Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical ...Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical for examining its influence.However,such analysis is confounded by the lack of spatial data at the appropriate unit for such analysis.The purpose of this paper is to develop and realize an open source implementation to automate land parcel classification,which is an initial step towards the goal of determining the impact of HOAs on urban land management.Using Maricopa County,Arizona as a testbed,we found that parcel merging processes reduce the number of subdivisions from 26,042 to 17,269,such that boundaries better align with neighborhood units to which rule sets like land covenants apply.Moreover,after an initial training period,this process was completed in just over 7 hours.This research is an important first step in enabling a number of analysis including determining the location and spatial extent of HOAs regionally and,eventually,nationally and determining proposed links between HOAs and land management outcomes.展开更多
Understanding and detecting the intended meaning in social media is challenging because social media messages contain varieties of noise and chaos that are irrelevant to the themes of interests.For example,conventiona...Understanding and detecting the intended meaning in social media is challenging because social media messages contain varieties of noise and chaos that are irrelevant to the themes of interests.For example,conventional supervised classification approaches would produce inconsistent solutions to detecting and clarifying whether any given Twitter message is really about a wildfire event.Consequently,a renovated workflow was designed and implemented.The workflow consists of four sequential procedures:(1)Apply the latent semantic analysis and cosine similarity calculation to examine the similarity between Twitter messages;(2)Apply Affinity Propagation to identify exemplars of Twitter messages;(3)Apply the cosine similarity calculation again to automatically match the exemplars to known training results,and(4)Apply accumulative exemplars to classify Twitter messages using a support vector machine approach.The overall correction ratio was over 90%when a series of ongoing and historical wildfire events were examined.展开更多
文摘Homeowners’Associations(HOAs)dictate landscape structure and management through legally enforceable land covenants at the neighborhood scale in the USA.Determining the location and spatial extent of HOAs is critical for examining its influence.However,such analysis is confounded by the lack of spatial data at the appropriate unit for such analysis.The purpose of this paper is to develop and realize an open source implementation to automate land parcel classification,which is an initial step towards the goal of determining the impact of HOAs on urban land management.Using Maricopa County,Arizona as a testbed,we found that parcel merging processes reduce the number of subdivisions from 26,042 to 17,269,such that boundaries better align with neighborhood units to which rule sets like land covenants apply.Moreover,after an initial training period,this process was completed in just over 7 hours.This research is an important first step in enabling a number of analysis including determining the location and spatial extent of HOAs regionally and,eventually,nationally and determining proposed links between HOAs and land management outcomes.
文摘Understanding and detecting the intended meaning in social media is challenging because social media messages contain varieties of noise and chaos that are irrelevant to the themes of interests.For example,conventional supervised classification approaches would produce inconsistent solutions to detecting and clarifying whether any given Twitter message is really about a wildfire event.Consequently,a renovated workflow was designed and implemented.The workflow consists of four sequential procedures:(1)Apply the latent semantic analysis and cosine similarity calculation to examine the similarity between Twitter messages;(2)Apply Affinity Propagation to identify exemplars of Twitter messages;(3)Apply the cosine similarity calculation again to automatically match the exemplars to known training results,and(4)Apply accumulative exemplars to classify Twitter messages using a support vector machine approach.The overall correction ratio was over 90%when a series of ongoing and historical wildfire events were examined.
