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DC Field | Value | Language |
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dc.contributor.author | A. Charoenpanyanet | en_US |
dc.date.accessioned | 2019-09-16T12:51:15Z | - |
dc.date.available | 2019-09-16T12:51:15Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 16866576 | en_US |
dc.identifier.other | 2-s2.0-85070765512 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070765512&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/66649 | - |
dc.description.abstract | © Geoinformatics International. There are three systems in the dengue virus transmission cycle: Human system, mosquito system, and temperature system. Therefore, the effect of temperature on the dengue virus incubation period was estimated as a spatial estimation. The temperature parameters from ground station in 2004-2013 are estimated by using the statistical technique. The temperature value in the Mueang Chiang Mai district in 2013 was calculated by using Land sat 8-TIRS. Thereafter, the temperatures were estimated as the spatial dimension based on remotely sensed data in every ÍOyears, that is, 2023, 2033, and 2043. These temperatures are used to estimate the dengue virus incubation period in Aedes mosquito through a suitable equation. It is evident from the study that the dengue virus incubation period in the Aedes mosquito has decreased steadily. The mean dengue virus incubation periods in 2013, 2023, 2033, and 2043 are 11.06 days, 10.30 days, 9.64 days, and 9.06 days, respectively. Furthermore, estimations for the dengue virus incubation period for 2023, 2033, and 2043 point out that the dengue virus incubation period decreases in accordance with priority in time. Areas that are suitable for a dengue virus incubation period of less than 5 days have expanded. | en_US |
dc.subject | Earth and Planetary Sciences | en_US |
dc.subject | Physics and Astronomy | en_US |
dc.subject | Social Sciences | en_US |
dc.title | Estimation of dengue virus incubation period in aedes mosquito from temperature variability based on remotely sensed data | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | International Journal of Geoinformatics | en_US |
article.volume | 15 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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