Abstract
This chapter provides a brief overview of instrumentation and methods for characterizing vegetation structure at the stand level, where a stand is defined as an area of relatively uniform physical environmental conditions, vegetation structure, and plant community composition (Barbour et al. 1987). By vegetation structure we mean the three-dimensional distribution of aboveground phyto-mass integrated over some period of time. We will not consider the temporal components of stand structure, such as diurnal variation in leaf orientation or seasonal phenology, focusing instead on methods for estimating structural variables at a particular point in time.
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References
Adams, J.B.; Smith, M.O.; Gillespie, A.R. Imaging spectrometry: Interpretation based on spectral mixture analysis. In: Pieters C.M.; Englert P., eds. Remote Geochemical Analysis: Elemental and Mineralogical Composition. Vol. 7. New York: Cambridge Univ. Pr.; 1993: 145–166.
Andrew, M.H.; Noble, I.R.; Lange, R.T.; Johnson, A.W. The measurement of shrub forage weight: Three methods compared. Aust. Range J. 3:74–82; 1981.
Asrar, G.; Myneni, R.B.; Kanemasu, E.T. Estimation of plant-canopy attributes from spectral reflectance measurements. In: Asrar, G., ed. Theory and Applications of Optical Remote Sensing. New York: Wiley; 1989:252–296.
Attema, E.P.W.; Ulaby, F.T. Vegetation modeled as a water cloud. Radio Sci. 13:357–364; 1978.
Barbour, M.G.; Burk, J.H.; Pitt, W.D. Terrestrial Plant Ecology. 2nd ed. Menlo Park, CA: Benjamin Cummings; 1987.
Barnes, W.L., Pagano, T.S.; Salomonson, V.V. Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AMI. IEEE Trans. Geosci. Remote Sens. 36:1088–1100; 1998.
Bidlake, W.R.; Black, R.A. Vertical distribution of leaf area in Larix occidentalis: A comparison of two estimation methods. Can. J. For. Res. 19:1131–1136; 1989.
Blair, J.B.; Coyle, D.B. Vegetation and topography mapping with an airborne laser altimeter using a high-efficiency laser and a scannable field-of-view telescope. In: Proceedings of the Second International Airborne Remote Sensing Conference and Exhibition. Vol. 2; Ann Arbor, MI: Environmental Research Institute of Michigan (ERIM); 1996:403–407.
Blair, J.B.; Coyle, D.B.; Bufton, J.L.; Harding, D.J. Optimization of an airborne laser altimeter for remote sensing of vegetation and tree canopies. Proc. IGARSS’94:939–941; 1994.
Bonham, C.D. Methods of Vegetation Analysis. New York: Wiley; 1989.
Brewer, K.R.W.; Hanif, H. Sampling with Unequal Probabilities. Lecture Notes in Statistics 15. New York: Springer-Verlag; 1983.
Bush, T.F.; Ulaby, F.T. Radar return from a continuous vegetation canopy. IEEE Anten. Propag. AP-24:269–276; 1976.
Carpenter, A.; West, N. Validating the reference-unit method of aboveground phyromass estimation on shrubs and herbs. Vegetatio 72:75–79; 1987.
Causton, D.R. Biometrical, structural and physiological relationships among tree parts. In: Cannell, M.G.R.; Jackson, J.E., eds. Attributes of Trees as Crop Plants. Huntingdon, UK: National Environmental Research Council; 1985:137–159.
Chen, S.G.; Ceulemans, R.; Impens, I. A Fractal-based Populus canopy structure model for the calculation of light interception. For. Ecol. Manage. 69:97–110; 1994.
Chiariello, N.R.; Mooney, H.A.; Williams, K. Growth, carbon allocation, and cost of plant tissues. In: Pearcy, R.W.; Ehleringer, J.; Mooney, H.A.; Rundel, P.W., eds. Plant Physiological Ecology: Field Methods and Instrumentation. London: Chapman and Hall; 1989:327–365.
Clark, D.B.; Clark, D.A.; Rich, P.M.; Weiss, S.; Oberbauer, S.F. Landscape-scale evaluation of understory light and canopy structure: Methods and application in a neotropical lowland rain forest. Can. J. For. Res. 26:747–757; 1996.
Cohen, W.G.; Spies, T.A. Estimating structural attributes of Douglas-fir/western hemlock forest stands from Landsat and SPOT imagery. Remote Sens. Environ. 41:1–17; 1992.
Cohen, W.B.; Spies, T.A.; Bradshaw, G.A. Semivariograms of digital imagery for analysis of conifer canopy structure. Remote Sens. Environ. 34:167–178; 1990.
Colwell, R.N., ed. Manual of Remote Sensing. Falls Church, VA: American Society of Photogrammetry and Remote Sensing; 1983.
Cottam, G; Curtis, J.T. The use of distance measures in phytosociological sampling. Ecology 37:451–460; 1956.
Crist, E.P.; Cicone, R.C. A physically-based transformation of Thematic Mapper data: The TM tasseled cap. IEEE Trans. Geosci. Remote Sens. GE-22:256–263. 1984.
Curtis, K.S. Linear measurements. In: Brinker, R.C.; Minnick, R. The Surveying Handbook. 2nd ed. New York: Chapman and Hall; 1995:42–50.
Daughtry, C.S.T. Direct measurements of canopy structure. Remote Sens. Rev. 5:45–60; 1990.
Defries, R.S.; Field, C.B.; Fung, L; Justice, C.O.; et al. Mapping the land surface for global atmosphere-biosphere models: Toward continuous distributions of vegetations functional properties. J. Geophys. Res. Atmos. 100:20867–20882; 1995.
Dobson, M.C.; Ulaby F.T.; Pierce L.E.; Sharik T.L.; Bergen, K.M.; Kellndorfer, J.; Kendra, J.R.; Li, E.; Lin, Y.C.; Nashashibi, A.; Sarabandi, K.; Siquiera, P. Estimation of forest biophysical characteristics in northern Michigan with SIR-C/X-SAR. IEEE Trans. Geosci. Remote Sens. 33:877–895; 1995.
Earle, D.F. McGowan, A.A. Evaluation and calibration of an automated rising plate meter for estimating dry matter yield of pasture. Aust. J. Exp. Agric. Anim. Husb. 19:337–350; 1979.
Etienne, M. Nondestructive methods for evaluating shrub biomass: A review. Acta Oecol. Oecol. Appl. 10:115–128; 1989.
Everitt, J.H.; Escobar, D.E.; Cavazos, I.; Noriega, J.R.; Davis, M.R. A three-camera multispectral digital video imaging system. Remote Sens. Environ. 54:333–337; 1995.
Fournier, R.A.; Landry, R.; August, N.M.; Fedosejevs, G.; Gauthier, R.P. Modelling light obstruction in three conifer forests using hemispherical photography and fine tree architecture. Agric. For. Meteorol. 82:47–72; 1996.
Frank, D.A.; Mcnaughton, S.J. Aboveground biomass estimation with the canopy intercept method: A plant growth form caveat. Oikos 57:57–60; 1990.
Franklin, J.F.; Strahler, A.H. Invertible canopy reflectance modeling of vegetation structure in semiarid woodland. IEEE Trans. Geosci. Remote Sens. 26:809–825; 1988.
Gong, P.; Pu, R.; Miller, J.R. Coniferous forest leaf area index estimation along the Oregon transect using Compact Airborne Spectrographic Imager Data. Photogram. Eng. Remote Sens. 61:1107–1117; 1995.
Gougeon, F.A. A crown following approach to the automatic delineation of individual tree crowns in high spatial resolution aerial images. Can. J. Remote Sens. 21(3):274–284; 1995.
Gotfryd, A; Hansell, R.I. The impact of observer bias on multivariate analysis of vegetation structure. Oikos 45:223–234; 1985.
Graetz, A.R.D. Remote sensing of ecosystem structure: An ecologist’s pragmatic view. In: Hobbs, E.R.J.; Mooney, H.A., eds. Remote Sensing and Biosphere Functioning. New York: Springer-Verlag; 1990:5–30.
Hagberg, J.O.; Ulander, L.M.H.; Askne, J. Repeat-pass SAR interferometry over forested terrain. IEEE Trans. Geosci. Remote Sens. 33:331–340; 1995.
Hall, F.G.; Shimabukuro, Y.; Huemmrich, K.F. Remote sensing of forest biophysical structure using mixture decomposition and geometric reflectance models. Ecol. Applic. 5:993–1013; 1995.
Halle, F.R.; Oldeman, A.A.; Tomlinson, P.B. Tropical trees and forests. Berlin: Springer-Verlag; 1978.
Hallikainen, M., Hyyppä, J.; Haapanen, J.; Taresl, J. A helicopter-borne 8 channel ranging scatterometer for remote sensing. IEEE Trans. Geosci. Remote Sens. 31:161–169; 1993.
Harrell, P.A.; Kasischke, E.S.; Bourgeau-Chavez, L.L.; Haney, E.M.; et al. Evaluation of approaches to estimating aboveground biomass in southern pine forests using SIR-C data. Remote Sens. Environ. 59(2):223–233; 1997.
Heilman, P.E.; Hinckley, T.M.; Roberts, D.A.; Ceulemans, R. Production physiology. In: Stettier R.F.; Bradshaw, H.W.; Heilman, P.E.; Hinckley, T.M., eds. Biology of Populus and Its Implications for Management and Conservation. Washington, D.C.: NRC Research Press; 1996:459–490.
Heller, R.C.; Ulliman, J.J. Forest resources assessments. In: Colwell, R.N., ed. Manual of Remote Sensing. Falls Church, VA: American Society of Photogrammetry and Remote Sensing; 1983; Ch. 34.
Henderson, F.M.; Lewis, A.J., eds. Principles and Applications of Imaging Radar. Manual of Remote Sensing, 3rd ed. Vol. 2 New York: Wiley; 1998.
Hess, L.L.; Melack, J.M.; Simonett, D.S. Radar detection of flooding beneath the forest canopy: A review. Int. J. Remote Sens. 11:1313–1325; 1990.
Honda, H.; Tomlinson, P.B.; Fisher, J.B. Computer simulation of branch interaction and regulation by unequal flow rates in botanical trees. Am. J. Bot. 68:569–585; 1981.
Horn, H.S. The Adaptive Geometry of Trees. Princeton, NJ: Princeton Univ. Pr.; 1971.
Howard, J.A. Remote Sensing of Forest Resources: Theory and Application. London: Chapman and Hall; 1991.
Husch, B.; Miller, C.I.; Beers, T.W. Forest Mensuration. 3rd ed. New York: Wiley; 1982.
Hutchings, N.J.; Phillips, A.H.; Dobson, R.C. An ultrasonic rangefinder for measuring the undisturbed surface height of continuously grazed grass swards. Grass Forage Sci. 45:119–128; 1990.
Hyyppä, J.; Hallikainen, M. Applicability of airborne profiling radar to forest inventory. Remote Sens. Environ. 57:39–57; 1996.
Imhoff, M.L. A theoretical analysis of the effect of forest structure on synthetic aperture radar backscatter and the remote sensing of biomass, IEEE Trans. Geosci. Remote Sens. 33:341–352; 1995.
Ivanov, N.; Boissard, P.; Chapron, M.; Valery, P. Estimation of the height and angles of orientation of the upper leaves in the maize canopy using stereovision. Agronomie 14:183–1194; 1994.
Justice, C.O.; Vermote, E.; Townshend, J.R.G.; Defries, R.; et al. The Moderate Resolution Imaging Spectroradiometer (MODIS): Land remote sensing for global change research. IEEE Trans. Geosci. Remote Sens. 36:1228-1249; 1998.
Kasischke, E.S.; Melack, J.M.; Dobson, M.C. The use of imaging radars for ecological applications: A review. Remote Sens. Environ. 59:141–156; 1997.
Kauth, R.J.; Thomas, G.S. The tasselled cap: A graphic description of the spectral-temporal development of agricultural crops as seen by LANDSAT. In: Proceedings of the Third Symposium on Machine Processing of Remotely Sensed Data. West Lafayette, IN: LARS, Purdue Univ.; 1976:4B-41-4B-51.
King, D. Airborne multispectral digital camera and video sensors: A critical review of system design and applications, Can. J. Remote Sens. 21:245–256; 1995.
Koike F. Reconstruction of two-dimensional tree and forest canopy profiles using photographs. J. Appl. Ecol. 22:921–929; 1985.
Koike, F.; Syahbuddin. Canopy structure of a tropical rain forest and the nature of an unstratified layer. Funct. Ecol. 7:230–235; 1993.
Kruijt, B. Estimating canopy structure of an oak forest at several scales. Forestry 62:269–284; 1989.
Kuuluvainen, T.; Pukkala, T. Simulation of within-tree and between-tree shading of direct radiation in a forest canopy: Effect of crown shape and sun elevation. Ecol. Model. 49:89–100; 1989.
Lang, A.R.G. An instrument for measuring canopy. Remote Sens. Rev. 5:61–71; 1990.
Lang, R.H.; Sidhu, J.S. Electromagnetic backscattering from a layer of vegetation: A discrete approach. IEEE Trans. Geosci. Remote Sens. GE-21:62–71; 1983.
Lemmon, P.E. A spherical densiometer for estimating forest overstory density. For. Sci. 2:314–320; 1956.
Li, X.W.; Strahler, A.H. Geometric-optical bidirectional reflectance modeling of a conifer forest canopy. IEEE Trans. Geosci. Remote Sens. Ge-24:906–919; 1985.
Li, X.; Strahler, A.H. Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing. IEEE Trans. Geosci. Remote Sens. 30:276–292; 1992.
Lowman, M.D.; Nadkarni, N.M., eds. Forest Canopies. London: Academic Press; 1995.
Maguire, D.A.; Bennett, W.S. Patterns in vertical distribution of foliage in young coastal Douglas-fir. Can. J. For. Res. 26:1991–2005; 1996.
Marshall, J.D.; Waring, R.H. Comparison of methods for estimating leaf-area index in old-growth Douglasfir. Ecology 67:975–979; 1986.
Martens, S.N.; Ustin, S.L.; Norman, J.M. Measurement of tree canopy architecture, Int. J. Remote Sens. 12(7): 1525–1545; 1991.
Martens, S.N.; Ustin, S.L.; Rousseau, R.A. Estimation of tree canopy leaf area index by gap fraction analysis. For. Ecol. Manage. 61:91–108; 1993.
McAuliffe, J.R. A rapid survey method for the estimation of density and cover in desert plant communities. J. Vegetat. Sci. 1:653–656; 1990.
McDonald, K.C.; Dobson, M.C.; Ulaby, FT. Using MIMICS to model L-band multiangle and multitemporal backscatter for a walnut orchard. IEEE Trans. Geosci. Remote Sens. 28:477–491; 1990.
McDonald, K.C.; Ulaby, FT. Radiative transfer modelling of discontinuous tree canopies at microwave frequencies. Int. J. Remote Sens. 14:2097–2128; 1993.
Means, J.E.; Acker, S.A.; Harding, D.A.; Lefsky, M.A.; Cohen, W.B.; Harmon, M.; Mckee, W.A. Use of laser altimetry to estimate forest stand characteristics in the western Cascades of Oregon. Unpublished manuscript; 1997.
Means, J.E.; Hansen, H.A.; Koerper, G.J.; Alaback, P.B.; M.W.; Klopsen, M.W. Software for Computing Plant Biomass: BIOPAK User’s Guide. Gen. Tech. Rep. PNW-GTR-340. Portland, Oregon: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station; 1994.
Monsi, M.; Saeki, S. Uber den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung fur den Stoffproduktion. Jpn. J. Bot. 14:22–52; 1953.
Mueller-Dombois, D.; Ellenberg, H. Aims and methods of vegetation ecology. New York: Wiley; 1974.
Myneni, R.B.; Asrar, G.; Gerstl, S.A.W. Radiative transfer in three dimensional leaf canopies, Trans. Theory Stat. Phys. 19:205–250; 1990.
Myneni, R.B.; Maggion, S.; Iaquinto, J.; Privette, J.L.; et al. Optical remote sensing of vegetation: Modeling, caveats and algorithms. 51(1):169–188; 1995.
Myneni, R.B.; Nemani, R.R.; Running, S.W. Estimation of global Leaf Area Index and absorbed PAR using radiative transer models. IEEE Trans. Geosci. Remote Sens. Environ. 35:1380–1393; 1997.
Nelson, R.; Swift, R.; Krabill, W. Using airborne laser to estimate forest canopy and stand characteristics. J. For. 86:31–38; 1988.
Nilson, T. A theoretical analysis of the frequency of gaps in plant stands. Agric. Meteorol. 8:25–38; 1971.
Nilsson, M. Estimation of tree heights and stand volume using an airborne lidar system. Remote Sens. Environ. 56:1–7; 1996.
Norman, J.M.; Campbell, G.S. Canopy structure. In: Pearcy, R.W.; Ehleringer, J.; Mooney, H.A.; Rundel, P.W., eds. Plant Physiological Ecology: Field Methods and Instrumentation. London: Chapman and Hall; 1989:301–325.
Norman, J.M.; Jarvis, P.G. Photosynthesis in Sitka spruce (Picea sitchensis (Bong.) Carr.). III. Measurements of canopy structure and interception of radiation. J. Appl. Ecol. 11:375–398; 1974.
Oker-Blom, P.; Pukkala, T.; Kuuluvainen, T. Relationship between radiation interception and photosynthesis in forest canopies: Effect of stand structure and latitude. Ecol. Model. 49:73–87; 1989.
Parker, G.G.; Smith, A.P.; Hogan, K.P. Access to the upper forest canopy with a large tower crane sampling the treetops in three dimensions. Bioscience 42:664–670; 1992.
Pech, R.P.; Graetz, R.D.; Davis, A.W. Reflectance modelling and the derivation of vegetation indices for an Australian semi-arid shrubland. Int. J. Remote Sens. 7:389–403; 1986.
Philipson, W.R., ed. Manual of Photographic Interpretation. 2nd ed. Falls Church, VA: American Society for Photogrammetry and Remote Sensing; 1997.
Pierce, L.E.; Ulaby, FT.; Sarabandi, K.; Dobson, M.C. Knowledge-based classification of polarimetric SAR images. IEEE Trans. Geosci. Remote Sens. 32:1081–1086; 1994.
Pitt, D.G.; Glover, G.R.; Jones, R.H. 1996. Two-phase sampling of woody and herbaceous plant communities using large scale aerial photographs. Can. J. For. Res. 26:509–524; 1996.
Polatin, P.K.; Sarabandi, K.; Ulaby, FT. An iterative inversion algorithm with application to the polarimetric radar response of vegetation canopies. IEEE Trans. Geosci. Remote Sens. 30:412–415; 1994.
Ranson, K.J.; Sun, G. An evaluation of AIRSAR and SIR-C/X-SAR images for mapping northern forest attributes in Maine, U.S.A. Remote Sens. Environ. 59:203–222; 1997.
Reed, B.C.; Brown, J.F.; Vanderzee D.; Loveland T.R.; et al. Measuring phenological variability from satellite imagery. J. Vegetat. Sci. 5:703–714; 1994.
Rich, P.M. Characterizing plant canopies with hemisherical photographs. Remote Sens. Rev. 5:13–29; 1990.
Richards, J.A.; Sun, G.O.; Simonett, D.S. L-band radar backscatter modeling of forest stands. IEEE Trans. Geosci. Remote Sens. GE-25:487–498; 1987.
Richardson, A.J.; Wiegand, C.L. Distinguishing vegetation from soil background information. Photogram. Eng. Remote Sens. 43:1541–1552; 1977.
Roberts, D.A.; Adams, J.B.; Smith, M.O. Discriminating green vegetation, non-photosynthetic vegetation and soils in AVIRIS data. Remote Sens. Environ. 44:1–25; 1993.
Roberts, D.A.; Gardner, M.; Church, R.; Ustin, S.; Scheer, G.; Green, R.O. Mapping chaparral in the Santa Monica Mountains using multiple endmember spectral mixture models. Remote Sens. Environ. 65:267–279; 1998a.
Roberts, D.A.; Brown, K.J.; Green, R.; Ustin, S.; Hinckley, T. Investigating the relationship between liquid water and leaf area in clonal Populus, Proc. 7th AVIRIS Earth Science Workshop JPL 97-21, Pasadena, CA 91109, 10 p; 1998b.
Rohlf, F.J.; Archie, J.W. Least-squares mapping using interpoint distances. Ecology 59:126–132; 1978.
Ross, J.P. The radiation regime and architecture of plant stands. The Hague, Netherlands: Dr. W. Junk; 1981.
Running, S.W.; Coughlan, J.C. A general model of forest ecosystem processes for regional applications. Ecol. Model. 42:125–154; 1988.
Sellers, P.J. Canopy reflectance, photosynthesis and transpiration. Int. J. Remote Sens. 6:1335–1372; 1985.
Sinoquet, H; Rivet, P. Measurement and visualization of the architecture of an adult tree based on a three-dimensional digitising device. Tree 11(5):265–270; 1997.
Sinoquet, H.; Valmorin, M.; Cabo, X.; Bonhomme, R. DAOLI: An automated laser distance system for measuring profiles of vegetation. Agric. For. Meteorol. 67:43–64; 1993.
Strahler, A.H.; Woodcock, C.E.; Smith, J.A. On the nature of models in remote sensing. Remote Sens. Environ. 20:131–139; 1986.
Sun, G.; Ranson, K.J. A three-dimensional radar back-scatter model of forest canopies. IEEE Trans. Geosci. Remote Sens. 33:372–382; 1995.
Sun, G.; Simonett, D.S.; Strahler, A.H.; A radar back-scattering model for discontinuous coniferous forests. IEEE Trans. Geosci. Remote Sens. 29:639–650; 1991.
Treuhaft, R.N.; Madsen, S.N.; Moghaddam, M.; van Zyl, J.J. Vegetation characteristics and underlying topography from interferometric radar. Radio Sci. 31:1449–1485; 1996.
Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8:127–150; 1979.
Ulaby, F.T.; Sarabandi, K.; McDonald, K.C.; Whitt, M.; Dobson, M.C. Michigan microwave canopy scattering model (MIMICS). Int. J. Remote Sens. 11:1223–1253; 1990.
Vanderbilt, V.C.; Silva, L.F.; Bauer, M.E. Canopy architecture measured with a laser. Appl. Opt. 29:99–106; 1990.
Van Pelt, R; North, MP. Analyzing canopy structure in Pacific Northwest old-growth forests with a stand-scale crown model. Northwest Sci. 70:15–30; 1996.
Wang, Y.; Davis, F.W.; Melack, J.M. Simulated and observed backscatter at P-, L-, and C-bands from ponderosa pine stands, IEEE Trans. Geosci. Remote Sens. 31:871–879; 1993.
Waring, R.H.; Way, J.; Hunt, E.R. Jr.; Morrissey, L.; Ranson, K.J.; Weishampel, J.F.; Oren, R.; Franklin, S.E. Imaging radar for ecosystem studies. Bioscience 45:715–723; 1995.
Way, J.; Paris, J.; Dobson, M.C.; McDonald, K.; Ulaby, F.T.; Weber, J.A.; Ustin, S.L.; Vanderbilt, V.C.; Kasischke, E.S. Diurnal change in trees as observed by optical and microwave sensors: The EOS synergism study. IEEE Trans. Geosci. Remote Sens. 29:807–821; 1991.
Way, J.; Zimmermann, R.; Rignot, E.; McDonald, K.; Oren, R. Winter and spring thaw as observed with imaging radar at BOREAS. J. Geophys. Res. Atmos. 102(ND24):29673–29684; 1997.
Welles, J.M. Some indirect methods of estimating canopy structure. Remote Sens. Rev. 5:31–43; 1990.
Welles, J.M.; Cohen, S. Canopy structure measurement by gap fraction analysis using commercial instrumentation. J. Exp. Bot. 47:1335–1342; 1996.
Weltz, M.A.; Ritchie, J.C.; Fox, H.D. Comparison of laser and field measurements of vegetation height and canopy cover. Water Resources Res. 30:1311–1319; 1994.
Wimbush, D.J.; Barrow, M.D.; Costin, A.B. Color stereo-photography for the measurement of vegetation. Ecology 48:150–152; 1967.
Wu, Y.; Strahler, A.H. Remote estimation of crown size, stand density, and biomass on the Oregon transect. Ecol. Applic. 4:299–312; 1994.
Zebker, H.; Goldstein, R. Topographic mapping from interferometric synthetic radar observations, J. Geophys. Res. 91:4993–5001; 1986.
Zeide, B. Fractal geometry in forestry applications, for. Ecol. Manage. 46(3-4): 179–188; 1991.
Zeide, B. Analysis of growth equations, For. Sci. 39(3):594–616; 1993.
Zoughi, R.; Wu, L.K.; Moore, R.K. Identification of the major backscattering sources in trees and shrubs at 10 GHz. Remote Sens. Environ. 19:269–290; 1986.
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Davis, F.W., Roberts, D. (2000). Stand Structure in Terrestrial Ecosystems. In: Sala, O.E., Jackson, R.B., Mooney, H.A., Howarth, R.W. (eds) Methods in Ecosystem Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1224-9_2
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