Version 1
: Received: 8 September 2018 / Approved: 11 September 2018 / Online: 11 September 2018 (11:17:43 CEST)
How to cite:
Wang, Z.; Mao, P.; Yang, H.; Zhao, Y.; He, T.; Dawson, R.J.; Li, Z. Measuring the Urban Land Surface Temperature Variations in Zhengzhou City Using the Landsat-Like Data. Preprints2018, 2018090192. https://doi.org/10.20944/preprints201809.0192.v1
Wang, Z.; Mao, P.; Yang, H.; Zhao, Y.; He, T.; Dawson, R.J.; Li, Z. Measuring the Urban Land Surface Temperature Variations in Zhengzhou City Using the Landsat-Like Data. Preprints 2018, 2018090192. https://doi.org/10.20944/preprints201809.0192.v1
Wang, Z.; Mao, P.; Yang, H.; Zhao, Y.; He, T.; Dawson, R.J.; Li, Z. Measuring the Urban Land Surface Temperature Variations in Zhengzhou City Using the Landsat-Like Data. Preprints2018, 2018090192. https://doi.org/10.20944/preprints201809.0192.v1
APA Style
Wang, Z., Mao, P., Yang, H., Zhao, Y., He, T., Dawson, R.J., & Li, Z. (2018). Measuring the Urban Land Surface Temperature Variations in Zhengzhou City Using the Landsat-Like Data. Preprints. https://doi.org/10.20944/preprints201809.0192.v1
Chicago/Turabian Style
Wang, Z., Richard J. Dawson and Zhenhong Li. 2018 "Measuring the Urban Land Surface Temperature Variations in Zhengzhou City Using the Landsat-Like Data" Preprints. https://doi.org/10.20944/preprints201809.0192.v1
Abstract
Satellite-based remote sensing technologies are utilized extensively to investigate urban thermal environments under rapid urban expansion. Current MODIS data is, however, unable to adequately represent the spatially detailed information because of its relatively coarser spatial resolution, while Landsat data can’t explore temporally the refined analysis due to the low temporal resolution. In order to resolve this situation, we used MODIS and Landsat data to generate “Landsat-like” data by using the flexible spatiotemporal data fusion method (FSDAF), and then studied spatiotemporal variation of land surface temperature (LST) and its driving factors. The results showed that 1) The estimated “Landsat-like” data have high precision; 2) By comparing 2013 and 2016 datasets, LST increases ranging from 1.8°C to 4°C were measurable in areas where the impervious surface area (ISA) increased, while LST decreases ranging from -3.52°C to -0.70°C were detected in areas where ISA decreased; 3) LST has a strongly negative relationship with the Normalized Difference Vegetation Index (NDVI), and a strongly positive relationship with Normalized Difference Built Index (NDBI) in summer; and 4) LST is well correlated with Building density (BD), in a complex conic mode, and LST may increase by 0.460°C to 0.786°C when BD increases by 0.1. Our findings can provide information useful for mitigating undesirable thermal conditions and for long-term urban thermal environmental management.
Keywords
Land surface temperature; the Flexible Spatiotemporal Data Fusion method; Landsat-like; Building density; urban expansion
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
