodudults
399 Umbraquults
401 Ochraquults
403 Calciaquerts
405 Calciusterts
406 Calcixererts
409 Dystraquerts
410 Dystruderts
412 Endoaquerts
413 Epiaquerts
414 Gypsitorrerts
415 Gypsiusterts
417 Haplotorrerts
418 Haploxererts
419 Hapluderts
420 Haplusterts
422 Natraquerts
424 Salitorrerts
429 Chromusterts
430 Pellusterts
431 Chromoxererts
432 Pelluderts
433 Torrerts

 此数据集属于公开数据,有关此数据产品正确引用的更多详细信息,请参阅 EnvirometriX Ltd。 引用参考: Tomislav Hengl, & Travis Nauman. (2018). Predicted USDA soil great groups at 250 m (probabilities) (Version v01)。【更多信息】https://zenodo.org/record/3528062#.ZDf0ruxBzUI

代码:

import aie
aie.Authenticate()
aie.Initialize()


#指定检索数据集
dataset = aie.Image('OPENLANDMAP_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_V01')
                
imgs = dataset.select(['grtgroup']);

map = aie.Map(
    center=imgs.getCenter(),
    height=800,
    zoom=2
)
vis_params = {
    'bands': 'grtgroup',
    'min': 0.0,
    'max': 433.0,
    '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.addLayer(
    imgs,
    vis_params,
    'Soil taxonomy great groups',
    bounds=imgs.getBounds()
)
map

 

 

​https://www.cbedai.net/xg

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