| |
| |
|
| |
| Leaf area index
|
| |
| Definition |
|
|
The total area of leaves (one-sided) in relationship to the ground below them.
|
|
| Rationale |
|
|
Leaf Area Index (LAI) describes a fundamental property of the plant canopy in its interaction with the atmosphere, especially concerning radiation, energy, momentum and gas exchange (Monteith and Unsworth, 1990). Leaf area plays a key role in the absorption of radiation, in the deposition of photosynthates during the diurnal and seasonal cycles, and in the pathways and rates of biogeochemical cycling within the canopy-soil system (Bonan, 1995; Van Cleve et al., 1983). Various soil-vegetation-atmosphere models and BGC models use LAI (Sellers et al., 1986; and Bonan, 1993a). Globally, it varies from less than 1 to above 10 but there is also significant variation within biomes at regional, landscape, and local levels.
|
|
| Users |
|
|
Climate modellers, weather forecast modellers, ecosystem modellers, BGC modellers, and atmosphere- ecosystem interaction modellers.
|
| |
| Assessment method |
|
Tiers 1-3: destructive sampling; allometric equations; indirect (light penetration-based estimates);
Tier 5: spectral radiance (high or medium resolution).
|
|
| Units of Measure |
|
|
m2/m2
|
|
| Frequency of measurement |
|
IOS: monthly;
Post-IOS: product to be issued every 10-30 days.
|
|
| Spatial resolution |
|
IOS: 1-8 km for global applications;
Post-IOS: 0.25-1.0 km.
|
|
| Accuracy/precision required |
|
IOS: 15-25% of true value;
Post-IOS: 5-15% of true value.
|
|
| Associated measurements |
|
|
LAI estimation from satellite data requires ground data for validation and testing for bias. Satellite data must be corrected for atmospheric effects, therefore requiring additional information on the state of the atmosphere (especially water vapour, aerosols, and ozone). Non-destructive (optical) measurements are the preferred approach for obtaining ground measurements (Chen and Cihlar, 1995b).
|
|
| Present status |
|
|
Similar to FPAR, a global LAI data set has been produced (Sellers, et al., 1994). LAI in the data set is calculated from FPAR which is treated as a linear function of the simple ratio. Different relationships between LAI and FPAR were used for two broad vegetation types. The validation of the data set has not yet been done (Hall, et al., 1995). There have been many published results on the relationship between vegetation indices and LAI for agricultural crops and grasslands, but similar results are limited for natural ecosystems.
|
|
| R and D needed |
|
- Development of methods for various biomes and validation. Improvement of methods to increase robustness and reduce dependence of ground data. Improvements in the canopy radiation models used as the basis for inferring FPAR from satellite measurements and for relating satellite values to various levels within the canopy.
- Complete testing of non-destructive ground methods in various biomes, especially needleleaf forests;
- Continue the development of prototype LAI products at various spatial resolutions. Test the ability of satellite data to produce LAI products in different parts of the phenological cycle. Test the use of products in models;
- Produce time series of LAI data at various spatial resolutions and coverage, from regional to global. Transfer and optimise methodologies to new data sources;
- Continue the testing and use of data in models.
|
|
References |
|
|
Bonan,
G.B. 1993
|
|
|
. Physiological derivation of the observed relationship
between net primary production and mean annual temperature. Tellus, Ser.13,
45, 397-408.
|
|
|
Bonan,
G.B. 1995. Land-atmospheric interactions for climate system models:
Coupling biophysical, biogeochemical and ecosystem dynamical processes. Remote
Sensing of Environment, 51, 57-73.
|
|
|
Chen,
J.M.; Cihlar, J. 1995
|
|
|
. Algorithms for retrieving LAI and FPAR of
boreal conifer forests using Landsat TM images. Digest of 17Th
Canadian Symposium on Remote Sensing, Saskatoon, Canada.
|
|
|
Hall,
F.G.; Townshend, J.R.; Engmann, E.T. 1995. Status of remote sensing
algorithms for estimation of land surface state parameters. Remote Sensing
of Environment, 51 138-156.
|
|
|
Monteith,
J.L.; Unsworth, M.H. 1990. Principles of Environmental Physics. Edward
Arnold, London, UK.
|
|
|
Sellers,
P.J.; Mintz, Y.; Sud, Y.C. and Dalcher 1986. A single biosphere model (SiB)
for use within general circulation models. Atmospheric Science, 43,
505-531.
|
|
|
Sellers,
P.J.; Los, S.O.; Tucker, C.J. Justice, C.O.; Dazlich, D.A.; Collatz, G.J.; Randall,
D.A. 1994. A global 1˚ by 1˚ NDVI data set for climatic studies,
pt.2: The adjustment of the NDVI and generation of global fields of terrestrial
biophysical parameters. International Journal of Remote Sensing, 17,
3519-3546.
|
|
|
Van
Cleve, K.; Oliver, L.A.; Schlender, R.; Viereck, L.A.
and Dynnes, C.T. 1983. Productivity and nutrient cycling in taiga forest
ecosystems. Canadian Forest Research, 13, 703-720.
|
|
| |
|
|
