Summary Results from:

Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements
As they relate to the validation of MOD15

Authors: Rasmus Fensholt, Inge Sandholt, Michael Schultz Rasmussen

Source: Remote Sensing of Environment 91 (2004) 490-507

Link to: Access Publication

Abstract:

On global and regional scales, earth observation (EO)-based estimates of leaf area index (LAI) provide valuable input to climate and hydrologic modelling, while fraction of absorbed photosynthetically active radiation (fAPAR) is a key variable in the assessment of vegetation productivity and yield estimates. Validation of moderate resolution imaging spectroradiometer (MODIS) LAI and fAPAR products is an important prerequisite to using these variables for global modelling or for local water resource modelling and net primary production (NPP) assessment, as in semi-arid West Africa and Senegal. In situ measurements of LAI and fAPAR from three sites in semi-arid Senegal were carried out in 2001 and 2002 for comparison with remotely sensed MODIS data. The seasonal dynamics of both in situ LAI and fAPAR were captured well by MODIS LAI and fAPAR. MODIS LAI is overestimated by approximately 2-15% and the overall level of fAPAR is overestimated by 8-20%. Both MODIS LAI and fAPAR are characterised by a moderate offset, which is slightly higher than can be explained by model and input data uncertainty. In situ fAPAR and normalised differential vegetation index (NDVI) for three different vegetation types showed a strong linear relationship, suggesting that covariance between fAPAR and NDVI is insensitive to variations in leaf angle distribution (LAD) and vegetative heterogeneity. A strong linear relation also exists between MODIS fAPAR and NDVI but with different regression coefficients than the in situ relation because of MODISŐ tendency to overestimate fAPAR. The fAPAR/NDVI relations found here, however, do not apply on a global scale but are only valid for similar sun-sensor view geometry and soil colour.