W.J.D. van Leeuwen

The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research

The first Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is planned for launch by NASA in 1998. This instrument will provide a new and improved capability for terrestrial satellite remote sensing aimed at meeting the needs of global change research. The MODIS standard products will provide new and improved tools for moderate resolution land surface monitoring. These higher order data products have been designed to remove the burden of certain common types of data processing from the user community and meet the more general needs of global-to-regional monitoring, modeling, and assessment. The near-daily coverage of moderate resolution data from MODIS, coupled with the planned increase in high-resolution sampling from Landsat 7, will provide a powerful combination of observations. The full potential of MODIS will be realized once a stable and well-calibrated time-series of multispectral data has been established. In this paper the proposed MODIS standard products for land applications are described along with the current plans for data quality assessment and product validation.

A comparison of vegetation indices over a global set of TM images for EOS-MODIS

Abstract A set of Landsat Thematic Mapper images representing a wide range of vegetation conditions from the NASA Landsat Pathfinder, global land cover test site (GLCTS) initiative were processed to simulate the Moderate Resolution Imaging Spectroradiometer (MODIS), global vegetation index imagery at 250 m pixel size resolution. The sites included boreal forest, temperate coniferous forest, temperate deciduous forest, tropical rainforest, grassland, savanna, and desert biomes. Differences and similarities in sensitivity to vegetation conditions were compared among various spectral vegetation indices (VIs). All VIs showed a qualitative relationship to variations in vegetation. However, there were significant differences among the VIs over desert, grassland, and forested biomes. The normalized difference vegetation index (NDVI) was sensitive to and responded primarily to the highly absorbing red reflectance band, while other indices such (is the soil and atmosphere resistant vegetation index (SARVI) were more responsive to variations in the near-infrared (NIR) band. As a result, we found the NDVI to mimic red reflectances and saturate over the forested sites while the SARVI, by contrast, did not saturate and followed variations in NIR refleetances. In the arid and semiarid biomes, the NDVI was much more sensitive to canopy background variations than the SARVI. Maximum differences among vegetation index behavior occurred over the evergreen needleleaf forest sites relative to the deciduous broadleaf forests and drier, grassland, and shrub sites. These differences appear to be useful in complementing the NDVI for improved monitoring of vegetation, with the NDVI sensitive to fraction of absorbed photosynthetic active radiation and the SARVI more sensitive to structural canopy parameters such as leaf area index and leaf morphology.

Effects of standing litter on the biophysical interpretation of plant canopies with spectral indices

Abstract Litter is frequently present within vegetation canopies and thus contributes to the overall spectral response of a canopy. Consequently, litter will affect spectral indices designed to be sensitive to green vegetation, soil brightness or other features. The main objectives of the current research were to 1) evaluate the spectral properties of green vegetation and litter and 2) quantify the effect of standing litter on the performance of spectral indices. The SAIL (scattering by arbitrarily inclined leaves) model was used to generate canopy reflectance “mixtures” and to estimate fractions of absorbed photosynthetically active radiation (fAPAR) with varying leaf area index (LAI), soil background, combinations of vegetation component spectral properties, and one or two horizontal vegetation layers. Spectral measurements of different bare soils and mature green and senescent leaves of representative plant species at the HAPEX-Sahel (Hydrological Atmospheric Pilot Experiment) study sites were used as input. The normalized difference vegetation index (NDVI), the soil adjusted vegetation index (SAVI), and the modified NDVI (MNDVI) and mixture model spectral indices were selected to evaluate their performance with respect to standing litter and green vegetation mixtures. Spectral reflectance signatures of leaf litter varied significantly, but strongly resembled soil spectral characteristics. The biophysical phyameters (LAI, fAPAR), derived from spectral vegetation indices, tended to be overestimated for randomly distributed, sparse green and litter vegetation cover mixtures, and underestimated for randomly distributed dense green and litter vegetation cover mixtures. All spectral indices and their biophysical interpretation were significantly altered by variability in 1) green leaf, leaf litter, and bark optical properties, 2) the amount and position of standing leaf litter, 3) leaf angle distribution, and 4) soil background. The NDVI response to these variables was inconsistent, and was the most affected by litter. The spectral mixture model indices, designed to be sensitive to litter, were shown to be promising for the identification of litter present among different ecosystems.

Normalization of multidirectional red and NIR reflectances with the SAVI

Directional reflectance measurements were made over a semidesert gramma (Bouteloua spp.) grassland at various times of the growing season. Azimuthal strings of view angle measurements from + 40° to − 40° were made for various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to these bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation activity. The NDVI response from the grassland canopy was strongly anisotropic about nadir view angles while the SAVI response was symmetric about nadir. This occurred for all sun angles, soil moisture condition, and grass densities. This enabled variations in SAVI-view angle response to be minimized with a cosine function. It is expected that this study will aid in improving the characterization of vegetation temporal activity from Landsat TM, SPOT, AVHRR, and the Earth Observing System MODIS sensor.

Vegetation detection through smoke‐filled AVIRIS images: An assessment using MODIS band passes

Radiometrically calibrated, Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) images acquired during the Smoke, Clouds and Radiation in Brazil (SCAR-B) experiment were processed to simulate vegetation index (VI) imagery with the Moderate Resolution Imaging Spectroradiometer (MODIS) band passes. Data sets were extracted from tropical forested areas, burned fields, and shrub/grassland areas over both clear and variable smoke conditions with average aerosol optical thickness (AOT) values at 0.67 μm of 0.14, 1.1, and 1.9, respectively. The atmospheric resistant VIs and various middle-infrared (MIR) derived VIs were then analyzed with respect to their ability to minimize atmospheric smoke contamination. The atmospheric resistant VIs utilized the blue band for correction of the red band, while the MIR-derived VIs used the MIR region (1.3 - 2.5 μm) as a substitute for the red band since it is relatively transparent to smoke, yet remains sensitive to green vegetation. The performance of these indices were assessed and compared with the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI). Over the tropical forests the NDVI and SAVI had high relative errors over all smoke-filled atmospheric conditions (50-80% error), while the atmospheric resistant VIs resulted in a 50-80% relative error only over thick levels of smoke. Over optically thin levels (AOT at 0.67 μm 40%), while all other indices had errors below 20%. In the shrub/grassland site, the atmospheric resistant indices behaved similarly with the MIR-derived indices, with both less sensitive to smoke than the NDVI and SAVI. We conclude that the MIR indices, particularly with MODIS band 7 (2.13 μm), are useful in vegetation monitoring over forested areas during the burning season. However, they did not perform well in areas outside of forests such as burned areas and shrub/grassland.

Deconvolution of remotely sensed spectral mixtures for retrieval of LAI, fAPAR and soil brightness

Abstract Linear mixture models have been used to invert spectral reflectances of targets at the Earths surface into proportions of plant and soil components. However, operational use of mixture models has been limited by a lack of biophysical interpretation of the results. The main objectives of this study were (1) to relate the deconvolved components of a mixture model with biophysical properties of vegetation and soil at the surface and (2) to apply the mixture model results to remotely sensed imagery. A radiative transfer model (SAIL: Scattering by Arbitrarily Inclined Leaves) was used to generate reflectance ‘mixtures’ from leaf and bare soil spectral measurements made at HAPEX-Sahel (Hydrological Atmospheric Pilot EXperiment) study sites. The SAIL model was used to create canopy reflectances and fractions of absorbed photosynthetically active readiation (fAPAR) for a range of mixed targets with varying leaf area index (LAI) and soils. A spectral mixture model was used to deconvolve the simulated reflectance data into component fractions, which were then calibrated to the SAIL-generated LAI, fAPAR and soil brightness. The calibrated relationships were validated with observational ground data (LAI, fAPAR and reflectance) measured at the HAPEX Sahel fallow bush/grassland, fallow grassland and millet sites. Both the vegetation and soil component fractions were found to be dependent upon soil background brightness, such that inclusion of the soil fraction information significantly improved the derivation of vegetation biophysical parameters. Soil brightness was also shown to be a useful parameter to infer soil properties. The deconvolution methodology was then applied to a nadir image of a HAPEX-Sahel site measured by the Advanced Solid State Array Spectroradiometer (ASA). Site LAI and fAPAR were successfully estimated by combining the fractional estimates of vegetation and soils, obtained through deconvolution of the ASAS image, with the calibrated relationships between vegetation fraction, LAI and fAPAR, obtained from the SAIL data.

Biophysical characterization and management effects on semiarid rangeland observed from Landsat ETM+ data

Semiarid rangelands are very sensitive to global climatic change; studies of their biophysical attributes are crucial to understanding the dynamics of rangeland ecosystems under human disturbance. In the Santa Rita Experimental Range, AZ, the vegetation has changed considerably, and there have been many management activities applied. This study calculates seven surface variables: the enhanced vegetation index, the normalized difference vegetation index (NDVI), surface albedos (total shortwave, visible, and near-infrared), leaf area index (LAI), and the fraction of photosynthetically active radiation (FPAR) absorbed by green vegetation from the Enhanced Thematic Mapper (ETM+) data. Comparison with the Moderate Resolution Imaging Spectroradiometer vegetation index and albedo products indicates they agree well with our estimates from ETM+, while their LAI and FPAR are larger than from ETM+. Human disturbance has significantly changed the cover types and biophysical conditions. Statistical tests indicate that surface albedos increased and FPAR decreased following tree-cutting disturbances. The recovery will require more than 67 years and is about 50% complete within 40 years at the higher elevation. Grass cover, vegetation indexes, albedos, and LAI recovered from cutting faster at the higher elevation. Woody plants, vegetation indexes, and LAI have recovered to their original characteristics after 65 years at the lower elevation. More studies are needed to examine the spectral characteristics of different ground components.

Discrimination of invaded and native species sites in a semi-desert grassland using MODIS multi-temporal data

Over the past several decades, one of the most significant changes in semi‐desert grasslands of the southwestern US has been the invasion of South African grass Eragrostis lehmanniana. The objective of this study was to characterize the phenology of systems occupied by E. lehmanniana and/or native grasses using time‐series of field observations and the Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index (MODIS NDVI) and brightness (red and near‐infrared reflectance) data. Results demonstrated that it was possible to use NDVI and/or spectral reflectance data to discern the phenological differences across a gradient of E. lehmanniana infested grasslands due to variations in plant biodiversity, morphology and seasonal productivity. This work establishes the feasibility of integrating field and MODIS vegetation and spectral time‐series data to characterise landscapes dominated by different herbaceous species, which in turn provides opportunities to monitor E. lehmanniana in semi‐arid environments at a large spatial scale.

Assessing Transmission of Crop Diseases by Insect Vectors in a Landscape Context

ABSTRACT Theory indicates that landscape composition affects transmission of vector-borne crop diseases, but few empirical studies have investigated how landscape composition affects plant disease epidemiology. Since 2006, Bemisia tabaci (Gennadius) has vectored the cucurbit yellow stunting disorder virus (CYSDV) to cantaloupe and honeydew melons (Cucumis melo L.) in the southwestern United States and northern Mexico, causing significant reductions in yield of fall melons and increased use of insecticides. Here, we show that a landscape-based approach allowing simultaneous assessment of impacts of local (i.e., planting date) and regional (i.e., landscape composition) factors provides valuable insights on how to reduce crop disease risks. Specifically, we found that planting fall melon fields early in the growing season, eliminating plants germinating from seeds produced by spring melons after harvest, and planting fall melon fields away from cotton and spring melon fields may significantly reduce the incidence of CYSDV infection in fall melons. Because the largest scale of significance of the positive association between abundance of cotton and spring melon fields and CYSDV incidence was 1,750 and 3,000 m, respectively, reducing areas of cotton and spring melon fields within these distances from fall melon fields may decrease CYSDV incidence. Our results indicate that landscape-based studies will be fruitful to alleviate limitations imposed on crop production by vector-borne diseases.

Radiative transfer in shrub savanna sites in Niger: preliminary results from HAPEX-Sahel. 3. Optical dynamics and vegetation index sensitivity to biomass and plant cover

Abstract A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (VI) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large VI dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.