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
- Chien-Chou Chen, Jen-Hsiang Chuang, Da-Wei Wang, Chien-Min Wang, Bo-Cheng Lin, Ta-Chien Chan, Balancing geo-privacy and spatial patterns in epidemiological studies , Geospatial Health: Vol. 12 No. 2 (2017)
- Lukáš Marek, Vít Pászto, Spatio-temporal outbreaks of campylobacteriosis and the role of fresh-milk vending machines in the Czech Republic: A methodological study , Geospatial Health: Vol. 12 No. 2 (2017)
- Matthias Eckardt, Conrad Freuling, Thomas Müller, Thomas Selhorst, Spatio-temporal analysis of fox rabies cases in Germany 2005-2006 , Geospatial Health: Vol. 10 No. 1 (2015)
- Antonio Scala, Antonio Bosco, Anna Paola Pipia, Claudia Tamponi, Vincenzo Musella, Nicola Costanzo, Francesco Testoni, Antonio Montisci, Giovanni Mocci, Alessandro Longhi, Laura Tilocca, Laura Rinaldi, Giuseppe Cringoli, Antonio Varcasia, Cystic echinococcosis in cattle dairy farms: spatial distribution and epidemiological dynamics , Geospatial Health: Vol. 12 No. 1 (2017)
- Nushrat Nazia, Spatial variations of COVID-19 risk by age in Toronto, Canada , Geospatial Health: Vol. 17 No. s1 (2022): Special issue on COVID-19
- Robert Bergquist, Prehistoric human migrations: a prospective subject for modelling using geographical information systems , Geospatial Health: Vol. 18 No. 1 (2023)
- Jason Onell Ardila Galvis, Oswaldo Santos Baquero, Ricardo Augusto Dias, Fernando Ferreira, Evelyn Nestori Chiozzotto, José Henrique Hildebrand Grisi-Filho, Monitoring techniques in the capture and adoption of dogs and cats , Geospatial Health: Vol. 10 No. 2 (2015)
- Xiaohui Xu, Hui Hu, Sandie Ha, Daikwon Han, Smartphone-assisted spatial data collection improves geographic information quality: pilot study using a birth records dataset , Geospatial Health: Vol. 11 No. 3 (2016)
- Kyungsoo Han, Sejin Park, Jürgen Symanzik, Sookhee Choi, Jeongyong Ahn, Trends in obesity at the national and local level among South Korean adolescents , Geospatial Health: Vol. 11 No. 2 (2016)
- Marcus Matheus Quadros Santos, Bianca Alessandra Gomes do Carmo, Taymara Barbosa Rodrigues, Bruna Rafaela Leite Dias, Cleyton Abreu Martins, Glenda Roberta Oliveira Naiff Ferreira, Andressa Tavares Parente, Cíntia Yollete Urbano Pauxis Aben-Atha, Sandra Helena Isse Polaro, Eliã Pinheiro Botelho, Spatial variability of mother-to-child human immunodeficiency virus transmission in a province in the Brazilian Rainforest: An ecological study , Geospatial Health: Vol. 17 No. 2 (2022)
<< < 32 33 34 35 36 37 38 > >>
You may also start an advanced similarity search for this article.