The Advanced Very High Resolution Radiometer (AVHRR) sensors aboard the different NOAA satellites provide a unique global remote sensing dataset that ranges from the 1980s to the present. Using these data, the NASA funded Long Term Data Record (LTDR) project aims to develop a quality and consistent Climate Data Record (CDR) of AVHRR data with the use of the Moderate Resolution Imaging Spectrometer (MODIS) instrument as a reference. The current product uses a simple climatology approach using the red band to mask clouds from land and has no internal algorithm to discern cloud from snow. Previous studies using AVHRR data make use of either MODIS climatology or multispectral threshold techniques. In this study, we aim to combine both approaches. We do this by assigning a probability of belonging to each class (cloud, land, snow or shadow) according to the distance of each pixel to the average climatology MODIS pixel, and to the multispectral clusters obtained using MODIS bands analogous to AVHRR. First, this approach is tested on MODIS data, and then applied to AVHRR. The main objective is to increase the overall accuracy of the classification, since errors in the cloud/snow mask have a significant impact on accurately determining global long-term trends of level-2 parameters such as surface albedo.
AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- 0402 Agricultural systems;
- 0426 Biosphere/atmosphere interactions;
- 0430 Computational methods and data processing;
- 0480 Remote sensing;