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The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center has processed and released 2100 Landsat Thematic Mapper and Enhanced Thematic Mapper Plus surface reflectance scenes, providing 30-m resolution wall-to-wall reflectance coverage for North America for epochs centered on 1990 and 2000. This dataset can support decadal assessments of environmental and land-cover change, production of reflectance-based biophysical products, and applications that merge reflectance data from multiple sensors [e.g., the Advanced Spaceborne Thermal Emission and Reflection Radiometer, Multiangle Imaging Spectroradiometer, Moderate Resolution Imaging Spectroradiometer (MODIS)]. The raw imagery was obtained from the orthorectified Landsat GeoCover dataset, purchased by NASA from the Earth Satellite Corporation. Through the LEDAPS project, these data were calibrated, converted to top-of-atmosphere reflectance, and then atmospherically corrected using the MODIS/6S methodology. Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product (the greater of 0.5% absolute reflectance or 5% of the recorded reflectance value). The rapid automated nature of the processing stream also paves the way for routine high-level products from future Landsat sensors.

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Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation-atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of Ϸ25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.remote sensing ͉ tropical forests phenology ͉ vegetation climate interaction T he trees of tropical rainforests are known to exhibit a range of phenological behavior, from episodes of ephemeral leaf bursts followed by long quiescent periods to continuous leafing, and from complete intraspecific synchrony to complete asynchrony (1). Several agents (e.g., herbivory, water stress, day length, light intensity, mineral nutrition, and flood pulse) have been identified as proximate cues for leafing and abscission in these communities (1-8). These studies were focused on the timing of phenological events but not on the accompanying changes in leaf area. Leaves selectively absorb solar radiation, emit longwave radiation and volatile organic compounds, and facilitate growth by regulating carbon dioxide influx and water vapor efflux from stomates. Therefore, leaf area dynamics are relevant to studies of climatic, hydrological, and biogeochemical cycles.The sheer size and diversity of rainforests preclude a synoptic view of leaf area changes from ground sampling. We therefore used data on green leaf area of the Amazon basin (Ϸ7.2 ϫ 10 6 km 2 ) derived from measurements made by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Na- Results Seasonality in LAI Time Series.Leaf area data for the Amazon rainforests exhibit notable seasonality, with an amplitude (peakto-trough difference) that is 25% of the average annual LAI of 4.7 (Fig. 1A). This average amplitude of 1.2 LAI is about twice the error of a single estimate of MODIS LAI, and thus is not an artifact of remote observation or data processing (see SI Materials and Methods). The aggregate phenological cycle appears timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of leaf flushing and abscission. These patterns result in leaf area leading solar radiation during the entire seasonal cycle, with higher leaf area during the shorter dry season when solar radiation loads are hig...

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Abstract. The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land surfaces with a spatial resolution of up to 250 m. Prior to the derivation of various biophysical parameters based on surface reflectances, the top of the atmosphere signals need to be radiometrically calibrated and corrected for atmospheric effects. The present paper describes in detail the state of the art techniques that will be used for atmospheric correction of MODIS bands 1 through 7, centered at 648, 858, 470, 555, 1240, 1640, and 2130 nm, respectively. Previous operational correction schemes have assumed a standard atmosphere with zero or constant aerosol loading and a uniform, Lambertian surface. The MODIS operational atmospheric correction algorithm, reported here, uses aerosol and water vapor information derived from the MODIS data, corrects for adjacency effects and takes into account the directional properties of the observed surface. This paper also describes the operational implementation of these techniques and its optimization. The techniques are applied to remote sensing data from the Landsat Thematic Mapper (TM), the NOAA advanced very high resolution radiometer (AVHRR), and the MODIS airborne simulator (MAS) and validated against ground-based measurements from the Aerosol Robotic Network (AERONET). IntroductionThe use of MODIS data for retrieval of land parameters, such as the bidirectional reflectance distribution function (BRDF), albedo, vegetation indices (VIs), fraction of absorbed photosynthetically active radiation (FPAR), and leaf area index (LAI), requires that the top of the atmosphere radiance be converted to surface reflectance. The process necessary for that conversion is called atmospheric correction. By applying the proposed algorithms and associated processing code, moderate resolution imaging spectroradiometer (MODIS) level lB radiances are corrected for atmospheric effects to generate the surface reflectance product. Atmospheric correction requires inputs that describe the variable constituents that influence the signal measured at the top of the atmosphere (see Figure 1 and Tables la and lb) and a correct modeling of the atmospheric scattering and absorption (i.e., a band absorption model and multiple-scattering vector code). In addition, an accurate correction requires a correction for the atmospheric point spread function (for high spatial resolution bands) and coupling of the surface BRDF and atmosphere effects.•Department of Geography, University of Maryland and NASA Theoretical BackgroundThe surface reflectance product will be computed from the MODIS calibrated radiance data (level lB) in bands 1 through 7 (centered at 648, 858, 470, 555, 1240, 1640, and 2130 nm, respectively). The product is an estimate of the surface spectral Rather than reproducing the ATBD contents, this paper focuses on several important and recent improvements to the algorithm, namely, the atmospheric point spread function correction an...

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