This dataset contains land surface soil moisture products with SMAP time-expanded daily 0.25°×0.25°in Qinghai-Tibet Plateau Area. The dataset was produced based on the Random Forest method by utilizing passive microwave brightness temperature along with some auxiliary datasets. The temporal resolution of the product in 1980,1985,1990,1995 and 2000 is monthly, by using SMMR, SSM/I, and SSMIS brightness temperature from 19 GHz V/H and 37 GHz V channels. The temporal resolution of the product between June 20, 2002 and Dec 30, 2018 is daily, by utilizing AMSR-E and AMSR2 brightness temperature from 6.925 GHz V/H, 10.65 GHz V/H, and 36.5 GHz V channels. The auxiliary datasets participating in the Random Forest training include the IGBP land cover type, GTOPO30 DEM, and Lat/Lon information.
CHAI Linna, ZHU Zhongli, LIU Shaomin
Soil data are extremely important at both global and local scales, and in the absence of reliable soil data, land degradation assessments, environmental impact studies and sustainable land management interventions are severely hampered。By Soil information data in the urgent need of the World, especially under the background of the convention on climate change, international institute for applied systems analysis (IIASA) and the UN food and agriculture organization (FAO) and the Kyoto protocol on Soil carbon measurement and the United Nations food and agriculture organization (FAO)/international global agriculture ecological assessment (GAEZ v3.0) jointly established under the sponsorship of a new generation of World Soil Database (Harmonized World Soil Database version 1.2) (HWSD V1.2). The 2010 data set of soil texture on the qinghai-tibet plateau was culled from the world soil database.Data format :grid format, projected as WGS84.The main soil classification system used is fao-90.Unique verification identifier of core soil institution unit: Mu_global-hwsd database soil mapping unit identifier that connects GIS layers. MU_SOURCE1 and MU_SOURCE2- source database mapping unit identifiers； SEQ- soil unit sequence in the composition of soil mapping unit; Soil classification system USES fao-7 classification system or fao-90 classification system (SU_SYM74 resp.su_sym90) or fao-85 (SU_SYM85). The main fields of the soil property sheet include: ID(database ID) MU_GLOBAL(soil unit identifier) (global) SU_SYMBOL Soil mapping unit SU_SYM74(FAO74classify ); SU_SYM85(FAO85classify); SU_SYM90（FAO90The soil name in a soil classification system)； SU_CODE Soil mapping unit code SU_CODE74 Soil unit name SU_CODE85 Soil unit name SU_CODE90 Soil unit name DRAINAGE(19.5); REF_DEPTH(Soil reference depth); AWC_CLASS(19.5); AWC_CLASS(Soil available water content); PHASE1: Real (The soil phase); PHASE2: String (The soil phase); ROOTS: String (Depth classification of obstacles to the bottom of the soil)； SWR: String (Characteristics of soil moisture content)； ADD_PROP: Real (A specific soil type in a soil unit that is associated with agricultural use)； T_TEXTURE(Topsoil texture); T_GRAVEL: Real (Percentage of aggregate volume on top)；( unit：%vol.) T_SAND: Real (Top sand content)； ( unit：% wt.) T_SILT: Real (surface silt content);(unit: % wt.) T_CLAY: Real (clay content on top);(unit: % wt.) T_USDA_TEX: Real (top-level USDA soil texture classification);(unit: name) T_REF_BULK: Real (top soil bulk density);(unit: kg/dm3.) T_OC: Real (top organic carbon content);(unit: % weight) T_PH_H2O: Real (top ph) (unit: -log(H+)) T_CEC_CLAY: Real (the cationic exchange capacity of the clay layer at the top);(unit: cmol/kg) T_CEC_SOIL: Real (cation exchange capacity of topsoil) (unit: cmol/kg) T_BS: Real (top basic saturation);(unit: %) T_TEB: Real (top exchange base);(unit: cmol/kg) T_CACO3: Real (top carbonate or lime content) (unit: % weight) T_CASO4: Real (top-level sulfate content);(unit: % weight) T_ESP: Real (top layer exchangeable sodium salt);(unit: %) T_ECE: Real (top-level conductivity).(unit: dS/m) S_GRAVEL: Real (percentage of bottom gravel volume);(unit: % vol.) S_SAND: Real (content of underlying sand);(unit: % wt.) S_SILT: Real (substratum silt content);(unit: % wt.) S_CLAY: Real (clay content in the bottom layer);(unit: % wt.) S_USDA_TEX: Real (USDA underlying soil texture classification);(unit: name) S_REF_BULK: Real (bulk density of underlying soil);(unit: kg/dm3.) S_OC: Real (bottom organic carbon content);(unit: % weight) S_PH_H2O: Real (base ph) (unit: -log(H+)) S_CEC_CLAY: Real (cation exchange capacity of the underlying cohesive soil);(unit: cmol/kg) S_CEC_SOIL: Real (cation exchange capacity of underlying soil) (unit: cmol/kg) S_BS: Real (underlying basic saturation);(unit: %) S_TEB: Real (underlying exchangeable base);(unit: cmol/kg) S_CACO3: Real (content of underlying carbonate or lime) (unit: % weight) S_CASO4: Real (substrate sulfate content);(unit: % weight) S_ESP: Real (underlying exchangeable sodium salt);(unit: %) S_ECE: Real (underlying conductivity).(unit: dS/m) This database is divided into two layers, in which the top layer (T) has a soil thickness of (0-30cm) and the bottom layer (S) has a soil thickness of (30-100cm).。 Refer to the instructions for other attribute values HWSD1.2_documentation.pdf，The Harmonized World Soil Database (HWSD V1.2) Viewer-Chinese description andHWSD.mdb。
Food and Agriculture Organization of the United Nations（FAO）
The data include soil organic matter data of Tibetan Plateau , with a spatial resolution of 1km*1km and a time coverage of 1979-1985.The data source is the soil carbon content generated from the second soil census data.Soil organic matter mainly comes from plants, animals and microbial residues, among which higher plants are the main sources.The organisms that first appeared in the parent material of primitive soils were microorganisms.With the evolution of organisms and the development of soil forming process, animal and plant residues and their secretions become the basic sources of soil organic matter.The data is of great significance for analyzing the ecological environment of Tibetan Plateau
FANG Huajun
The data set includes the sample survey data of alpine grassland and alpine meadow in Maduo County in September 2016. The sample size is 50cm × 50cm. The investigation contents include coverage, species name, vegetation height, biomass (dry weight and fresh weight), longitude and latitude coordinates, slope, aspect, slope position, soil type, vegetation type, surface characteristics (litter, gravel, wind erosion, water erosion, saline alkali spot, etc.), utilization mode, utilization intensity, etc.
LI Fei, Fei Li, Zhijun Zhang, Fei Li, Zhijun Zhang
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