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| Aims | Methods: remote sensing and GIS | Concept illustrated | Geography and scale | Data sources | Software used | Major findings | Reference |
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| The relationship between the incidence of VL and certain physioenvironmental factors was explored, using a combination of a geographical information system (GIS), satellite imagery, and data collected “on the ground” | Supervised classification (Maximum Likelihood algorithm) | Thiessen polygon, overlay, and index model | Northeastern Gangetic Plain, large scale | NOAA (AVHRR) | ERDAS imagine v9.3, ArcGIS v9.2 | It was found that the presence of water bodies, woodland and urban, built-up areas, soil of the fluvisol type, air temperatures of 25.0–27.5 degrees C, relative humidities of 66%–75%, and an annual rainfall of 100–<160 cm were all positively associated with the incidence of VL | Bhunia et al., 2010 [13, 14] |
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| To study the relationship between the incidence of kala-azar and topography and vegetation density | Digital elevation model (DEM), normalized difference vegetation index (NDVI) | Overlay, spectral indices
| India, large scale | SRTM, Landsat TM 5 | ERDAS imagine v9.3, ArcGIS v9.2 | (i) The results show significant variation in case diversity within the defined gradient.
(ii) Results also showed that most of the cases occurred in nonvegetative areas or low density vegetation zones. | Bhunia et al., 2010 [13, 14] |
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To delineate the potential hydrological relationship between the vector and
kala-azar transmission, the associations between inland water bodies, sand fly
prevalence, and Leishmania infections | Normalized difference pond index (NDPI), nearest neighbour analysis, radial basic function interpolation | Spectral indices, geostatistics | Lalganj and Hajipur block (Vaishali district, Bihar, India), medium to fine | Landsat 5 TM | ERDAS Imagine v9.3, ArcGIS v9.2 | The higher moisture content of the surrounding areas of nonperennial rivers and lesser density of water bodies play an important role in the maintenance of sand fly density, promoting transmission of the disease | Bhunia et al., 2011 [25] |
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The spatial distribution of reported kala-azar cases in the
4 study periods of Muzaffarpur district, Bihar, India, during
the period from 1990 to 2008 | Spatial analysis | Database queries | Muzaffarpur district (Bihar, India), medium | — | ArcGIS v9.2 | Within the district, the blocks with the highest number of cases shifted from east (1990–98) to west (1999–2008) that may correspond to a rise in herd immunity in western blocks | Malaviya et al., 2011 [26] |
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The study focused on
examining disease distribution
in a kala-azar endemic region
in Bihar, India | Spatial analysis and standard deviation of ellipse | Geostatistics | Muzaffarpur district (Bihar, India), fine | — | ArcGIS v9.2 | Mean centre of case observations within the district was identified which may aid to delineate ideal location to monitor and manage the deadly disease for epidemiological surveillance and control
Standard deviation of ellipse (SDE) was drawn to understand the directional distribution of disease | Bhunia et al., 2012 [12] |
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| To examine the relationship between LULC classes and their suitability for vector habitats in areas endemic for kala-azar at different spatial scales | Thematic maps and satellite supervised classification (Maximum Likelihood algorithm) | Overlay, buffering, land use/land cover | Vaishali and Muzaffarpur districts (Bihar, India), large to fine scale | AVHRR, MODIS, Landsat TM, LISS IV | ERDAS imagine v9.3, ArcGIS v9.2 | At national level, the fact that the highest information values were attained from areas associated with water bodies, closed shrub land, and urban areas indicates that these features are likely to contain vector habitats
At state level, only a minor part of the total area seemed suitable for vector habitats. The highest information values were attained from bare areas or places with sparse or herbaceous vegetation, which indicates that these features support the presence of vectors
At district level, high suitability for sand fly habitats was attributed to
marshy land, dry or moist fallow, and settlements, but areas associated with water-bodies, sandy areas, and plantations also indicated relatively high suitability
At village level, the high suitability of some LULC types occupying grass/weeds covers land, marshy land, dry fallow, areas associated with water bodies and settlements. The plantation class assigned as medium potential for the sand fly habitat | Bhunia et al., 2012 [22] |
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