Dataset of key elements of desertification in typical watershed of Central and Western Asia (Amu River Basin)

Data Set of Key Elements of Desertification in Typical Watershed of Central and Western Asia includes four parts: distribution and change of agricultural land of Amu River Basin, distribution and change of grassland of Amu River Basin, distribution and change of shrub land of Amu River Basin, distribution and change of forests of Amu River Basin. the spatial resolution of data is 30 m. All the data is based on Landsat TM/ETM image data in 1990, 2000 and 2010. The data produced by the key laboratory of remote sensing and GIS, Xinjiang institute of ecology and geography, Chinese Academy of Sciences. Data production Supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Grant No. XDA20030101.

0 2019-11-19

China lake dataset (1960s-2015)

The multi-decadal lake number and area changes in China during 1960s–2015 are derived from historical topographic maps and >3831 Landsat satellite images, including lakes as fine as ≥1 km2 in size. The total area of lakes in China has increased by 5858.06 km2 (9%) between 1960s and 2015, and with heterogeneous spatial variations. Lake area changes in the Tibetan Plateau, Xinjiang, and Northeast Plain and Mountain regions reveal significant increases of 5676.75, 1417.15, 1134.87 km2 (≥15%), respectively, but the Inner-Mongolian Plateau shows an obvious decrease of 1223.76 km2 (22%). We find that 141 new lakes have appeared predominantly in the arid western China; but 333 lakes, mainly located in the humid eastern China, have disappeared over the past five decades.

0 2019-11-12

River lake ice range / coverage data set v1.0

There are many lakes in the Qinghai Tibet Plateau. The glacial phenology and duration of lakes in this region are very sensitive to regional and global climate change, so they are used as the key indicators of climate change research, especially the comparative study of the three polar environmental changes of the earth. However, due to its poor natural environment and sparse population, there is a lack of conventional field measurement of lake ice phenology. The lake ice was monitored with a resolution of 500 meters by using the normalized difference snow index (NDSI) data of MODIS. The traditional snow map algorithm is used to detect the lake daily ice amount and coverage under the condition of sunny days, and the lake daily ice amount and coverage under the condition of cloud cover are re determined through a series of steps based on the spatiotemporal continuity of the lake surface conditions. Through time series analysis, 308 lakes larger than 3km2 are identified as effective records of lake ice range and coverage, forming a daily lake ice range and coverage data set, including 216 lakes.

0 2019-11-05

River lake ice phenology data in QPT(2002-2018) v1.0

River lake ice phenology is sensitive to climate change and is an important indicator of climate change. 308 excel file names correspond to Lake numbers. Each excel file contains six columns, including daily ice coverage information of corresponding lakes from July 2002 to June 2018. The attributes of each column are: date, lake water coverage, lake water ice coverage, cloud coverage, lake water coverage and lake ice coverage after cloud treatment. Generally, the ice cover area ratio of 0.1 and 0.9 is used as the basis to distinguish the lake ice phenology. The excel file contained in the data set can further obtain four lake ice phenological parameters: Fus, fue, bus, bue, and 92 lakes. Two parameters, Fus and bue, can be obtained.

0 2019-10-28

0 2019-10-28

Daily 0.01 °× 0.01 ° surface temperature data (v1.0) based on myd21a1 temperature data in Qilian Mountain Area (2018)

This dataset contains monthly and daily 0.01°×0.01° (2018) LST products in Qilian Mountain Area. The dataset was produced based on MYD21A1 LST products at a resolution of 0.01° along with some auxiliary datasets. The auxiliary datasets include Lat/Lon and the Julian Day information. MYD21A1 is the official LST product of MODIS, and the data is divided into day and night, using TES algorithm. Download URL: https://urs.earthdata.nasa.gov.

0 2019-10-27

Vegetation Index (NDVI) data of Tibetan Plateau

The data include NDVI data of Tibetan Plateau region, with spatial resolution 1000m, time resolution 16d, and time coverage in 2000, 2005, 2010 and 2015.The data source is MOD13A2(C6).NDVI is a kind of vegetation index formed by combining visible light and near-infrared bands of satellites according to the spectral characteristics of vegetation.NDVI is a simple, effective and empirical measure of surface vegetation.The data is of great significance for analyzing the ecological environment of Tibetan Plateau.

0 2019-10-27

Land Surface Temperature (LST) Monthly/Day Dataset (V1.0) based on AVHRR brightness temperature (BT) (0.05°×0.05°) and MYD21A1 LST products (0.01°×0.01°) in Qilian Mountain Area

This dataset contains monthly 0.05°×0.05° (1982, 1985, 1990, 1995, and 2000), 0.01°×0.01° (2005, 2010, 2015, 2017 and 2018), and daily 0.01°×0.01° (2018) LST products in Qilian Mountain Area. The dataset was produced based on SW algorithm by AVHRR BT from thermal infrared channels (CH4: 10.5µm to 11.3µm; CH5: 11.5µm to 12.5µm) at a resolution of 0.05°, MYD21A1 LST products at a resolution of 0.01° along with some auxiliary datasets. The auxiliary datasets include IGBP land cover type, AVHRR NDVI products, Modern Era Retrospective-Analysis for Research and Applications-2 (MERRA-2) reanalysis data, ASTER GED, Lat/Lon and the Julian Day information.

0 2019-10-23

Global 0.05° near-surface freeze-thaw states data set (2002-2018)

The near-surface freeze-thaw affects the water and energy exchanges mode and efficiency between the land and atmosphere. The transition of the freeze/thaw state affects the pattern of runoff concentration, which has an important impact on regional and global water cycle. Based on the remote sensing data of AMSR-E/2 passive microwave sensors and MODIS optical sensor, this data set uses the discriminant function algorithm and its downscaling method to produce a global mapping of near-surface freeze-thaw states with higher spatial resolution. This product covers the time period from 2002 to 2018 (daily), and spatial coverage is global scale (spatial resolution of 0.05°). It can be used to analyze the start/end time of global near-surface freeze/thaw states, the duration of freezing/thawing and their changing trends, and provide data support for studying the mechanism of water cycle and energy exchanges in the context of global change.

0 2019-10-21