Remote sensing products of thermal collapse in Heihe permafrost region of the Tibetan Plateau (2009-2018)

Global warming and human activities have led to the degradation of permafrost and the collapse of permafrost, which have seriously affected the construction of permafrost projects and the ecological environment. Based on high-resolution satellite images, the permafrost of oboling in Heihe River Basin of Qinghai Tibet Plateau is taken as the research area, and the object-oriented classification technology of machine learning is used to extract the thermal collapse information in the research area. The results show that from 2009 to 2019, the number of thermal collapse increased from 12 to 16, and the total area increased from 14718.9 square meters to 28579.5 square meters, nearly twice. The combination of high spatial resolution remote sensing and object-oriented classification method has a broad application prospect in the monitoring of thermal thawing and collapse of frozen soil.

0 2020-03-14

HiWATER: WATERNET observation dataset in the upper reaches of the Heihe River Basin (2014)

This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since January 2014. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. Please refer to "waternet data document 20141206. Docx" for details

0 2020-03-13

HiWATER:WATERNET observation dataset in the upper reaches of the Heihe River Basin (2013)

This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since the end of June 2013. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification.

0 2020-03-13

Time series data of snow area ratio in the Arctic (2000-2019)

The fraction snow cover (FSC) is the ratio of the snow cover area SCA to the pixel space. The data set covers the Arctic region (35 ° to 90 ° north latitude). Using Google Earth engine platform, the initial data is the global surface reflectance product with a resolution of 1000m with mod09ga, and the data preparation time is from February 24, 2000 to November 18, 2019. The methods are as follows: in the training sample area, the reference data set of FSC is prepared by using Landsat 8 surface reflectance data and snomap algorithm, and the data set is taken as the true value of FSC in the training sample area, so as to establish the linear regression model between FSC in the training sample area and NDSI based on MODIS surface reflectance products. Using this model, MODIS global surface reflectance product is used as input to prepare snow area ratio time series data in the Arctic region. The data set can provide quantitative information of snow distribution for regional climate simulation and hydrological model.

0 2020-03-13

Long-term series of daily snow depth in Euroasia (1980-2016)

The “long-term series of daily snow depth in Eurasia” was produced using the passive microwave remote sensing data. The temporal range is 1980~2016, and the coverage is the Eurasia continent. The spatial resolutions is 0.25° and the temporal resolution is daily. A dynamic brightness temperature gradient algorithm was used to derive snow depth. In this algorithm, the spatial and temporal variations of snow characteristics were considered and the spatial and seasonal dynamic relationships between the temperature difference between 18 GHz and 36 GHz and the measured snow depth were established. The long-term sequence of satellite-borne passive microwave brightness temperature data used to derive snow depth came from three sensors (SMMR, SSM/I and SSMI/S), and there is a certain system inconsistency among them. So, the inter-sensor calibration was performed to improve the temporal consistency of these brightness temperature data before snow depth derivation. The accuracy analysis shows that the relative deviation of Eurasia snow depth data is within 30%. The data are stored as a txt file every day, each file includes a file header (projection mode) and a 720*332 snow depth matrix, and each snow depth represents a 0.25°*0.25° grid. For details of the data, please refer to data specification “Snow depth dataset of Eurasian (Version 1.0) (1980-2016).doc”

0 2020-03-13

The silicon dioxide content of snowmelt water and soil water in Hulugou small watershed (2013-2014)

1、 Data Description: the data includes the content of silica in snowmelt water and soil water in hulugou small watershed from May 2013 to April 2014. 2、 Sampling location: the sampling point of snowmelt water is located near 600m below No.2 meteorological station, with ground elevation of 3514.45m, longitude and latitude of 99 ° 53 ′ 20.655 ″ e, 38 ° 14 ′ 14.987 ″ n. The sampling point of soil water is located at 300m above and below the No.2 meteorological station, with the longitude and latitude of 99 ° 53 ′ 31.333 ″ E and 38 ° 13 ′ 50.637 ″ n. 3、 Measurement method: the content of silica in the sample was measured by ICP-AES. Silicon dioxide is replaced by the value of Si in the solution.

0 2020-03-12

Glacier forefront snowmelt water temperature and near-surface temperature observations of hulugou watershed(July-September 2012)

From July 21 to September 2, 2012, the observation data of snowmelt water temperature and near surface temperature in hulugou small watershed were observed by hobo automatic temperature recorder, with the observation frequency of once / 15 minutes, and the near surface temperature recorder was 20cm away from the surface. The observation point 01 is an ice lake, which is formed by the permanent snow supply of Hunan slope. The lake is approximately triangular, and the long side trend is parallel to the slope foot, with the coordinates of 99 ° 53 ′ 11 ″ E and 38 ° 13 ′ 6 ″ n. The observation period is from July 21, 2012 to September 2, 2012. No.02 observation point is located under the ice lake, the source of the East tributary of hulugou, the foot of permanent snow slope and the lower edge of snow melting. The coordinates are 99 ° 53 ′ 12 ″ e, 38 ° 13 ′ 6 ″ n. The observation period is from July 21, 2012 to September 2, 2012. The distance between the two points is relatively close, and the near surface temperature is the uniform temperature, which is the near surface temperature of point 01.

0 2020-03-11

Frozen depth of frozen ground in Hulugou sub-basin of the Heihe River Basin (2013)

1. Data overview: This data set is the data set of frozen depth of permafrost observed artificially in qilian station from January 1, 2013 to December 31, 2013, and observed at 08 o 'clock every day. 2. Data content: The data content is the frozen depth data set of the tundra.The frozen depth (length) of the water in the inner rubber tube is used as a record to determine the freezing level and the upper and lower depth of the frozen layer according to the freezing position and length of the water in the frozen pot.In centimeters (cm), round off the whole number and round off the decimal.Observe once a day at 0:8. 3. Space and time range: Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2981.0 m

0 2020-03-11

Frozen depth of frozen ground in Hulugou, a sub-basin of Heihe River Basin (2012)

1. Data overview: This data set is the data set of frozen depth of permafrost observed artificially in qilian station from January 1, 2012 to December 31, 2012, and observed at 08 o 'clock every day. 2. Data content: The data content is the frozen depth data set of the tundra.The frozen depth (length) of the water in the inner rubber tube is used as a record to determine the freezing level and the upper and lower depth of the frozen layer according to the freezing position and length of the water in the frozen pot.In centimeters (cm), round off the whole number and round off the decimal.Observe once a day at 0:8. 3. Space and time range: Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2981.0 m

0 2020-03-11

Frozen depth of frozen ground in Hulugou sub-basin of the Heihe River Basin (2011)

1. Data overview: this data set is the data set of artificial observation of frozen soil depth at Qilian station from January 1, 2011 to December 31, 2011, at 08:00 every day. 2. Data content: data content is frozen depth data set of permafrost. Frozen soil observation uses the frozen depth (length) of water poured into the rubber inner tube as a record. According to the position and length of water frozen in the permafrost buried in the soil, the frozen layer and its upper and lower limit depths are measured. In centimeters (CM), rounded to the nearest whole number. Observe once every day at 0.8 o'clock. 3. Space time scope: geographic coordinates: longitude: 99 ° 53 ′ E; latitude: 38 ° 16 ′ n; altitude: 2981.0m

0 2020-03-11