Data content: this data set is the historical archived satellite data of the domestic high score series (GF1 / 2 / 3 / 4) in the key river and lake research areas of the Qinghai Tibet Plateau from 2015 to 2020, which can cover the typical river and lake areas for effective monitoring. The time range of the data is from 2015 to 2020. Data source and processing method: the data are level 1 products. After equalizing radiation correction, the changes affecting the sensors are corrected by the equalizing functions of different detectors. Some data are based on the Landsat 8 images in the same period as the base map, and control points are selected for geometric correction of the images. Then, orthophoto correction is carried out based on DEM data, and band fusion processing is carried out for the corresponding data. Data quality description: the Gaofen series satellites are processed by the China Resources Satellite Application Center. There are raw data received by the satellite ground receiving station of the Chinese Academy of Sciences and processed products at all levels. Among them, level 1a (pre-processing level radiometric correction image product): image data processed by data analysis, uniform radiometric correction, noise removal, MTFC, CCD splicing, band registration, etc; And provide RPC files for satellite direct attitude orbit data production. Refer to the data website of China Resources Satellite Application Center for details. Data application achievements and prospects: the data are domestic high-resolution data with high resolution, which can be used to monitor the changes of the Qinghai Tibet Plateau as a water tower in Asia and the generated images, and test the accuracy of other data in the region
2022-08-29
The dataset is the remote sensing image data ofGF-1 satellite in the Qinghai-Tibet engineering corridor obtained by China High Resolution Earth Observation Center. After the fusion processing of multispectral and panchromatic bands, the image data with a spatial resolution of 2 m is obtained. In the process of obtaining ground vegetation information, the classification technology of combining object-oriented computer automatic interpretation and manual interpretation is adopted, The object-oriented classification technology is to collect adjacent pixels as objects to identify the spectral elements of interest, make full use of high-resolution panchromatic and multispectral data space, texture and spectral information to segment and classify, and output high-precision classification results or vectors. In actual operation, the image is automatically extracted by eCognition software. The main processes are image segmentation, information extraction and accuracy evaluation. After verification with the field survey, the overall extraction accuracy is more than 90%.
2022-08-29
Based on a large number of measured aboveground biomass data of grassland, the temperate grassland types were divided according to the vegetation type map of China in 1980s Based on the Landsat remote sensing data of engine platform, the random forest model of grassland aboveground biomass and remote sensing data was constructed for different grassland types. On the basis of reliable verification, the annual aboveground biomass of grassland from 1993 to 2019 was estimated, and the annual spatial data set of aboveground biomass of temperate grassland in Northern China from 1993 to 2019 was formed. Aboveground biomass is defined as the total amount of organic matter of vegetation living above the ground in unit area. The original grid value has been multiplied by a factor of 100, unit: 0.01 g / m2 (g / m2). This data set can provide a scientific basis for the dynamic monitoring and evaluation of temperate grassland resources and ecological environment in northern China.
2022-04-18
Evapotranspiration over the Qinghai Tibet Plateau is calculated by etwatch, a land surface evapotranspiration remote sensing model based on multi-scale and multi-source data. Etwatch adopts the method of combining the residual term method with P-M formula to calculate evapotranspiration. Firstly, according to the characteristics of the data image, the suitable model is selected to retrieve the evapotranspiration on a sunny day; the remote sensing model is often lack of data because the weather conditions can not obtain a clear image. In order to obtain the daily continuous evapotranspiration, the penman Monteith formula is introduced, and the evapotranspiration results on a sunny day are regarded as the "key frame", and the surface impedance information of the key frame is used as the basis to construct the surface impedance Based on the daily meteorological data, the time series data of evapotranspiration are reconstructed. Through the data fusion model, the high spatial and temporal resolution evapotranspiration data set is constructed by combining the low and medium resolution evapotranspiration temporal variation information with the high resolution evapotranspiration spatial difference information, so as to generate the 8 km resolution evapotranspiration of the Qinghai Tibet Plateau Data sets (1990-2015).
2022-04-18
Surface solar irradiance (SSI) is one of the products of FY-4A L2 quantitative inversion. It covers a full disk without projection, with a spatial resolution of 4km and a temporal resolution of 15min (there are 40 observation times in the whole day since 20180921, except for the observation of each hour, there is one observation every 3hr before and after the hour）, and the spectral range is 0.2µ m～5.0 µ m. The output elements of the product include total irradiance, direct irradiance on horizontal plane and scattered irradiance, the effective measurement ranges between 0-1500 w / m2. The qualitative improvement of FY-4A SSI products in coverage, spatial resolution, time continuity, output elements and other aspects makes it possible to further carry out its fine application in solar energy, agriculture, ecology, transportation and other professional meteorological services. The current research results show that the overall correlation of FY-4A SSI product in China is more than 0.75 compared with ground-based observation, which can be used for solar energy resource assessment in China.
2022-04-18
Based on the medium resolution long time series remote sensing image Landsat, the data set obtained six periods of ecosystem type distribution maps of the Qinghai Tibet Plateau in 1990 / 1995 / 2002 / 2005 / 2010 / 2015 through image fusion, remote sensing interpretation and data inversion, and made the original ecological base map of the Qinghai Tibet Plateau in 25 years (1990-2015). According to the area statistics of various ecosystems in the Qinghai Tibet Plateau, the area of woodland and grassland decreased slightly, the area of urban land, rural residential areas and other construction land increased, the area of rivers, lakes and other water bodies increased, and the area of permanent glacier snow decreased from 1990 to 2015. The atlas can be used for the planning, design and management of ecological projects in the Qinghai Tibet Plateau, and can be used as a benchmark for the current situation of the ecosystem, to clarify the temporal and spatial pattern of major ecological projects in the Qinghai Tibet Plateau, and to reveal the change rules and regional differences of the pattern and function of the ecosystem in the Qinghai Tibet Plateau.
2022-04-18
This dataset contains the glacier outlines in Qilian Mountain Area in 2020. The dataset was produced based on classical band ratio criterion and manual editing. Chinese GF series images collected in 2020 were used as basic data for glacier extraction. Google images and Map World images were employed as reference data for manual adjusting. The dataset was stored in SHP format and attached with the attributions of coordinates, glacier ID and glacier area. Consisting of 1 season, the dataset has a spatial resolution of 2 meters. The accuracy is about 1 pixel (±2 meter). The dataset directly reflects the glacier distribution within the Qilian Mountain in 2020, and can be used for quantitative estimation of glacier mass balance and the quantitative assessment of glacier change’s impact on basin runoff.
2022-04-18
The data set is based on a series of microwave remote sensing data, including Special Sensor Microwave Imager (SSM/I), Advanced Microwave Scanning Radiometer for Earth Observation System (AMSR-E), etc., which can be used as a reference for primary productivity. The data is from Liu et al. (2015), and the specific calculation method is shown in the article. The source data range is global, and Tibetan Plateau region is selected in this data set. This data set is often used to evaluate the temporal and spatial patterns of vegetation greenness and primary productivity, which has practical significance and theoretical value.
2022-04-15
This dataset includes one scene acquired on (yy-mm-dd) 2012-07-25, covering the natural oasis eco-hydrology experimental area in the lower reaches of the Heihe River Basin. This datum contains panchromatic and multi-spectral bands, with spatial resolution of 0.6 m and 2.4 m, respectively. The data product level of this image is Level 2A. QuickBird dataset was acquired through purchase.
2021-07-27
Data content: precipitation data of the Aral Sea basin from 2015 to 2018. Data sources and processing methods: from the new generation of global precipitation measurement (GPM) of NASA (version 06, global precipitation observation program), the daily rainfall can be obtained by adding the three-hour rainfall data, and then the eight day rainfall can be obtained. Data quality: the spatial resolution is 0.1 ° x 0.1 ° and the temporal resolution is 8 days. The value of each pixel is the sum of rainfall in 8 days. Data application results: under the background of climate change, it can be used to analyze the correlation between meteorological elements and vegetation characteristics.
2021-02-23
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