MODIS daily cloud-free snow cover area product for Sanjiangyuan from 2000 to 2018

The dataset was produced based on MODIS data. Parameters and algorithm were revised to be suitable for the land cover type in the Three-River-Source Regions. By using the Markov de-cloud algorithm, SSM/I snow water equivalent data was fused to the result. Finally, high accuracy daily de-cloud snow cover data was produced. The data value is 0(no snow) or 1(snow). The spatial resolution is 500m, the time period is from 2000-2-24 to 2018-12-31. Data format is geotiff, Arcmap or python+GDAL were recommended to open and process the data.

0 2021-03-28

250m remote sensing phenological product data set of Sanjiangyuan National Park (2001-2018)

This dataset is land surface phenology estimated from 16 days composite MODIS NDVI product (MOD13Q1 collection6) in the Three-River-Source National Park from 2001 to 2018. The spatial resolution is 250m. The variables include Start of Season (SOS) and End of Season (EOS). Two phenology estimating methods were used to MOD13Q1, polynomial fitting based threshold method and double logistic function based inflection method. There are 4 folders in the dataset. CJYYQ_phen is data folder for source region of the Yangtze River in the national park. HHYYQ_phen is data folder for source region of Yellow River in the national park. LCJYYQ_phen is data folder for source region of Lancang River in the national park. SJY_phen is data folder for the whole Three-River-Source region. Data format is geotif. Arcmap or Python+GDAL are recommended to open and process the data.

0 2021-03-28

Remote sensing inversion product of diurnal evapotranspiration in the middle reaches of Heihe River (2012)

Evapotranspiration monitoring is very important for agricultural water resource management, regional water resource utilization planning and sustainable development of social economy. The limitation of traditional monitoring et method is that it can't be observed in large area at the same time, so it can only be limited to the observation point. Therefore, the cost of personnel and equipment is relatively high. It can't provide the ET data of different land use types and crop types. Remote sensing can be used for quantitative monitoring of ET. the feature of remote sensing information is that it can reflect not only the macro structural characteristics of the earth's surface, but also the micro local differences. This data uses MODIS data and m-sebal model from June to September 2012 and time scale expansion scheme based on reference evaporation ratio to estimate the spatial and temporal distribution of evapotranspiration in the whole growth season of the middle reaches of Heihe River, and uses ground observation data to evaluate m-sebal model and time scale expansion scheme in detail. Its time resolution is day by day, spatial resolution is 250m, and data coverage is in the middle reaches of Heihe River, unit: mm. The projection information of the data is as follows: UTM projection, 47N.

0 2020-03-08