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Title: Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model

Authors:
;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1531176
Grant/Contract Number:  
SC0016438
Resource Type:
Published Article
Journal Name:
Environmental Modelling and Software
Additional Journal Information:
Journal Name: Environmental Modelling and Software; Journal ID: ISSN 1364-8152
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Gao, Jing, and O'Neill, Brian. Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model. United Kingdom: N. p., 2019. Web. doi:10.1016/j.envsoft.2019.06.015.
Gao, Jing, & O'Neill, Brian. Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model. United Kingdom. doi:10.1016/j.envsoft.2019.06.015.
Gao, Jing, and O'Neill, Brian. Mon . "Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model". United Kingdom. doi:10.1016/j.envsoft.2019.06.015.
@article{osti_1531176,
title = {Data-driven spatial modeling of long-term urban land development potential for global environmental change impact assessment: The SELECT model},
author = {Gao, Jing and O'Neill, Brian},
abstractNote = {},
doi = {10.1016/j.envsoft.2019.06.015},
journal = {Environmental Modelling and Software},
number = ,
volume = ,
place = {United Kingdom},
year = {2019},
month = {7}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1016/j.envsoft.2019.06.015

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