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Table 1 Characteristics of studies using RS techniques in disease control studies during 1996-2003

From: Remote sensing and disease control in China: past, present and future

Disease Study area Study aim RS Spatial analysis Reference
schistosomiasis South of the Yellow River To explore the possibility of using prediction model for schistosomiasis surveillance. NOAA-AVHRR, 1 km Overlay analysis [33]
schistosomiasis Dantu county, Zhenjiang city, Jiangsu province To quantitatively measure the changes of marshland area related to schistosomiasis. Aerial photography maps Manual measurement [34]
schistosomiasis Anning River, Xichang city, Sichuan province To determine whether environmental conditions observable via Landsat TM imagery correlate with the presence of snails. Landsat TM, 30 m Unsupervised and supervised classification [35]
schistosomiasis Yangtze River within Nanjing city, Jiangsu province To understand the distribution of snail habitats in the lake and marshland regions. Landsat MSS, 30 m Tasseled Cap Transformation [3638]
schistosomiasis Liupo village, Guichi region, Anhui province To identify the suitable vegetation types for snails. Landsat TM, 30 m Unsupervised classification [39]
schistosomiasis Poyang Lake Identify the water regions in schistosomiasis epidemic regions. Landsat TM, 30 m Visual interpretation [40]
schistosomiasis Poyang lake To identify snail habitats in Poyang Lake regions. Landsat TM, 30 m Unsupervised classification [41]
Malaria Jiangsu Province To explore the possibilities of predict the trend of malaria epidemic with RS images. NOAA-AVHRR, 1 km Correlation analysis [42]
schistosomiasis Jiangning county To explore the relationship of NDVI and snail habitats. NOAA-AVHRR and MODIS Terra, 1 km Linear regression [43]
Dengue fever Guangdong province To explore the relationship of NDVI and Aedes density. NOAA-AVHRR, 1 km Linear regression [44]