Details

Autor(en) / Beteiligte

• Anno, S
• Takagi, M
• Tsuda, Y
• Yotopranoto, S
• Dachlan, Y P
• Bendryman, S S
• Ono, M
• Kawabata, M

Titel

Analysis of relationship between Anopheles subpictus larval densities and environmental parameters using Remote Sensing (RS), a Global Positioning System (GPS) and a Geographic Information System (GIS)

Ist Teil von

• Kobe journal of the medical sciences, 2000-12, Vol.46 (6), p.231

Ort / Verlag

Japan

Erscheinungsjahr

2000

Quelle

MEDLINE

Beschreibungen/Notizen

• Remote Sensing (RS), a Global Positioning System (GPS) and a Geographic Information System (GIS) were used to analyze relationship between Anopheles subpictus larval densities and environmental parameters in the Sekotong district on Lombok Island, Indonesia. Distance from the coast to larval habitats, season and surface water were considered as environmental parameters for determining An. subpictus larval densities. Japanese Earth Resources Satellite (JERS) Visible and Near Infrared Radiometer (VNIR) satellite imagery for the area acquired by National Space Development Agency of Japan (NASDA) were used to detect water, which could be used to characterize larval habitats. Data on larval sampling sites obtained from a GPS were entered into a GIS for mapping larval habitats to measure distance between the coast and the larval habitats. A GIS was used for overlaying of data coverages (i.e., water distribution from RS data and larval habitats coupled with data on larval densities) to identify factors that may explain the spatial distribution patterns of larval densities. An. subpictus larval densities were significantly associated with season and distance from the coast to larval habitats. The rainy season and the distance from the coast to larval habitats were critical environmental determinants for presence of An. subpictus larvae in the study. In this paper, we investigated relationship between An. subpictus larval densities and the environmental parameters using RS/GPS/GIS to determine if these tools could be used to predict larval densities.