Vegetation cover data set of Altun mountain national key prevention area in 2022

English name

CSTR

CSTR:11738.11.NCDC.HHSTBC.DB4002.2023

DOI

10.12072/ncdc.hhstbc.db4002.2023

Share type

Apply to Access

Category

Soil and Water Conservation

contributors

Datasets description

 <p>The vegetation coverage data set of national key prevention areas in Altun Mountain in 2022 includes the statistical table of forest and grass vegetation coverage in Ruoqiang county and Qiemo County of Xinjiang Uygur Autonomous Region in 2022, which is based on the processing of satellite remote sensing image with spatial resolution of 2m. The saved format is xlsx. The data name adopts the form of "key management area + year + vegetation coverage statistical table", such as“ ×× Key governance areas ×× Statistical table of annual vegetation coverage. The vegetation coverage is divided into five levels: high coverage, medium high coverage, medium coverage, medium low coverage and low coverage.</p>

Base information

collect time	2021/01/01 - 2021/12/31
collect place	Altun mountain national key prevention area
data size	66.4 KiB

Data source description

                                                                                                                         <p>The 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.</p>

Data processing method

                                                                                                                         <p>Based on the method of remote sensing estimation, the normalized vegetation index (NDVI) is used to estimate the vegetation coverage by using the pixel dichotomy model. The method is to first calculate the NDVI of each pixel using the near infrared band and red band data of multispectral images, and then use the model to calculate the vegetation coverage of the whole region. Then the land use type data from remote sensing interpretation and the vegetation coverage data from remote sensing estimation are superimposed to obtain the vegetation coverage information of each pixel. Finally, according to the classification rules, the vegetation coverage was classified, and the statistical table of forest and grass vegetation coverage was obtained.</p>

Data quality description

                                                                                                                                             <ol>

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

In order to protect the rights and interests of the platform's scientific and technological resources, expand the services of the platform center, and enhance the application potential of scientific and technological resources, resource users are requested to mark and quote the research results (including published papers, treatises, data products, unpublished research reports, data products, etc.) generated by the use of resources in the following manner.

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 cover data set of Altun mountain national key prevention area in 2022. National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2023. https://cstr.cn/CSTR:11738.11.NCDC.HHSTBC.DB4002.2023.
. Vegetation cover data set of Altun mountain national key prevention area in 2022. National Cryosphere Desert Data Center(http://www.ncdc.ac.cn), 2023. https://www.doi.org/10.12072/ncdc.hhstbc.db4002.2023.

EndnoteEN BibtexEN RISEN

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 cover data set of Altun mountain national key prevention area in 2020
2	Vegetation cover data set of Altun mountain national key prevention area in 2018
3	Vegetation cover data set of national key prevention area in Altun Mountain in 2019
4	Vegetation cover data set of Altun mountain national key prevention area in 2020
5	Data set of soil and water conservation measures in national key prevention area of Altun Mountain in 2023
6	Data set of soil and water conservation measures in national key prevention area of Altun Mountain in 2024
7	Soil erosion data set of Altun mountain national key prevention area in 2022
8	Vegetation coverage data set of Altay national key prevention area in 2022
9	Data set of soil and water conservation measures in national key prevention area of Altun Mountain in 2022
10	Data set of soil erosion plots in national key prevention area of Altun Mountain in 2022

#	title	file size
1	2022年黄河流域（片）阿尔金山国家级重点预防区植被覆盖度图.docx	66.4 KiB

add comment

Scan and browse on mobile

How to get the data

Theme:
Statistical table of vegetation coverage
Time:
2022
Place:
Ruoqiang County

east

west

south

north

Export metadata

Contact information

contributors:
author:: LI Suoya
manager:: Li Suya

Platform Service information

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