Airborne MSS data to estimate GLAI

Abstract Airborne multispectral scanner ( MSS) data, collected in June 1984, were used to estimate the green leaf area index ( GLAI) for 60 km2 of grassland. The methodology involved (i) radiometric and atmospheric correction, (ii) production of a vegetation index image, (iii) calculation of a calibration relationship between a vegetation index and GLAI, (iv) production of an image of estimated GLAI by inversion of the calibration relationship in (iii), and (v) accuracy assessment. The initial accuracy of GLAI estimation was ± 0-75 GLAI for an area and 17-40 per cent at the 95 per cent confidence level, for a six-class classification. Refinements to the methodology were evaluated by their effect upon the accuracy of GLAI estimation. In order of increasing importance these refinements were: suppression of environmental effects on the remotely sensed data, processing on a per-field rather than a per-pixel basis, calculation of the calibration relationship between a vegetation index and GLAI, using ground-ba...

[1]  Christopher O. Justice,et al.  Unsupervised classification of MSS Landsat data for mapping spatially complex vegetation , 1980 .

[2]  P. Curran,et al.  The accuracy of ground data used in remote-sensing investigations , 1985 .

[3]  J. E. Chance,et al.  Crop identification and leaf area index calculations with Landsat multitemporal data , 1981 .

[4]  G. Asrar,et al.  Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat1 , 1984 .

[5]  D. Williams.  Overview of the NERC airborne thematic mapper campaign of September 1982 , 1984 .

[6]  Ghassem R. Asrar,et al.  Leaf-area estimates from spectral measurements over various planting dates of wheat , 1985 .

[7]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[8]  W. E. Boyd,et al.  Determination of range biomass using Landsat , 1979 .

[9]  N. Goel,et al.  Inversion of vegetation canopy reflectance models for estimating agronomic variables. I. Problem definition and initial results using the Suits model , 1983 .

[10]  Estimating leaf-area index of wheat with LANDSAT data , 1979 .

[11]  D. S. Kimes,et al.  Remote sensing of row crop structure and component temperatures using directional radiometric temperatures and inversion techniques , 1983 .

[12]  A. Wald.  The Fitting of Straight Lines if Both Variables are Subject to Error , 1940 .

[13]  C. Tucker.  Asymptotic nature of grass canopy spectral reflectance. , 1977, Applied optics.

[14]  J. R. Jensen.  Biophysical Remote Sensing , 1983 .

[15]  G. Badhwar,et al.  Classification of corn and soybeans using multitemporal thematic mapper data , 1984 .

[16]  Compton J. Tucker,et al.  A critical review of remote sensing and other methods for non-destructive estimation of standing crop biomass , 1980 .

[17]  Giles M. Foody,et al.  Land-Cover Mapping from Synthetic Aperture Radar: The Importance of Radiometric Correction , 1986 .

[18]  M. Duggin.  Factors limiting the discrimination and quantification of terrestrial features using remotely sensed radiance , 1985 .

[19]  Ghassem R. Asrar,et al.  Estimates of leaf area index from spectral reflectance of wheat under different cultural practices and solar angle , 1985 .

[20]  Paul J. Curran,et al.  Simple size for ground and remotely sensed data , 1986 .

[21]  P. Curran.  Principles of remote sensing , 1984 .

[22]  Vytautas Klemas,et al.  Remote sensing of biomass and annual net aerial primary productivity of a salt marsh , 1984 .

[23]  Edward J. Milton,et al.  A portable multiband radiometer for ground data collection in remote sensing , 1980 .

[24]  Curran Pj.  Estimating green LAI from multispectral aerial photography , 1983 .

[25]  P. J. Curran,et al.  The estimation of green-leaf-area index from remotely sensed airborne multispectral scanner data , 1984 .

[26]  V. Klemas,et al.  Quantitative assessment of tidal wetlands using remote sensing , 1980 .

[27]  D. Deering.  Measuring forage production of grazing units from Landsat MSS data , 1975 .

[28]  Richard L. Thompson,et al.  Inversion of vegetation canopy reflectance models for estimating agronomic variables. V. Estimation of leaf area index and average leaf angle using measured canopy reflectances , 1984 .

[29]  P. Sprent.  Models in regression and related topics , 1971 .

[30]  P. S. Lloyd.  The Grassland Vegetation of the Sheffield Region: II. Classification of Grassland Types , 1972 .

[31]  P. J. Curran,et al.  Multispectral remote sensing for the estimation of green leaf area index , 1983, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.

[32]  P. J. Curran,et al.  The importance of measurement error for certain procedures in remote sensing at optical wavelengths , 1986 .

[33]  T. Ford.  Limestones and caves of the Peak District , 1977 .

[34]  James E. McMurtrey,et al.  Temporal relationships between spectral response and agronomic variables of a corn canopy , 1981 .

[35]  A. Hay.  Sampling designs to test land-use map accuracy , 1979 .

[36]  Mike I. Pedley.  Combined remotely sensed and map data as an aid to image interpretation and analysis , 1986 .