Rivers and flooded areas identified by medium-resolution remote sensing improve risk prediction of the highly pathogenic avian influenza H5N1 in Thailand
Submitted: 15 December 2014
Accepted: 15 December 2014
Published: 1 November 2013
Accepted: 15 December 2014
Abstract Views: 1504
PDF: 957
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Similar Articles
- Amare Sewnet Minale, Kalkidan Alemu, Mapping malaria risk using geographic information systems and remote sensing: The case of Bahir Dar City, Ethiopia , Geospatial Health: Vol. 13 No. 1 (2018)
- Zar Chi Htwe, Wongsa Laohasiriwong, Kittipong Sornlorm, Roshan Mahato, Spatial pattern and heterogeneity of chronic respiratory diseases and relationship to socio-demographic factors in Thailand in the period 2016 to 2019 , Geospatial Health: Vol. 18 No. 1 (2023)
- Verónica Andreo, Juan Rosa, Karina Ramos, O. Daniel Salomón, Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes , Geospatial Health: Vol. 17 No. 1 (2022)
- Sabelo Nick Dlamini, Jonas Franke, Penelope Vounatsou, Assessing the relationship between environmental factors and malaria vector breeding sites in Swaziland using multi-scale remotely sensed data , Geospatial Health: Vol. 10 No. 1 (2015)
- Suparerk Suerungruang, Kittipong Sornlorm, Wongsa Laohasiriwong, Roshan Kumar Mahato, Spatial association and modelling of under-5 mortality in Thailand, 2020 , Geospatial Health: Vol. 18 No. 2 (2023)
- Juree Sansuk, Kittipong Sornlorm, Spatial associations between chronic kidney disease and socio-economic factors in Thailand , Geospatial Health: Vol. 19 No. 1 (2024)
- Alice Nardoni Marteli, Laurindo Antonio Guasselli , Décio Diament , Gabriele Ozório Wink , Vitor Vieira Vasconcelos , Spatio-temporal analysis of leptospirosis in Brazil and its relationship with flooding , Geospatial Health: Vol. 17 No. 2 (2022)
- Ei Sandar U, Wongsa Laohasiriwong, Kittipong Sornlorm, Spatial autocorrelation and heterogenicity of demographic and healthcare factors in the five waves of COVID-19 epidemic in Thailand , Geospatial Health: Vol. 18 No. 1 (2023)
- Rufin K. Assaré, Ying-Si Lai, Ahoua Yapi, Yves-Nathan T. Tian-Bi, Mamadou Ouattara, Patrick K. Yao, Stefanie Knopp, Penelope Vounatsou, Jürg Utzinger, Eliézer K. N'Goran, The spatial distribution of Schistosoma mansoni infection in four regions of western Côte d'Ivoire , Geospatial Health: Vol. 10 No. 1 (2015)
- Suparat Tappo, Wongsa Laohasiriwong, Nattapong Puttanapong, Spatial association of socio-demographic, environmental factors and prevalence of diabetes mellitus in middle-aged and elderly people in Thailand , Geospatial Health: Vol. 17 No. 2 (2022)
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.