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| 005 | 20231004164404.0 | ||
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| 008 | 231004b |||||||| |||| 00| 0 eng d | ||
| 100 |
_aPan, Haozhi _958361 |
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| 245 | _aAn urban informatics approach to understanding residential mobility in Metro Chicago/ | ||
| 260 |
_bSage, _c2020. |
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| 300 | _aVol. 47, Issue 8, 2020, ( 1456–1473 p.) | ||
| 520 | _aThis paper proposes that urban informatics can represent a flow of information from diverse and voluminous data into and back from the planning process. We present a proof-of-concept of how an urban informatics approach can improve public understanding of essential information in the planning process, and we propose a theoretical construct of how it can make planning processes more democratic and participatory, especially for disadvantaged groups. Specifically, this study uses a multi-dimensional spatial scan technique to discover household movement patterns in Chicago from millions of household address records between 2006 and 2015. The results locate the types of movement and displacement associated with specific places at a highly detailed spatial resolution. A user-interface is developed and proposed to enhance sharing of the information to the general public and involves diverse stakeholders in policy-making processes. | ||
| 700 |
_aChen, Si _958362 |
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| 700 |
_aGao, Yizhao _958363 |
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| 700 |
_aDeal, Brian _958364 |
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| 700 |
_aLiu, Jinfang _958365 |
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| 773 | 0 |
_08876 _917104 _dLondon Pion Ltd. 2010 _tEnvironment and planning B: planning and design (Urban Analytics and City Science) _x1472-3417 |
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| 856 | _uhttps://doi.org/10.1177/2399808320924437 | ||
| 942 |
_2ddc _cEJR |
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| 999 |
_c14865 _d14865 |
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