# Presentation: 202742

## Biophysical products from Landsat

**LANDSAT Science Team Meeting**
**June 12-14, 2007**

**Ramakrishna Nemani**
- NASA Ames Research Center
**Ranga Myneni**
- Boston University
**Jennifer Dungan**
- NASA Ames Research Center

## Planned Contribution

- Develop an operational capability to produce vegetation green leaf area index (LAI) from Landsat data by adapting a physically based approach conceived and implemented by the MODIS Science team.
- LAI- Leaf Area Index is defined as one-sided green leaf area per unit ground area in broadleaf canopies and as the projected needle leaf area in coniferous forests.
- LAI is an important variable for quantifying the cycling of water, carbon and nutrients through ecosystems.

## Good practice on reporting predictions

- “When reporting the estimated value and uncertainty of such a measurand, one should always make clear that the measurand is defined by a particular method of measurement and indicate what that method is. One should also give the measurand a name which indicates that it is defined by a measurement method, for example, by adding a modifier such as `conventional.’”
- 				-Taylor and Kuyatt (1994)

## NIST standard concepts and terminologyTaylor and Kuyatt (1994)

**Accuracy** – a qualitative statement about the closeness of the measurement to the value of the variable of interest (the measurand)
**Precision** – a qualitative statement about the repeatability and/or reproducibility of the measurement
**Repeatability** – the closeness of the agreement between the results of successive measurements of the same measurand carried out under the same conditions of measurement
**Reproducibility** - closeness of the agreement between the results of measurements of the same measurand carried out under changed conditions of measurement
**Random error** - result of a measurement minus the mean that would result from an infinite number of measurements of the same measurand carried out under repeatability conditions
**Systematic error** (sometimes called bias) - mean that would result from an infinite number of measurements of the same measurand carried out under repeatability conditions minus the value of the measurand

## NIST standard concepts and terminology(continued)

**Standard uncertainty** – a quantitative statement expressed as the standard deviation of repeated or reproduced measurements obtained using statistical or other methods.  The suggested symbol is ui
**Combined standard uncertainty **–** **the standard uncertainty obtained by combining the individual standard uncertainties using the law of propagation of uncertainty.  The suggested symbol is  uc
**Expanded uncertainty **–** **the measure of uncertainty that defines an interval about the measurement result y within which the value of the measurand Y is confidently believed to lie. The suggested symbol is U;  U = kuc(y) and it is confidently believed that Y-U ≤ Y ≤ y+U, which is commonly written as Y = y ± U.  The conventional coverage factor k is 2; this should be specified.

## OLI Requirements

_**5.6.1**__**	**__**Absolute Radiometric Uncertainty**_
- OLI-792	The OLI absolute radiometric uncertainty shall be as given in Table 5.6-1 for the range of Ltypical to 0.9 Lmax (Table 5.6-2).
- OLI-1420  At any other radiance across the range of 0.3 Ltypical to Ltypical the absolute uncertainty shall not exceed the values in Table 5.6-1 by more than 0.5%. This requirement applies to extended, spatially uniform, unpolarized targets with a known spectral shape.
- OLI-793  Pre-launch radiance uncertainties shall be established relative to National Institute for Standards and Technology (NIST) standards.
- OLI-794  Uncertainty estimates shall include the NIST standard uncertainties.

| Parameter | Requirement (1-sigma) |
| --- | --- |
| Radiance | 5% |
| Top of Atmosphere (TOA) Reflectance | 3% of actual TOA |

## Questions

- Radiometric specifications are required to be standard uncertainties.  How were these determined?
- What are the implications of the specifications for OLI for standard uncertainties of surface spectral reflectance?
- How will reflectance uncertainties influence the uncertainty of leaf area index predictions?
- What influences LAI accuracy more -- assumptions in the model or propagation of input error sources?