DNS is one of the most actively used distributed databases on earth, accessed by millions of people every day to transparently convert host names into IP addresses and vice versa. In order to improve their performance, DNS servers also keep temporary records of all requested domain names in their cache. While most of the DNS servers are configured to be used by their local users only, there still exist many DNS servers that respond to public queries. Querying these DNS servers reveals the recently visited domains. Exploiting the geographically distributed nature of DNS, one can gather usage statistics ranging from a single DNS server to global scale. In particular, this enables collecting statistics about geographic differences in web browsing behavior between different regions of a country or the world. In this paper, we present methods to identify these public DNS servers, discuss how to effectively crawl them, and describe our algorithm to extract usage estimations from the crawl data. We also evaluate our estimation algorithm using extensive simulations, and finally use our algorithms to crawl 150 U.S. universities for various domains, and explore the effects of location and time on the access rate of these domains.