Are there sufficient Landsat observations for retrospective and continuous monitoring of land cover changes in China?

Remote Sensing

Volumn 11, Issue 15, 2019, Pages

  Zhou, Yan ^a,b   Dong, Jinwei ^b   Liu, Jiyuan ^b   Metternicht, Graciela ^c   Shen, Wei ^a   You, Nanshan ^b   Zhao, Guosong ^b   Xiao, Xiangming ^d  

^a CHINA UNIVERSITY OF GEOSCIENCES   (China)

^b INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

^c UNIVERSITY OF NEW SOUTH WALES   (Australia)

^d UNIVERSITY OF OKLAHOMA   (United States)

Author keywords

China; Continuous monitoring; Data availability; Google Earth Engine (GEE); Land cover changes; Landsat

Indexed keywords

ENGINES; MONITORING;

CHINA; CONTINUOUS MONITORING; DATA AVAILABILITY; GOOGLE EARTHS; LAND-COVER CHANGE; LANDSAT;

LANDFORMS;

EID: 85070446547     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs11151808     Document Type: Article

References (52)

1. Armesto, J.J.; Manuschevich, D.; Mora, A.; Smith-Ramirez, C.; Rozzi, R.; Abarzua, A.M.; Marquet, P.A. From the Holocene to the Anthropocene: A historical framework for land cover change in southwestern South America in the past 15,000 years. Land Use Policy 2010, 27, 148-160
2. Dong, J.W.; Kuang, W.H.; Liu, J.Y. Continuous land cover change monitoring in the remote sensing big data era. Sci. China Earth Sci. 2017, 60, 2223-2224
3. Xiao, C.; Li, P.; Feng, Z.;Wu, X. Spatio-temporal differences in cloud cover of Landsat-8 OLI observations across China during 2013-2016. J. Geogr. Sci. 2018, 28, 429-444
4. Xu, N.; Gong, P. Significant coastline changes in China during 1991-2015 tracked by Landsat data. Sci. Bull. 2018, 63, 883-886
5. Liu, J.; Kuang, W.; Zhang, Z.; Xu, X.; Qin, Y.; Jia, N.; Zhou, W.; Zhang, S.; Li, R.; Yan, C.; et al. Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s. J. Geogr. Sci. 2014, 24, 195-210
6. Chang, B.; Li, R.; Zhu, C.; Liu, K. Quantitative Impacts of Climate Change and Human Activities on Water-Surface Area Variations from the 1990s to 2013 in Honghu Lake, China. Water 2015, 7, 2881-2899
7. Friedl, M.A.; McIver, D.K.; Hodges, J.C.F.; Zhang, X.Y.; Muchoney, D.; Strahler, A.H.; Woodcock, C.E.; Gopal, S.; Schneider, A.; Cooper, A.; et al. Global land cover mapping from MODIS: Algorithms and early results. Remote Sens. Environ. 2002, 83, 287-302
8. Foley, J.A.; Ruth, D.; Asner, G.P.; Carol, B.; Gordon, B.; Carpenter, S.R.; Chapin, F.S.; Coe, M.T.; Daily, G.C.; Gibbs, H.K.; et al. Global consequences of land use. Science 2005, 309, 570-574
9. 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.; et al. Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. Int. J. Remote Sens. 2013, 34, 2607-2654
10. Gong, P.; Liu, H.; Zhang, M.; Li, C. Stable classification with limited sample: Transferring a 30-m resolution sampleset collected in 2015 to mapping 10-m resolution global land cover in 2017. Sci. Bull. 2019, 64, 370-373
11. Azzari, G.; Lobell, D.B. Landsat-based classification in the cloud: An opportunity for a paradigm shift in land cover monitoring. Remote Sens. Environ. 2017, 202, 64-74
12. Liu, J.; Ning, J.; Kuang, W.; Xu, X.; Zhang, S.; Yan, C.; Li, R.; Wu, S.; Hu, Y.; Du, G.; et al. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015. Acta Geogr. Sin. 2018, 73, 789-802
13. Chen, J.; Chen, J.; Liao, A.; Cao, X.; Chen, L.; Chen, X.; He, C.; Han, G.; Peng, S.; Lu, M.; et al. Global land cover mapping at 30 m resolution: A POK-based operational approach. Isprs J. Photogramm. Remote Sens. 2015, 103, 7-27
14. Wu, B.; Yuan, Q.; Yan, C.; Wang, Z.; Yu, X.; Li, A.; Ma, R.; Huang, J.; Chen, J.; Chang, C. Land Cover Changes of China From 2000 to 2010. Quat. Sci. 2014, 34, 723-731
15. Lambin, E.F.; Geist, H.J. Land-Use and Land-Cover Change: Local Processes and Global Impacts; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2006; Volume 18
16. Grübler, A. Changes in Land Use and Land Cover: A Global Perspective; Cambridge University Press: Cambridge, UK, 1994; pp. 287-328
17. Turner, B.L.; Meyer, W.B. Global Land-Use and Land-Cover Change: An Overview; Cambridge University Press: Cambridge, UK, 1994; pp. 3-10
18. Dong, J.; Metternicht, G.; Hostert, P.; Fensholt, R.; Chowdhury, R.R. Remote sensing and geospatial technologies in support of a normative land system science: Status and prospects. Curr. Opin. Environ. Sustain. 2019, 38, 44-52
19. Guo, H.D.; Wang, L.Z.; Liang, D. Big Earth Data from space: A new engine for Earth science. Sci. Bull. 2016, 61, 505-513
20. Zhu, Z.; Wulder, M.A.; Roy, D.P.; Woodcock, C.E.; Hansen, M.C.; Radeloff, V.C.; Healey, S.P.; Schaaf, C.; Hostert, P.; Strobl, P.; et al. Benefits of the free and open Landsat data policy. Remote Sens. Environ. 2019, 224, 382-385
21. Hermosilla, T.;Wulder, M.A.; White, J.C.; Coops, N.C.; Hobart, G.W.; Campbell, L.B. Mass data processing of time series Landsat imagery: Pixels to data products for forest monitoring. Int. J. Digit. Earth 2016, 9, 1035-1054
22. White, J.C.;Wulder, M.A. The Landsat observation record of Canada: 1972-2012. Can. J. Remote Sens. 2014, 39, 455-467
23. Wulder, M.A.; White, J.C.; Loveland, T.R.; Woodcock, C.E.; Belward, A.S.; Cohen, W.B.; Fosnight, E.A.; Shaw, J.; Masek, J.G.; Roy, D.P. The global Landsat archive: Status, consolidation, and direction. Remote Sens. Environ. 2016, 185, 271-283
24. Markham, B.L.; Helder, D.L. Forty-year calibrated record of earth-reflected radiance from Landsat: A review. Remote Sens. Environ. 2012, 122, 30-40
25. Wulder, M.A.; White, J.C.; Goward, S.N.; Masek, J.G.; Irons, J.R.; Herold, M.; Cohen,W.B.; Loveland, T.R.; Woodcock, C.E. Landsat continuity: Issues and opportunities for land cover monitoring. Remote Sens. Environ. 2008, 112, 955-969
26. Zhu, Z.;Woodcock, C.E. Continuous change detection and classification of land cover using all available Landsat data. Remote Sens. Environ. 2014, 144, 152-171
27. Zhu, Z.; Zhang, J.; Yang, Z.; Aljaddani, A.H.; Cohen, W.B.; Qiu, S.; Zhou, C. Continuous monitoring of land disturbance based on Landsat time series. Remote Sens. Environ. 2019
28. Wulder, M.A.; Loveland, T.R.; Roy, D.P.; Crawford, C.J.; Masek, J.G.; Woodcock, C.E.; Allen, R.G.; Anderson, M.C.; Belward, A.S.; Cohen, W.B.; et al. Current status of Landsat program, science, and applications. Remote Sens. Environ. 2019, 225, 127-147
29. Dwyer, J.L.; Roy, D.P.; Sauer, B.; Jenkerson, C.B.; Zhang, H.K.K.; Lymburner, L. Analysis Ready Data: Enabling Analysis of the Landsat Archive. Remote Sens. 2018, 10, 1363
30. Zhu, Z.; Fu, Y.C.; Woodcock, C.E.; Olofsson, P.; Vogelmann, J.E.; Holden, C.; Wang, M.; Dai, S.; Yu, Y. Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000-2014). Remote Sens. Environ. 2016, 185, 243-257
31. Dong, J.; Xiao, X.; Chen, B.; Torbick, N.; Jin, C.; Zhang, G.; Biradar, C. Mapping deciduous rubber plantations through integration of PALSAR and multi-temporal Landsat imagery. Remote Sens. Environ. 2013, 134, 392-402
32. Liu, R.; Yang, L. Generation of new cloud masks from MODIS land surface reflectance products. Remote Sens Environ 2013, 133, 21-37
33. Whitcraft, A.K.; Vemiote, E.F.; Becker-Reshef, I.; Justice, C.O. Cloud cover throughout the agricultural growing season: Impacts on passive optical earth observations. Remote Sens. Environ. 2015, 156, 438-447
34. Zhu, Z.;Woodcock, C.E. Automated cloud, cloud shadow, and snow detection in multitemporal Landsat data: An algorithm designed specifically for monitoring land cover change. Remote Sens. Environ. 2014, 152, 217-234
35. Zhu, Z. Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications. Isprs J. Photogramm. Remote Sens. 2017, 130, 370-384
36. Zhu, Z.; Wang, S.X.; Woodcock, C.E. Improvement and expansion of the Fmask algorithm: Cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel 2 images. Remote Sens. Environ. 2015, 159, 269-277
37. Zou, Z.; Xiao, X.; Dong, J.; Qin, Y.; Doughty, R.B.; Menarguez, M.A.; Zhang, G.; Wang, J. Divergent trends of open-surface water body area in the contiguous United States from 1984 to 2016. Proc. Natl. Acad. Sci. USA 2018, 115, 3810-3815
38. Sano, E.E.; Ferreira, L.G.; Asner, G.P.; Steinke, E.T. Spatial and temporal probabilities of obtaining cloud-free Landsat images over the Brazilian tropical savanna. Int. J. Remote Sens. 2007, 28, 2739-2752
39. Whitcraft, A.K.; Becker-Reshef, I.; Justice, C.O.AFramework for Defining Spatially Explicit Earth Observation Requirements for a Global Agricultural Monitoring Initiative (GEOGLAM). Remote Sens. 2015, 7, 1461-1481
40. Whitcraft, A.K.; Becker-Reshef, I.; Killough, B.D.; Justice, C.O. Meeting Earth Observation Requirements for Global Agricultural Monitoring: An Evaluation of the Revisit Capabilities of Current and Planned Moderate Resolution Optical Earth Observing Missions. Remote Sens. 2015, 7, 1482-1503
41. Chen, X.; Hu, B.; Yu, R. Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China. Glob. Chang. Biol. 2005, 11, 1118-1130
42. Zhang, Z.;Wang, X.; Zhao, X.; Liu, B.; Yi, L.; Zuo, L.;Wen, Q.; Liu, F.; Xu, J.; Hu, S. A 2010 update of National Land Use/Cover Database of China at 1:100000 scale using medium spatial resolution satellite images. Remote Sens. Environ. 2014, 149, 142-154
43. Asner, G.P. Cloud cover in Landsat observations of the Brazilian Amazon. Int. J. Remote Sens. 2001, 22, 3855-3862
44. Lu, D.; Batistella, M.; Moran, E. Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon. Photogramm. Eng. Remote Sens. 2015, 74, 157-169
45. Ju, J.; Roy, D.P. The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally. Remote Sens. Environ. 2008, 112, 1196-1211
46. Wulder, M.A.; Hilker, T.; White, J.C.; Coops, N.C.; Masek, J.G.; Pflugmacher, D.; Crevier, Y. Virtual constellations for global terrestrial monitoring. Remote Sens. Environ. 2015, 170, 62-76
47. Zhang, W.; Li, A.; Jin, H.; Bian, J.; Zhang, Z.; Lei, G.; Qin, Z.; Huang, C. An Enhanced Spatial and Temporal Data Fusion Model for Fusing Landsat and MODIS Surface Reflectance to Generate High Temporal Landsat-Like Data. Remote Sens. 2013, 5, 5346-5368
48. Houborg, R.; McCabe, M.F. Daily Retrieval of NDVI and LAI at 3 m Resolution via the Fusion of CubeSat, Landsat, and MODIS Data. Remote Sens. 2018, 10, 890
49. Sidhu, N.; Pebesma, E.; Camara, G. Using Google Earth Engine to detect land cover change: Singapore as a use case. Eur. J. Remote Sens. 2018, 51, 486-500
50. Griffiths, P.; Nendel, C.; Hostert, P. Intra-annual reflectance composites from Sentinel-2 and Landsat for national-scale crop and land cover mapping. Remote Sens. Environ. 2019, 220, 135-151
51. 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.; et al. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 2013, 342, 850-853
52. Pekel, J.F.; Cottam, A.; Gorelick, N.; Belward, A.S. High-resolution mapping of global surface water and its long-term changes. Nature 2016, 540, 418-422