Moose’s Populated Places Dataset Investigated by UAV in Nanwenghe National Nature Reserve
WANG Dongliang1
1 Key Laboratory of Land Surface Pattern and Simulation，Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China
DOI:10.3974/geodb.2022.11.05.V1
Published:Nov. 2022
Visitors：3768 Data Files Downloaded：22
Data Downloaded：5.88 MB Citations：
Key Words：
Nanwenghe National Nature Reserve,wetland,Moose (Alces alces),UAV remote sensing
Abstract：
The Nanwenghe National Nature Reserve is located at the southern foot of Yilehuli Mountain in the Great Khingan Mountains, between 51°05′07″N and 51°39′24″N, 125°07′55″E and 125°50′05″E, with a total area of 2,283.24 km². In the reserve, the distribution core area of moose is 542.48 km². The survey was carried out from March 24 to April 1, 2022. Based on the fixed wing UAV platform, the author investigated the population number of moose in Nanwenghe National Nature Reserve in Heilongjiang Province. 17,818 UAV aerial images were obtained, and the effective area of the spliced digital orthophoto map reached 206.9 km². Then the Moose’s populated places were interpreted. The dataset includes: (1) boundary data of the protected area and the distribution core area of moose; (2) Moose’s populated places data. The dataset is archived in .shp format, and consists of 21 files with data size of 463 KB (Compressed into one file with 273 KB).
Foundation Item：
Ministry of Science and Technology of the People's Republic of China (2021xjkk1402)
Data Citation：
WANG Dongliang. Moose’s Populated Places Dataset Investigated by UAV in Nanwenghe National Nature Reserve[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.11.05.V1.
References：
[1] Luo, W., Shao, Q. Q., Wang, D. L., et al. An object-oriented classification method for detection of large wild herbivores: a case study in the source region of Three Rivers in Qinghai [J]. Chinese Journal of Wildlife, 2017, 38(4): 561-564.
[2] Hodgson, J. C., Mott, R., Baylis, S. M., et al. Drones count wildlife more accurately and precisely than humans [J]. Methods in Ecology and Evolution, 2018(9): 1160-1167.
[3] Julie, L., Simon, L., Samuel, Q., et al. UAS imagery reveals new survey opportunities for counting hippos [J]. PLoS ONE, 2018, 13(11): e0206413.
Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 1 |
NWH_Moose.rar |
273.82KB |
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