Abstract
By making use of the image data of Landsat8 OLI newly launched by the United States and taking Liaocheng, Shandong Province as an example, we conduct computer correction and enhancement for the remote sensing image data of Liaocheng through the adoption of ENVI (a remote sensing image processing software) to extract information of cultivated land with the methods of visual interpretation, supervised classification and unsupervised classification. The result shows that based on the combination of Band5, 4, 3 and Band6, 5, 2 of Landsat8 OLI data, a relatively satisfactory cultivated land information can be acquired through visual interpretation, interactive methods of supervised classification and unsupervised classification.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Quarmby, N.A., Milnes, M., Hindle, T.L., et al.: The use of multi-temporal NDVI measurements from AVHRR data for crop yield estimation and prediction. Int. J. Remote Sens. 14(2), 199–210 (1993)
Fulu, T., Masayuki, Y., Zhao, Z., et al.: Remote sensing of crop production in China by production efficiency models: models comparisons, estimates and uncertainties. Ecol. Model. 183(4), 385–396 (2005)
Deng, J.-S., Wang, K., Shen, Z.-Q., et al.: Decision tree algorithm of automatically extracting farmland information from SPOT-5 images based on characteristic bands. Trans. Chin. Soc. Agric. Eng. 20(6), 145–148 (2004)
Mesev, V.: The use of census data in urban imagine classification. Photogramm. Eng. Remote Sens. 64(5), 431–438 (1998)
NASA: LDCM Launch. http://www.nass.gov/mission_pages/landsat/launch/index.html. Accessed 18 Apr 2013
NASA: A Closer Look at LDCM’s First Scene. http://www.nasa.gov/mission_pageslandsat/news/first-images-feature.html. Accessed 18 Apr 2013
Qian, H.-s.: Selection of the optimum temporal for crop estimation using remote sensing data: main food crops in China. Acta Ecologica Sinica 18(1), 48–55 (1998). (in Chinese with English abstract)
Wang, Y.-l., Ma, Z.: Visual interpretation TM image land use classification by applied the software of ENVI. Mod. Surv. Mapp. 34(1), 11–13 (2011)
Zhao, G.-x., Dou, Y.-x., Tian, W.-x., et al.: Study on automatic abstraction methods of cultivated land information from satellite Remote Sensing Images. Scientia Geographica Sinica 21(4), 224–229 (2001)
Acknowledgment
Funds for this research was provided by the Special Public Welfare Industry (agriculture) Research project – Huang Huai Basin Wheat Corn Rice Field with Water Section Fertilizer Medicine Comprehensive Technology Solutions and Shandong Province Agriculture Major Application of Technology Innovation Project – Wheat Disease Early Information Quickly Identify Key Technology Research and Application.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 IFIP International Federation for Information Processing
About this paper
Cite this paper
Niu, L., Cui, T., Sun, J., Zhang, X. (2019). Application of the Data from Landsat8 OLI - The New Generation of Landsat Series in the Cultivated Land Information Extraction. In: Li, D. (eds) Computer and Computing Technologies in Agriculture X. CCTA 2016. IFIP Advances in Information and Communication Technology, vol 509. Springer, Cham. https://doi.org/10.1007/978-3-030-06155-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-06155-5_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-06154-8
Online ISBN: 978-3-030-06155-5
eBook Packages: Computer ScienceComputer Science (R0)
