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Research Article

A new computationally efficient algorithm to generate global fractional vegetation cover from Sentinel-2 imagery at 10 m resolution

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Article: 2344592 | Received 18 Aug 2023, Accepted 14 Apr 2024, Published online: 30 Apr 2024

References

  • Baret, F., B. de Solan, R. Lopez-Lozano, K. Ma, and M. Weiss. 2010. “GAI Estimates of Row Crops from Downward Looking Digital Photos Taken Perpendicular to Rows at 57.5° Zenith Angle: Theoretical Considerations Based on 3D Architecture Models and Application to Wheat Crops.” Agricultural and Forest Meteorology 150: 1393–1401. https://doi.org/10.1016/j.agrformet.2010.04.011.
  • Baret, F., S. Jacquemoud, and J.-F. Hanocq. 1993. “The Soil Line Concept in Remote Sensing.” Remote Sensing Reviews 13: 281–284.
  • Briegleb, B. P., P. Minnis, V. Ramanathan, and E. Harrison. 1986. “Comparison of Regional Clear-Sky Albedos Inferred from Satellite Observations and Model Computations.” Journal of Climate and Applied Meteorology 25: 214–226. https://doi.org/10.1175/1520-0450(1986)025<0214:CORCSA>2.0.CO;2.
  • Briegleb, B., and V. Ramanathan. 1982. “Spectral and Diurnal Variations in Clear Sky Planetary Albedo.” Journal of Applied Meteorology 21: 1160–1171. https://doi.org/10.1175/1520-0450(1982)021<1160:SADVIC>2.0.CO;2.
  • Chang, C.-I., and D. C. Heinz. 2000. “Constrained Subpixel Target Detection for Remotely Sensed Imagery.” IEEE Transactions on Geoscience and Remote Sensing 38: 1144–1159. https://doi.org/10.1109/36.843007.
  • Chen, M., E. K. Melaas, J. M. Gray, M. A. Friedl, and A. D. Richardson. 2016. A New Seasonal-Deciduous Spring Phenology Submodel in the Community Land Model 4.5: Impacts on Carbon and Water Cycling Under Future Climate Scenarios. Global Change Biology.
  • Chopping, M., M. North, J. Chen, C. B. Schaaf, J. B. Blair, J. V. Martonchik, and M. A. Bull. 2012. “Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscapes Assessed with High Quality Reference Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5: 44–58. https://doi.org/10.1109/JSTARS.2012.2184270.
  • Choudhury, B. J., N. U. Ahmed, S. B. Idso, R. J. Reginato, and C. S. T. Daughtry. 1994. “Relations Between Evaporation Coefficients and Vegetation Indices Studied by Model Simulations.” Remote Sensing of Environment 50: 1–17. https://doi.org/10.1016/0034-4257(94)90090-6.
  • Deardorff, J. W. 1978. “Efficient Prediction of Ground Surface Temperature and Moisture with Inclusion of a Layer of Vegetation.” Journal of Geophysical Research: Oceans 83: 1889–1903. https://doi.org/10.1029/JC083iC04p01889.
  • Dickinson, R. E. 1983. “Land Surface Processes and Climate—Surface Albedos and Energy Balance.” In Advances in Geophysics, edited by B. Saltzman, 305–353. Amsterdam: Elsevier.
  • Ding, Y., X. Zheng, K. Zhao, X. Xin, and H. Liu. 2016. “Quantifying the Impact of NDVIsoil Determination Methods and NDVIsoil Variability on the Estimation of Fractional Vegetation Cover in Northeast China.” Remote Sensing 8: 29. https://doi.org/10.3390/rs8010029.
  • Donohue, R. J., M. L. Roderick, and T. R. Mcvicar. 2008. “Deriving Consistent Long-Term Vegetation Information from AVHRR Reflectance Data Using a Cover-Triangle-Based Framework.” Remote Sensing of Environment 112: 2938–2949. https://doi.org/10.1016/j.rse.2008.02.008.
  • Elmore, A. J., J. F. Mustard, S. J. Manning, and D. B. Lobell. 2000. “Quantifying Vegetation Change in Semiarid Environments: Precision and Accuracy of Spectral Mixture Analysis and the Normalized Difference Vegetation Index.” Remote Sensing of Environment 73: 87–102. https://doi.org/10.1016/S0034-4257(00)00100-0.
  • Feng, G., J. G. Masek, M. R. Schwaller, and F. F. Hall. 2006. “On the Blending of the Landsat and MODIS Surface Reflectance: Predicting Daily Landsat Surface Reflectance.” IEEE Transactions on Geoscience and Remote Sensing 44: 2207–2218. https://doi.org/10.1109/TGRS.2006.872081.
  • Gitelson, A. A., Y. J. Kaufman, R. Stark, and D. Rundquist. 2002. “Novel Algorithms for Remote Estimation of Vegetation Fraction.” Remote Sensing of Environment 80: 76–87. https://doi.org/10.1016/S0034-4257(01)00289-9.
  • Gutman, G., and A. Ignatov. 1998. “The Derivation of the Green Vegetation Fraction from NOAA/AVHRR Data for Use in Numerical Weather Prediction Models.” International Journal of Remote Sensing 19: 1533–1543. https://doi.org/10.1080/014311698215333.
  • Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, et al. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342: 850–853. https://doi.org/10.1126/science.1244693.
  • Harsanyi, J. C., and C. I. Chang. 1994. “Hyperspectral Image Classification and Dimensionality Reduction: An Orthogonal Subspace Projection Approach.” IEEE Transactions on Geoscience and Remote Sensing 32: 779–785. https://doi.org/10.1109/36.298007.
  • Hilker, T., M. A. Wulder, N. C. Coops, J. Linke, G. Mcdermid, J. G. Masek, G. Feng, and J. C. White. 2009. “A New Data Fusion Model for High Spatial- and Temporal-Resolution Mapping of Forest Disturbance Based on Landsat and MODIS.” Remote Sensing of Environment 113: 1613–1627. https://doi.org/10.1016/j.rse.2009.03.007.
  • Jacquemoud, S., W. Verhoef, F. Baret, C. Bacour, P. J. Zarco-Tejada, G. P. Asner, C. François, and S. L. Ustin. 2009. “PROSPECT+SAIL Models: A Review of Use for Vegetation Characterization.” Remote Sensing of Environment 113: S56–S66. https://doi.org/10.1016/j.rse.2008.01.026.
  • Jia, K., S. Liang, X. Gu, F. Baret, X. Wei, X. Wang, Y. Yao, L. Yang, and Y. Li. 2016. “Fractional Vegetation Cover Estimation Algorithm for Chinese GF-1 Wide Field View Data.” Remote Sensing of Environment 177: 184–191. https://doi.org/10.1016/j.rse.2016.02.019.
  • Jia, K., S. Liang, S. Liu, Y. Li, Z. Xiao, Y. Yao, B. Jiang, et al. 2015. “Global Land Surface Fractional Vegetation Cover Estimation Using General Regression Neural Networks from MODIS Surface Reflectance.” IEEE Transactions on Geoscience and Remote Sensing 53: 4787–4796. https://doi.org/10.1109/TGRS.2015.2409563.
  • Jiapaer, G., X. Chen, and A. Bao. 2011. “A Comparison of Methods for Estimating Fractional Vegetation Cover in Arid Regions.” Agricultural and Forest Meteorology 151: 1698–1710. https://doi.org/10.1016/j.agrformet.2011.07.004.
  • Kang, S., S. W. Running, J. H. Lim, M. Zhao, C. R. Park, and R. Loehman. 2003. “A Regional Phenology Model for Detecting Onset of Greenness in Temperate Mixed Forests, Korea: An Application of MODIS Leaf Area Index.” Remote Sensing of Environment 86: 232–242. https://doi.org/10.1016/S0034-4257(03)00103-2.
  • Li, W., F. Baret, M. Weiss, S. Buis, R. Lacaze, V. Demarez, J. F. Dejoux, M. Battude, and F. Camacho. 2017. “Combining Hectometric and Decametric Satellite Observations to Provide Near Real Time Decametric FAPAR Product.” Remote Sensing of Environment 200: 250–262. https://doi.org/10.1016/j.rse.2017.08.018.
  • Li, X., G. M. Foody, D. S. Boyd, Y. Ge, Y. Zhang, Y. Du, and F. Lin. 2020. “SFSDAF: An Enhanced FSDAF That Incorporates Sub-Pixel Class Fraction Change Information for Spatio-Temporal Image Fusion.” Remote Sensing of Environment 237: 111537. https://doi.org/10.1016/j.rse.2019.111537.
  • Liang, S. L. 2004. Quantitative Remote Sensing of Land Surfaces. Hoboken: John Wiley-Sons, Inc.
  • Liang, S., and J. Wang. 2020. “Preface to the Second Edition.” In Advanced Remote Sensing (Second Edition), edited by S. Liang and J. Wang, 477–510. Amsterdam: Elsevier.
  • Lucht, W., C. B. Schaaf, and A. H. Strahler. 2000. “An Algorithm for the Retrieval of Albedo from Space Using Semiempirical BRDF Models.” IEEE Transactions on Geoscience and Remote Sensing 38: 977–998. https://doi.org/10.1109/36.841980.
  • Ma, X., J. Ding, T. Wang, L. Lu, H. Sun, F. Zhang, X. Cheng, and I. Nurmemet. 2023. “A Pixel Dichotomy Coupled Linear Kernel-Driven Model for Estimating Fractional Vegetation Cover in Arid Areas from High-Spatial-Resolution Images.” IEEE Transactions on Geoscience and Remote Sensing 61: 4406615.
  • Ma, X., L. Lu, J. Ding, F. Zhang, and B. He. 2021. “Estimating Fractional Vegetation Cover of Row Crops from High Spatial Resolution Image.” Remote Sensing 13: 3874. https://doi.org/10.3390/rs13193874.
  • Miller, J. B. 1964. “An Integral Equation from Phytology.” Journal of the Australian Mathematical Society 4: 397–402. https://doi.org/10.1017/S1446788700025210.
  • Minnis, P., and E. F. Harrison. 1984a. “Diurnal Variability of Regional Cloud and Clear-Sky Radiative Parameters Derived from GOES Data. Part I: Analysis Method.” Journal of Applied Meteorology and Climatology 23: 993–1011.
  • Minnis, P., and E. F. Harrison. 1984b. “Diurnal Variability of Regional Cloud and Clear-Sky Radiative Parameters Derived from GOES Data. Part II: November 1978 Cloud Distributions.” Journal of Climate and Applied Meteorology 23: 1012–1031. https://doi.org/10.1175/1520-0450(1984)023<1012:DVORCA>2.0.CO;2.
  • Montandon, L. M., and E. E. Small. 2008. “The Impact of Soil Reflectance on the Quantification of the Green Vegetation Fraction from NDVI.” Remote Sensing of Environment 112: 1835–1845. https://doi.org/10.1016/j.rse.2007.09.007.
  • Mu, X., S. Huang, G. Yan, W. Song, and G. Ruan. 2015. “Validating GEOV1 Fractional Vegetation Cover Derived from Coarse-Resolution Remote Sensing Images Over Croplands.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8: 439–446. https://doi.org/10.1109/JSTARS.2014.2342257.
  • Mu, X., W. Song, Z. Gao, T. R. Mcvicar, R. J. Donohue, and G. Yan. 2018. “Fractional Vegetation Cover Estimation by Using Multi-Angle Vegetation Index.” Remote Sensing of Environment 216: 44–56. https://doi.org/10.1016/j.rse.2018.06.022.
  • Neilson, R. P. 1995. “A Model for Predicting Continental-Scale Vegetation Distribution and Water Balance.” Ecological Applications 5: 362–385. https://doi.org/10.2307/1942028.
  • Nilson, T. 1971. “A Theoretical Analysis of the Frequency of Gaps in Plant Stands.” Agricultural Meteorology 8: 25–38. https://doi.org/10.1016/0002-1571(71)90092-6.
  • Okin, G. S. 2007. “Relative Spectral Mixture Analysis — A Multitemporal Index of Total Vegetation Cover.” Remote Sensing of Environment 106: 467–479. https://doi.org/10.1016/j.rse.2006.09.018.
  • Ross, J. 1981. The Radiation Regime and Architecture of Plant Stands. Berlin Heidelberg: Springer.
  • Sellers, P. J. 1985. “Canopy Reflectance, Photosynthesis and Transpiration.” International Journal of Remote Sensing 6 (8): 1335–1372. https://doi.org/10.1080/01431168508948283.
  • Song, W., X. Mu, T. R. McVicar, Y. Knyazikhin, X. Liu, L. Wang, Z. Niu, and G. Yan. 2022. “Global Quasi-Daily Fractional Vegetation Cover Estimated from the DSCOVR EPIC Directional Hotspot Dataset.” Remote Sensing of Environment 269: 112835. https://doi.org/10.1016/j.rse.2021.112835.
  • Song, W., X. Mu, G. Ruan, Z. Gao, L. Li, and G. Yan. 2017. “Estimating Fractional Vegetation Cover and the Vegetation Index of Bare Soil and Highly Dense Vegetation with a Physically Based Method.” International Journal of Applied Earth Observation and Geoinformation 58: 168–176. https://doi.org/10.1016/j.jag.2017.01.015.
  • Strugnell, N. C., and W. Lucht. 2001. “An Algorithm to Infer Continental-Scale Albedo from AVHRR Data, Land Cover Class, and Field Observations of Typical BRDFs.” Journal of Climate 14: 1360–1376. https://doi.org/10.1175/1520-0442(2001)014<1360:AATICS>2.0.CO;2.
  • Teluguntla, P., P. S. Thenkabail, A. Oliphant, J. Xiong, M. K. Gumma, R. G. Congalton, K. Yadav, and A. Huete. 2018. “A 30-m Landsat-Derived Cropland Extent Product of Australia and China Using Random Forest Machine Learning Algorithm on Google Earth Engine Cloud Computing Platform.” ISPRS Journal of Photogrammetry and Remote Sensing 144: 325–340. https://doi.org/10.1016/j.isprsjprs.2018.07.017.
  • Uptmoor, R., K. Pillen, and C. Matschegewski. 2017. “Combining Genome-Wide Prediction and a Phenology Model to Simulate Heading Date in Spring Barley.” Field Crops Research 202: 84–93. https://doi.org/10.1016/j.fcr.2016.08.006.
  • Verhoef, W. 1984. “Light Scattering by Leaf Layers with Application to Canopy Reflectance Modeling: The SAIL Model.” Remote Sensing of Environment 16: 125–141. https://doi.org/10.1016/0034-4257(84)90057-9.
  • Wang, B., K. Jia, S. Liang, X. Xie, X. Wei, X. Zhao, Y. Yao, and X. Zhang. 2018. “Assessment of Sentinel-2 MSI Spectral Band Reflectances for Estimating Fractional Vegetation Cover.” Remote Sensing 10: 1927.
  • Wang, Q., K. Peng, Y. Tang, X. Tong, and P. M. Atkinson. 2021. “Blocks-removed Spatial Unmixing for Downscaling MODIS Images.” Remote Sensing of Environment 256: 112325. https://doi.org/10.1016/j.rse.2021.112325.
  • Wang, H., I. C. Prentice, T. F. Keenan, T. W. Davis, I. J. Wright, W. K. Cornwell, B. J. Evans, and C. Peng. 2017. “Towards a Universal Model for Carbon Dioxide Uptake by Plants.” Nature Plants 3: 734–741. https://doi.org/10.1038/s41477-017-0006-8.
  • Weiss, M., and F. Baret. 2016. S2toolbox Level 2 Products: Lai, Fapar, Fcover. Avignon:. Institut National de la Recherche Agronomique (INRA).
  • White, M. A., P. E. Thornton, and S. W. Running. 1997. “A Continental Phenology Model for Monitoring Vegetation Responses to Interannual Climatic Variability.” Global Biogeochemical Cycles 11: 217–234. https://doi.org/10.1029/97GB00330.
  • Wilson, J. W. 1960. “Inclined Point Quadrats.” New Phytologist 59: 1–7. https://doi.org/10.1111/j.1469-8137.1960.tb06195.x.
  • Wittich, K., and O. Hansing. 1995. “Area-averaged Vegetative Cover Fraction Estimated from Satellite Data.” International Journal of Biometeorology 38: 209–215. https://doi.org/10.1007/BF01245391.
  • Xiao, J. F., and A. Moody. 2005. “A Comparison of Methods for Estimating Fractional Green Vegetation Cover Within a Desert-to-Upland Transition Zone in Central New Mexico, USA.” Remote Sensing of Environment 98: 237–250. https://doi.org/10.1016/j.rse.2005.07.011.
  • Zeng, X., R. E. Dickinson, A. Walker, M. Shaikh, R. S. Defries, and J. Qi. 2000. “Derivation and Evaluation of Global 1-km Fractional Vegetation Cover Data for Land Modeling.” Journal of Applied Meteorology 39: 826–839. https://doi.org/10.1175/1520-0450(2000)039<0826:DAEOGK>2.0.CO;2.
  • Zhang, Y., G. M. Foody, F. Ling, X. Li, Y. Ge, Y. Du, and P. M. Atkinson. 2018. “Spatial-temporal Fraction map Fusion with Multi-Scale Remotely Sensed Images.” Remote Sensing of Environment 213: 162–181. https://doi.org/10.1016/j.rse.2018.05.010.
  • Zhang, X., C. Liao, J. Li, and Q. Sun. 2013. “Fractional Vegetation Cover Estimation in Arid and Semi-Arid Environments Using HJ-1 Satellite Hyperspectral Data.” International Journal of Applied Earth Observation and Geoinformation 21: 506–512. https://doi.org/10.1016/j.jag.2012.07.003.
  • Zhanqing, L., J. Cihlar, Z. Xingnian, L. Moreau, and L. Hung. 1996. “The Bidirectional Effects of AVHRR Measurements Over Boreal Regions.” IEEE Transactions on Geoscience and Remote Sensing 34: 1308–1322. https://doi.org/10.1109/36.544556.
  • Zhu, X., J. Chen, F. Gao, X. Chen, and J. G. Masek. 2010. “An Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model for Complex Heterogeneous Regions.” Remote Sensing of Environment 114: 2610–2623. https://doi.org/10.1016/j.rse.2010.05.032.