Researchers that make use of Type II Data may be subject to additional restrictions to protect any applicable commercial or confidentiality interests. Some examples of Type II data restrictions may include: locations of rare or endangered species, data that are covered under prior licensing or copyright (e.g., SPOT satellite data), or covered by the Human Subjects Act, Student Dissertation data and those data related to the FCE LTER Program but not funded by the National Science Foundation (NSF) under LTER grants #DEB-9910514, and # DBI-0620409. The justification for exceptions must be well documented and approved by the lead PI and Site Data Manager. Type II data are considered to be exceptional and should be rare in occurrence. These data are classified as 'Type II' whereby original FCE LTER experimental data collected by individual FCE researchers to be released to restricted audiences according to terms specified by the owners of the data. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. However, these models reveal a wide disparity in their attention to policy factors. Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth.
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