{'fraction_non_alphanumeric': 0.00929368029739777, 'fraction_numerical': 0.0037174721189591076, 'mean_word_length': 5.493975903614458, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Remotely sensed vegetation cover in the Land Data Assimilation Systems project

Over the past decade, remotely sensed vegetation datasets have become increasing detailed and accurate. We examine the impact of such data sets on LDAS land surface modeling through several experiments utilizing the Mosaic LSM. Simulations were conducted using 1 degree ISLSCP data and 1 kilometer EROS data over Oklahoma, and results were compared to soil moisture and soil temperature information available from the Oklahoma Mesonet network of instruments.