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Institute of Tibetan Plateau Research, CAS

Address:16 Lincui Road, Chaoyang District, Beijing 100101, P.R. China

E-mail: data@itpcas.ac.cn

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Geomorphological of China
  • 2019-06-15
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The landform information integration in western China was completed by a team led by Dr. Xie chuanjie, from the institute of geography, resources and environment, Chinese academy of sciences.It includes 1:400,000 national geomorphologic database and 1:100,000 western geomorphologic database. 1:400,000 geomorphologic data are "China geomorphologic map (1:400,000)" edited by LI Bingyuan and "China and its adjacent areas geomorphologic map (1:400,000)" edited by CHEN Zhiming. Scan and register the data, vectorize all the registered maps by using ArcMap software, and establish their own classification and code system. According to map spots (common staining) and symbols, geomorphic types are divided into basic geomorphic types and morphological structure types (points, lines and planes). 1:1000000 western geomorphic data is integrated and updated by digital geomorphology based on multi-source data such as remote sensing image and adopts hierarchical interpretation method.Plains and mountains;Primary geomorphic types (25 types),10 genetic types: secondary genetic types: subdivision of morphological differences. The type of geomorphic material whose composition or lithology is determined. Conducted among 16 landscape points of interpretation work, their Numbers are: 45 (Kathmandu), G - G - 46 (the) wrong, H - 44 (pli), 45 (xigaze), H - H - 46 (Lhasa), H - 47 (qamdo), 43 (Islamabad), I - I - 44 (lion spring river), 45 (change), I - I - (amdo) 46, 47 (yushu), J - I - 43 (kashi) (wada), J, J - 44-45 (JuMo), 46 (golmud), J J - - 47 (xining)

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WATER: Dataset of surface roughness measurements in the Biandukou foci experimental area during the pre-observation Period
  • 2019-05-23
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The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were included. With the roughness grid board 110cm long and the measuring intervals of 1cm, the samples were collected along the soil surface from south to north and from east to west, respectively. The coordinates of sample points would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The roughness data files were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further checking. Those provide reliable ground data for improving and verifying the microwave remote sensing algorithms.

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WATER: Dataset of ground truth measurement synchronizing with PROBA CHRIS in the A'rou foci experimental area on Jun. 23, 2008
  • 2019-05-23
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The dataset of ground truth measurement synchronizing with PROBA CHRIS was obtained in No. 2 and 3 quadrates of the A'rou foci experimental area on Jun. 23, 2008. Observation items included: (1) quadrates investigation including GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. Data were archived in Excel format. (2) roughness by the self-made roughness board and the camera. The processed data were archived as .txt files. (3) BRDF by ASD FieldSpec (350~2 500 nm), with 20% reference board and the observation platform made by Beijing Normal University. The processed reflectance and transmittivity were archived as .txt files. (4) LAI of stellera and pasture by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards. Data included original photos (.JPG) and those processed by can_eye5.0 (in Excel). For more details, see Readme file. Five files were included, spectrum in No.2 quadrate, multiangle observations in No.2 and 3 quadrates, roughness photos in No.2 and 3 quadrates, the fisheye camera observations, and the No.2 and 3 quadrates investigation.

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WATER: Dateset of surface roughness measurements in the A'rou foci experimental area
  • 2019-05-23
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The dataset of surface roughness measurements was obtained in A1, A2, A3, L1, L2, L3, L4, L5 and L6 of the A'rou foci experimental area. The quadrates were changed into 3×3 subsites during the foci experimental period, with each one spanning a 30×30 m2 plot. With the roughness plate 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. As for the sampling lines, the samples were collected every 100 m along them from south to north. Photos were named in the form of A3-1EW, indicating No. 1 point in A3 measured from east to west. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 radius is also included for further checking. Those provide reliable ground data for improving and verifying the remote sensing algorithms. Nine files were included, ARou_SampleArea1, ARou_SampleArea2, ARou_SampleArea3, ARou_SampleLine1, ARou_SampleLine2, ARou_SampleLine3, ARou_SampleLine4, ARou_SampleLine5 and ARou_SampleLine6.

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WATER: Dataset of surface roughness measurements in the Linze grassland foci experimental area
  • 2019-05-23
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The dataset of surface roughness measurements was obtained in the reed plot A, the saline plots B and C of the Linze grassland foci experimental area on Jun. 7, 18 and 25, 2008. All the quadrates were divided into 4×4 subsites, with each one spanning a 120×120 m2 plot. With the roughness plate 110cm long and the measuring points distance 1cm, the samples were collected from south to north and from east to west, respectively. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were included this dataset. The roughness data were initialized with the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further checking.

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WATER: Dataset of surface roughness measurements in the E’bao foci experimental area during the pre-observation period
  • 2019-05-23
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The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the E’bao foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. With the roughness board 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be calculated based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were archived. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further validation.

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WATER: Dateset of the ground-based RPG-8CH-DP microwave radiometer observations in the Biandukou foci experimental area
  • 2019-05-23
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The dateset of the ground-based RPG-8CH-DP microwave radiometer observations was obtained in the Biandukou foci experimental area from Mar. 14 to 17, 2008. Observation items included the brightness temperature by the ground-based microwave radiometer (18.7GHz and 36.5GHz), the soil temperature by the thermal resistor, the gravimetric soil moisture by the microwave drying method, and the surface roughness by the grid board. The wheat stubble land (38°15'44.13"N, 100°55'35.34"E) was chosen for continuous observations from 11:00 to 24:00 on Mar. 14, with the incidence 20°-70° and the step length 5°. The rape stubble land (38°15'23.17"N, 100°58'37.84"E) was chosen for continuous observations from 10:00 to 21:30 on Mar. 16, with the incidence 20°-70° and the step length 5°. The deep plowed land (38°18'8.28"N, 101° 3'27.22"E) was chosen for short time observations from 17:26 to 19:20 on Mar. 17, with the azimuth angle 240°-300° and the step length 10°, the incidence 40°-70° and the step length 5°. The brightness temperature was archived as .BRT and .txt files (the ASCII format). Each row in .txt was listed by year, month, date, hour, minute, second, 6.925GHz (h), 6.925GHz (v), 10.65GHz (h), 10.65GHz (v) , 18.7GHz (h), 18.7GHz (v), 36.5GHz (h), 36.5GHz (v), the elevation angle, and the azimuth angle. Values for 6.925GHz and 10.65GHz were zero due to malfunction. The roughness data were obtained by the grid board and the camera and the RMS height (cm) and correlation length (cm) were also calculated and archived, which could be opened by Notepad or Microsoft Office Word. Those provide reliable reference for the roughness of the same land cover type. The gravimetric soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The file can be opened by Microsoft Office Word. The shallow layer soil moisture was measured by hydra prob from 12:00 to 17:00 on 14 and by the Hydra probe (straight downward for 0-5cm) and HH2 (level into the soil surface) on 16. The surface temperature was measured by the thermal resistor. The file can be opened by Microsoft Office Word. Four data files were included, the brightness temperature, the surface temperature, the soil moisture and the surface roughness.

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WATER: Dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission in the Biandukou foci experimental area on May 25, 2008
  • 2019-05-23
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The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Biandukou foci experimental area on May 25, 2008. Observation items included: (1) the soil temperature in L1, L2, L3, L4, L5, L6 and L7; (2) roughness measured by the roughness grid board and collected by the digital camera. Files with "result" field were processed data, in which the first row was RMS height (cm; one value), the second row was distance (cm), and the third row was correlation function (cm; changed into correlation length when it is 1/e). (3) GPR and TDR data. Five files were included, roughness photos and preprocessed data, the soil temperature, coordinates of quadrates and sampling lines, GPR and microwave radiometer data. All were archived as Excel and .txt files. Those provide reliable ground data for development and validation of soil moisture and freeze/thaw algorithms from active remote sensing approaches.

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WATER: Dataset of surface roughness at the super site around the Dayekou Guantan forest station
  • 2019-05-23
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The dataset of surface roughness was obtained at the super site (100m×100m, pure Qinghai spruce) around the Dayekou Guantan forest station. 25 corner points and 16 center points were collected and each point was measured twice and photos were taken. With the roughness plate 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The photos were processed using ArcView software; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 radius is also included for further checking. Those provide reliable ground data for improving and verifying the remote sensing algorithms.

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WATER: Dataset of surface roughness measurements in the Huazhaizi desert steppe foci experimental area
  • 2019-05-23
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The dataset of surface roughness measurements by phototaking was obtained in the Huazhaizi desert steppe foci experimental area. Observation items included: (1) Surface roughness synchronizing with ASAR and MODIS in Huazhaizi desert No. 2 plot on May 24, 2008. (2) Surface roughness synchronizing with WiDAS in Huazhaizi desert No. 1 plot on May 30, 2008. The self-made roughness reference board (Cold and Arid Regions Environmental and Engineering Research Institute, CAS), the digital camera and the compass were used. Sample points were selected at equal intervals along the diagonals and marked in the photos.

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