The Union government has revised its 10-year-old remote sensing data policy, easing restrictions on high-resolution satellite imagery of ‘sensitive areas' in the country.
At a time when use of satellite images for all sort of purposes has grown dramatically, the new policy tries, as the earlier one did, to balance the demand for higher resolution data with the country's security considerations. But these days, high resolution images of Indian cities are freely accessible through Internet resources such as Google Maps and Google Earth.
Fifteen years back, when India's IRS-1C was launched, its panchromatic camera, with a resolution of 5.8 metres, gave the highest resolution images available from any civilian satellite in the world. Large blocks of imagery taken by the satellite over the country were, however, considered sensitive and not released. Each of those blocks could cover hundreds of square kilometres on the ground.
A few years later, in 1999, the American Ikonos satellite, which could take images with a resolution of one metre, was launched. In 2001, India launched its own one-metre-resolution remote sensing satellite, the Technology Experiment Satellite, which was primarily intended for the security services.
In August 2001, the then Minister of State, Vasundhara Raje, announced in the Rajya Sabha that the government had adopted a comprehensive remote sensing data policy. High-resolution images had immense potential to support local-level development and cadastral applications, she said. A “regulated distribution” of such images can not only take care of the user community's requirements, but also the national security interests.
The 2001 policy made all data with coverage over India of up to 5.8 metre resolution readily available. But data with 5.8 metre or better resolution had to be screened “so that images of sensitive areas are excluded.”
The implementation of this policy meant that these ‘sensitive areas' would be blanked out or their image quality deliberately degraded before the data was supplied to users within the country.
This practice also had the consequence, as some experts remarked, that these masked portions gave unmistakeable indications of where the country's key facilities were located. Besides, high-resolution images of India taken by foreign commercial satellites such as Ikonos could be readily purchased abroad.
The revised remote sensing data policy, which has just been announced, has lifted restrictions on the supply of satellite data with resolutions of up to one metre.
However, all data involving better than one metre resolution will need to be screened and cleared. The new policy also states that “specific requests for data of sensitive areas, by any user, can be served only after obtaining clearance” from the government's High Resolution Image Clearance Committee.
The Cartosat-2 satellite, which the Indian Space Research Organisation (ISRO) launched in 2007, gives images with a resolution of one metre. The Cartosat-2A and Cartosat-2B that followed can take images with a resolution of 0.8 metres.
But much higher resolution images are available from U.S. commercial satellites. The QuickBird's cameras have a resolution of 0.6 metres; the WorldView-1 (0.5 metres); WorldView-2 (0.46 metres); and GeoEye-1 (0.41 metres). As a result, the views of many Indian cities on Google Maps and Google Earth, which use commercially available imagery, can have a resolution of about half a metre.
The new policy will simplify access to data from the existing Indian remote sensing satellites, observed Arup Dasgupta, who was the Deputy Director of ISRO's Space Applications Centre in Ahmedabad when he retired. He is currently managing editor of the industry magazine, Geospatial World .
But Indian companies could find access to the higher resolution data from American satellites problematic unless they were working on a government-sponsored project, he told this correspondent. The requirement for images with a resolution of less than a metre was “definitely picking up” because of its usefulness for urban planning and infrastructure mapping.
