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Global land cover mapping at 30 m resolution: A POK-based operational approach

Lookup NU author(s): Professor Jon MillsORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products.Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. To handle the classification process of 10 land cover types, a split-and-merge strategy was employed, i.e. firstly each class identified in a prioritized sequence and then results are merged together. For the identification of each class, a robust integration of pixel-and object-based classification was developed. To improve the quality of the classification results, a knowledge-based interactive verification procedure was developed with the support of web service technology. The performance of the POK-based approach was tested using eight selected areas with differing landscapes from five different continents. An overall classification accuracy of over 80% was achieved. This indicates that the developed POK-based approach is effective and feasible for operational GLC mapping at 30 m resolution. (C) 2014 The Authors. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Publication metadata

Author(s): Chen J, Chen J, Liao AP, Cao X, Chen LJ, Chen XH, He CY, Han G, Peng S, Lu M, Zhang WW, Tong XH, Mills J

Publication type: Article

Publication status: Published

Journal: ISPRS Journal of Photogrammetry and Remote Sensing

Year: 2015

Volume: 103

Pages: 7-27

Print publication date: 01/05/2015

Online publication date: 19/10/2014

Acceptance date: 03/09/2014

Date deposited: 19/08/2015

ISSN (print): 0924-2716

ISSN (electronic): 1872-8235

Publisher: Elsevier


DOI: 10.1016/j.isprsjprs.2014.09.002


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Funder referenceFunder name
2009AA122001/003863 Project of China
41231172National Science Foundation of China