Yanmin Shuai

Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-Based Estimates of Directional Reflectance and Albedo

The quantification of uncertainty in satellite-derived global surface albedo products is a critical aspect in producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A challenge in validating albedo measurements acquired from space is the ability to overcome the spatial scaling errors that can produce disagreements between satellite and field-measured values. Here, we present the results from an accuracy assessment of MODIS and Landsat-TM albedo retrievals, based on collocated comparisons with tower and airborne Cloud Absorption Radiometer (CAR) measurements collected during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC). The initial focus was on evaluating inter-sensor consistency through comparisons of intrinsic bidirectional reflectance estimates. Local and regional assessments were then performed to obtain estimates of the resulting scaling uncertainties, and to establish the accuracy of albedo reconstructions during extended periods of precipitation. In general, the satellite-derived estimates met the accuracy requirements established for the high-quality MODIS operational albedos at 500 m (the greater of 0.02 units or ±10% of surface measured values). However, results reveal a high degree of variability in the root-mean-square error (RMSE) and bias of MODIS visible (0.3-0.7 μm) and Landsat-TM shortwave (0.3-5.0 μm) albedos; where, in some cases, retrieval uncertainties were found to be in excess of 15 %. Results suggest that an overall improvement in MODIS shortwave albedo retrieval accuracy of 7.8%, based on comparisons between MODIS and CAR albedos, resulted from the removal of sub-grid scale mismatch errors when directly scaling-up the tower measurements to the MODIS satellite footprint.

Daily MODIS 500 m reflectance anisotropy direct broadcast DB products for monitoring vegetation phenology dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Fusion of Satellite Land Surface Albedo Products Across Scales Using a Multiresolution Tree Method in the North Central United States

Land surface albedo is a key factor in climate change and land surface modeling studies, which affects the surface radiation budget. Many satellite albedo products have been generated during the last several decades. However, due to the problems resulting from the sensor characteristics (spectral bands, spatial and temporal resolutions, etc.) and/or the retrieving procedures, surface albedo estimations from different satellite sensors are inconsistent and often contain gaps, which limit their applications. Many approaches have been developed to generate the complete albedo data set; however, most of them suffer from either the persistent systematic bias of relying on only one data set or the problem of subpixel heterogeneity. In this paper, a data fusion method is prototyped using multiresolution tree (MRT) models to develop spatially and temporally continuous albedo maps from different satellite albedo/reflectance data sets. Data from the Multiangle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus are used as examples, at a study area in the north central United States mostly covered by crop, grass, and forest, from June to September 2005. Results show that the MRT data fusion method is capable of integrating the three satellite data sets at different spatial resolutions to fill the gaps and to reduce the inconsistencies between different products. The validation results indicate that the uncertainties of the three satellite products have been reduced significantly through the data fusion procedure. Further efforts are needed to evaluate and improve the current algorithm over other locations, time periods, and land cover types.

Angular Effects and Correction for Medium Resolution Sensors to Support Crop Monitoring

Remote sensing imagery at medium spatial resolutions (20-60 m) such as Landsat, the advanced wide field sensor (AWiFS) and the disaster monitoring constellation (DMC) have been broadly used in mapping crop types and monitoring crop conditions. This paper examines the influence of viewing and illumination angular effects on surface reflectance of typical surface and crop types for both narrow swath (e.g., Landsat) and wide swath (e.g., AWiFS) sensors. Three types of angular effects: 1) view angle effect; 2) day of year effect; and 3) mean local time drift effect were analyzed based on both field and satellite bi-directional reflectance distribution function (BRDF) measurements. In order to correct these angular effects, a BRDF look-up map (LUM) for major cover types was built using the cropland data layer (CDL) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) BRDF products. The BRDF LUM was applied to an AWiFS image to correct view angle effects in an agricultural area in central Illinois. The resulting nadir BRDF-adjusted reflectance (NBAR) provides a consistent data source for intra-annual crop condition monitoring and inter-annual time-series analysis.

Multiscale climatological albedo look-up maps derived from moderate resolution imaging spectroradiometer BRDF/albedo products

Abstract Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents albedo look-up maps (LUMs) using a multiscale hierarchical approach based on moderate resolution imaging spectroradiometer (MODIS) bidirectional reflectance distribution function (BRDF)/albedo products and Landsat imagery. Ten years (2001 to 2011) of MODIS BRDF/albedo products were used to generate global albedo climatology. Albedo LUMs of land cover classes defined by the International Geosphere-Biosphere Programme (IGBP) at multiple spatial resolutions were generated. The albedo LUMs included monthly statistics of white-sky (diffuse) and black-sky (direct) albedo for each IGBP class for visible, near-infrared, and shortwave broadband under both snow-free and snow-covered conditions. The albedo LUMs were assessed by using the annual MODIS IGBP land cover map and the projected land use scenarios from the Intergovernmental Panel on Climate Change land-use harmonization project. The comparisons between the reconstructed albedo and the MODIS albedo data product show good agreement. The LUMs provide high temporal and spatial resolution global albedo statistics without gaps for investigating albedo variations under different land cover scenarios and could be used for land surface modeling.

Early Spring Post-Fire Snow Albedo Dynamics in High Latitude Boreal Forests Using Landsat-8 OLI Data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Monitoring vegetation phenology using improved MODIS products

Land surface vegetation phenology is an important process for the real-time monitoring and detecting inter-annual variability in terrestrial ecosystem carbon exchange and climate-biosphere interactions. Crop phenology is an important factor that influences crop growth and yield estimation models. Since the mid-1980s, coarse-resolution, temporally-composited satellite data have been used to study vegetation phenology. View-angle corrected nadir reflectances from the 16-day, 1km operational MODIS BRDF/Albedo product are currently used to monitor global land cover dynamics. In this paper, we developed an improved methodology for using the new 500-m MODIS BRDF/Albedo Version 005 product to monitor global vegetation phenology by utilizing time series of the Normalized Difference Vegetation Index (NDVI). The method adopts a rolling strategy for the continuous updating of the underlying anisotropy (or BRDF shape), so that the latest land surface BRDF information can be used as prior-knowledge for next retrieval. Using this approach, transition dates for vegetation phenology in time series of NDVI can be determined from MODIS data at finer temporal and spatial resolution. Preliminary results based on monitoring crops in northern China demonstrate the effectiveness of our rolling retrievals coupled with the improved spatial resolution of the new MODIS product.