Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products

Cohen, Warren B.; Maiersperger, T.; Yang, Zhiqiang; Gower, Stith T.; Turner, David P.; Ritts, William D.; Berterretche, Mercedes; Running, Steven W.

doi:10.1016/j.rse.2003.06.006

Cited by 213 publications

(152 citation statements)

References 35 publications

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“…The two sites in this study (Table 1) are part of a network of nine sites (BigFoot, 2003) at which a standard protocol is being applied for validation of MODIS land cover, LAI, GPP, and NPP products (Cohen, Maiersperger, Gower, Turner, & Running, 2003;Reich, Turner, & Bolstad, 1999). The general approach was to calibrate and validate a daily time step carbon cycle process model with field measurements, and run the model cell by cell over a 25-m grid covering an area of 25 km 2 .…”

Section: Overviewmentioning

confidence: 99%

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

Turner

2003

Remote Sensing of Environment

131

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The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km 2 ) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm-daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms. D

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Section: Overviewmentioning

confidence: 99%

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

Turner

2003

Remote Sensing of Environment

131

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“…The MISR product underestimates MODIS LAI by 0.9 LAI at the Harvard Forest site. This result may indicate better MISR retrievals since MODIS overestimates ground measurements (Cohen et al, 2003).…”

Section: Validation Of Misr Lai Product At Other Sitesmentioning

confidence: 88%

“…The BigFoot team (WWW5) performed validation of MODIS LAI products at Bondville, a cropland site in Illinois, USA; Konza Prairie Biological Station, Manhattan, Kansas, USA; and the Harvard Forest, (a temperate mixed forest site in Massachusetts, USA) sites (Cohen et al, 2003). At Konza and Bondville, Collection 4 MODIS LAI was close to BigFoot field measurements scaled to MODIS resolution.…”

Section: Validation Of Misr Lai Product At Other Sitesmentioning

confidence: 99%

Analysis of the MISR LAI/FPAR product for spatial and temporal coverage, accuracy and consistency

Tan

et al. 2007

Remote Sensing of Environment

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The Multi-angle Imaging SpectroRadiometer (MISR) instrument provides global imagery at nine discrete viewing angles and four visible/nearinfrared spectral bands. MISR standard products include green leaf area index (LAI) of vegetation and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). This paper describes the research basis for transitioning the MISR LAI/FPAR products from provisional to validation status. The efforts included not only comparisons to field data but also analyses of relationships, consistency and complementarity between various MISR products derived by independent algorithms. For example, we show how the energy absorbed by the ground below vegetation can be estimated from two independent MISR products, FPAR and BHRPAR (bi-hemispheric reflectance at PAR wavelengths). Further, we show that this information can be used to derive at least three measures of canopy structure -Beer's law extinction coefficient, mean leaf inclination and the gap fraction or vegetation ground cover. The spatial and temporal coverage of the LAI/FPAR product is mainly limited by cloud contamination. However, when a successful aerosol retrieval is performed, typically 95% of pixels have surface reflectance retrievals suitable as input to the LAI/FPAR algorithm. The algorithm provides LAI/FPAR retrievals in 50-80% of these pixels with suitable input. The early versions of the algorithm overestimated LAI values in grasses and broadleaf crops. The MISR LAI product from the recalibrated algorithm (version 3.3) is assessed by comparison with field data collected in a 3 × 3 km agricultural area (grasses and cereal crops) near Avignon, France. LAI retrievals in other biomes are compared to MODIS LAI product of known accuracy. The MISR LAI product shows structural and phenological variability in agreement with data. Our results suggest that the product is accurate to within 0.66 LAI in herbaceous vegetation and savannas and is an overestimate by about 1 LAI in broadleaf forests. LAI retrievals over needle leaf forests remain at provisional quality level.

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“…Although the reflectance data can be used in high-resolution LAI mapping, vegetation indexes are more often used in validation activities. Commonly used vegetation indexes include normalized difference vegetation index (NDVI) [36], simple ratio (SR) [37], and reduced simple ratio (RSR) [38]. In mountainous areas, slope extracted from digital elevation model (DEM) data is often used to account for the terrain effects [31,39].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A Cost-Constrained Sampling Strategy in Support of LAI Product Validation in Mountainous Areas

Yin

Zeng

et al. 2016

Remote Sensing

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Abstract:Increasing attention is being paid on leaf area index (LAI) retrieval in mountainous areas. Mountainous areas present extreme topographic variability, and are characterized by more spatial heterogeneity and inaccessibility compared with flat terrain. It is difficult to collect representative ground-truth measurements, and the validation of LAI in mountainous areas is still problematic. A cost-constrained sampling strategy (CSS) in support of LAI validation was presented in this study. To account for the influence of rugged terrain on implementation cost, a cost-objective function was incorporated to traditional conditioned Latin hypercube (CLH) sampling strategy. A case study in Hailuogou, Sichuan province, China was used to assess the efficiency of CSS. Normalized difference vegetation index (NDVI), land cover type, and slope were selected as auxiliary variables to present the variability of LAI in the study area. Results show that CSS can satisfactorily capture the variability across the site extent, while minimizing field efforts. One appealing feature of CSS is that the compromise between representativeness and implementation cost can be regulated according to actual surface heterogeneity and budget constraints, and this makes CSS flexible. Although the proposed method was only validated for the auxiliary variables rather than the LAI measurements, it serves as a starting point for establishing the locations of field plots and facilitates the preparation of field campaigns in mountainous areas.

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Comparisons of land cover and LAI estimates derived from ETM+ and MODIS for four sites in North America: a quality assessment of 2000/2001 provisional MODIS products

Cited by 213 publications

References 35 publications

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

Analysis of the MISR LAI/FPAR product for spatial and temporal coverage, accuracy and consistency

A Cost-Constrained Sampling Strategy in Support of LAI Product Validation in Mountainous Areas

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