OBJECTIVE: To probe rational indices suitable for ecological surveillance on breeding ground for Oncomelania hupensis snails in areas prevalent with islet-type schisitosomiasis using remote sensing technology. METHODS: Three adjacent islets, prevalent with islet-type schistosomiasis, along the Yangtze River within the boundaries of Dongzhi County, Anhui Province were selected as study field for remote sensing analysis. Multi-spectral data were composed and non-supervisedly classified in computer with Idisi software for remote sensing analysis. Values of the normalized difference vegetation index (NDVI), green vegetation index (GVI), bright index (BI), which reflect the greenness and brightness of landscape, were also calculated. Finally, all the results were comprehensively analyzed, combined with data from the field investigation. RESULTS: NDVI, GVI and BI could depict characteristics of the landscape quantitatively. Values of NDVI, BI and GVI were varied in different types of landscapes, and 95% confidence interval of these values suitable for breeding of snails was 0.0522 approximately 0.3566, 2.4162 approximately 28.2672 and 29.3404 approximately 40.3135, respectively. Classification of NDVI showed that type 5 anf type 6 were main breeding ground for snails, and type 4 with values of NDVI from 0 to 0.1 was potential areas for snail propagation. Classification of GVI showed that types 5, 6 and 7 were main breeding ground for snails, and also type 4 with values of GVI from 2 to 10 was potential areas for snail propagation. Both NDVI and GVI showed type 2 and type 3 were temporarily not suitable for snail breeding. CONCLUSION: Index figures of NDVI and GVI re-formed by reasonable classification could reflect not only breeding ground for snails and range of the areas for snail propagation in islets, but also their evolving rules, i.e., status of new marshland formation and vegetation growth.
OBJECTIVE: To probe rational indices suitable for ecological surveillance on breeding ground for Oncomelania hupensis snails in areas prevalent with islet-type schisitosomiasis using remote sensing technology. METHODS: Three adjacent islets, prevalent with islet-type schistosomiasis, along the Yangtze River within the boundaries of Dongzhi County, Anhui Province were selected as study field for remote sensing analysis. Multi-spectral data were composed and non-supervisedly classified in computer with Idisi software for remote sensing analysis. Values of the normalized difference vegetation index (NDVI), green vegetation index (GVI), bright index (BI), which reflect the greenness and brightness of landscape, were also calculated. Finally, all the results were comprehensively analyzed, combined with data from the field investigation. RESULTS: NDVI, GVI and BI could depict characteristics of the landscape quantitatively. Values of NDVI, BI and GVI were varied in different types of landscapes, and 95% confidence interval of these values suitable for breeding of snails was 0.0522 approximately 0.3566, 2.4162 approximately 28.2672 and 29.3404 approximately 40.3135, respectively. Classification of NDVI showed that type 5 anf type 6 were main breeding ground for snails, and type 4 with values of NDVI from 0 to 0.1 was potential areas for snail propagation. Classification of GVI showed that types 5, 6 and 7 were main breeding ground for snails, and also type 4 with values of GVI from 2 to 10 was potential areas for snail propagation. Both NDVI and GVI showed type 2 and type 3 were temporarily not suitable for snail breeding. CONCLUSION: Index figures of NDVI and GVI re-formed by reasonable classification could reflect not only breeding ground for snails and range of the areas for snail propagation in islets, but also their evolving rules, i.e., status of new marshland formation and vegetation growth.