[Study on unsupervised classification in marshland of endemic area of Schistosomiasis Japonica using satellite TM image data].
OBJECTIVE
To categorize the vegetation of marshland in the endemic areas of Schistosomiasis Japonica using satellite thematic mapper (TM)data in Liupo Village, Anhui Province.


METHODS
Data of three satellite TM hands, namely TM3, TM4 and TM5, were selected to be used in classification with principal component analysis. Then, satellite TM images were applied to false color composite and unsupervised classification with computer software to manage the images. Finally, the resulting clusters were identified and reclassified by site visits to categorize the land coverage and vegetation.


RESULTS
Five classifications of land coverage were generated, including poplar forest, bulrush and marshland, all with snail habitants. Based on the survey in the spring of 1998, the overall live snail density and infested snail density in the study areas were 0.510/0.11 m2 and 0.007/0.11 m2, respectively.


CONCLUSIONS
Unsupervised classification, which is a technique for the interpretation of remotely sensed imagery, can contribute to the classification of environment with snail habitants and ecological diseases and become a new method in epidemiological studies.
Lin
T
T
Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China.
Jiang
Q
Q
Zhang
S
S
D000818:Animals; D002681:China / Q000453:epidemiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D017215:Satellite Communications / Q000295:instrumentation; D012549:Schistosoma japonicum; D012554:Schistosomiasis japonica / Q000453:epidemiology*; D012908:Snails / Q000469:parasitology*