Skip to main content

Geometric-Optical Modeling of Forests as Remotely-Sensed Scenes Composed of Three-Dimensional, Discrete Objects

  • Chapter
Book cover Photon-Vegetation Interactions

Abstract

Mathematical modeling of the interaction of electromagnetic radiation with vegetation canopies is a research field that has been highly active in recent years. Modeling a canopy as a “turbid medium” of leaf and foliage elements in a slab geometry, the general equations of radiative transfer (Chandrasekhar 1950) have been approximated and solved in various ways and with varying types of description of the canopy. For example, both Suits (1972) and Verhoef (1984) use a four-stream approximation of the radiation flow and its interaction with canopy elements that has its origin in work by Schuster (1905) and Schwartzchild (1914). Cooper et al. (1982) and Kimes (1984) also use multistream approximations which, along with a variety of models for photon transport, are comprehensively reviewed in Myneni et al. (1989). In these models, the canopy elements are parameterized by such variables as the reflectance and transmittance of the leaf, leaf area index, and the leaf angle distribution. Many of these models are one-dimensional, in that the canopies vary only with height above the soil or ground surface.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Abbreviations

B, B’:

random sets of points within a space of arbitrary dimension

b:

vertical radius of spheroid

Covf(d):

punctual covariance of scene

d:

distance vector between two background points

dl,d2 :

intermediate variables in calculation of disk overlap function

ds-v :

distance between centers of illumination and viewing projections

dv:

elementary volume element for space of arbitrary dimension

f(x):

spatial binary (0,1) function returning 1 if point x lies in sunlit background, 0 else

G(θ):

projected area of a crown at angle θ

G(θ, z):

projected area of leaf at angle θ, depth z

G1 :

area of a single canopy envelope within a section z + dz

H:

total depth of canopy

h:

height of spheroid above ground plane

Ic :

radiance of sunlit crown or leaf

IG :

radiance of sunlit background

IS :

radiance of scene

Is :

radiance of an individual pixel

IT :

radiance of shaded crown or leaf

IZ :

radiance of shaded background

IPOV:

Instantaneous Field of View of a sensor

JP(d):

convolution of point spread function with its conjugate at distance d

KG, KZ, KC, K T :

proportion of scene in scene component, spheroid canopy model

kG, kZ, kC, kT :

proportion of scene component within a individual pixel

LG, LZ, LC, LT :

proportion of scene in scene component, leaf canopy model

N(z):

number of leaf centers in a section of the canopy between z and z + dz

Ō(θs, θV, ϕ):

average overlap of illumination and viewing shadows on the plane for each of a collection of objects above the plane

O(θs, θV, ϕ, r):

overlap area of illumination and viewing shadows on the background plane for a spheroid-on-a-stick of radius r

O(θs, θV, ϕ, z - t):

overlap of illumination and viewing shadows for a leaf at distance z - t

O*(d):

overlap function for compound figure of illumination and viewing projections for a discrete object on a plane

P:

subscript denoting pixel

PSF:

Point Spread Function

p(dv):

probability that a point falls within elementary volume element dv

p(r):

probability density function for r

p(θ):

gap fraction at angle θ

p(θ, z):

gap fraction at angle θ, depth z for leaf canopy

R2 :

domain of two-space containing the scene

r:

horizontal radius of spheroid

rs, rv :

radius of disc with area equal to elliptical projection of spheroid onto background area

ss, sv :

intermediate variables in computation of disc overlap function

t:

position vector variable of integration; variable of integration for canopy depth

ts, tv :

intermediate variables in computation of disc overlap function

V(KG):

global (punctual) variance of KG

V(kG):

variance of kG observed within pixels of an image

w:

intermediate depth within canopy

x:

point (coordinate vector) in two-space

z:

depth within canopy, 0 at top to H at ground surface

z’:

variable of integration for canopy depth

λ:

density of object centers on the plane

λ(z):

volume density of leaf centers at depth z

λ(d):

punctual variogram at distance d

γp(d):

variogram at distance d regularized over a pixel P

θs, θV :

illumination (Is) or viewing angle (v), measured from nadir

θ’s, θ’v :

nadir angle of direction vector associated with spheroid and illumination or viewing angle

σ2 p(kG):

parametric variance of KG within pixels

ϕ:

azimuth angle between illumination and viewing positions

χ:

intermediate variable (angle) in disc overlap function

ψ:

phase angle between illumination and viewing direction vectors for spheroid

References

  • Chandrasekhar S (1950) Radiative Transfer. Oxford Univ Press, Lond

    Google Scholar 

  • Cooper K, Smith JA, Pitts D (1982) Reflectance of a vegetation canopy using the adding method. Appl Opt 21:4112–4118

    Article  PubMed  CAS  Google Scholar 

  • Franklin J, Strahler AH (1988) Invertible canopy reflectance modeling of vegetation structure in semiarid woodland. IEEE Trans Geosci Remote Sens 26:809–825

    Article  Google Scholar 

  • Franklin J, Michaelson J, Strahler AH (1985) Spatial analysis of density dependent pattern in coniferous forest stands. Vegetado 64:29–36

    Article  Google Scholar 

  • Getis A, Boots B (1978) Models of spatial processes. Cambridge Univ Press, Lond New York

    Google Scholar 

  • Hafley WI, Scheuner HT (1977) Statistical distributions for fitting diameter and height data in even aged stands. Can For J Res 7:481–489

    Article  Google Scholar 

  • Jupp DLB, Walker J, Penridge LK (1986) Interpretation of vegetation structure in Landsat MSS imagery: A case study in disturbed semi-arid eucalypt woodlands, Part 2: Model-based analysis. J Environ Manage 23:35–57

    Google Scholar 

  • Jupp DLB, Strahler AH, Woodcock CE (1988) Autocorrelation and regularization in digital images I. Basic theory. IEEE Trans Geosci Remote Sens 26:463–473

    Article  Google Scholar 

  • Jupp DLB, Strahler AH, Woodcock CE (1989) Autocorrelation and regularization in digital images II. Simple image models. IEEE Trans Geosci Remote Sens 27:247–258

    Article  Google Scholar 

  • Kimes DS (1984) Modeling the directional reflectance from complete homogeneous vegetation canopies with various leaf-orientation distributions J Opt Soc Am Al:725

    Google Scholar 

  • Kimes DS, Newcomb WW, Nelson RF, Schutt JB (1986) Directional reflectance distributions of a hardwood and pine forest canopy. IEEE Trans Geosci Remote Sens GE-24: 281–293

    Article  Google Scholar 

  • Li X, Strahler AH (1985) Geometric-optical modeling of a conifer forest canopy. IEEE Trans Geosci Remote Sens GE-23:705–721

    Article  Google Scholar 

  • Li X, Strahler AH (1986) Geometric-optical bidirectional reflectance modeling of a coniferous forest canopy. IEEE Trans Geosci Remote Sens GE-24:906–919

    Article  Google Scholar 

  • Li X, Strahler AH (1988) Modeling the gap probability of a discontinuous vegetation canopy. IEEE Trans Geosci Remote Sens 26:161–170

    Article  Google Scholar 

  • Matheron G (1965) Les variables régionalisées et leur estimation. Masson et Cie, Paris

    Google Scholar 

  • Myneni RB, Ross J, Asrar G (1989) A review on the theory of photon transport in leaf canopies. Agric For Meterol 45:1–153

    Article  Google Scholar 

  • Otterman J, Weiss GH (1984) Reflection from a field of randomly located vertical protrusions. Appl Opt 23:1931–1936

    Article  PubMed  CAS  Google Scholar 

  • Schuster A (1905) Radiation through foggy atmospheres. Astrophys J 21:1–22

    Article  Google Scholar 

  • Schwartzchild K (1914) Sitz Lings ber Preuss Akad Wiss, Berlin, pp 1183

    Google Scholar 

  • Serra J (1982) Image analysis and mathematical morphology. Academic Press, Lond New York

    Google Scholar 

  • Spanner MA, Pierce LL, Peterson DL, Running SW (1990) Remote sensing of temperate coniferous forest leaf area index: The influence of canopy closure, understory vegetation and background reflectance. Int J Remote Sens 11:95–112

    Article  Google Scholar 

  • Strahler AH, Woodcock CE, Smith JA, (1986) On the nature of models in remote sensing. Remote Sens Environ 20:121–139

    Article  Google Scholar 

  • Strahler AH, Wu Y, Franklin J (1988) Remote estimation of tree size and density from satellite imagery by inversion of a geometric-optical canopy model. In: Proc 22nd Int Symp Remote Sens Environ, Abidjan, Côte D’Ivoire, Oct 20–26, 1988. Environ Res Inst Michigan, Ann Arbor, MI, USA, pp 377–388

    Google Scholar 

  • Suits GH (1972) The calculation of the directional reflectance of a vegetative canopy. Remote Sens Environ 2:117–125

    Article  Google Scholar 

  • Verhoef W (1984) Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model. Remote Sens Environ 16:125–141

    Article  Google Scholar 

  • Walker J, Jupp DLB, Penridge LK, Tian G (1986) Interpretation of vegetation structure in Landsat MSS imagery: A case study in disturbed semi-arid eucalypt woodlands, Part 1: Field data analysis. J Environ Manage 23:19–34

    Google Scholar 

  • Woodcock CE, Strahler AH, Jupp DLB (1988a) The use of variograms in remote sensing I: Scene models and simulated images. Remote Sens Environ 25:323–348

    Article  Google Scholar 

  • Woodcock CE, Strahler AH, Jupp DLB (1988b) The use of variograms in remote sensing II: Real digital images. Remote Sens Environ 25:349–379

    Article  Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1991 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Strahler, A.H., Jupp, D.L.B. (1991). Geometric-Optical Modeling of Forests as Remotely-Sensed Scenes Composed of Three-Dimensional, Discrete Objects. In: Myneni, R.B., Ross, J. (eds) Photon-Vegetation Interactions. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75389-3_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-75389-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-75391-6

  • Online ISBN: 978-3-642-75389-3

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics