Vegetation coverage data set of Liupanshan national key prevention area in Ziwuling in 2023

English name

CSTR

CSTR:11738.11.NCDC.HHSTBC.DB6643.2024

DOI

10.12072/ncdc.hhstbc.db6643.2024

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Category

Soil and Water Conservation

contributors

Datasets description

 <p>The vegetation coverage data set of Liupanshan national key prevention area in Ziwuling in 2023 includes Yaozhou District, Wangyi District, Yintai District, Yijun County, Chencang District, Longxian County, Qianyang County, Linyou County, Binxian County, Changwu County, Xunyi County, Chunhua County, Ganquan County, Fuxian County, Luochuan County, Huanglong County, Huangling County, Qingshui County, Zhangjiachuan county, Kongtong District, Chongxin County, Huating County in Gansu Province The statistical tables of vegetation coverage in Jingning County, Zhengning County, Longde County and Jingyuan County of Ningxia Hui Autonomous Region in 2023 are obtained by processing the satellite remote sensing image with spatial resolution of 2m, and the storage format is xlsx. /p>

Base information

collect time	2021/01/01 - 2021/12/31
collect place	Ziwuling Liupanshan national key prevention area
data size	4.8 MiB

Data source description

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The data sources of land use are ZY-3 and Gao FEN-1 satellite images, which are mainly obtained from the information center of the Ministry of water resources. 2. Vegetation data sources are ZY-3 and Gao FEN-1 satellite images, which are mainly obtained from the information center of the Ministry of water resources. 3.1:50000 DEM is mainly obtained from the information center of the Ministry of water resources.

Data processing method

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Based on the thematic maps of land use, vegetation coverage and slope, the soil erosion intensity was graded by ArcGIS software. 2. The land use processing method is based on ecognition software platform, using the method of object-oriented computer automatic classification and manual visual interpretation to extract the land use data of the study area year by year. Finally, three methods are used to verify the accuracy of the data: field sample point survey, high-resolution image recognition and Google Earth sample point recognition. 3. The processing method of vegetation coverage is based on remote sensing estimation, and the normalized vegetation index (NDVI) is used to estimate the vegetation coverage by pixel dichotomy model. First, the NDVI of each pixel is calculated by using the near-infrared and red band data of multispectral images. Then, the model is used to calculate the vegetation coverage of the whole region, and the vegetation coverage is classified according to the classification rules. Finally, the land use type data obtained from remote sensing interpretation and the vegetation coverage data obtained from remote sensing estimation are used for superposition operation, The vegetation coverage information of each pixel was obtained. 4. Slope data processing method is based on 1:50000 DEM extraction.

Data quality description

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Remote sensing images are preprocessed by radiation correction, orthorectification, fusion and mosaic. 2. The actual surface area corresponding to the minimum spot area is not less than 0.1 h ^, the polygons have no overlap, no gap, and the spot attributes have no vacancy or redundancy. 3. Before the remote sensing image interpretation, the remote sensing image, typical investigation and field comparison methods are used to establish the remote sensing interpretation marks of forest and grass sample plots. 4. Based on remote sensing images, combined with interpretation marks, extract land use types. 5. Review of interpretation results: no less than 5% of the total map spots shall be selected for verification. 6. The number and results of field verification samples meet the requirements of technical specification for remote sensing monitoring of soil and water conservation (sl592-2012). For verification spots, 10% are selected as verification samples for field verification.

Citations and annotations

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For the achievements published in English, please refer to the following specifications： The dataset is provided by National Cryosphere Desert Data Center. (http://www.ncdc.ac.cn).

Data reference

. Vegetation coverage data set of Liupanshan national key prevention area in Ziwuling in 2023. National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2024. https://cstr.cn/CSTR:11738.11.NCDC.HHSTBC.DB6643.2024.
. Vegetation coverage data set of Liupanshan national key prevention area in Ziwuling in 2023. National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2024. https://www.doi.org/10.12072/ncdc.hhstbc.db6643.2024.

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license agreement

This work is licensed under CC BY 4.0 (Creative Commons Attribution 4.0 International License).

Relevant data
File list

#	Dataset title
1	Vegetation coverage data set of Liupan Mountain National key prevention area in Ziwuling in 2021
2	Vegetation coverage data set of Liupan Mountain National key prevention area in Ziwuling in 2020
3	Vegetation coverage data set of Liupan Mountain National key prevention area in Ziwuling in 2019
4	Vegetation coverage data set of Liupan Mountain National key prevention area in Ziwuling in 2022
5	Vegetation coverage data set of Liupanshan national key prevention area in Ziwuling in 2024
6	Soil erosion data set of Liupanshan national key prevention area in Ziwuling in 2023
7	Data set of soil and water conservation measures in Liupanshan national key prevention area of Ziwuling in 2023
8	Data set of soil erosion plots in national key prevention area of Liupan Mountain in Ziwuling in 2023
9	Soil erosion data set of Liupanshan national key prevention area in Ziwuling in 2021
10	Soil erosion data set of Liupanshan national key prevention area in Ziwuling in 2024

#	title	file size
1	2023年黄河流域（片）子午岭-六盘山预防区植被覆盖度统计图.jpg	4.8 MiB

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How to get the data

Theme:
Statistical table of vegetation coverage
Time:
2023
Place:
Ziwuling Liupanshan national key prevention area

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Platform Service information

contacts:: Li Hongxing
phone:: 0931-4967592
mailbox:: ncdc@lzb.ac.cn