Upscaling in situ leaf area index (LAI) measurements to the footprint scale is important for the validation of medium resolution remote sensing products. However, surface heterogeneity and temporal variation of vegetation make this difficult. In this study, a two-step upscaling algorithm was developed to obtain the representative ground truth of LAI time series in heterogeneous surfaces based o...

A new moisture adjusted vegetation index (MAVI) is proposed using the red, near infrared, and shortwave infrared (SWIR) reflectance in band-ratio form in this paper. The effectiveness of MAVI in retrieving leaf area index (LAI) is investigated using Landsat-5 data and field LAI measurements in two forest and two grassland areas. The ability of MAVI to retrieve forest LAI under different backgro...

When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent cropl...

To test the prediction that elevated CO2 increases the maximum leaf area index (LAI) through a stimulation of photosynthesis, we exposed model herbaceous communities to two levels of CO2 crossed with two levels of soil fertility. Elevated CO2 stimulated the initial rate of canopy development and increased cumulative LAI integrated over the growth period, but it had no effect on the maximum LAI....

Leaf area index (LAI) is an important input in spatially distributed modeling of surface energy balance, evapotranspiration, and vegetation productivity. Remote sensing can facilitate the rapid collection of LAI information on individual fields over large areas in a timely and cost-effective manner. In this study, we developed a set of LAI models using least square regression (LSR) and artifici...

Light canopy transmittance and the Beer-Lambert equation were utilized to assess monthly leaf area index (LAI) of a tropical deciduous forest ecosystem on the west coast of Mexico. The light transmittance coefficient (k) was obtained by analyzing vertical leaf and light distribution in the forest canopy. An independent LAI estimate was obtained using litterfall data. The calculated k value was ...

The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (LaiRM), which when scaled to the moderate LAI resolution (i.e., >1 km) allows for comparison and analysis with this LAI product. This research addresses two major sources of uncertainty in the creation of the LAI-RM: (1) the uncertain...

An operational system was developed for mapping the leaf area index (LAI) for carbon cycle models from the moderate resolution imaging spectroradiometer (MODIS) data. The LAI retrieval algorithm is based on Deng et al. [2006. Algorithm for global leaf area index retrieval using satellite imagery. IEEE Transactions on Geoscience and Remote Sensing, 44, 2219-2229], which uses the 4-scale radiativ...

Leaves are the primary interface where energy, water and carbon exchanges occur between the forest ecosystems and the atmosphere. Leaf area index (LAI) is a measure of the amount of leaf area in a stand, and the tree crown size characterizes how leaves are clumped in the canopy. Both LAI and tree crown size are of essential ecological and management value. There is a lot of interest in extracti...

Hyperspectral reflectance derived vegetation indices (VIs) are used for non-destructive leaf area index (LAI) monitoring for precise and efficient N nutrition management. This study tested the hypothesis that there is potential for using various hyperspectral VIs for estimating LAI at different growth stages of rice under varying N rates. Hyperspectral reflectance and crop canopy LAI measuremen...