1:100000 landuse dataset of Gansu province (1995)

1:100000 landuse dataset of Gansu province (1995)


This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment".

According to the 1:100,000 landuse data of gansu province, a hierarchical land cover classification system is adopted, which divides the whole country into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.


File naming and required software

File name: data is stored in vector SHP format, file name "Gansu-1995";
Data reading: Arcgis, Qgis and other remote sensing software can be used to open and read.


Data Citations Data citation guideline What's data citation?
Cite as:

Liu, J., Zhuang, D., Wang, J., Zhou, W., Wu, S. (2013). 1:100000 landuse dataset of Gansu province (1995). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Socioeco.tpdc.270643. CSTR: 18406.11.Socioeco.tpdc.270643. (Download the reference: RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.


References literature

1.Liu, J.Y., Liu, M.L., Zhuang, D.F., Zhang, Z.X., & Deng, X.Z. (2003). Study on spatial pattern of land-use change in China during 1995—2000, Science in China (D), 46(4), 373-384. (View Details | Download )

2.Li, Z. , Shao, Q. , Xu, Z. , & Cai, X. . (2010). Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method: a case study of swat model applied to yingluoxia watershed in northwest china. Journal of Hydrology (Amsterdam), 385(1-4), 76-83. (View Details )

3.Li, Z. , Xu, Z. , Shao, Q. , & Yang, J. . (2009). Parameter estimation and uncertainty analysis of swat model in upper reaches of the heihe river basin. Hydrological Processes, 23(19), 2744-2753. (View Details )

4.Liu, J., & Deng, X. (2010). Progress of the research methodologies on the temporal and spatial process of LUCC. Chinese Science Bulletin. 55, 1354–1362. https://doi.org/10.1007/s11434-009-0733-y. (View Details )

5.Li Z, Xu Z, Li Z. Performance of WASMOD and SWAT on hydrological simulation in Yingluoxia watershed in northwest of China[J]. Hydrological Processes, 2011, 25(13): 2001–2008. doi:10.1002/hyp.7944 (View Details )


Copyright & License

To respect the intellectual property rights, protect the rights of data authors, expand services of the data center, and evaluate the application potential of data, data users should clearly indicate the source of the data and the author of the data in the research results generated by using the data (including published papers, articles, data products, and unpublished research reports, data products and other results). For re-posting (second or multiple releases) data, the author must also indicate the source of the original data.


License: This work is licensed under an Attribution 4.0 International (CC BY 4.0)


Related Resources
Comments

Current page automatically show English comments Show comments in all languages

Download Follow
Keywords
Geographic coverage
East: 109.00 West: 92.00
South: 32.00 North: 42.00
Details
  • Temporal resolution: Yearly
  • Spatial resolution: 10m - 100m
  • File size: 177 MB
  • Views: 7192
  • Downloads: 24
  • Access: Requestable
  • Temporal coverage: 1995-01-08 To 1996-01-07
  • Updated time: 2021-04-19
Contacts
: LIU Jiyuan   ZHUANG Dafang   WANG Jianhua   ZHOU Wancun   WU Shixin  

Distributor: A Big Earth Data Platform for Three Poles

Email: poles@itpcas.ac.cn

Export metadata