Current Browsing: 2011


HiWATER: 30m month compositing Leaf Area Index (LAI) product of the Heihe River Basin

The 30 m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. This data uses the domestic satellite HJ / CCD data with high time resolution (2 days after Networking) and spatial resolution (30 m) to construct the multi angle observation data set. Considering the impact of surface classification and terrain fluctuation, the algorithm is selected according to the characteristics of different vegetation types Choosing a suitable parameterization scheme of integrated model, inversion Lai based on look-up table method. The remote sensing data acquired every month can provide more angles and more observations than the single day sensor data, but the quality of multi-phase and multi angle observation data is uneven due to the difference of on orbit operation time and performance of the sensor. Therefore, in order to effectively use multi temporal and multi angle observation data, a data quality inspection scheme is designed. Using the Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats from dayokou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches to verify the Lai in July, the inversion results are in good agreement with the measurement results, and the average error is less than 1; in addition, the Lai inversion results of the combined multi temporal and multi angle observation data are in good agreement with the ground measurement data (R2=0.9,RMSE=0.42)。 In a word, the 30 m / month synthetic leaf area index (LAI) data set of Heihe River Basin comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, so as to better serve the application of remote sensing data products.

2020-03-13

HiWATER: 30m month compositing Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product of the Heihe River Basin

The 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. This data uses the characteristics of HJ / CCD data of China's domestic satellite, which has both high time resolution (2 days after Networking) and spatial resolution (30 m), to construct multi angle observation data set, considering different vegetation types, based on land cover classification map, combined with 30 m /Monthly synthetic leaf area index (LAI) products were produced by fapar-p model based on energy conservation. Based on the principle of energy conservation, the algorithm considers the multiple bounces between vegetation, soil and vegetation, as well as the influence of various factors such as sky scattered light. By analyzing the process of the interaction between photons and canopy, from the point of view that the movement of photons in the canopy is equal to the probability of re collision when multiple scattering occurs, a uniform and continuous vegetation fAPAR model is established. In addition, the effects of various factors on the fAPAR model were analyzed, including soil and leaf reflectance, aggregation index, and G function. The algorithm is highly dynamic, and can get better results for different soil background, vegetation type, radiation conditions, light and observation geometry, weather conditions. Compared with the data of corn canopy par measurement in Yingke irrigation area of Zhangye City, Gansu Province on July 8, 2012, the 30 m / month fAPAR product has a high consistency with the ground observation data, and the error with the observation value is less than 5%. In a word, the 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River Basin comprehensively uses the multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, and better serves the application of remote sensing data products.

2020-03-13

HiWATER: 1km/5day compositing vegetation index (NDVI/EVI) product of the Heihe River Basin (2011-2014)

The 1km / 5day vegetation index (NDVI / EVI) data set of Heihe River basin provides a 5-day resolution NDVI / EVI composite product from 2011 to 2014. The data uses the characteristics of FY-3 data, a domestic satellite, with high time resolution (1 day) and spatial resolution (1km), to construct a multi angle observation data set, which is the basis for analyzing multi-source data sets and existing composite vegetation index products and algorithms On the basis of this, an algorithm system of global composite vegetation index production based on multi-source data set is proposed. The vegetation index synthesis algorithm of MODIS is basically adopted, that is, the algorithm system of BRDF angle normalization method, cv-mvc method and MVC method based on the semi empirical walthal model. Using the algorithm system, the composite vegetation index is calculated for the first level data and the second level data, and the quality is identified. Multi-source data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm system first classifies the quality of multi-source data sets, which can be divided into primary data, secondary data and tertiary data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. In the middle reaches of Heihe River, the verification results of farmland and forest areas show that the NDVI / EVI composite results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (RMSE = 0.105). Compared with the time series of MODIS mod13a2 product, it fully shows that when the time resolution is increased from 16 days to 5 days, a stable and high-precision vegetation index can describe the details of vegetation growth in detail. In a word, the NDVI / EVI data set of Heihe River Basin, which is 1km / 5day, comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products and better serves the application of remote sensing data products.

2020-03-13

HiWATER: 1km/5day compositing Fraction Vegetation Cover (FVC) product of Heihe River Basin

The 1 km / 5-day FVC data set of Heihe River basin provides the 5-day FVC synthesis results from 2011 to 2014. The data uses the data of Terra / MODIS, Aqua / MODIS, and domestic satellites fy3a / MERSI and fy3b / MERSI to build a multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. The whole country is divided into different vegetation divisions and land types, and the conversion coefficient of NDVI and FVC is calculated respectively. The conversion coefficient look-up table and 1km / 5-day synthetic NDVI product production area 1km / 5-day synthetic FVC product are used. In the Heihe River Basin, 1 km / 5-day synthetic FVC products can directly obtain vegetation coverage ratio through high-resolution data to reduce the impact of low-resolution data heterogeneity; in addition, select the typical period of vegetation growth and change, obtain the corresponding growth curve parameters of each pixel by fitting the vegetation index of each pixel time series; and then cooperate with land use map and vegetation classification map, To find the representative uniform pixel of the region to train the conversion coefficient of vegetation index. Compared with the results of high-resolution aster reference FVC in Heihe River Basin, the first step is to aggregate the aster products in Heihe River basin to 1km scale by combining the measured ground data and using the scale up method, and to obtain the aster aggregate FVC data, which is based on spot vegetation remote sensing data released by geoland 2 project (geov1 for short) The results show that the results of geov1 are higher than those of ASTER image combined with ground measurement, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin are between the two, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin in the experimental area are better than those of geov1 products. In a word, the comprehensive utilization of multi-source remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products can better serve the application of remote sensing data products.

2020-03-13

HiWATER: 1km/5day compositing Leaf Area Index (LAI) product of the Heihe River Basin (2010-2014)

The 1 km / 5-day Lai data set of Heihe River basin provides the 5-day Lai synthesis results of 2010-2014. The data uses Terra / MODIS, Aqua / MODIS, as well as domestic satellites fy3a / MERSI and fy3b / MERSI sensor data to build a multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. Multi-source remote sensing data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm first classifies the quality of multi-source data sets, which can be divided into first level data, second level data and third level data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. The purpose of quality evaluation and classification is to provide the basis for the selection of the optimal data set and the design of inversion algorithm flow. Leaf area index product inversion algorithm is designed to distinguish mountain land and vegetation type, using different neural network inversion model. Based on global DEM map and surface classification map, PROSAIL model is used for continuous vegetation such as grassland and crops, and gost model is used for forest and mountain vegetation. Using the reference map generated by the measured ground data of the forests in the upper reaches of Heihe River and the oasis in the middle reaches, and scaling up the corresponding high-resolution reference map to 1km resolution, compared with the Lai product, the product has a good correlation between the farmland and the forest area and the reference value, and the overall accuracy basically meets the accuracy threshold of 0.5%, 20% specified by GCOS. By cross comparing this product with Lais products such as MODIS, geov1 and glass, the accuracy of this Lai product is better than that of similar products compared with reference value. In a word, the synthetic Lai data set of 1km / 5 days in Heihe River Basin comprehensively uses multi-source remote sensing data to improve the estimation accuracy and time resolution of Lai parameter products, so as to better serve the application of remote sensing data products.

2020-03-13

The experimental data of water consumption and water consumption pattern of desert plants (2011)

A small lysimeter was made by ourselves, which simulated the natural conditions and selected typical desert plants as the object to study the water consumption and its law. Repeat 3 times for each plant.

2020-03-12

The data of photosynthetic organ level gas exchange measurements of desert plants (2011)

In the middle of July, 2011, 1. Elaeagnus angustifolia, 2. Blister. Using Li-6400 portable photosynthesis system (li-cor, USA) and li-3100 leaf area meter, the photosynthetic physiological characteristics of desert plants were observed. The symbols in the observation data have the following meanings: Obs, number of observations;Photo, net photosynthetic rate, moles of CO2 times m minus 2 times s minus 1; Cond, stomatal conductance, mol H2O•m -- 2•s -- 1;Ci, intercellular CO2 concentration, moles of CO2 times mol-1; Trmmol, transpiration rate, mmol H2O•m -- 2•s -- 1;Vpdl, water vapor pressure deficit, kPa; Area, leaf Area, cm2;Tair, atmospheric temperature, ℃; Tleaf, leaf surface temperature, ℃;CO2R, CO2 concentration in the reference chamber, moles of CO2•mol-1; CO2S, sample chamber CO2 concentration, moles of CO2•mol-1;H2OR, water in the reference chamber, mmol H2O•mol-1; H2OS, sample chamber moisture, mmol H2O•mol-1;PARo, photon flux density, mole •m -- 2•s -- 1; Rh-r, reference room air relative humidity, %;Rh-s, relative humidity of air in sample room, %; PARi, photosynthetic effective radiation, moles •m -- 2•s -- 1;Press, atmospheric pressure, kPa; Others are the state parameters of the instrument at the time of measurement.

2020-03-12

Datasets of rainfall characteristics for intceotion of alpine shrubs in Hulu Watershed in the upstream of Heihe River Basin

This data set is the precipitation characteristic data in the precipitation interception data of alpine shrub in hulugou basin in the upper reaches of Heihe River in 2012. The observation date is from October 2, 2011 to September 24, 2012. The observation contents include precipitation, precipitation duration, precipitation intensity and frequency of throughfall. The observation data are recorded by self recording rain gauge and artificial rain gauge.

2020-03-11

Manual observation of meteorological data in Hulugou sub-basin of Heihe River Basin (2011)

1. Data overview In 2011, the manual observation data set of standard meteorological field of Qilian station was used to observe various meteorological elements at 8:00, 14:00 and 20:00 every day. 2. Data content Data content includes dry bulb temperature, wet bulb temperature, maximum temperature, minimum temperature, surface temperature (0cm), shallow surface temperature (5cm, 10cm, 15cm, 20cm), maximum ground temperature and minimum ground temperature. 3. Time and space Geographic coordinates: longitude: 99.9e; latitude: 38.3n; altitude: 2980m

2020-03-11

Ground water level dataset in Hulugou sub-basin of Heihe River Basin

1. Data overview: This data set is the daily scale groundwater level data of Qilian station from November 1, 2011 to December 31, 2011. In October 2011, two groundwater monitoring wells were arranged in hulugou small watershed. Well 1 is located beside the general control hydrological section of hulugou watershed, with a depth of 12.8m and an aperture of 12cm. Well 2 is located in the east of the Delta, about 100m away from the river, with a depth of 14.7m and an aperture of 12cm. 2. Data content: U20hobo water level sensor is arranged in the groundwater well, which is mainly used to monitor the change of groundwater level and temperature in hulugou small watershed. The data content is the temperature and atmospheric pressure inside the hole, and the data is the daily scale data. 3. Space time scope: Geographic coordinates of well 1: longitude: longitude: 99 ° 53 ′ E; latitude: 38 ° 16 ′ n; altitude: 2974m (near the hydrological section at the outlet of the basin). Geographic coordinates of well 2: longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3204.1m (east side of the East Branch of the delta).

2020-03-11