Evaluation of BRDF Archetypes for Representing Surface Reflectance Anisotropy Using MODIS BRDF Data
نویسندگان
چکیده
Bidirectional reflectance distribution function (BRDF) archetypes extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo product over the global Earth Observing System Land Validation Core Sites can be used to simplify BRDF models. The present study attempts to evaluate the representativeness of BRDF archetypes for surface reflectance anisotropy. Five-year forward-modeled MODIS multi-angular reflectance (MCD-ref) and aditional actual MODIS multi-angular observations (MCD-obs) in four growing periods in 2008 over three tiles were taken as validation data. First, BRDF archetypes in the principal plane were qualitatively compared with the time-series MODIS BRDF product of randomly sampled pixels. Secondly, BRDF archetypes were used to fit MCD-ref, and the average root-mean-squared errors (RMSEs) over each tile were examined for these five years. Finally, both BRDF archetypes and the MODIS BRDF were used to fit MCD-obs, and the histograms of the fit-RMSEs were compared. The consistency of the directional reflectance between the BRDF archetypes and MODIS BRDFs in nadir-view, hotspot and entire viewing hemisphere at 30° and 50° solar geometries were also examined. The results confirm that BRDF archetypes are representative of surface reflectance anisotropy for available snow-free MODIS data. OPEN ACCESS Remote Sens. 2015, 7 7827
منابع مشابه
Analysis of Extracting Prior BRDF from MODIS BRDF Data
Many previous studies have attempted to extract prior reflectance anisotropy knowledge from the historical MODIS Bidirectional Reflectance Distribution Function (BRDF) product based on land cover or Normalized Difference Vegetation Index (NDVI) data. In this study, the feasibility of the method is discussed based on MODIS data and archetypal BRDFs. The BRDF is simplified into six archetypal BRD...
متن کاملDeriving Albedo from Coupled MERIS and MODIS Surface Products
MERIS Level 2 surface reflectance products are now available to the scientific community. This paper demonstrates the production of MERIS-derived surface albedo and Nadir Bidirectional Reflectance Distribution Function (BRDF) adjusted reflectances by coupling the MERIS data with MODIS BRDF products. Initial efforts rely on the specification of surface anisotropy as provided by the global MODIS ...
متن کاملCalibration of Brdf Effects in Paddy Field Reflectance from Temporal Modis Images
Moderate Resolution Imaging Spectroradiometer (MODIS) has a potential for more detailed daily monitoring of land covers and their change than ever because two bands, red and near-infrared bands, have 250m spatial resolutions. On the other hand, the use of MODIS data requires attention to Bidirectional Reflectance Distribution Function (BRDF) effect, which is one of the most important factors to...
متن کاملImproved Topographic Normalization for Landsat TM Images by Introducing the MODIS Surface BRDF
In rugged terrain, the accuracy of surface reflectance estimations is compromised by atmospheric and topographic effects. We propose a new method to simultaneously eliminate atmospheric and terrain effects in Landsat Thematic Mapper (TM) images based on a 30 m digital elevation model (DEM) and Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric products. Moreover, we define a norm...
متن کاملEvaluation of Medium Spatial Resolution BRDF-Adjustment Techniques Using Multi-Angular SPOT4 (Take5) Acquisitions
High-resolution sensor Surface Reflectance (SR) data are affected by surface anisotropy but are difficult to adjust because of the low temporal frequency of the acquisitions and the low angular sampling. This paper evaluates five high spatial resolution Bidirectional Reflectance Distribution Function (BRDF) adjustment techniques. The evaluation is based on the noise level of the SR Time Series ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 7 شماره
صفحات -
تاریخ انتشار 2015