Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10260241 | Urban Climate | 2015 | 13 Pages |
Abstract
The increased temperatures of urban areas raise significant economic and health-related issues that affect more than half of the world population. This fact raised the need to assess and monitor the urban thermal environment and spurred the development of supportive information for decision-making, such as heat wave risk maps. Most of these require access to high spatiotemporal temperature measurements so as to be fully effective. However, even to this day, such datasets are difficult to obtain. Many remote sensing scientists support the view that the spatial enhancement of geostationary satellite land surface temperature data (LST) can provide the needed datasets. This approach has received significant attention in recent years and considerable progress was made in the development of relevant algorithms. The objective of this article is twofold. Firstly, to introduce the reader to the processing chain that leads to the production of spatially enhanced LST data, and secondly to highlight the exploitability of such datasets. This article presents these in the context of a service that the Institute for Astronomy, Astrophysics, Space Applications, and Remote Sensing of the National Observatory of Athens (IAASARS/NOA) is implementing, which aim is to operationally provide high spatiotemporal urban temperature data to several different end-users.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Earth and Planetary Sciences (General)
Authors
Panagiotis Sismanidis, Iphigenia Keramitsoglou, Chris T. Kiranoudis,