In addition, generation of orthophotos reduces inherent errors of photographs such
as radial distortions, etc. Since the 1970s the uses of space-borne remote sensing
techniques have increased exponentially. Techniques of image enhancement, feature
extraction, image fusion, and classification have been continuously improving, which
can be applied to detect and map degradation features. On the other hand, qualities of
remote sensing products are also improving in both spatial (80x80m of Landsat MSS to
30x30m of Land TM to 1x1 m of IKONOS) as well as spectral aspects (SPOT 3 bands,
Landsat TM 7 bands). Since hyperspectral data represent an almost continuous spectral
response, making it possible to have laboratory-like reflectance curves of earth surface
features, it is easier to characterize objects and provide wider scope for differentiating
land degradation features (Figure 1, Shrestha et al. 2003). Hyperspectral data thus
provide new possibilities for mapping land degradation.
There has also been substantial
improvement in field data capture
techniques. Use of automated
data loggers helps in detailed
analysis of rainfall data, which
is crucial in applications such
as erosion modelling. Similarly,
Global Positioning System (GPS)
receivers help in locating the
sample points precisely. And more
recently, combination of a handheld
computer and GPS (Mobile
GIS) helps in digitizing features
such as land use boundaries,
infrastructure, sample locations or
land degradation features directly
in the field (Figure 2). It is also
easier to estimate and map, for
example, the area affected by recent
flooding, landslides, gullied area,
etc. Map layers can be displayed
as different coverages in the handheld
computer, which makes field
checking more accurate and reliable
(Figure 3). Another advantage is
updating of map layers directly in
the field.