Third Pole 1:100,000 airport and runway data set include：airport（Tibet_Airport）and(Tibet_Airport_runways) vector space data set and its attribute name:Airport name(Name）、Name of airport（CNTRY_NAME）、Airport country abbreviation（CNTRY_CODE）、latitude（LATITUDE）、longitude（LONGITUDE）. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, D_WGS_1984 datum surface
ADC WorldMap
Antarctic 1:100,000 airport distribution data set includes vector space data and related attribute data of airports (Antarctic_Airport) and airport runways (Antarctic_Airport_runways)：Airport Name(Name), airport country Name（CNTRY_NAME）, airport country abbreviation（CNTRY_CODE）, LATITUDE, LONGITUDE. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, WGS84 datum surface，Antarctic specific projection parameters（South_Pole_Stereographic）.
ADC WorldMap
Arctic 1:100,000 airport distribution data set includes vector space data and related attribute data of airports (Arctic_Airport) and airport runway (Arctic_Airport_runways) in the arctic range: airport Name, airport country Name, airport country abbreviation (CNTRY_CODE), LATITUDE and LONGITUDE. The data comes from the 1:100,000 ADC_WorldMap global data set, which is a comprehensive, up-to-date and seamless geographic digital data after the data quality inspection of topology, warehousing and other data. The world map coordinate system is latitude and longitude, WGS84 datum surface, and the arctic data set is the special projection parameter for the arctic (North_Pole_Stereographic).
ADC WorldMap
The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
The dataset combined with crop phrenology data and field management data which were investigated near the 13 eddy covariance (EC) stations. 1.1 Objective of investigation Objectives of investigation is to supply assistant information for experiment on EC, meteorology, and biophysics parameter. 1.2 Investigation spots and items Investigation spots include Jiu She of Shiqiao village (EC3), Xiaoman southern road (EC16), Wu She of Five stars village (EC13), Wu She of Xiaoman village (EC14), Er She of Shiqiao village (EC5), Liu She of Zhonghua village (EC11), Liu She of Shiqiao village (EC2), Wu She of JinCheng village (EC7), EC6, Liu She of Jincheng village (EC8), Yi She of Kangning village (EC9), Er She of Kangning village (EC10), and Si She of Jingcheng village (EC12). Investigation items comprise crop type, crop name, seed time, seed type, plant span, row span, field area, germination time, three leaves period, seven leaves period, farming way, farming time, irrigation time, irrigation water volume, fertilization time, fertilization type, and fertilization rate. The time used in this dataset is in UTC+8 Time. 1.3 Data collection Data was collected by using ask-reply approach according to investigation tables.
GE Yingchun, Ma Chunfeng, LI Xin
According to the characteristics of the selected field and its surrounding area, a trime tube is arranged in the corn field, and 5 trime tubes are arranged in a direction perpendicular to the field path. When monitoring soil moisture content in the TDR vertical direction, the unit is every 10cm. Monitor down. Location: N 38 ° 52′27.6 ″ E 100 ° 21′14.0 ″ The submitted data includes the water content of the farmland and its surrounding soil (TDR monitoring) after three irrigations in a selected farmland in Yingke Irrigation District, encrypted monitoring after irrigation, one group every 3 hours within 24 hours, and 3 groups per day for the next 5 days. -10 days are two groups per day, and 10-15 days are one group per day.
HUANG Guanhua, JIANG Yao
The field experiments of water consumption and irrigation water productivity of corn and cotton were arranged in 2012 and 2013, and the field experiments of irrigation water productivity of corn and sunflower under different mulching and cultivation methods were arranged in 2014. The characteristics of water consumption and irrigation water demand of three crops under different soil conditions, as well as the relationship between key soil properties and crop yield and irrigation water productivity were obtained.
SU Yongzhong
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