Geospatial knowledge-based verification and improvement of GlobeLand30

Science China Earth Sciences

Volumn 59, Issue 9, 2016, Pages 1709-1719

  Zhang, WeiWei ^a,b   Chen, Jun ^a   Liao, AnPing ^a   Han, Gang ^a   Chen, XueHong ^c   Chen, LiJun ^a   Peng, Shu ^a   Wu, Hao ^a   Zhang, Jun ^a  

^a NATIONAL GEOMATICS CENTER OF CHINA   (China)

^b SUZHOU UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^c BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Consistency; Data quality; Geospatial knowledge; GlobeLand30; Land cover; Verification

Indexed keywords

MAPPING; VERIFICATION;

CONSISTENCY; DATA QUALITY; GEO-SPATIAL; GLOBELAND30; LAND COVER;

KNOWLEDGE BASED SYSTEMS;

DATA QUALITY; GIS; KNOWLEDGE BASED SYSTEM; LAND COVER; MAPPING METHOD; SPATIAL ANALYSIS; SPATIAL RESOLUTION; WORLD WIDE WEB;

EID: 84975226434     PISSN: 16747313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11430-016-5318-4     Document Type: Article

References (52)

1. Alimujiang K, Tateishi R. 2007. Global urban mapping using coarse resolution remote sensing data with the reference of Landsat imageries. In: The 28th Asian Conference on Remote Sensing. Kuala Lumpur, Malaysia Nov. 12–16
2. Ban Y F, Gong P, Giri C. 2015. Global land cover mapping using Earth observation satellite data: Recent progresses and challenges. ISPRS-J Photogramm Remote Sens, 103: 1–6
3. Bontemps S, Defourney P, Van Bogaert E, Arino O, Kalogirou V, Perez J R. 2011. Globcover2009 Products Description and Validation Report. ESA
4. Brovelli M A, Molinari M E, Hussein E, Chen J, Li R. 2015. The first comprehensive accuracy assessment of GlobeLand30 at a national level: Methodology and results. Remote Sens, 7: 4191–4212
5. Chen J. 1984. The application of DTM in improving classification accuracy of remote sensing imagery (in Chineses). Geom Inform Sci Wuhan Univ, 9: 69–81
6. Chen J, Chen J, Gong P, Liao A P, He C Y. 2011. Higher resolution global land cover mapping (in Chineses). Geom World, 4: 12–14
7. Chen J, Ban Y, Li S. 2014a. China: Open access to Earth land-cover map. Nature, 514: 23
8. Chen J, Chen J, Liao A P, Cao X, Chen L J, Chen X H, Peng S, Han G, Zhang H W, He C Y, Wu H, Lu M. 2014b. Concepts and key techniques for 30 m global land cover mapping (in Chineses). Acta Geod Cartogr Sin, 43: 551–557
9. Chen J, Chen J, Liao A P, Cao X, Chen L J, Chen X H, He C Y, Han G, Peng S, Lu M, Zhang W W, Tong X H, Mills J. 2015. Global land cover mapping at 30 m resolution: A POK-based operational approach. ISPRS-J Photogramm Remote Sens, 103: 7–27
10. Chen J, Dowman I, Li S N, Li Z L, Madden M, Mills J, Paparoditis N, Rottensteiner F, Sester M, Toth C, Trinder J, Heipk C. 2016. Information from imagery: ISPRS scientific vision and research agenda. ISPRS-J Photogram Remote Sens, 115: 3–21
11. Cogley J, Graham. 2010. A more complete version of the world glacier inventory. Ann Glaciol, 50: 32–33
12. Comber A, Fisher P, Wadsworth R. 2004. Integrating land-cover data with different ontologies: Identifying change from inconsistency. Int J Geogr Inf Sci, 18: 691–708
13. Costa H, Carrão H, Bação F, Caetano M. 2014. Combining per-pixel and object-based classifications for mapping land cover over large areas. Int J Remote Sens, 35: 738–753
14. Fang J Y, Song Y C, Liu H Y, Piao S L. 2002. Vegetation-climate relationship and its application in the division of vegetation zone in China. Acta Bot Sin, 44: 1105–1122
15. Gong P. 2009. Assessment of GLC map accuracies using flux net location data (in Chineses). Progr Nat Sci, 19: 754–759
16. Gong P, Wang J, Yu L, Zhao Y C, Zhao Y Y, Liang L, Niu Z G, Huang X M, Fu H H, Liu S, Li C C, Li X Y, Fu W, Liu C X, Xu Y, Wang X Y, Cheng Q, Hu L Y, Yao W B, Zhang H, Zhu P, Zhao, Z Y, Zhang H Y, Zheng Y M, Ji L Y, Zhang Y W, Chen H, Yan A, Guo J H, Yu L, Wang L, Liu X J, Shi T T, Zhu M H, Chen Y L, Yang G W, Tang P, Xu B, Giri C, Clinton N, Zhu Z L, Chen J, Chen J. 2013. Finer resolution observation and monitoring of GLC: First mapping results with Landsat TM and ETM+ data. Int J Remote Sens, 34: 2607–264
17. Giri C, Peng B, Long J, Loveland T R. 2013. Next generation of global land cover characterization, mapping, and monitoring. Int J Appl Earth Obs, 25: 30–37
18. Guide E U. 2008. ENVI on-line Software User’s Manual. ITT Visual Information Solutions
19. Han G, Chen J, He C Y, Li S, Wu H, Liao A, Peng S. 2015. A web-based system for supporting GLC data production. ISPRS-J Photogramm Remote Sens, 103: 66–80
20. Harris P M, Ventura S J. 1995. The integration of geographic data with remotely sensed imagery to improve classification in an urban area. Photogramm Eng Remote Sens, 61: 993–998
21. Hansen M C, Loveland T R. 2012. A review of large area monitoring of land cover change using landsat data. Remote Sens Environ, 122: 66–74
22. Hansen M C, Potapov P V, Moore R, Hancher M, Turubanova S A, Tyukavina A, Thau D, Stehman S V, Goetz S J, Loveland T R, Kommareddy A, Egorov A, Chini L, Justice C O, Townshend J R G. 2013. High-resolution global maps of 21st-century forest cover change. Science, 342: 850–853
23. Herold M, Mayaux P, Woodcock C E, Baccini A, Schmullius C. 2008. Some challenges in GLC mapping: An assessment of agreement and accuracy in existing 1 km datasets. Remote Sens Environ, 112: 2538–2556
24. Homer C, Dewitz J, Fry J, Coan M, Hossain N, Larson C, Herold N, McKerrow A, VanDriel J N, Wickham J. 2007. Completion of the 2001 national land cover database for the conterminous United States. Photogramm Eng Remote Sens, 73: 337–341
25. Hu L Y, Chen Y L, Xu Y, Zhao Y Y, Wang J, Gong P. 2014. A 30 meter land cover mapping of China with an efficient clustering algorithm CBEST. Sci China Earth Sci, 57: 2293–2304
26. Ju J, Gopal S, Kolaczyk E D. 2005. On the choice of spatial and categorical scale in remote sensing land cover classification. Remote Sens Environ, 96: 62–77
27. Judex M, Thamm H P, Menz G. 2006. Improving land-cover classification with a knowledge based approach and ancillary data. In: Process of Workshop of Earsel SIG on Land Useand Land Cover 2006. Bonn, Germany, Sep 28–30. 184–191
28. Kantakumar L N, Kumar S, Schneider K. 2016. Spatiotemporal urban expansion in Pune metropolis, India using remote sensing. Habitat Int, 5: 11–22
29. Liao A P, Chen L J, Chen J, He C Y, Cao X, Chen J, Peng S, Sun F D, Gong P. 2014. High-resolution remote sensing mapping of global land cover. Sci China Earth Sci, 57: 2305–2316
30. Liu J Y, Kuang W H, Zhang Z X, Xu X L, Qin Y W, Ning J, Zhou W C, Zhang S W, Li R D, Yan C Z, Wu S X, Shi X Z, Jiang N, Yu D S, Pan X Z, Chi W F. 2014. Spatiotemporal characteristics, patterns and causes of land use changes in China since the late 1980s (in Chineses). J Geogr Sci, 69: 3–14
31. Lu D, Weng Q. 2007. A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens, 28: 823–870
32. Manandhar R, Odeh I O A, Ancev T. 2009. Improving the accuracy of land use and land cover classification of Landsat data using post-classification enhancement. Remote Sens, 1: 330–344
33. Manakos I, Chatzopoulos-Vouzoglanis K, Petrou Z I, Filchev L, Apostolakis A. 2014. Globalland30 mapping capacity of land surface water in Thessaly, Greece. Land, 4: 1–18
34. Mwaniki W M, Möller S M. 2015. Knowledge based multi-source, time series classification: A case study of central region of Kenya. Appl Geogr, 60: 58–68
35. Mueller-Warrant G W, Whittaker G W, Banowetz G M, Griffith S M, Barnhart B L. 2015. Methods for improving accuracy and extending results beyond periods covered by traditional ground-truth in remote sensing classification of a complex landscape. Int J Appl Earth Obs Geoinf, 38: 115–128
36. Niu Z G, Gong P, Chen X, Guo J H, Wang L, Huang H B, Shen S Q, Wu J Z, Wang X F, Wang X W, Ying Q, Liang L, Zhang L N, Wang L, Yao Q, Yang Z Z, Guo Z Q, Dai Y J. 2009. Geographical characteristics of China’s wetlands derived from remotely sensed data. Sci China Ser D-Earth Sci, 52: 723–738
37. Ramankutty N, Evan A T, Monfreda C, Foley J A. 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob Biogeochem Cycle, 22: 1–19
38. Ran Y H, Li X. 2015. First comprehensive fine-resolution global land cover map in the world from China: Comments on global land cover map at 30-m resolution. Sci China Earth Sci, 58: 1677–1678
39. Shi J C. 2014. Enhancing remote sensing research on global change to improve our understanding on Earth system processes. Sci China Earth Sci, 57: 2281–2282
40. Tong X H, Wang Z H, Xie H, Liang D, Jiang Z, Li J. 2011. Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products. Comput Geosci, 37: 1570–1583
41. Verburg P H, Neumann W, Linda N L. 2011. Challenges in using land use and land cover data for global change studies. Glob Change Biol, 17: 974–989
42. Wang L, Sousa W P, Gong P. 2004. Integration of object-based and pixel- based classification for mapping mangroves with Ikonos imagery. Int J Remote Sens, 25: 5655–5668
43. Wang J, Zhao Y Y, Li C C, Ye L, Liu D S, Gong P. 2015. Mapping global land cover in 2001 and 2010 with spatial-temporal consistency at 250 m resolution. ISPRS-J Photogram Remote Sens, 103: 38–47
44. Whigham D F. 2009. Global distribution, diversity and human alterations of wetland resources. In: Barker T, Maltby E, eds. The Wetlands Handbook. Oxford: Blackwell Publishing Ltd. 43–64
45. Wu J H, Zhang S, Jiang Y, Kang M Y, Qiu Y. 2004. Phytogeography (in Chineses). 4th ed. Beijing: Higher Education Press. 318–327
46. Xu G H, Ge Q S, Gong P, Fang X Q, Cheng B B, He B, Luo Y, Xu B. 2013. Societal response to challenges of global change and human sustainable development. Chin Sci Bull, 58: 3161–3168
47. Yao T D, Thompson L, Yang W, Yu W S, Gao Y, Guo X J, Yang X X, Duan K Q, Zhao H B, Xu B Q, Pu J C, Lu A X, Xiang Y, Kattel D B, Joswiak D. 2012. Different glacier status with atmospheric circulation in Tibetan Plateau and surroundings. Nat Clim Change, 2: 663–667
48. Yu L, Wang J, Li X C, Li C C, Zhao Y Y, Gong P. 2014. A multi- resolution global land cover dataset through multisource data aggregation. Sci China Earth Sci, 57: 2317–2329
49. Zhang J, Wu S H, Liu Y H, Yang Q Y, Zhang Y H. 2007. Simulation of distribution of agricultural output value influenced by land use and topographical indices in Tibet (in Chineses). Trans CSAE, 23: 59–65
50. Zhang W W, Liao A P, Peng S, Zheng X Y, Li M. 2015. Check and modification of GlobeLand30 with MODIS NDVI. In: Process SPIE 9675. AOPC 2015: Image Processing and Analysis, 96750O, doi: 10.1117/12.2197830
51. Zhang Z X, Wang X, Zhao X L, Liu B, Yi L, Zuo L J, Wen Q K, Liu F, Xu J Y, Hu S G. 2014. A 2010 update of National Land Use/Cover Database of China at 1:100000 scale using medium spatial resolution satellite images. Remote Sens Environ, 149: 142–154
52. Zhang Z X, Zhao X L, Wang X. 2012. Monitor of land Use of China Using Remote Sensing (in Chineses). Beijing: Start Map Press. 63–70