Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: Theory and algorithm

Wanner, W.; Strahler, Alan H.; Hu, Baoxin; Lewis, P.; Müller, J.; Li, X.; Schaaf, Crystal B.; Barnsley, Michael J.

doi:10.1029/96jd03295

Cited by 295 publications

(159 citation statements)

References 48 publications

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“…Specifically, the MODIS MCD43A1 product provides BRDF parameter weights of the RossThickLiSparseReciprocal BRDF model, i.e. weights of the isotropic, volumetric and geometric kernel functions (Wanner et al, 1997). The weights are derived separately for each of the seven observed visible to mid-infrared bands, at 500-m resolution in eight-day intervals .…”

Section: Methodsmentioning

confidence: 99%

Characterising Vegetated Surfaces Using Modis Multiangular Satellite Data

McCamley

Grant

Jones

et al. 2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Bidirectional Reflectance Distribution Functions (BRDF) seek to represent variations in surface reflectance resulting from changes in a satellite's view and solar illumination angles. BRDF representations have been widely used to assist in the characterisation of vegetation. However BRDF effects are often noisy, difficult to interpret and are the spatial integral of all the individual surface features present in a pixel. This paper describes the results of an approach to understanding how BRDF effects can be used to characterise vegetation. The implementation of the Ross Thick Li Sparse BRDF model using MODIS is a stable, mature data product with a 10 year history and is a ready data source. Using this dataset, a geometric optical model is proposed that seeks to interpret the BRDF effects in terms of Normalised Difference Vegetation Index (NDVI) and a height-to-width ratio of the vegetation components. The height-to-width ratio derived from this model seeks to represent the dependence of NDVI to changes in view zenith angle as a single numeric value.The model proposed within this paper has been applied to MODIS pixels in central Australia for areas in excess of 18,000 km 2 . The study area is predominantly arid and sparsely vegetated which provides a level of temporal and spatial homogeneity. The selected study area also minimises the effects associated with mutual obscuration of vegetation which is not considered by the model.The results are represented as a map and compared to NDVI derived from MODIS and NDVI derived from Landsat mosaics developed for Australia's National Carbon Accounting System (NCAS). The model reveals additional information not obvious in reflectance data. For example, the height-to-width ratio is able to reveal vegetation features in arid areas that do not have an accompanying significant increase in NDVI derived from MODIS, i.e. the height-to-width ratio reveals vegetation which is otherwise only apparent in NDVI derived from the higher resolution Landsat NCAS dataset.

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Section: Methodsmentioning

confidence: 99%

Characterising Vegetated Surfaces Using Modis Multiangular Satellite Data

McCamley

Grant

Jones

et al. 2012

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…3 that contains quality flags and masks is also used. For more details about these products we refer the reader to (Wanner, 1997); (Strahler, 1999) and (Schaaf, 2002).…”

Section: Data Selection and Statisticsmentioning

confidence: 99%

Evaluation of the Main Ceos Pseudo Calibration Sites Using Modis BRDF/Albedo Products

Kharbouche

Müller

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission I, WG I/3KEY WORDS: Satellites, Calibration, Multi-Spectral, BRDF/Albedo, MODIS ABSTRACT:This work describes our findings about an evaluation of the stability and the consistency of twenty primary PICSs (Pseudo-Invariant Calibration Sites). We present an analysis of 13 years of 8-daily MODIS products of BRDF parameters and white-sky-albedos (WSA) over the shortwave band. This time series of WSA and BRDFs shows the variation of the "stability" varies significantly from site to site. Using a 10x10 km window size over all the sites, the change in of WSA stability is around 4% but the isotropicity, which is an important element in inter-satellite calibration, can vary from 75% to 98%. Moreover, some PICS, especially, Libya-4 which is one of the PICS which is most employed, has significant and relatively fast changes in wintertime. PICS observations of BRDF/albedo shows that the Libya-4 PICS has the best performance but it is not too far from some sites such as Libya-1 and Mali. This study also reveals that Niger-3 PICS has the longest continuous period of high stability per year, and Sudan has the most isotropic surface. These observations have important implications for the use of these sites.

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“…It is derived from the integral of the bidirectional reflectance distribution function (BRDF) over hemispheric space. The BRDF is estimated using a three parameter kernel-driven semi-empirical RossThick-LiSparse-Reciprocal (RTLSR) model to characterize the anisotropic reflectivity of the land surface [47,48]. Considering the effects of registration error on the validation results, the mean MCD43B3 albedo within the study area was utilized to represent the average condition of MCD43B3 in an effort to reduce the errors caused by geometric registration.…”

Section: Study Area and Datasetsmentioning

confidence: 99%

Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe

Xiao

Wen

et al. 2015

Remote Sensing

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Abstract:To evaluate and improve the quality of land surface albedo products, validation with ground measurements of albedo is crucial over the spatially and temporally heterogeneous land surface. One of the essential steps for satellite albedo product validation is coarse scale observation technique development with long time ground-based measurements. In this paper, the optimal nodes were selected from the wireless sensor network (WSN) to perform observation at large scale and in longer time series for validation of albedo products. The relative difference is used to analyze the spatiotemporal representativeness of each node. The random combination method is used to assess the number of required sites (NRS) and then to identify the most representative combination (MRC). On this basis, an upscaling OPEN ACCESS Remote Sens. 2015, 7 14758 transform function with different weights for each node in the MRC, which are calculated with the ordinary least squares (OLS) linear regression method, is used to upscale WSN node albedo from point scale to the field scale. This method is illustrated by selecting the optimal nodes and upscaling surface albedo from point observation to the field scale in the Heihe River basin, China. Primary findings are: (a) The method of reducing the number of observations without significant loss of information about surface albedo at field scale is feasible and effective; (b) When only few sensors are available, the most representative locations in time and space should be the first priority; when a number of sensors are available in the heterogeneous land surface, it is preferable to install them in different land surface, rather than the most representative locations; (c) The most representative combination (MRC) combined with the upscaling weight coefficients can give a robust estimate of the field mean surface albedo. These efforts based on ground albedo observations promote the chance to use point information for validation of coarse scale albedo products. Moreover, a preliminary validation of the MODIS (Moderate Resolution Imaging Spectroradiometer) albedo product was performed as the tentative application for upscaling predictions.

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Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: Theory and algorithm

Cited by 295 publications

References 48 publications

Characterising Vegetated Surfaces Using Modis Multiangular Satellite Data

Characterising Vegetated Surfaces Using Modis Multiangular Satellite Data

Evaluation of the Main Ceos Pseudo Calibration Sites Using Modis BRDF/Albedo Products

Optimal Nodes Selectiveness from WSN to Fit Field Scale Albedo Observation and Validation in Long Time Series in the Foci Experiment Areas, Heihe

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