MODIS Snow Cover Mapping Decision Tree Technique: Snow and Cloud Discrimination
نویسندگان
چکیده
Accurate mapping of snow cover continues to challenge cryospheric scientists and modelers. The Moderate-Resolution Imaging Spectroradiometer (MODIS) snow data products have been used since 2000 by many investigators to map and monitor snow cover extent for various applications. Users have reported on the utility of the products and also on problems encountered. Three problems or hindrances in the use of the MODIS snow data products that have been reported in the literature are: cloud obscuration, snow/cloud confusion, and snow omission errors in thin or sparse snow cover conditions. Implementation of the MODIS snow algorithm in a decision tree technique using surface reflectance input to mitigate those problems is being investigated. The objective of this work is to use a decision tree structure for the snow algorithm. This should alleviate snow/cloud confusion and omission errors and provide a snow map with classes that convey information on how snow was detected, e.g. snow under clear sky, snow under cloud, to enable users’ flexibility in interpreting and deriving a snow map. Results of a snow cover decision tree algorithm are compared to the standard MODIS snow map and found to exhibit improved ability to alleviate snow/cloud confusion in some situations allowing up to about 5% increase in mapped snow cover extent, thus accuracy, in some scenes.
منابع مشابه
An investigation on the feasibility of applying MODIS snow cover products in cloudy weather by the employment of its integration with microwave images
Variation of snow cover area (SCA) in small to large scale catchment can be studied using MODIS snow products on daily to montly time step since the year 2000. However, one of the major problems in applying the MODIS snow products is cloud obscuration which limits the utilization of these products. In the current study, variation of SCA was investigated in Karoun basin, western part of Iran, us...
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