This dataset includes raster data on the entrance density of plateau rat and rabbit caves in the Sanjiangyuan area (unit: pieces) and the proportion of bare land caused by rat and rabbit disturbances (unit:%). The data reflects the average state of the growing season (June September) from 2015 to 2018, with a spatial resolution of 1km p>
collect time | 2015/07/01 - 2018/08/31 |
---|---|
collect place | Sanjiangyuan |
altitude | 2568.0m - 6535.0m |
data size | 2.0 MiB |
data format | TIFF |
Coordinate system | WGS84 |
This dataset is based on our self-developed random model to simulate production p>
Regarding the simulation of rat hole density for plateau pika, firstly, based on the species distribution model of Bayesian additive regression tree, the suitable habitat for plateau pika was simulated. The suitable habitat reflects the habitat preferences of plateau pika in different regional environments, providing key prior information for simulating rat hole density at the regional scale. We have independently developed a new stochastic model that fully utilizes the existing rat hole density survey data in the Three River Source Area, and combines it with the spatial distribution probability provided by suitable habitats to simulate the rat hole density in the Three River Source Area at a scale of 1km. The naked spot data of mice and rabbits is estimated by fitting the statistical relationship between mouse hole density and bare ground ratio using drone data, combined with simulated mouse hole density. We fitted three statistical relationships, representing low bare spot, medium bare spot, and high bare spot, respectively. The vegetation coverage data from satellite remote sensing is used to determine the statistical relationships between different regions. For more details, please refer to our paper by Chen et al. 2024 published in GRL p>
The data provider fully utilizes existing field survey data and drone data, combined with models for regional simulation. At the same time, based on satellite remote sensing data, accuracy checks and outlier removal are performed on the simulation results, and the final data can better reflect the real world situation p>
# | number | name | type |
1 | 2019QZKK0905 | National key R & D plan | |
2 | 2022YFF0711703 | National key R & D plan |
# | title | file size |
---|---|---|
1 | data.zip | 2.0 MiB |
©Copyright 2005-. Northwest Institute of Eco-Environment and Resources, CAS.
Donggang West Road 320, Lanzhou, Gansu, China (730000)