Share This Article:

Comparison of a New Percent Tree Cover Dataset with Existing One and Categorical Land Cover Datasets in Eurasia

Full-Text HTML Download Download as PDF (Size:1008KB) PP. 345-357
DOI: 10.4236/ars.2013.24037    4,163 Downloads   6,137 Views   Citations

ABSTRACT

The global tree cover percentage is an important parameter used to understand the global environment. However, the available percent tree cover products on global or continental-scale are few, and efforts to quantitatively validate these maps have been limited. We produced a new percent tree cover dataset at 500 m resolution in 2008 for Eurasia using reference data interpreted from Google Earth. It is a part of percent tree cover (PTC) data in Global Mapping project. In this study, the dataset was compared with existing global percent tree cover dataset, MODIS Vegetation Continuous Fields, MOD44B. We assessed the agreement of these datasets with two existing global categorical land cover datasets and statistic data in Eurasia. The result showed that estimates of tree cover in our new map and MOD44B were relatively similar at randomly sampled sites. Our map and MOD44B agreed with either or both of land cover maps at 93% of sites and 91% of sites, respectively, for pixel blocks. However, we found that MOD44B disagreed with our map and categorical land cover datasets at about half of the sampled sites where the difference of tree cover percentage between our map and MOD44B was large, especially in the areas with significant differences (more than 50%). Disagreed areas were concentrated in forests of Russia and Indonesia, and in herbaceous dominated vegetation of UK and Ireland. We also found that both our map and MOD44B were somewhat different from the data reported by FRA 2010.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

T. Kobayashi and R. Tateishi, "Comparison of a New Percent Tree Cover Dataset with Existing One and Categorical Land Cover Datasets in Eurasia," Advances in Remote Sensing, Vol. 2 No. 4, 2013, pp. 345-357. doi: 10.4236/ars.2013.24037.

References

[1] FAO (Food and Agriculture Organization of the United Nations), “Forest Resources Assessment Programme Working Paper 33: FRA 2000 on Definitions of Forest and Forest Change,” FAO, Rome, 2000.
[2] FAO (Food and Agriculture Organization of the United Nations), “Global Forest Resources Assessment 2000 Main Report,” FAO, Rome, 2001.
[3] R. S. DeFries, M. C. Hansen and J. R. G. Townshend, “Global Continuous Fields of Vegetation Characteristics: a Linear Mixture Model Applied to Multi-Year 8 km AVHRR Data,” International Journal of Remote Sensing, Vol. 21, No. 6-7, 2000, pp. 1389-1414.
http://dx.doi.org/10.1080/014311600210236
[4] R. S. DeFries, M. C. Hansen, J. R. G. Townshend, A. C. Janetos and T. R. Loveland, “A New Global 1-km Dataset of Percentage Tree Cover Derived from Remote Sensing,” Global Change Biology, Vol. 6, No. 2, 2000, pp. 247-254.
http://dx.doi.org/10.1046/j.1365-2486.2000.00296.x
[5] M. C. Hansen, R. S. DeFries, J. R. G. Townshend, M. Carroll, C. Dimiceli and R. A. Sohlberg, “Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm,” Earth Interactions, Vol. 7, No. 10, 2003, pp. 115.
http://dx.doi.org/10.1175/1087-3562(2003)007<0001:GPTCAA>2.0.CO;2
[6] Rokhmatuloh, D. Nitto, H. Al-Bilbisi, K. Arihara and R. Tateishi, “Estimating Percent of Tree Cover Using Regression Tree Method with Very-High-Resolution QuickBird Images as Training Data,” Journal of the Remote Sensing Society of Japan, Vol. 27, No. 1, 2007, pp. 1-12.
[7] R. Rokhmatuloh, R. Tateishi, H. Al-Bilbisi, K. Arihara, T. Kobayashi, D. Nitto, et al., “Global Percent Tree Cover Mapping Using Regression Tree Method: An Advantage of QuickBird Images as Training Data,” Asian Journal of Geoinformatics, Vol. 10, No. 2, 2010, pp. 21-28.
[8] Geospatial Information Authority of Japan, Chiba University and Collaborating Organizations, “Global Map— Global Land Cover (GLCNMO), Global Map—Percent Tree Cover [Dataset],” 2008.
http://www.iscgm.org/login.html
[9] S. Berberoglu, O. Satir and P. M. Atkinson, “Mapping Percentage Tree Cover from Envisat MERIS Data Using Linear and Nonlinear Techniques,” International Journal of Remote Sensing, Vol. 30, No. 18, 2009, pp. 4747-4766.
http://dx.doi.org/10.1080/01431160802660554
[10] J. Heiskanen and S. Kivinen, “Assessment of Multispectral, -Temporal and -Angular MODIS Data for Tree Cover Mapping in the Tundra-Taiga Transition Zone,” Remote Sensing of Environment, Vol. 112, No. 5, 2008, pp. 2367-2380. http://dx.doi.org/10.1016/j.rse.2007.11.002
[11] M. Schwarz and N. E. Zimmermann, “A New GLMBased Method for Mapping Tree Cover Continuous Fields Using Regional MODIS Reflectance Data,” Remote Sensing of Environment, Vol. 95, No. 4, 2005, pp. 428-443. http://dx.doi.org/10.1016/j.rse.2004.12.010
[12] M. C. Hansen, R. S. DeFries, J. R. G. Townshend, L. Marufu and R. Sohlberg, “Development of MODIS Tree Cover Validation Data Set for Western Province, Zambia,” Remote Sensing of Environment, Vol. 83, No. 1-2, 2002, pp. 320-335.
http://dx.doi.org/10.1016/S0034-4257(02)00080-9
[13] M. C. Hansen, R. S. DeFries, J. R. G. Townshend, R. Sohlberg, C. Dimiceli and M. Carroll, “Towards an Operational MODIS Continuous Field of Percent Tree Cover Algorithm: Examples Using AVHRR and MODIS Data,” Remote Sensing of Environment, Vol. 83, No. 1-2, 2002, pp. 303-319.
http://dx.doi.org/10.1016/S0034-4257(02)00079-2
[14] M. A. White, J. D. Shaw and R. D. Ramsey, “Accuracy Assessment of the Vegetation Continuous Field Tree Cover Product Using 3954 Ground Plots in the SouthWestern USA,” International Journal of Remote Sensing, Vol. 26, No. 12, 2005, pp. 2699-2704.
http://dx.doi.org/10.1080/01431160500080626
[15] F. S. Cardozo, Y. E. Shimabukuro, G. Pereira and F. B. Silva, “Using Remote Sensing Products for Environmental Analysis in South America,” Remote Sensing, Vol. 3, No. 10, 2011, pp. 2110-2127.
http://dx.doi.org/10.3390/rs3102110
[16] M. A. Lefsky, “A Global Forest Canopy Height Map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System,” Geophysical Research Letters, Vol. 37, No. 15, 2010, Article ID: L15401. http://dx.doi.org/10.1029/2010GL043622
[17] J. Heiskanen, “Evaluation of Global Land Cover Data Sets over the Tundra-Taiga Transition Zone in Northernmost Finland,” International Journal of Remote Sensing, Vol. 29, No. 13, 2008, pp. 3727-3751.
http://dx.doi.org/10.1080/01431160701871104
[18] P. M. Montesano, R. Nelson, G. Sun, H. Margolis, A. Kerber and K. J. Ranson, “MODIS Tree Cover Validation for the Circumpolar Taiga-Tundra Transition Zone,” Remote Sensing of Environment, Vol. 113, No. 10, 2009, pp. 2130-2141. http://dx.doi.org/10.1016/j.rse.2009.05.021
[19] O. Arino, P. Bicheron, F. Achard, J. Latham, R. Witt and J. L. Weber, “GLOBCOVER: The Most Detailed Portrait of Earth,” European Space Agency Bulletin, Vol. 136, 2008, pp. 24-31.
[20] M. A. Friedl, D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, et al., “MODIS Collection 5 Global Land Cover: Algorithm Refinements and Characterization of New Datasets,” Remote Sensing of Environment, Vol. 114, No. 1, 2010, pp. 168-182.
http://dx.doi.org/10.1016/j.rse.2009.08.016
[21] M. Herold, P. Mayaux, C. E. Woodcock, A. Baccini and C. Shmullius, “Some Challenges in Global Land Cover Mapping: An Assessment of Agreement and Accuracy in Existing 1 km Datasets,” Remote Sensing of Environment, Vol. 112, No. 5, 2008, pp. 2538-2556.
http://dx.doi.org/10.1016/j.rse.2007.11.013
[22] D. Pflugmacher, O. N. Krankina, W. B. Cohen, M. A. Friedl, D. Sulla-Menashe, R. E. Kennedy, et al., “Comparison and Assessment of Coarse Resolution Land Cover Maps for Northern Eurasia,” Remote Sensing of Environment, Vol. 115, No. 12, 2011, pp. 3539-3553.
http://dx.doi.org/10.1016/j.rse.2011.08.016
[23] T. Kobayashi, J. Tsend-Ayush and R. Tateishi, “A New Tree Cover Percentage Map in Eurasia at 500m Resolution Using MODIS Data,” Remote Sensing. (unpublished)
[24] M. C. Hansen, R. S. DeFries, J. R. G. Townshend, M. Carroll, C. Dimiceli and R. A. Sohlberg, “Vegetation Continuous Fields MOD44B, 2008 Percent Tree Cover, Collection 5 [Dataset],” 2011.
http://www.glcf.umd.edu/data/vcf/
[25] FAO (Food and Agriculture Organization of the United Nations), “Global Forest Resources Assessment 2010,” 2010. http://www.fao.org/forestry/fra/fra2010/en/
[26] International Steering Committee for Global Mapping, “ISCGM Website,” 2013.
http://www.iscgm.org/cgi-bin/fswiki/wiki.cgi
[27] N. T. Hoan, R. Tateishi and H. Al-Bilbisi, “Global MODIS 2008 Data User’s Manual,” Chiba University, Chiba, 2011.
[28] C. B. Schaaf, F. Gao, A. H. Strahler, W. Lucht, X. Li, T. Tsang, et al., “First Operational BRDF, Albedo Nadir Reflectance Products from MODIS,” Remote Sensing of Environment, Vol. 83, No. 1-2, 2002, pp. 135-148.
http://dx.doi.org/10.1016/S0034-4257(02)00091-3
[29] C. Schaaf, “MODIS BRDF/Albedo Product (MCD43) User’s Guide,” 2004.
http://www-modis.bu.edu/brdf/userguide/intro.html
[30] C. Schaaf, J. Liu, F. Gao, Z. Jiao, Y. Shuai and A. Strahler, “Collection 005 Change Summary for MODIS BRDF/Albedo (MCD43) Algorithms,” n.d.
http://landweb.nascom.nasa.gov/QA_WWW/forPage/C005_Change_BRDF.pdf
[31] FAO (Food and Agriculture Organization of the United Nations), “Global Forest Resources Assessment Update 2005: Terms and definitions,” FAO, Rome, 2004.
[32] European Space Agency (ESA) and Université catholique de Louvain (UCL), “GLOBCOVER 2009 Product Description and Validation Report,” 2011.
http://due.esrin.esa.int/globcover/
[33] A. Di Gregorio and L. J. M. Jansen, “Land Cover Classification System: Classification Concepts and User Manual,” FAO, Rome, 2000.
[34] European Space Agency (ESA) and the ESA GlobCover Project, led by MEDIAS-France, “GlobCover Land Cover V2.3 Product,” 2010. http://due.esrin.esa.int/globcover/
[35] NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center, “MODIS Collection 5.1 Land Cover Type Product for 2008 [Dataset],” 2012.
http://reverb.echo.nasa.gov/
[36] T. R. Loveland and A. S. Belward, “The IGBP-DIS Global 1 km Land Cover Data Set, DISCover: First Results,” International Journal of Remote Sensing, Vol. 18, No. 15, 1997, pp. 3291-3295.
http://dx.doi.org/10.1080/014311697217099
[37] M. A. Friedl, D. K. McIver, J. C. F. Hodges, X. Y. Zhang, D. Muchoney, A. H. Strahler, et al., “Global Land Cover Mapping from MODIS: Algorithms and Early Results,” Remote Sensing of Environment, Vol. 83, No. 1-2, 2002, pp. 287-302. http://dx.doi.org/10.1080/014311697217099
[38] M. L. Clark, T. M. Aide, H. R. Grau and G. Riner, “A Scalable Approach to Mapping Annual Land Cover at 250 m Using MODIS Time Series Data: A Case Study in the Dry Chaco Ecoregion of South America,” Remote Sensing of Environment, Vol. 114, No.11, 2010, pp. 2816-2832. http://dx.doi.org/10.1016/j.rse.2010.07.001
[39] M. C. Peel, B. L. Finlayson and T. A. McMahon, “Updated World Map of the Koppen-Geiger Climate Classification,” Hydrology and Earth System Sciences, Vol. 11, No. 5, 2007, pp. 1633-1644.
http://dx.doi.org/10.5194/hess-11-1633-2007

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.