Mapping misery — and anticipating it

Flood detection, flood plain mapping, and flood inundation mapping of rivers susceptible to flooding is a basic satellite-imagery task.

In India, LANDSAT data has been used to map floods in the Ganga-Kosi plains. The Space Application Centre has also completed one LANDSAT project with the Ganga Flood Control Commission and the Survey of India. Various features like river courses, river levels, flood plains, and inundated areas have been compiled in standard Geological Survey of India (GSI) accuracy-level maps.

Similarly, snow melt in the Sutlej-Beas catchment and its inflow into the Govind Sagar reservoir has been carried out on satellite images from the National Oceanographic and Atmospheric Administration (NOAA), USA, with 90 per cent accuracy. Remote sensing has also been employed to predict storm floods.

Drought, long considered a meteorological phenomenon, is today increasingly believed to be human-made. Drought vulnerability depends on the extent to which physical and climatic conditions play an adverse role in increasing unstable agriculture.

Agricultural drought is monitored through the Crop Moisture Index (CMI), which is calculated using a model that combines precipitation and temperature data with that of soil, evaporation-transpiration, and other local factors. CMI employees very limited point measurements, and does not determine drought footprint or moisture stress foci.

Drought remote sensing has been successfully used during experiments conducted by Thompson and Wehmanen. One method is qualitative: it measures vegetative vigour by juxtaposing colour infrared LANDSAT images with corresponding images of the previous year (if that was a normal year), and with an immediately preceding image, of say, 18 days previous.

A second quantitative method, developed by Kauth and Thomas and taken up at the Space Application Centre, Ah-medabad, estimates severity of drought. Accentuated `brightness-greenness’ in bands of images is an indication of important agricultural features, and suppressed in `yellowness-brightness’ and `none-such-brightness’….

In the public eye, cyclones and remote sensing go together. Remote sensing continuously provides visual and infrared pictures of cloud development, as well as land-sea temperature details. Coupled with data on other meteorological features like wind velocity, it is possible to forecast cyclones to the day.

As in Gujarat recently, advance cyclone warning helps in evacuation and in limiting the nature, extent, and magnitude of human and material damage.

Excerpted from `India Disasters Report’, edited by Parasuraman S. and Unnikrishnan P.V.,OUP, Rs 345