Ni-Meister Research Lab

Publications

Peer-reviewed Book Cahpters

• Terrestrial Ecosystem Modeling

1. Ni-Meister, W., W. Yang, and N. Kiang, 2010. A clumped-foliage canopy radiative transfer model for a global dynamic terrestrial ecosystem model I: Theory, Agriculture and Forest Meteorology, 150(7-8):881-894, doi:10.1016/j.agrformet.2010.02.009.


2. Yang, W., W. Ni-Meister, N. Kiang, P. R. Moorcroft, A. H. Strahler and A. Oliphant, 2010. A clumped-foliage canopy radiative transfer model for a global dynamic terrestrial ecosystem model I: Validation, Agriculture and Forest Meteorology, 150(7-8):895907, doi:10.1016/j.agrformet.2010.02.008.



• Canopy Radiative Transfer

1. Widlowski, J-L, C. Mio, M. Disney, J. Adams, I. Andredakis, C. Atzberger, J. Brennan, L Busetto, M. Chelle, G Ceccherini, R Colombo, J-F Côté, A. Eenmäe, R. Essery, J-P. Gastellu-Etchegorry, N. Gobron, E.Grau, V. Haverd, L. Homolová, H. Huang, L. Hunt, Kobayashi , B. Koetz, A. Kuusk, J. Kuusk, M. Lang, P. E. Lewis, J. L. Lovell,Z. Malenovsky, M. Meroni, F. Morsdorf, M. Mõttus, T. Nilson, W. Ni‐Meister, B. Pinty, M. Rautiainen, M. Schlerf, B. Somers, J. Stuckens, M. M. Verstraete, W. Yang, F. Zhao, T. Zenone, (2015), The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing, Remote Sensing of Environment, 169: 418–437.


2. Widlowski, J.-L., B. Pinty, M. Clerici, Y. Dai, M. De. Kauwe, K. de Ridder, A. Kallel, H. Kobayashi, T. Lavergne, W. Ni-Meister, A. Olchev, T. Quaife, S. Wang, W. Yang, Y. Yang, and H. Yuan, 2011. RAMI4PILPS: An intercomparison of formulations for the partitioning of solar radiation in land surface models, Journal of Geophysical Research, 116:G02019, doi: 10.1029/2010JG001511.


3. Pereira, J., B. Mota, J. L. Privette, K. K. Caylor, J. M.N. Silva, A. C.L. Sá, and W. Ni-Meister, 2004. A simulation analysis of the detectability of understory burns in miombo woodlands, Remote Sensing of Environment, 96(3): 296-310.


4. Pinty B., J. Widlowski, M. Taberner, N. Gobron, M. Verstraete, M. Disney, F. Gascon, J. Gastellu, L. Jiang, A. Kuusk, P. Lewis, X. Li, W. Ni-Meister, T. Nilson, P. North, W. Qin, L. Su, S. Tang, R. Thompson, W. Verhoef, H. Wang, G. Yan, H. Zang, 2004. The Radiation transfer Model Intercomparison (RAMI) Exercise: Results from the second phase, Journal of Geophysics Research, 109, D06210, 10.1029/2003JD004252.


5. Yang, R., M.A. Friedl, and W. Ni, 2001. Parameterization of shortwave radiation fluxes for nonuniform vegetation canopies in land surface models, Journal of Geophysical Research, 106(D13):14275-14286.


6. Ni, W., and D.L.B. Jupp, 2000. Spatial variance in directional remote sensing imagery – recent developments and future perspectives, Remote Sensing Review, 18(2-4):441-479.


7. Ni, W. and X. Li, 2000. A coupled vegetation – soil bidirectional reflectance model for a semi-arid landscape, Remote Sensing of Environment, 74:113-124.


8. Ni, W., X. Li, C.E. Woodcock, M. Caetano, and A.H. Strahler, 1999. An analytical model of bidirectional reflectance over discontinuous plant canopies, IEEE Transactions on Geoscience and Remote Sensing, 37(2):987-999.


9. Ni, W., C.E. Woodcock, and D.L.B. Jupp, 1999. Variance in bidirectional reflectance over discontinuous plant canopies, Remote Sensing of Environment, 69(1): 1-15.


10. Ni, W., X., Li, C.E. Woodcock, J.L. Roujean, and R. Davis, 1997. Transmission of solar radiation in boreal conifer forests: measurements and models, Journal of Geophysical Research, 102(D24): 29555-29566.



• Lidar Remote Sensing and Fusion with Optical Remote Sensing

1. Ni-Meister, W., A. Rojas, and S. Lee, 2022. Direct use of large-footprint lidar waveforms to estimate aboveground biomass, Remote Sensing of Environment, 280, 113147. https://doi.org/10.1016/j.rse.2022.113147.


2. Wang, Q. and W. Ni-Meister, Forest canopy height and gaps from multiangular BRDF, assessed with airborne LiDAR Data, Remote Sens. 2019, 11, 2566; doi:10.3390/rs11212566.


3. Marrs, J. and W. Ni-Meister. Machine learning techniques for tree species cclassification using Co-registered LiDAR and hyperspectral data. Remote Sens. 2019, 11, 819.


4. Ni-Meister, W., W. Yang, S. Lee,, A. Strahler and F. Zhao, (2018), Validating modeled lidar waveforms in forest canopies with airborne laser scanning data, Remote Sensing of Environment, 204:229-243.


5. Yang, X., A. H. Strahler, C. B. Schaaf, D. L.B. Jupp, T. Yao, F. Zhao, Z. Wang, D. S. Culvenor, G. J. Newnham, J. L. Lovell, R. O. Dubayah, C. E. Woodcock, W. Ni-Meister, 2013. Three-dimensional forest reconstruction and structural parameter retrievals using a terrestrial full-waveform lidar instrument (Echidna®), Remote Sensing of Environment, 135:36-51.


6. Shi Y., S. Choi, X. Ni, S. Ganguly, G. Zhang, H. V. Duong, M. A. Lefsky, M. Simard, S. S. Saatchi, S. Lee, W. Ni-Meister, S. Piao, C. Cao, R. R. Nemani,R. B. Myneni, 2013. Allometric scaling and resource limitations model of tree heights: Part 1. Model optimization and testing over continental USA, Remote Sensing,5:284-306; doi:10.3390/rs5010284.


7. Choi, S., X. Ni, Y. Shi, S. Ganguly, G. Zhang, H. V. Duong, M. A. Lefsky, M. Simard, S. S. Saatchi, S. Lee, W. Ni-Meister, S. Piao, C. Cao, R. R. Nemani, R. B. Myneni, 2013. Allometric scaling and resource limitations model of tree heights: Part 2. Site based testing of the model, Remote Sensing,5:202-223; doi:10.3390/rs5010202.


8. Green, G., S. Ahearn, and W. Ni-Meister, 2013. The Future of national-scale three-dimensional landscape mapping, ISPRS Journal of Photogrammetry Engineering and Remote Sensing , 79(2):185-194.


9. Zhao, F., A. H. Strahler, C. L. Schaaf, T. Yao, X. Yang, Z. Wang, M. A. Schull, M. O. Román, C. E. Woodcock, P. Olofsson, W. Ni-Meister, D. L.B. Jupp, J. L. Lovell, D. S. Culvenor, G. J. Newnham, 2012. Measuring gap fraction, element clumping index and LAI in Sierra Forest stands using a full-waveform ground-based lidar. Remote Sensing of Environment, 135:73-79.


10. Yang, W., W. Ni-Meister, and S. Lee, 2011. Assessment of the impacts of surface topography, off-nadir pointing and vegetation structure on vegetation lidar waveforms using an extended geometric optical and radiative transfer model, Remote Sensing of Environment, 15(11):2810-2822.


11. Lee, S., W. Ni-Meister, W. Yang: Physically based vertical vegetation structure retrieval from ICESat data, 2011. Validation using airborne data in White Mountain National Forest, New Hampshire, USA, Remote Sensing of Environment, 115(11):2776-2785.


12. Zhao, F., X. Yang, M. Schull, M. Roman-Colon, T. Yao, Z. Wang, Q. Zhang, D. Jupp, D. Culvenor, G. Newnham, W. Ni-Meister, C. Schaaf, C. Woodcock, and A. Strahler, 2011. Measuring leaf area index, foliage profile, and stand height in New England forest stands using ground-based lidar. Remote Sensing of Environment, 115(11):2954-2964.


13. Yao, T. , X. Yang, F. Gao, Z. Wang, Q. Zhang, D. Jupp, D. Culvenor, G. Newnham, W. Ni-Meister, C.B. Schaaf, C. Woodcock, and A. Strahler, 2011. Estimation of forest structure parameter and biomass New England forest stands using Echidna ground-based lidar. Remote Sensing of Environment, 115(11):2965-2974.


14. Ni-Meister, W., S. Lee, A. H. Strahler, C. E. Woodcock,C. Schaaf, J. Ranson, G.Sun, and J. B. Blair, 2010. Assessing general relationships between above-ground biomass and vegetation structure parameters for improved carbon estimate from vegetation lidar, Journal of Geophysical Research, VOL. 115, G00E11, doi:10.1029/2009JG000936.


15. Ni-Meister, W., A. H. Strahler, C. E. Woodcock, C. Schaaf, D. L. B. Jupp, T. Yao, F. Zhao, and X. Yang, 2008. Modeling the hemispherical scanning, below-canopy lidar and vegetation structure characteristics with a geometric optical and radiative transfer model, Canadian Journal of Remote Sensing, 34(Suppl. 2): S385-S397。


16. Strahler, A. H, D. L. B. Jupp, C. E. Woodcock, C. B. Schaaf, T. Yao, F. Zhao, X. Yang, J. Lovell, D. Culvenor, G. Newnham, W. Ni-Meister, and W. Boykin-Morris, 2008. Retrieval of forest structural parameters using a ground-based lidar instrument (Echidna@) Canadian Journal of Remote Sensing,34(Suppl. 2):S426-S440.


17. Ni-Meister, W., D.L.B. Jupp, and R. Dubayah, 2001. Modeling lidar waveforms in heterogeneous and discrete canopies, IEEE Transactions on Geoscience and Remote Sensing, 39(9):1943-1958.



• Multiangular Remote Sensing

1. Wang, Q., Y. Pang, Z. Li, G. Sun, E. Xhen, and W. Ni-Meister, 2018. The potential of forest biomass inversion based on vegetation indices using multi-angle CHRIS/PROBA data, Remote sensing, 2018,8, 891; doi:10.3390/rs8110891.


2. Gao, X., A.R. Huete, W. Ni, and, T. Miura, 2001. Review of optical-biophysical relationships of pure vegetation spectral without background contamination, Remote Sensing of Environment, 74:609-620.


3. Li, X., W. Ni, B. Hu, C.E. Woodcock, and A.H. Strahler, 1997. Decoupling path-scattering of light in a homogeneous layer and multiple bouncing at its non-Lambertian bottom, Science in China, (series E), 39(6): 656-669b.


4. Li, X., W. Ni, B. Hu, A.H. Strahler, and C.E. Woodcock, 1996. Path-scattering of light in a homogeneous layer and multiple bouncing at its Non-Lambertian bottom, China Science, (series E) (In Chinese), 26(5): 457-466a.



• Microwave Remote Sensing

1. Pistolesi, L. L., W. Ni-Meister, and K. C. McDonald, 2015. Mapping wetlands in the Hudson Highlands ecoregion with ALOS PALSAR: An effort to identify potential swamp forest habitat for Golden-winged Warblers, Wetland Ecology and Management, 23:95-112, DOI 10.1007/s11273-014-9381-3.


2. Peng, P., J. Shi, W. Ni-Meister, T. Zhao, and D. Ji, 2014. Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA) Products and Their Potential Hydrological Application at an Arid and Semiarid Basin in China, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2014.2320756, 2014.



• Data Assimilation

  1. Ni-Meister, W., 2008. Recent advances on soil moisture data assimilation, Physical Geography, 29(1):19-37.
  
  
  2. Ni-Meister, W., P. Houser, and J. Walker, 2006. Soil moisture initialization for climate prediction: Assimilation of SMMR soil moisture data into a land surface model, Journal of Geophysical Research Vol.111, D20102, doi:10.1029/2006JD007190.
  
  
  3. Ni-Meister, W., J. Walker, and P. Houser, 2005. Soil moisture initialization for climate prediction: Characterization of model observation errors, Journal of Geophysical Research, Vol.110, D13111,doi:10.1029/2004JD005745.
  
  

• Snow-Vegetation and Surface Hydrology

1. Ni-Meister, W. and H. Gao, 2011. Assessing the impacts of vegetation heterogeneity on energy fluxes and snowmelt in boreal forests, Journal of Plant Ecology, 4:37-47.


2. Ni, W. and C.E. Woodcock, 2000. Effect of canopy structure and the presence of snow on the albedo of boreal conifer forest, Journal of Geophysical Research, 105(D9): 11879-11888.


3. Hardy, J.P., R.E. Davis, R. Jordan, W. Ni, and C.E. Woodcock, 1998. Snow ablation modeling in conifer and deciduous stands of the boreal forest, Hydrological Processes, 12:1763-1778.


4. Davis, R.E., J. Hardy, W. Ni, C.E. Woodcock, C. McKenzie, R. Jordan, and X. Li, 1997. Variation of snow cover processes in the boreal forest: a parametric study on the effects of conifer canopy, Journal of Geophysical Research, 102(D24): 29389-29396.


5. Hardy, J.P., R. Davis, R. Jordan, X. Li, C. Woodcock, W. Ni, and J. McKenzie, 1997. Snow ablation modeling at the stand scale in a boreal jack pine forest, Journal of geophysical Research, 102(D24):29397-29406.



• Land Atmosphere Interactions

1. Kutter, E., C. Yi, G. Hendrey, H. Liu, T. Eaton, W. Ni-Meister, 2017. Recirculation over complex terrain, Journal of Geophysical Research – Atmosphere, 122(12), 2017. DOI: 10.1002/2016JD026409.


2. Dong, J. and W. Ni-Meister, 2011. Analysis of diurnal boundary layer development in boreal forests: measurements and simulations, Journal of Plant Ecology, doi: 10.1093/jpe/rtr00:1-15.


3. Dong, J., W. Ni-Meister, and P. R. Houser, 2007. Impacts of vegetation and cold season processes on soil moisture -- climate relationships over Eurasia, Journal of Geophysical Research, Vol. 112,D09106, doi:10.1029/2006JF007774.


4. Ni, W., 1997. A coupled transilience model for turbulent air flow in plant canopy and planetary boundary layer, Agricultural and Forest Meteorology, 86: 77-105.


5. Zhang, X., D. Yang, and W. Ni, 1993. PE (Potential Evapotranspiration ) index and vegetation-climate classification-major methods and PEP programs, Acta Phytoecological ET Geobotanica Sinica (in Chinese), Vol. 17, Feb.



• Water Quality

1. Nath, B., Ni-Meister, W., Choudhury, R., 2020. Impact of urbanization on land use and land cover change in Guwahati city, India and its implication on declining groundwater level, Groundwater for Sustainable Development, doi: https://doi.org/10.1016/j.gsd.2020.100500.


2. Lee, S., W. Ni-Meister, D. Toll, J. Nigro, A. L. Gutierrez-Magness and T. Engman, 2010. Assessing the hydrologic performance of the EPA’s nonpoint source water quality assessment decision support tool using North American Land Data Assimilation System (NLDAS) products, Journal of Hydrology, 387(3-4):212-220, doi:10.1016/j.jhydrol.2010.04.009.


3. Nigro, J., D. Toll, E. Partington, W. Ni-Meister, S. Lee, A. Gutierrez-Magnesse, T. Engman, and K. Arsenault, 2010. NASA-modified precipitation products to improve EPA nonpoint source water quality modeling for the Chesapeake Bay, Journal of Environmental Quality, 39: 4: 1388-1401, doi:10.2134/jeq2009.0161.


4. Lee, S. and W. Ni-Meister, 2006. Monitoring coastal estuary water clarity using landsat multispectral data, Middle States Geographer, 39:43-51.

Peer-reviewed Book Chapter

1. Ni-Meister, W., 2015. Aboveground terrestrial biomass and carbon stock estimations from multisensory remote sensing. Remote Sensing Handbook, CRC Press(2015), ISBN-13: 978-1482218015, ISBN-10: 1482218011.


2. Green, G., S. Ahearn, and W. Ni-Meister, 2015. Downscaling On Demand: Examples in Forest Canopy Mapping, Why Scale Still Matters: Applications That Advance GIScience and Remote Sensing ,CRC Press.


3. Zhang, X. and W. Ni-Meister, 2014. Remote sensing of forest biomass, Biophysical Applications of Satellite Remote Sensing edited by Jonathan Hanes, Publisher: Springer; 2014 edition, ISBN-10: 3642250467 and ISBN-13: 978-3642250460, Pages 63-98 (Chapter 3)


4. Ni-Meister, W., 2013. Soil Moisture Data Assimilation for State Initialization of Seasonal Climate Prediction, Land Surface Observation, Modeling and Data Assimilation edited by S. Liang, X. Li, and X. Xie. Publisher: World Scientific Publishing Company; 1 edition (November 24, 2013), ISBN-10: 9814472603 and ISBN-13: 978-9814472609, Pages 379-404 (Chapter 12).


5. Geiger B. and W. Ni. 2004. Directional reflection properties of heterogeneous surfaces, book chapter in Bidirectional Properties of Land Surfaces edited by M. Schoenermarck, publisher: Wissenschaft & Technik Verlag, Pages 147-172.


6. Meister, G., K. Tornow, and W. Ni, 2004. Geometrical Optical BRDF Models, book chapter in Bidirectional Properties of Land Surfaces edited by M. Schoenermarck, publisher: Wissenschaft & Technik Verlag, Pages:82-104.