Meteorologists have been using satellite images for monitoring storms for about thirty years. One of the most important applications in this endeavour is to determine the strength and intensity of a storm. In the late 1960's, meteorologists began observing tropical cyclones at more frequent intervals. The infrared sensors aboard polar orbiting satellites began providing day-and-night observations while geo-stationary satellite provided the continuous coverage during daytime. There exists a very efficient cyclone warning system in India which is comparable to the best known in the world. The approach essentially involves the prediction of the track and intensity of the cyclone using conventional as well as satellite and radar-based techniques (Kellar, 1997).
A network of 10-cyclone detection radar covering entire East and West Coasts is being used for cyclone warning each with a range of 400 km. When cyclone is beyond the range of coastal radar, its intensity and movement is monitored with the help of INSAT, and NOAA series of satellites. The INSAT provides every three-hourly cloud pictures over the Indian subcontinent. For precise location, every half-an-hour pictures are used. Warnings are issued by the Area Cyclone Warning Centers (ACWS) located at Calcutta, Madras, and Bombay; and Cyclone Warning Centers (CWC) located at Bhubaneswar, Visakhapatnam and Ahmedabad. Around 100 disaster warning systems have been installed in cyclone-prone villages of Andhra Pradesh and Tamilnadu. It is planned to expand such facility with another 100 DWS in Orissa and West Bengal on the East coast. The DWC disseminates warning of impending event to village administration, District Collector, State Government officials, etc. The most memorable use of DWS system has been during the cyclone that hit the Andhra Pradesh coast on may 9, 1990, in evacuating over 1,70,000 people. The information helped saving thousands of lives and livestock in this area. Additional DWS units are being established to cover the entire coastal areas of the country.
The most striking advantage of the earth observation satellite data has been demonstrated during the recent Orissa super-cyclone event. A severe cyclonic storm with a wind speed about 260 kmph hit the Orissa coast at Paradip on 29-oct-99 causing extensive damage to human life, property, live stock and public utilities. The National Remote Sensing Agency acted promptly and provided spatial extent of inundated areas using pre-cyclone IRS LISS-III data collected on 11th October, 1999 and Radarsat Synthetic Aperture Radar(SAR) data of 2nd November, 1999 since cloud -free optical sensor data over the cyclone-hit area were not available (Fig.3). The map showing inundated area as on 2nd Nov, 1999 was drapped over topographical map, and was delivered to the Orissa Government on 3rd Nov,1999. Information, thus generated, was effectively used by various departments of Orissa Government involved in relief operations. Subsequently, the recession of inundated areas was also studied using Radarsat and IRS data of 5th,8th,11th,13th and 14th November, 1999. An estimated 3.75 lakh ha in Jagatsinghpur, Kendrapara, Bhadrak, Balasore, Jajpur, besides Cuttack, Khurda and Puri districts had been found to be inundated. In addition, the crop damage assessment was also made and maps along with block-wise statistics derived using pre-and post-cyclone NDVI image from IRS WiFS data were also provided to Orissa Government.
India is the worst flood-affected country in the world after Bangladesh and accounts for one-fifth of the global death count due to floods. About 40 million hectares or nearly 1/8th of India's geographical area is flood-prone. An estimated 8 million hectares of land are affected annually. The cropped area affected annually ranges from 3.5 million ha during normal floods to 10 million ha during worst flood. Flood control measures consists mainly of construction of new embankments, drainage channels and afforestation to save 546 towns and 4700 villages. Optical and microwave data from IRS, Landsat ERS and Radarsat series of satellites have been used to map and monitor flood events in near real-time and operational mode(Fig.4). Information on inundation and damage due to floods is furnished to concerned departments so as to enable them organising necessary relief measures and to make a reliable assessment of flood damage. Owing to large swath and high repetivity, WiFS data from IRS-1C and -1D hold great promise in floods monitoring.
Based on satellite data acquired during pre-flood, flood and post-flood along with ground information, flood damage assessment is being carried out by integrating the topographical, hydrological and flood plain land use/land cover information in a GIS environment. In addition, spaceborne multispectral data have been used for studying the post-flood river configuration, and existing flood control structures , and identification of bank erosion-prone areas and drainage congestion, and identification of flood risk zones.
Flood Disaster Impact Minimization
Flood forecasts are issued currently by Central Water Commission using conventional rainfall runoff models with an accuracy of around 65% to 70% with a warning time of six to twelve hours. The poor performance is attributed to the high spatial variability of rainfall not captured by ground measurements and lack of spatial information on the catchment characteristics of the basin such as current hydrological land use / land cover, spatial variability of soils, etc. Incorporation of remote sensing inputs such as satellite-derived rainfall estimates, current hydrological land use / land cover, soil information, etc. in rainfall-runoff model subsequently improves the flood forecast. Improvements in flood forecasting was tested in lower Godavari basin in a pilot study titled "Spatial Flood Warning System". Under this project, a comprehensive database including Digital Elevation Model (DEM) generated using Differential Global Positioning System (DGPS), hydraulic/hydrologic modeling capabilities and a Decision Support System (DSS) for appropriate relief response has been addressed in collaboration with concerned departments of Andhra Pradesh Government. Initial results have been quite encouraging. The deviation in the flood forecast from actual river flood has been within 15%.
Earthquakes are caused by the abrupt release of strain that has built up in the earth's crust. Most zones of maximum earthquake intensity and frequency occur at the boundaries between the moving plates that form the crust of the earth. Major earthquakes also occur within the interior of crustal plates such as those in China, Russia and the south-east United States. A considerable research has been carried out to predict earthquakes using conventional technologies, but the results to date are inconclusive. Seismic risk analysis based on historic earthquakes and the presence of active faults is an established method for locating and designing dams, power plants and other projects in seismically active areas. Landsat-TM and SPOT images, and Radar interferograms have been used to detect the active faults (Merifield and Lamer 1975; Yeats et al.1996; Massonnet et al. 1993). Areas rocked by Landers earthquake (South California) of magnitude 7.3 were studied using ERS-1 SAR interferometry which matched extremely well with a model of the earth's motion as well as the local measurements (Masonnet and Advagna 1993). Active faults on the seafloor could also be detected by side-scan sonar system (Prior et al, 1979). The earthquake prediction is still at experimental stage. Successful prediction of minor earthquake have, however, been reported. Among the major earthquakes, Chinese scientists predicted an earthquake 1-2 days ahead in 1975 (Vogel, 1980). Information on earthquake is ,generally, obtained from a network of seismographic stations. However, very recently the space geodetic techniques and high resolution aerial and satellite data have been used for earthquake prediction. Space geodetic technique with Global Positioning System (GPS) provides an accuracy of a centimetre over 1000 km and , thus, helps in measuring the surface deformations and monitoring accelerated crystal deformations prior to earth quakes with required accuracy.
Earthquake risk assessment involves identification of seismic zones through collection of geological / structural, geophysical (primarily seismological) and geomorphologic data and mapping of known seismic phenomena in the region, (mainly epicenters with magnitudes). Such an effort calls for considerable amount of extrapolation and interpolation on the basis of available data. There is also a tendency for earthquake to occur in "gaps" which are in places along an earthquake belt where strong earthquake had not previously been observed. The knowledge of trends in time or in space helps in defining the source regions of future shocks (Karnik and Algermissen, 1978). Satellite imagery could be used in delineating geotectonic structures and to clarify seismological conditions in earthquake risk zones. Accurate mapping of geomorphologic features adjoining lineaments reveals active movement or recent tectonic activity along faults. The relationship between major lineaments and the seismic activity has been observed in Latur area of Maharastra, India. Space techniques have overcome the limitations of ground geodetic surveys/measurements and have become an essential tool to assess the movement/displacements along faults/plate boundaries to even millimetre level accuracy.
Using Very Long Baseline Interferometry (VLBI), it has been possible to record accurately the plate movement of the order of centimetre along baseline of hundreds of kilometre. Similarly, satellite-based Global Positioning system (GPS) has emerged as a powerful geodetic tool for monitoring (geological) changes over time which is the key for understanding the long-term geo-dynamical phenomena. GPS has been particularly useful in measuring the more complex deformation patterns across plate boundaries where large and regional scale strain builds up. Plate movements, slips along faults etc. have been measured using differential GPS to an accuracy of sub-centimetres.
Many times precursors of volcanic eruptions have been observed in various areas of volcanic activity. Ground deformations, changes in the compositions of gases emitting from volcanic vents, changes in the temperatures of fumaroles, hot springs and crater lakes as well as earth tremors are preceding volcanic eruptions. Thermal infrared remote sensing has been applied for volcanic hazard assessment. However, deficiencies of equipment and coverage suggest that thermal infrared has not been adequately evaluated for surveillance of volcanoes. The National Remote Sensing Agency has demonstrated the potential of multi-temporal Landsat-TM thermal band data in the surveillance of active volcanoes over Barren island volcano which erupted during March 1991 to September 1991 (Bhatacharya et al. 1992). In the last three decades, aircraft and satellite-based thermal infrared (TIR) data have been used extensively to detect and monitor many of the active volcanoes around the world. Repetitive coverage, regional scale, and low cost of thermal infrared images from satellites make it an alternative tool for monitoring volcanoes. Although the spatial resolution of NOAA environment satellite is too coarse to record details of surface thermal patterns, the plumes of smoke and ash from volcanoes could be detected which is useful in planning the rehabilitation of affected areas.
Studies have shown that the upward migration of magma from the earth's crust just before eruption inflates the volcanic cone. Such premonitory signs can easily and quickly be detected with the aid of differential SAR interferometry. Extensive calibrations in a variety of test areas have shown that by using this technique, changes on the earth's surface can be detected to a centimetre accuracy.
Aerial photographs and large-scale satellite images have been used to locate the areas with the incidence of landslide. Higher spatial resolution and stereo imaging capability of IRS -IC and -1D enable further refining the location and monitoring of landslides. A number of studies have been carried out in India using satellite data and aerial photographs to develop appropriate methodologies for terrain classification and preparation of maps showing landslide hazards in the Garhwal Himalayan region, Nilagiri hills in south India and in Sikkim forest area. Such studies have been carried out using mostly aerial photographs because of their high resolution enabling contour mapping with intervals of better than 2m in height. The availability of 1m resolution data from the future IRS mission may help generating contour maps at 2m intervals making thereby space remote sensing a highly cost effective tool in landslide zonation.
Crop Pest and Diseases
One of the successful programmes where space technology has been used in risk assessment from crop pests/diseases is the Desert Locust Satellite Applications project of the UN/FAO for the International Desert Locust Commission. Temporal and spatial distribution of desert vegetation and rainfall derived from NOAA-AVHRR data have been used to identify the potential Locust breeding grounds. In India, the desert locust is epidemic over 2 lakhs sq.km spread over Rajasthan, Gujarat and Haryana states. Improved desert locust forecasting system is being tried with the help of satellite data by the locust warning organizations by narrowing down the potential breeding areas to undertake aerial spraying for arresting further growth of locust.
Several thousands of hectares of forests are burnt annually due to manmade forest fires causing extensive damage to forest wealth. The behaviour of forest fire depends upon three parameters: fuel, weather, and topography. Each parameter has several characteristic parameters. The most important task in the preparedness phase is to assess the risk. For risk assessment variables such as land use/land cover, demography, infrastructure and urban interface are considered. Effective mitigation of forest fire involves fuel (land cover, weather, terrain, vegetation type and moisture level) mapping, identification of fire risk areas, rapid detection, local and global fire monitoring and assessment of burnt areas. The analysis of near-real time low spatial resolution (1km) and high repetivity data from NOAA and high spatial resolution data with low repetivity from earth resources satellites could provide the information on areas under fire. The IRS satellite data have been used for monitoring forest fires over Nagarhole Wild Life Sanctuary of Southern India.
Apart from loss of human lives, natural disasters inflict severe damage to ecology and economy of a region. Space technology has made significant contribution in all the three phases, i.e. preparedness, prevention and relief of disaster management. With a constellation of both INSAT and IRS series of satellites, India has developed an operational mechanism for disaster warning especially cyclone and drought, and their monitoring and mitigation. However, prediction of certain events likes earthquake, volcanic eruption and flood is still at experimental level. Developments in space-based earth observation and weather watch capabilities in future may help refining existing models/approaches for prediction of such events and their management.
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