Spatial variability of terrestrial laser scanning based leaf area index

International Journal of Applied Earth Observation and Geoinformation

Volumn 19, Issue 1, 2012, Pages 226-237

  Zheng, Guang ^a   Moskal, L Monika ^b  

^a NANJING UNIVERSITY   (China)

^b University of Washington   (United States)

Author keywords

Effective leaf area index (LAIe); Heterogeneous forest; Occlusion; Spatial variation; Terrestrial laser scanning (TLS)

Indexed keywords

AZIMUTH; DATA PROCESSING; DATA SET; DOMINANCE; FOREST CANOPY; FOREST COVER; LASER METHOD; LEAF AREA INDEX; SPATIAL VARIATION; STAND DYNAMICS;

CONIUM; PSEUDOTSUGA; PSEUDOTSUGA MENZIESII; TSUGA; TSUGA HETEROPHYLLA;

EID: 84872764059     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2012.05.002     Document Type: Article

References (50)

1. Anderson, M.C., Neale, C.M.U., Li, F., Norman, J.M., Kustas, W.P., Jayanthi, H., Chavez, J., 2004. Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sensing of Environment 92, 447-464.
2. Antyufeev, V.S., Marshak, A.L., 1990. Inversion of Monte-Carlo model for estimating vegetation canopy parameters. Remote Sensing of Environment 33, 201-209.
3. Barrett, D.J., Hatton, T.J., Ash, J.E., Ball, M.C., 1996. Transpiration by trees from contrasting forest types. Australian Journal of Botany 44, 249-263.
4. Berterretche, M., Hudak, A.T., Cohen, W.B., Maiersperger, T.K., Gower, S.T., Dungan, J., 2005. Comparison of regression and geostatistical methods for mapping Leaf Area Index (LAI) with Landsat ETM+ data over a boreal forest. Remote Sensing of Environment 96, 49-61.
5. Besl, P.J., Mckay, N.D., 1992. A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 239-256.
6. Brakke, T.W., Kanemasu, E.T., Steiner, J.L., Ulaby, F.T., Wilson, E., 1981. Microwave radar response to canopy moisture, leaf area index and dry weight of wheat, corn, and sorghum. Remote Sensing of Environment 11, 207-220.
7. Brown, L., Chen, J.M., Leblanc, S.G., Cihlar, J., 2000. A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forests: an image and model analysis. Remote Sensing of Environment 71, 16-25.
8. Casa, R., Jones, H.G., 2005. LAI retrieval from multiangular image classification and inversion of a ray tracing model. Remote Sensing of Environment 98, 414-428.
9. Chen, J.M., Black, T.A., 1992. Defining leaf area index for non-flat leaves. Plant Cell and Environment 15, 421-429.
10. Chen, J.M., Black, T.A., 1991. Measuring leaf area index of plant canopies with branch architecture. Agricultural and Forest Meteorology 57, 1-12.
11. Chen, J.M., Chen, X.Y., Ju, W.M., Geng, X.Y., 2005a. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs. Journal of Hydrology 305, 15-39.
12. Chen, J.M., Cihlar, J., 1996. Retrieving leaf area index of boreal conifer forests using landsat TM images. Remote Sensing of Environment 55, 153-162.
13. Chen, J.M., Leblanc, S.G., 1997. A four-scale bidirectional reflectance model based on canopy architecture. IEEE Transactions on Geosciences and Remote Sensing 35, 1316-1337.
14. Chen, J.M., Menges, C.H., Leblanc, S.G., 2005b. Global mapping of foliage clumping index using multi-angular satellite data. Remote Sensing of Environment 97, 447-457.
15. Chen, J.M., Pavlic, G., Brown, L., Cihlar, J., Leblanc, S.G., White, H.P., Hall, R.J., Peddle, D.R., King, D.J., Trofymow, J.A., Swift, E., Van Der Sanden, J., Pellikka, P.K.E., 2002. Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements. Remote Sensing of Environment 80, 165-184.
16. Clawges, R., Vierling, L., Calhoon, M., Toomey, M., 2007. Use of a ground-based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis). International Journal of Remote Sensing 28, 4331-4344.
17. Cleugh, H.A., Leuning, R., Mu, Q.Z., Running, S.W., 2007. Regional evaporation estimates from flux tower and MODIS satellite data. Remote Sensing of Environment 106, 285-304.
18. Danson, F.M., Hetherington, D., Morsdorf, F., Koetz, B., Allgower, B., 2007. Forest canopy gap fraction from terrestrial laser scanning. IEEE Geoscience and Remote Sensing Letters 4, 157-160.
19. Dietz, J., Holscher, D., Leuschner, C., Hendrayanto, 2006. Rainfall partitioning in relation to forest structure in differently managed montane forest stands in Central Sulawesi, Indonesia. Forest Ecology and Management 237, 170-178.
20. Duchemin, B., Hadria, R., Erraki, S., Boulet, G., Maisongrande, P., Chehbouni, A., Escadafal, R., Ezzahar, J., Hoedjes, J.C.B., Kharrou, M.H., Khabba, S., Mougenot, B., Olioso, A., Rodriguez, J.C., Simonneaux, V., 2006. Monitoring wheat phenology and irrigation in Central Morocco: on the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices. Agricultural Water Management 79, 1-27.
21. Dufrene, E., Davi, H., Francois, C., Le Maire, G., Le Dantec, V., Granier, A., 2005. Modelling carbon and water cycles in a beech forest. Part I: Model description and uncertainty analysis on modelled NEE. Ecological Modelling 185, 407-436.
22. Henning, J.G., Radtke, P.J., 2006. Detailed stem measurements of standing trees from ground-based scanning lidar. Forest Science 52, 67-80.
23. Hopkinson, C., Chasmer, L., Young-Pow, C., Treitz, P., 2004. Assessing forest metrics with a ground-based scanning lidar. Canadian Journal of Forest Research-Revue Canadienne de Recherche Forestiere 34, 573-583.
24. Hosoi, F., Omasa, K., 2007. Factors contributing to accuracy in the estimation of the woody canopy leaf area density profile using 3D portable lidar imaging. Journal of Experimental Botany 58, 3463-3473.
25. Hosoi, F., Omasa, K., 2006. Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning lidar. IEEE Transactions on Geosciences and Remote Sensing 44, 3610-3618.
26. Houldcroft, C.J., Campbell, C.L., Davenport, I.J., Gurney, R.J., Holden, N., 2005. Measurement of canopy geometry characteristics using LiDAR laser altimetry: a feasibility study. IEEE Transactions on Geosciences and Remote Sensing 43, 2270-2282.
27. Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., Baret, F., 2004. Review of methods for in situ leaf area index determination - Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology 121, 19-35.
28. Lefsky, M.A., Cohen, W.B., Acker, S.A., Parker, G.G., Spies, T.A., Harding, D., 1999. Lidar remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sensing of Environment 70, 339-361.
29. Lim, K., Treitz, P., Baldwin, K., Morrison, I., Green, J., 2003. Lidar remote sensing of biophysical properties of tolerant northern hardwood forests. Canadian Journal of Remote Sensing 29, 658-678.
30. Lovell, J.L., Jupp, D.L.B., Newnham, G.J., Culvenor, D.S., 2011. Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint. ISPRS Journal of Photogrammetry and Remote Sensing 66, 46-55.
31. Maas, H.G., Bienert, A., Scheller, S., Keane, E., 2008. Automatic forest inventory parameter determination from terrestrial laser scanner data. International Journal of Remote Sensing 29, 1579-1593.
32. Moskal, L.M., Zheng, G., 2011. Retrieving forest inventory variables with terrestrial laser scanning (TLS) in urban heterogeneous forest. Remote Sensing 4, 1-20.
33. Murphy, G., 2008. Determining stand value and log product yields using terrestrial lidar and optimal bucking: a case study. Journal of Forestry 106, 317-324.
34. Nilson, T., 1971. A theoretical analysis of the frequency of gaps in plant stands. Agricultural Meteorology 8, 25-38.
35. Patenaude, G., Hill, R.A., Milne, R., Gaveau, D.L.A., Briggs, B.B.J., Dawson, T.P., 2004. Quantifying forest above ground carbon content using LiDAR remote sensing. Remote Sensing of Environment 93, 368-380.
36. Riano, D., Valladares, F., Condes, S., Chuvieco, E., 2004. Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests. Agricultural and Forest Meteorology 124, 269-275.
37. Richardson, J.J., Moskal, L.M., Kim, S.H., 2009. Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR. Agricultural and Forest Meteorology 149, 1152-1160.
38. Takeda, T., Oguma, H., Sano, T., Yone, Y., Fujinuma, Y., 2008. Estimating the plant area density of a Japanese larch (Larix kaempferi Sarg.) plantation using a groundbased laser scanner. Agricultural and Forest Meteorology 148, 428-438.
39. Thomas, J.H., 1987. Area projections of fisheye photographic lenses. Agricultural and Forest Meteorology 39, 215-223.
40. Van Der Zande, D., Hoet, W., Jonckheere, L., Van Aardt, J., Coppin, P., 2006. Influence of measurement set-up of ground-based LiDAR for derivation of tree structure. Agricultural and Forest Meteorology 141, 147-160.
41. Van Leeuwen, M., Nieuwenhuis, M., 2010. Retrieval of forest structural parameters using LiDAR remote sensing. European Journal of Forest Research 129, 749-770.
42. Watt, P.J., Donoghue, D.N.M., 2005. Measuring forest structure with terrestrial laser scanning. International Journal of Remote Sensing 26, 1437-1446.
43. Weiss, M., Baret, F., Smith, G.J., Jonckheere, I., Coppin, P., 2004. Review of methods for in situ leaf area index (LAI) determination. Part II. Estimation of LAI, errors and sampling. Agricultural and Forest Meteorology 121, 37-53.
44. Wilson, J.W., 1960. Inclined point quadrats. New Phytologist 59, 1-7.
45. Zhao, K.G., Popescu, S., 2009. Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA. Remote Sensing of Environment 113, 1628-1645.
46. Zheng, G., Chen, J.M., Tian, Q., Ju, W.M., Xia, X.Q., 2007. Combining remote sensing imagery and forest age inventory for biomass mapping. Journal of Environmental Management 85, 616-623.
47. Zheng, G., Moskal, L.M. Computational geometry based retrieval of effective leaf area index using terrestrial laser scanning. IEEE Transactions on Geoscience and Remote Sensing, http://dx.doi.org/10.1109/TGRS.2012.2187907, in press-a.
48. Zheng, G., Moskal, L.M. Leaf orientation retrieval from terrestrial laser scanning. IEEE Transactions on Geoscience and Remote Sensing, http://dx.doi.org/10.1109/TGRS.2012.2188533, in press-b.
49. Zheng, G., Moskal, L.M. Retrieval of effective leaf area index in heterogeneous forests with a terrestrial laser scanner. IEEE Transactions on Geoscience and Remote Sensing, in press-c.
50. Zheng, G., Moskal, L.M., 2009. Retrieving leaf area index (LAI) using remote sensing: theories, methods and sensors. Sensors 9, 2719-2745.