Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/33246
Title: Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+
Authors: Zhang, Y.
Balzter, Heiko
Zou, C.
Xu, H.
Tang, F.
First Published: 8-Jul-2015
Citation: International Journal of Applied Earth Observation and Geoinformation, 2015, 42, pp. 87-96 (10)
Abstract: Landscape patterns in a region have different sizes, shapes and spatial arrangements, which contribute to the spatial heterogeneity of the landscape and are linked to the distinct behavior of thermal environments. There is a lack of research generating landscape metrics from discretized percent impervious surface area data (ISA), which can be used as an indicator of urban spatial structure and level of development, and quantitatively characterizing the spatial patterns of landscapes and land surface temperatures (LST). In this study, linear spectral mixture analysis (LSMA) is used to derive sub-pixel ISA. Continuous fractional cover thresholds are used to discretize percent ISA into different categories related to urban land cover patterns. Landscape metrics are calculated based on different ISA categories and used to quantify urban landscape patterns and LST configurations. The characteristics of LST and percent ISA are quantified by landscape metrics such as indices of patch density, aggregation, connectedness, shape and shape complexity. The urban thermal intensity is also analyzed based on percent ISA. The results indicate that landscape metrics are sensitive to the variation of pixel values of fractional ISA, and the integration of LST, LSMA. Landscape metrics provide a quantitative method for describing the spatial distribution and seasonal variation in urban thermal patterns in response to associated urban land cover patterns.
DOI Link: 10.1016/j.jag.2015.06.007
ISSN: 0303-2434
Links: http://www.sciencedirect.com/science/article/pii/S0303243415001361
http://hdl.handle.net/2381/33246
Embargo on file until: 8-Jul-2017
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2015 Elsevier B.V. All rights reserved. This manuscript version is made available after the end of the embargo period under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Description: The file associated with this record is under a 24-month embargo from publication in accordance with the publisher's self-archiving policy, available at http://www.elsevier.com/about/company-information/policies/sharing. The full text may be available in the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Geography

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