UCL DEPARTMENT OF GEOGRAPHY GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing (PPRS) Radiative Transfer Theory at optical wavelengths applied.

Slides:



Advertisements
Similar presentations
Lumped Parameter Modelling UoL MSc Remote Sensing Dr Lewis
Advertisements

Radiative Transfer Theory at Optical wavelengths applied to vegetation canopies: part 2 UoL MSc Remote Sensing Dr Lewis
UoL MSc Remote Sensing Dr Lewis
Optical Modeling of a-Si:H Thin Film Solar Cells with Rough Interfaces Speaker : Hsiao-Wei Liu 08/18/2010 Wed.
The Asymptotic Ray Theory
GEOGRAPHIC INFORMATION SYSTEM (GIS) AND REMOTE SENSING Lecture 4 Zakaria Khamis.
Environmental Remote Sensing GEOG 2021 Spectral information in remote sensing.
Land Data Assimilation
BIOP – Center for Biomedical Optics and New Laser Systems Light scattering from a single particle Peter E. Andersen Optics and Fluid Dynamics Dept. Risø.
Spectral Reflectance Curves
Plant Canopy Analysis Gaylon S. Campbell, Ph.D. Decagon Devices and Washington State University.
RESEARCH ON FPAR VERTICAL DISTRIBUTION IN DIFFERENT GEOMETRY MAIZE CANOPY Dr.Liu Rongyuan Pro. Huang Wenjiang
Overview of PROSPECT and SAIL Model 2nd IR/Microwave emissivity group meeting NOAA/NESDIS/STAR Bo Qian
1 Remote Sensing and Image Processing: 5 Dr. Mathias (Mat) Disney UCL Geography Office: 301, 3rd Floor, Chandler House Tel: (x24290)
Spectral Reflectance Curves Lecture 5. When specular reflection occurs, the surface from which the radiation is reflected is essentially smooth (i.e.
RADIATIVE PROPERTIES OF REAL MATERIALS Electromagnetic Theory: ▪ ideal, optically smooth surface ▪ valid for spectral range larger than visible Real Materials:
PhD remote sensing course, 2013 Lund University Understanding Vegetation indices PART 1 Understanding Vegetation indices PART 1 : General Introduction.
A Short Note on Selecting a Microwave Scattering or Emission Model A.K. Fung 1 and K. S. Chen 2 1 Professor Emeritus University of Texas at Arlington Arlington,
Radar, Lidar and Vegetation Structure. Greg Asner TED Talk.
Near Surface Soil Moisture Estimating using Satellite Data Researcher: Dleen Al- Shrafany Supervisors : Dr.Dawei Han Dr.Miguel Rico-Ramirez.
Atmospheric effect in the solar spectrum
Energy interactions in the atmosphere
METO 621 Lesson 12. Prototype problems in Radiative Transfer Theory We will now study a number of standard radiative transfer problems. Each problem assumes.
Dr. Jie ZouPHY Chapter 35 The Nature of Light and the Laws of Geometric Optics.
Understanding Multispectral Reflectance  Remote sensing measures reflected “light” (EMR)  Different materials reflect EMR differently  Basis for distinguishing.
Reflection and Refraction of Light
1 Satellite Remote Sensing of Particulate Matter Air Quality ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan.
Radiative Transfer Theory at Optical and Microwave wavelengths applied to vegetation canopies: part 1 UoL MSc Remote Sensing course tutors: Dr Lewis
Notes adapted from Prof. P. Lewis GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing (PPRS) Radiative Transfer Theory at.
UCL DEPARTMENT OF GEOGRAPHY GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing (PPRS) Radiative Transfer Theory at optical wavelengths applied.
Radiative Transfer Theory at Optical and Microwave wavelengths applied to vegetation canopies: part 2 UoL MSc Remote Sensing course tutors: Dr Lewis
Body Waves and Ray Theory
Pat Arnott, ATMS 749 Atmospheric Radiation Transfer CH4: Reflection and Refraction in a Homogenous Medium.
Objectives  The objectives of the workshop are to stimulate discussions around the use of 3D (and probably 4D = 3D+time) realistic modeling of canopy.
RADIATIVE TRANSFER MODEL
A.Olioso, S. Jacquemoud* & F. Baret UMR Climat, Sol et Environnement INRA Avignon, France * Institut de Physique du Globe de Paris (IPGP) Département de.
EM propagation paths 1/17/12. Introduction Motivation: For all remote sensing instruments, an understanding of propagation is necessary to properly interpret.
Attenuation by absorption and scattering
Remote Sensing Energy Interactions with Earth Systems.
Reflection and Refraction
Karnieli: Introduction to Remote Sensing
MVP: a model to simulate the spatial patterns of photosynthetically active radiation under discrete forest canopies Conghe Song and Lawrence E. Band Presented.
GEOG Fall 2003 Overview of Microwave Remote Sensing (Chapter 9 in Jensen) from Prof. Kasischke’s lecture October 6,2003.
Canopy Radiation Processes EAS Background Absorption of solar radiation drives climate system exchanges of energy, moisture, and carbon. Absorption.
Electromagnetic Radiation Most remotely sensed data is derived from Electromagnetic Radiation (EMR). This includes: Visible light Infrared light (heat)
Lecture 21 Nature of Light Reflection and Refraction
 Introduction  Surface Albedo  Albedo on different surfaces  Seasonal change in albedo  Aerosol radiative forcing  Spectrometer (measure the surface.
Remote Sensing of Vegetation. Vegetation and Photosynthesis About 70% of the Earth’s land surface is covered by vegetation with perennial or seasonal.
1 Lecture 7 Land surface reflectance in the visible and RIR regions of the EM spectrum 25 September 2008.
BIOPHYS: A Physically-based Algorithm for Inferring Continuous Fields of Vegetative Biophysical and Structural Parameters Forrest Hall 1, Fred Huemmrich.
Beyond Spectral and Spatial data: Exploring other domains of information GEOG3010 Remote Sensing and Image Processing Lewis RSU.
The link between particle properties (size, composition, shape, internal structure) and IOP Emmanuel Boss.
GEOG2021 Environmental Remote Sensing Lecture 3 Spectral Information in Remote Sensing.
1 PHY Lecture 5 Interaction of solar radiation and the atmosphere.
Geometric optical (GO) modeling of radiative transfer in plant canopy Xin Xi.
Physics 213 General Physics Lecture Last Meeting: Electromagnetic Waves, Maxwell Equations Today: Reflection and Refraction of Light.
GEOGG121: Methods Inversion I: linear approaches Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel:
Remcom Inc. 315 S. Allen St., Suite 416  State College, PA  USA Tel:  Fax:   ©
Interactions of EMR with the Earth’s Surface
Beyond Spectral and Spatial data: Exploring other domains of information: 2 GEOG3010 Remote Sensing and Image Processing Lewis RSU.
Electromagnetic Radiation
Understanding Multispectral Reflectance
GEOG2021 Environmental Remote Sensing
HSAF Soil Moisture Training
Active Microwave Remote Sensing
Using vegetation indices (NDVI) to study vegetation
Spectral Signatures and Their Interpretation
Lumped Parameter Modelling
Vegetation.
Lumped Parameter Modelling
Presentation transcript:

UCL DEPARTMENT OF GEOGRAPHY GEOGG141/ GEOG3051 Principles & Practice of Remote Sensing (PPRS) Radiative Transfer Theory at optical wavelengths applied to vegetation canopies: part 1 Notes adapted from Prof. P. Lewis Dr. Mathias (Mat) Disney UCL Geography Office: 113, Pearson Building Tel:

UCL DEPARTMENT OF GEOGRAPHY Aim of this section Introduce RT approach as basis to understanding optical and microwave vegetation response enable use of models enable access to literature

UCL DEPARTMENT OF GEOGRAPHY Scope of this section Introduction to background theory –RT theory –Wave propagation and polarisation –Useful tools for developing RT Building blocks of a canopy scattering model –canopy architecture –scattering properties of leaves –soil properties

UCL DEPARTMENT OF GEOGRAPHY Reading Full notes for these lectures Books Jensen, J. (2007) Remote Sensing: an Earth Resources Perspective, 2 nd ed., Chapter 11 ( ), 1 st ed chapter 10. Liang, S. (2004) Quantitative Remote Sensing of Land Surfaces, Wiley, Chapter 3 (76-142). Monteith, J. L. and Unsworth, M. H. (1990) Principles of Environmental Physics, 2 nd ed., ch 5 & 6. Papers Feret, J-B. et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112, Jacquemoud. S. and Baret, F. (1990) PROSPECT: A model of leaf optical properties spectra, RSE, 34, Nilson, T. and Kuusk, A. (1989) A canopy reflectance model for the homogeneous plant canopy and its inversion, RSE, 27, Price, J. (1990), On the information content of soil reflectance spectra RSE, 33, Walthall, C. L. et al. (1985) Simple equation to approximate the bidirectional reflectance from vegetative canopies and bare soil surfaces, Applied Optics, 24(3),

UCL DEPARTMENT OF GEOGRAPHY Why build models? Assist data interpretation calculate RS signal as fn. of biophysical variables Study sensitivity to biophysical variables or system parameters Interpolation or Extrapolation fill the gaps / extend observations Inversion estimate biophysical parameters from RS aid experimental design plan experiments

UCL DEPARTMENT OF GEOGRAPHY

Radiative Transfer Theory Applicability –heuristic treatment consider energy balance across elemental volume –assume: no correlation between fields –addition of power not fields no diffraction/interference in RT –can be in scattering –develop common (simple) case here

UCL DEPARTMENT OF GEOGRAPHY Radiative Transfer Theory Case considered: –horizontally infinite but vertically finite plane parallel medium (air) embedded with infinitessimal oriented scattering objects at low density –canopy lies over soil surface (lower boundary) –assume horizontal homogeneity applicable to many cases of vegetation But…..?

UCL DEPARTMENT OF GEOGRAPHY Building blocks for a canopy model Require descriptions of: –canopy architecture –leaf scattering –soil scattering

UCL DEPARTMENT OF GEOGRAPHY Canopy Architecture 1-D: Functions of depth from the top of the canopy (z).

UCL DEPARTMENT OF GEOGRAPHY Canopy Architecture 1-D: Functions of depth from the top of the canopy (z). 1.Vertical leaf area density (m 2 /m 3 ) 2.the leaf normal orientation distribution function (dimensionless). 3.leaf size distribution (m)

UCL DEPARTMENT OF GEOGRAPHY Canopy Architecture Leaf area / number density – (one-sided) m 2 leaf per m 3 LAI

UCL DEPARTMENT OF GEOGRAPHY Canopy Architecture Leaf Angle Distribution

UCL DEPARTMENT OF GEOGRAPHY Archetype Distributions:  planophile   erectophile   spherical   plagiophile   extremophile  Leaf Angle Distribution

UCL DEPARTMENT OF GEOGRAPHY Archetype Distributions: Leaf Angle Distribution

UCL DEPARTMENT OF GEOGRAPHY RT theory: infinitesimal scatterers –without modifications (dealt with later) In optical, leaf size affects canopy scattering in retroreflection direction –‘roughness’ term: ratio of leaf linear dimension to canopy height also, leaf thickness effects on reflectance /transmittance Leaf Dimension

UCL DEPARTMENT OF GEOGRAPHY Canopy element and soil spectral properties Scattering properties of leaves –scattering affected by: Leaf surface properties and internal structure; leaf biochemistry; leaf size (essentially thickness, for a given LAI). Excellent review here:

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf surface properties and internal structure optical Specular from surface Smooth (waxy) surface - strong peak hairs, spines - more diffused

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf surface properties and internal structure optical Diffused from scattering at internal air-cell wall interfaces Depends on total area of cell wall interfaces Depends on refractive index: varies: nm

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf surface properties and internal structure optical More complex structure (or thickness): - more scattering - lower transmittance - more diffuse

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112,

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112,

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112,

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf water Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112,

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry –pigments: chlorophyll a and b,  -carotene, and xanthophyll absorb in blue (& red for chlorophyll) –absorbed radiation converted into: heat energy, flourescence or carbohydrates through photosynthesis

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Leaf biochemstry –Leaf water is major consituent of leaf fresh weight, around 66% averaged over a large number of leaf types –other constituents ‘dry matter’ cellulose, lignin, protein, starch and minerals –Absorptance constituents increases with concentration reducing leaf reflectance and transmittance at these wavelengths.

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Optical Models –flowering plants: PROSPECT – a generalised plate model Figure from: & see for more detail on various approaches to leaf optical properties modellinghttp://teledetection.ipgp.jussieu.fr/opticleaf/models.htm Jacquemoud. S. and Baret, F. (1990) PROSPECT: A model of leaf optical properties spectra, RSE, 34,

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves Optical Models –flowering plants: PROSPECT – extension of plate model to N layers

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of leaves leaf dimensions –optical increase leaf area for constant number of leaves - increase LAI increase leaf thickness - decrease transmittance (increase reflectance)

UCL DEPARTMENT OF GEOGRAPHY Scattering properties of soils Optical and microwave affected by: –soil moisture content –Wetter soils are darker (optical); have lower dielectric (microwave) –soil type/texture –soil surface roughness –shadowing (optical) –coherent scattering (microwave)

UCL DEPARTMENT OF GEOGRAPHY soil moisture content Optical –effect essentially proportional across all wavelengths enhanced in water absorption bands

UCL DEPARTMENT OF GEOGRAPHY soil texture/type Optical –relatively little variation in spectral properties –Price (1990): PCA on large soil database % of variation in 4 PCs –Stoner & Baumgardner (1982) defined 5 main soil types: organic dominated minimally altered iron affected organic dominated iron dominated Price, J. (1990), On the information content of soil reflectance spectra RSE, 33,

UCL DEPARTMENT OF GEOGRAPHY Soil roughness effects Affects directional properties of reflectance (optical particularly) Simple models: –as only a boundary condition, can sometimes use simple models e.g. Lambertian e.g. trigonometric (Walthall et al., 1985; Nilson and Kuusk 1990) where θ v,i are the view and illumination (sun) zenith angles; ϕ is relative azimuth angle ( ϕ i - ϕ v ).

UCL DEPARTMENT OF GEOGRAPHY Soil roughness effects Rough roughness: –optical surface scattering clods, rough ploughing –use Geometric Optics model (Cierniewski) –projections/shadowing from protrusions

UCL DEPARTMENT OF GEOGRAPHY Soil roughness effects Rough roughness: –optical surface scattering Note backscatter reflectance peak (‘hotspot’) minimal shadowing backscatter peak width increases with increasing roughness

UCL DEPARTMENT OF GEOGRAPHY Soil roughness effects Rough roughness: –volumetric scattering consider scattering from ‘body’ of soil –particulate medium –use RT theory (Hapke - optical) –modified for surface effects (at different scales of roughness)

UCL DEPARTMENT OF GEOGRAPHY Summary Introduction –Examined rationale for modelling –discussion of RT theory –Scattering from leaves Canopy model building blocks –canopy architecture: area/number, angle, size –leaf scattering:spectral & structural –soil scattering:roughness, type, water