| LDR | | 02785nam u200469 4500 |
| 001 | | 000000420693 |
| 005 | | 20190215164659 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438026001 |
| 035 | |
▼a (MiAaPQ)AAI10787085 |
| 035 | |
▼a (MiAaPQ)cornellgrad:10754 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 333 |
| 100 | 1 |
▼a Smith, Stephen D.
▼0 (orcid)0000-0003-3633-8655. |
| 245 | 10 |
▼a Development and Application of a Census-Based Regional Residential Growth Model for Biodiversity Risk Assessment. |
| 260 | |
▼a [S.l.]:
▼b Cornell University.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 147 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B. |
| 500 | |
▼a Adviser: Milo E. Richmond. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Cornell University, 2018. |
| 520 | |
▼a The USGS National GAP Program is a biodiversity mapping program implemented at the state level via the Cooperative Fish & Wildlife Research Units (CFWRU). The New York CFWRU completed NY-GAP analysis in 2001, providing, for the first time, a sta |
| 520 | |
▼a Initial efforts resulted in a regression model which predicted 77 of the 2,212 total BG in the study area to be prime candidates for a substantial percentage of the predicted new residential growth. These BGs, classified as intensive growth area |
| 520 | |
▼a Additional model development provided a slight improvement to the predictability of the model while using only digitally available regional data. The second model explained 38% of the variance associated with the identification of IGAs and ident |
| 520 | |
▼a A third modeling effort was undertaken to improve upon the earlier residential housing prediction models based on regression analysis of Census-based BG data and physiographic variables aggregated to the BG level geography. It was hypothesized t |
| 520 | |
▼a These efforts to model residential growth at the landscape scale support the hypothesis that the spatial distribution of residential housing growth can be modeled using Census Block Group (BG) level data and other publicly available data to prov |
| 590 | |
▼a School code: 0058. |
| 650 | 4 |
▼a Natural resource management. |
| 650 | 4 |
▼a Wildlife conservation. |
| 650 | 4 |
▼a Land use planning. |
| 690 | |
▼a 0528 |
| 690 | |
▼a 0284 |
| 690 | |
▼a 0536 |
| 710 | 20 |
▼a Cornell University.
▼b Natural Resources. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-10B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0058 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997379
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |