While MODIS represents a key instrument in advancing the study of vector-borne diseases at continental to global scales, the ASTER is a valuable tool in studying and understanding processes at local to regional scales. As the only high spatial resolution instrument onboard Terra or Aqua, ASTER provides the ‘zoom lens’ for the other instruments. Such a utility enables the epidemiologist to focus on smaller-scale studies in areas of interest identified in large-scale studies by AVHRR or MODIS imagery. Local-scale public health studies utilizing satellite imagery have traditionally relied upon Landsat Thematic Mapper (TM) or SPOT High Resolution Visible (HRV) imagery to carry out basic mapping (Dister et al., 1997
; Hay, 1997
; Hay et al., 1998
). In a similar manner to the way MODIS displays substantial improvements over its predecessor, AVHRR, so ASTER represents the next step on from the SPOT HRV and Landsat TM. demonstrates the detail obtainable using the fine spatial resolution of ASTER imagery for Kisumu, Kenya, compared to that of AVHRR () and MODIS (). demonstrates the potential of the imagery in clearly defining settlement extent and type, enabling more accurate estimates of populations at risk and disease burden. The ASTER sensors display improvements in spatial resolution, number of spectral channels, radiometric calibration, choice of bandwidths, range of derived products and, most importantly in many cases, the cost of imagery compared to their counterparts. Although many high spatial resolution sensors have been launched in recent years, factors including spectral band limitations, mission lifespans and charging policies, make them less attractive to the field of public health and epidemiology than ASTER. This is particularly true when one considers that those areas of the world where vector-borne diseases pose the greatest obstacles are those where funds for control and research are the least.
ASTER is a cooperative effort between NASA and Japan’s Ministry of Economic Trade and Industry (METI) with the collaboration of scientific and industry organisations in both countries (Kahle et al., 1991
). The sensor covers a wide spectral region with 14 bands from the visible to the thermal infrared (TIR), with high spatial, spectral and radiometric resolution. details ASTERs bandpass specifications and shows how spatial resolution varies with wavelength: 15 m in visible and near infrared (VNIR), 30 m in the shortwave infrared (SWIR) and 90 m in the thermal infrared. ASTER can acquire around 650 scenes per day, each covering an area 60 km × 60 km. The three VNIR bands were designed to have similar bandpasses to those of the Landsat TM and the optical sensor (OPS) of the Japanese Earth Resources Satellite (JERS-1) (Yamaguchi et al., 1998
). This design should allow for possible comparisons between previous epidemiological studies made using these sensors and new studies using ASTER. It also allows for potential consistent temporal monitoring of specific areas to continue, despite the introduction of a new generation sensor. Such a feature is vital if long-term studies of disease cycles or changes in populations at risk are to be undertaken. As described for MODIS however, inconsistencies between ASTER and its predecessor sensors mean great care must be taken to ensure confident comparisons can be made. The spectral ranges of the SWIR bands were selected mainly for the purpose of surface soil and mineral mapping (Yamaguchi et al., 2001
), but reflectance measurements in the 2–4 μm range (also known as MIR) are correlated with surface temperature, water content and structure of vegetation canopies, and therefore, of use in epidemiological studies. Finally, the multispectral TIR data allows for a more accurate determination of the variable spectral emissivity of the land surface and a more accurate determination of the LST (Fujisada, 1994
Spectral bandpass details of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)
As with MODIS imagery, a large part of the time-consuming process of atmospheric correction, geo-registration, composition and processing of ASTER imagery has been reduced by the provision of readily available ASTER products. Whereas a vast array of higher-order products are produced and archived from MODIS imagery, many with obvious public health applications, the range available from ASTER imagery is not as comprehensive. Satellite-derived LST has a history of use within epidemiology and public health, and the advent of ASTER means that this information is now available at 90 m spatial resolution at low cost (Gillespie et al., 1998
). The provision of LST imagery as a higher-order product should also introduce consistency in LST derivation, leading to more direct cross-comparability between different local-scale studies.
Due to the topographically restricted distributions of many vectors of disease, a commonly-used product in epidemiology and public health studies is the digital elevation model (DEM), and most of the studies that have incorporated a DEM have used the 1 km spatial resolution USGS model (USGS/NASA, 2002b). The VNIR backward viewing band of ASTER now allows for high spatial resolution stereoscopic observation and the consequent production of a DEM product. With a 30 m spatial resolution, 7 m height accuracy and coincident registration with other ASTER imagery, the DEM product represents a potentially valuable source of altitude information for small-scale epidemiological studies. Compared to the ready-for-use wide product range of MODIS, the provision for ASTER of just LST and a DEM may seem disappointing from a public health and epidemiology perspective. However, surface reflectance imagery is available from which further relevant environmental and climatic variables can be derived. These may include NDVI at 15 m spatial resolution from the VNIR bands, use of the middle infrared bands as they are, derivation of air temperature estimates from LST and NDVI at 90 m spatial resolution, and land cover or ecozones through supervised or unsupervised classification of all bands. The challenge exists to continue the epidemiological work undertaken with AVHRR imagery (Anyamba and Eastman, 1996
; Linthicum et al., 1999
; Goetz et al., 2000
; Hay, 2000
) in producing new environmental and climatic variables from ASTER imagery.