Dataset Edition

General information
Dataset nameTERRA - MODIS - Leaf Area Index - West Africa - 0.01
Data typeBIOSPHERE
Created on2016-11-28
Useful in the framework ofOPERATIONAL-DATA > Satellite products
Dataset Contact(s)
Data access Original dataset as provided by the Principal Investigator
History

ISSUE2016-11-29

PurposeThese products are derived from the MOD15_BU 1km data set generated at the Boston University and available to download on the site ftp://primavera.bu.edu/pub/datasets/MODIS/MOD15_BU/.

LAI (m²/m²) is defined as half the total foliage area per unit ground surface area. The FAPAR is the daily fraction of photosynthetically active radiation (PAR: [0.4-0.7µm]) absorbed by vegetation. FAPAR is dimensionless. The main algorithm use to generate the LAI and FAPAR is based on a 3D radiative model depending on the vegetation structure (Knyazikhin et al., 1998). If the main algorithm fails, a back-up procedure is applied to assess LAI and FAPAR from vegetation indices (Myneni et al., 1997).

A bug was found in the code generating MOD15A2 FPAR product: FPAR under diffuse radiation was produced instead of FPAR under direct solar radiation, as required by the product specifications. The correction scheme to calculate FPAR under direct radiation for MOD15_BU was proposed, and MOD15_BU FPAR data set was re-processed in January 2005. These changes have no impact on the LAI algorithm. The reprocessed version of MOD15_BU LAI/FPAR products is called version 4.1.

The MODIS LAI, FAPAR and QA products cover the period from February, 2000 to July 2005 with a monthly temporal resolution.

Data encoding: The encoding used for QA is:
1 – 4 : “High quality level”: defined as number of pixels generated by main algorithm without saturation. The higher the value, the higher the quality
5 – 8: “Low quality level”: defined as 4 + number of pixels generated by main algorithm with saturation and backup algorithm. The higher the value, the higher the quality

At the same resolution and the same month, QA for FAPAR is the same with QA for LAI.

The QA file for December 2000 is missing.

For LAI, FAPAR and QA:
· Urban, built-up class : 250
· Permanent wetlands, marshes : 251
· Perennial snow, ice, tundra : 252
· Barren desert, or sparsely vegetated area : 253
· Water(ocean or inland) : 254
· Fill value for non-computed pixels or missing pixels : 255

Projection: The original MOD15_BU products are presented in the sinusoïdal projection. They have been put in the geographical lat/lon projection (“plate-carrée”) with a grid step equal to 0.01°. The pixels of the grid are located by the coordinates of their center. The “West_Africa” area covers the zone from 25° West to 25° East, and from 5° South to 20° North.

Quality analysis: Best quality retrievals are obtained with the Main RT-based algorithm. In case of high LAI (>3.5) surface reflectances have low sensitivity to LAI (saturation domain). Only retrievals by main algorithm (with or without saturation) are recommended for application studies.
In case of main algorithm failure, the back-up algorithm (LAI/FPAR-NDVI empirical relationships) is employed. Such retrievals have generally low reliability and are not recommended for application studies, including validation.
The biome LAI profiles have generally the expected shape. Needle leaf forests, however, show anomalous seasonality. Low LAI during winter time is due to low availability (low solar zenith angle) and poor quality (snow and cloud contamination) of input reflectance data. The Main algorithm mostly fails and unreliable LAI retrievals over needle leaf forests are generated by the back-up algorithm.

Validation:
· Grass savanna, Senegal, western sudano-sahelian zone, 2001-2002 Seasonal dynamics of both in situ LAI and FPAR were captured well by MODIS LAI and FPAR (Figure below). MODIS LAI is overestimated by approximately 2-15% and the overall level of FPAR is overestimated by 8-20%. (Fensholt et al., 2004)

· Coniferous forests, Finland, June 2000
Comparison of aggregated high-resolution LAI map, derived from in-situ measurements, and corresponding MODIS LAI suggests satisfactory behavior of the MODIS LAI algorithm although variation in MODIS LAI product is higher than expected (Wang et al., 2004).

· Croplands, Alpilles, France, February-March 2001
MODIS LAI is accurate to within 0.3LAI; precision is 20%, uncertainty is 25%. Biome misidentification deteriorates the accuracy by factor of 2 (Tan et al., 2004).

Any details about the MODIS LAI/FAPAR products and the algorithms are available on the Boston University website : http://cybele.bu.edu.
Instrument
SatelliteTERRA
InstrumentMODIS
Instrument typeImaging Spectrometers/Radiometers
Parameters
Parameter nameleaf area index
Parameter keywordBiosphere > Vegetation > Vegetation Index
Unit
Coverage
Temporal Coverage
Date begin2000-02-01Date end2006-12-31
Geographic Coverage
Area nameWest Africa
West bounding coordinate (°)-25East bounding coordinate (°)25
North bounding coordinate (°)20South bounding coordinate (°)-5
Data resolution
Temporal resolution0000-01-00 00:00:00
Latitude resolution0.01
Longitude resolution0.01
Data use information
Use constraintsPublic data
Data policyAMMA data policy
Data format(s)NetCDF