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Technology trends in Remote Sensing and data analysis

P. S. Roy1, Vandana Agarwal2
1Dean, 2Scientist ‘SD’, Geoinformatics Division
IIRS, Dehra Dun
1[email protected], 2[email protected] Since the beginning of the space age, a remarkable progress has been made in utilising remote sensing data to describe, study, monitor and model the earth’s surface and interior. Improvements in sensor technology, especially in the spatial, spectral, radiometric and temporal resolution, have enabled the scientific community to operationalise the methodology. The trend of development of remote sensing is being from panchromatic, multi-spectral, hyper-spectral to ultra-spectral with the increase in spectral resolution. On the other hand, spatial resolution is reaching its highest side of one metre resolution. The operational remote sensing satellites LANDSAT, Indian Remote Sensing Satellites (IRS series of satellites), IKONOS etc. are providing earth data in different improved spatial and spectral resolutions. The value added products such as Orthophotos, standard DEMs, DEMs with specified level of details, geocoded images, fused images are providing the user community a big support.

Future Indian Remote Sensing Satellites
The futuristic scenario of the Indian Remote Sensing Satellite programme includes Technology Experiment Satellite (TES), RESOURCESAT (IRS P6), CARTOSAT (IRS P5) and OCEANSAT (IRS P7) satellites.

TES Mission will be launched in July 2000 having PAN sensor with 2.5 metres resolution with high temporal resolution. This satellite is launched to provide hands on experience in complex mission operations like step and stare manoeuvres and onboard earth rotation compensation etc.

Resourcesat (IRS P6) will have three sensors, LISS-3, LISS-4 and Advanced WiFS (AWiFS). This satellite will provide an enhanced multispectral/ spatial coverage. AWiFS has a greatly improved spatial resolution of 70 metres resolution with repetivity of five days.

Cartosat (IRS P5) is scheduled to be launched in March 2002 to generate orthoimage, DEMs, and to generate high precision georeferencing for cartographic mapping.

Oceansat (IRS P7) is scheduled for launch in year 2003. The applications shall include measurements of sea surface temperature, chlorophyll pigments and sea surface wind direction and speed.

High Resolution Satellite Data
Viewed from the point of view of information content, higher spatial resolution permits the discrimination of smaller units of material on the earth’s surface. At present, the civilian systems having high spatial resolution are the panchromatic data from IRS-1C and IKONOS satellites having 5 metres and one metre resolution respectively.

IKONOS satellite also has 4 metre multispectral data. Similar satellites from ORBIMAGE and EarthWatch Inc. are planned for launch this year. The prohibitive cost of commercial satellites is a major hindrance in their widespread use.

New high resolution satellites are also planned. The European Space Agency (ESA) has scheduled next year launch of the biggest EO satellite to date. ENVISAT-1 will have improved technical characteristics compared to its predecessors (ERS-1 and 2 with advanced synthetic aperture radar). The operating characteristics of these new high resolution sensors are summarised in Table 1.

Wide Field Sensors for regional scale mapping
WiFS data of IRS 1C/1D provides the advantage of covering a very large area in a single instantaneous field of view (IFOV), avoiding any illumination difference. Suitability of such moderate resolution data for regional vegetation as compared to AVHRR data marks better choice for monitoring and research. The pixel size of 188 metres suits regional scale mapping. WiFS data enables rapid change assessment and early warning in certain episodic events like forest fire, drought etc. Its high temporal resolution i.e. five days and large area coverage (810×810 sq kms) is helpful in developing improved yield models and assessing crop condition.

Digital Elevation Models
Acquiring highly detailed elevation data always has been a complicated business. Although GPS technology and digital photogrammetry have improved the process, there is still a considerable amount of effort and time involved. < Recent developments of light detection and ranging (LIDAR) and laser terrain mapping systems, however, may dramatically reduce the time and efforts needed. With current systems, it is possible to survey by air thousands of square kilometres in less than 12 hours and have a highly detailed digital terrain model available within 24 hours, with vertical accuracy of 15 centimetres and an elevation relative accuracy of about 5 centimetres.

IRS 1C and IRS 1D satellites are also providing the stereo pair of images for use in generation of the DEM. The costs of generating DEM vs. level of detail are given in the following figure. Where :

  1. : Aerial Photography (tropical)
  2. : Aerial Photography (Urban)
  3. : STAR 3I, Interferometric Radar
  4. : Airborne Laser Scanner
  5. : STAR 3I, Global Terrain
  6. : IRS/Spot Satellite
  7. : Satellite Stereo (RADARSAT)
  8. : ‘Global Terrain’

Hyperspectral Imaging
Hyperspectral imaging refers to the image of a scene over a large number of discrete, contiguous spectral bands such that a complete reflectance spectrum can be obtained.

One of the major hyperspectrometers is Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS). AVIRIS was designed to image 224 contiguous bands in the region from 0.4 – 2.5 micro metres. The increased spectral range in the visible region allows biologists to study important reactions in the vegetation and shallow water biology. The resolution of the system is of the order of 10 nm, providing sufficient resolution to detect most absorption features. A few of the air-borne and space-borne sensors are as given in Table 2.

Image Compression
Imagery data are voluminous and even in today’s fast communicating world of the internet, it is difficult to transfer the image data. Image compression technologies, however, now make it possible to quickly move imagery via the Web. The latest technologies include Image Pyramids, fractal and Wavelet Compression.

Image Analysis Techniques
Recent analysis techniques are Image Fusion, Interferometry, Decision Support Systems etc.

Image Fusion
The merging of multisensor data is becoming widely used with diverse types of data as a result of improvements in terms of better sensor resolution and rapid advances in computer image analysis. The advancements in image analysis have allowed for greater.

Table 1: High Resolution Satellites

Sensor Vis
Bands S
Visible (m)
Resolution IR Swath Stereo
QuickBird 3 1 1 1 3.3 22 Yes
Ikonos 3 1 1 1 3.3 12 Yes
Orbview-3 3 1 1 1 4 8 Yes
Eros 1 1.5 13 Yes
RS PS 1 2.5 30 Yes

Table 2: Hyperspectral Imaging Sensors

Sensor Spectral
Bandwidth (Spectral
AVIRIS 224 400-2450 9.6 11 20
COIS 210 400-2450 10 30 >200 5
Hyperion 220 400-2500 10 7.5 10
Warfighter 200 400-2500 10 5 1

flexibility and use of innovative techniques for combining and integrating multi-resolution and multi -spectral data. The aims of image and data fusion are to sharpen images, improve geometric corrections, provide stereo-viewing capabilities for stereo-photogrammetry, to enhance certain features not visible in either of the single data alone, detect changes using multi-temporal data, substitute missing information in one image with signals from another sensor image (e.g. clouds-VIR, shadows-SAR) and to replace defective data.

Image fusion is performed at three different processing levels: at pixel level, feature and decision levels. Image fusion at pixel level means fusion at the lowest processing level referring to the merging of measured physical parameters. Fusion at feature level requires an extraction of objects recognised in the various data sources. Decision-level fusion represents a method that uses value added data where the input images are processed individually for information extraction.

Radar Interferometry
Since the performance of optical sensors to generate digital elevation models is somewhat less than desirable, the capabilities of coherent RADAR systems have been explored to get inexpensive DEM data to the land areas of the globe. ERS 1 and 2 as well as JERS -1 and Radarsat have not only become an effective tool to image the earth’s surface through clouds and at night in an “all weather system”, due to the coherent nature of the active sensing system, they have also permitted Radar Interferometry, which has the potential of deriving a digital elevation model. Radar Interferometry is a rapidly developing field in which two or more radar images of the same location are processed together.

Decision Support System(DSS)
A Decision Support System is an interactive, flexible and adaptable computer based information system, specially developed for supporting the solution of a particular ill-structured problem for improved decision making. It utilises data, it provides easy user interface and it allows for the decision -maker’s own insights. Most sophisticated DSS also utilises models, it is built by an iterative process, it supports phases of decision making, and it includes a knowledge base.