Directory UMM :Data Elmu:jurnal:P:Photogrametry & Remotesensing:Vol55.Issue1.Feb2000:

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ISPRS Journal of Photogrammetry & Remote Sensing 55 2000 9–12

www.elsevier.nlrlocaterisprsjprs

Short communication

How well do we understand Earth observation electro-optical

sensor parameters?

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George Joseph

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Space Applications Centre, ISRO, Ahmedabad 380 053, India

Abstract

Since the launch of LANDSAT-1, the Earth observation systems’ capability and utilisation has increased substantially. The past decade has seen a number of remote sensing satellites with improved capabilities. Understanding the sensor parameters from a user’s standpoint is not that easy. In the context of increasing relevance and dependence on fusion of data from various sensors, there is an urgent need to standardise the sensor parameters specified. The present paper is an attempt to raise some of the concerns regarding specifying spatial, radiometric, spectral and temporal resolution. I solicit inputs from the readers on the points raised to formulate a consolidated recommendation for the ISPRS Council to propose to the international community.q_{2000 Published by Elsevier Science B.V. All rights reserved.}

Keywords: resolution; MTF; signal-to-noise ratio; revisit period; bandwidth; sensor parameter standardisation; sensor characterisation

The extensive use of LANDSAT data for monitor-ing and management of various resources along with detailed field and laboratory studies have pointed out the need for Earth observation sensors of improved performance. The users started demanding data with better spatial, spectral, radiometric and temporal res-olutions. The need for improvement of the quality of

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This short contribution of Dr. George Joseph, President of ISPRS Technical Commission I, which I have put under the heading ‘‘Communication’’, aims at expressing his opinion on the definition and standardisation of appropriate electro-optical sensor parameters for sensor performance characterisation. As the author also points out, comments and remarks from other members of our community, and especially the related ISPRS Working Group Ir1 ‘‘Sensor Parameter Standardisation and Calibration’’, are wel-come. The Editor-in-Chief.

)_{E-mail address: george@ad1.vsnl.net.in G. Joseph .Ž .}

data products is also apparent, especially in the area

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of geometric locationrinternal distortions and

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diometric accuracy absoluterrelative . For many applications, like disaster monitoringrmitigation, agriculture, etc., quick delivery of data is demanded. While we discuss the sensor performance improve-ment, I would like to touch upon a few performance parameters, which in my opinion, require better clar-ity among the user communclar-ity.

Spatial resolution is one of the sensor parameters often mentioned but, in my opinion, also one that is least understood. Is spatial resolution the smallest object we can discern in the imagery? Our experi-ence shows that in LANDSAT TM imagery, we can see roads, with widths much smaller than the speci-fied resolution of 30 m, provided there is adequate contrast compared to the surroundings. The sensor designers came out with another terminology: the

0924-2716r00r$ - see front matterq_{2000 Published by Elsevier Science B.V. All rights reserved.}

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( ) G. JosephrISPRS Journal of Photogrammetry & Remote Sensing 55 2000 9–12

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Instantaneous Geometric Field of View IGFOV . The IGFOV can be defined as the geometric size of the image projected by the detector on the ground through the optical system, called often pixel foot-print. Any optical system reduces the contrast in the image compared to the contrast of the objects im-aged. This is expressed as the Modulation Transfer

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Function MTF . The question is: are we justified in specifying the sensor quality just in terms of the geometric projection, without any consideration of the contrast reduction it produces? How do we judge the image quality of different sensors with same IGFOV, but different MTF? Keeping this in mind, a concept of Effective Instantaneous Field of View

Ž_{EIFOV was developed in NASA SP 335 1973 .}. Ž .

EIFOV is defined as the resolution corresponding to

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a spatial frequency ground resolution for which the system MTF is 50%. This concept appears to be a good measure to compare different sensors. How-ever, if the MTF curve shapes are different, the EIFOV may not be a good indicator for intercompar-ison of the sensor quality. Anyway, this concept did not gain popularity amongst the sensor designers. To add to the confusion, a new terminology has been

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added: Ground Sample Distance GSD . That means that the data can be generated by sampling at certain

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specified ground distances although GSD is

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times used as synonym of IGFOV . Consider the pushbroom sensors, which are currently used in many

Ž_{especially high-resolution}. _{Earth observation}

sys-tems. In the along-track direction, if radiometric and electronic performance allow, the GSD can be made smaller than the IGFOV to achieve better image quality because of reduction of smear. Does across-track performance improves just because, the data are resampled at smaller intervals compared to IG-FOV? Can 5-m IGFOV sensor data, sampled at 1 m, have the same performance as a 1-m IGFOV sensor? What is the maximum allowable ratio of IGFOV over GSD?

Generally, MTF is considered as an indicator for how sharp the edges are after the contract reduction during imaging. However, MTF is also a measure of how accurately the actual radiance from a pixel is measured, since a lower MTF indicates contribution

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from other pixels to the pixel under observation and

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vice versa . Consider an object with 100% contrast

Ž_{white surrounded by black objects . When the con-}.

trast in the image space is 10%, this indicates that only 10% of the actual energy is measured. This could lead to problems in multi-spectral classifica-tion, since the radiance of a pixel measured is depen-dent on the adjacent pixel nature. Thus, the same object with different surroundings will have different signatures. This concern was raised by Norwood

Ž_{1974 . Therefore, the question is what is ‘‘radiomet-}.

rically accurate IFOV’’? Let us define this as the resolution for which the MTF is higher than 0.95. Thus, the instrument designer should specify three parameters relating to resolution.

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1. Instantaneous Geometric Field of View IGFOV

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2. Radiometrically accurate IFOV RAIFOV 3. MTF at IGFOV

For completeness, the designer should also give

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the sensor swath, i.e. the Total Field of View TFOV . All this should be referred to the orbit height or expressed in terms of angular measures.

Another performance parameter I would like to touch upon is radiometric resolution. The radiometric

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resolution is the noise equivalent reflectance or

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temperature NEDr or NEDT . This can be defined

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as the minimum change in reflectance temperature that can be detected by the sensor. It depends on a number of parameters such as, the signal-to-noise

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ratio SrN , the saturation radiance setting and the number of quantisation bits. SPOT has an eight-bit quantisation, while the IRS LISS cameras have seven-bit quantisation. In principle, both can have the same NEDr for specific reflectance radiance, if SrN and saturation setting can be properly chosen. Current systems are being designed with 11 or more bit digitisation. Such systems, unless they have a corresponding SrN, do not imply a better radiomet-ric resolution. The resolution capability of an instru-ment in terms of quantisation does not necessarily give an idea of its precision or accuracy with which it can measure. Nevertheless, higher number of bits increases the dynamic range, so that measurement of very variable objects, from ocean to snow, can be performed without gain change.

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G. JosephrISPRS Journal of Photogrammetry & Remote Sensing 55 2000 9–12 11

Radiance. For example, one should state that ‘‘the

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data are digitised to 12 bits with NEDR‘‘ x’’mWr

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cm rsteradianrmm for Band 1, etc. ’’. Many users may not get a real feel of the radiometric quality with the NEDR. It may be easier to compare sensors Žand to get a real feel by giving the S. rN at two radiance values. In addition, this SrN is the actually measured quantity, while NEDR is a derived

param-eter. It is suggested that for land observation sensors, the lower values of the radiance unit per micron

Ž_R ._{may be selected as 5 mWrcm}2_{rsteradianrmm} L

for the VNIR region and 1 mWrcm2_{rsteradianrmm} Ž .

for SWIR. The upper reference level RU may be set as 25 mWrcm2_{rsteradianrmm for VINIR and 5}

mWrcm2rsteradianrmm for SWIR. The lower value has been chosen based on the average vegetation reflectance, while for ocean observation, a 10 times

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lower value can be chosen suggestions for other reference values or methods of specifying them are

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solicited by the author .

The spectral bandwidth is another important sen-sor parameter. Each band is defined in terms of a ‘‘central’’ wavelength and a bandwidth. When one says that the TM band 1 is 0.45–0.52mm, what does this really mean? In an ideal case, the system re-sponse should be 1 between 0.45 and 0.52mm and 0 for wavelengths outside this range. Of course, this is not practical. There are a number of ways in which

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effective bandwidths are expressed Palmer, 1984 . Usually, this is defined as the 50% of the peak value

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on either side, i.e. lower and upper cut-off for the time being, let us not be concerned about how the peak is defined in a practical filter, in presence of

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ringing . What about the response beyond the 50% points? How does this affect the radiometric accu-racy? This is very important especially when the spectral resolution is high as in the case of ocean colour sensors. However, there are practical limita-tions in the reduction of the out-of-band response, which depend on the filter fabrication technology and the filter design. Here, the out-of-band contribu-tion is referred to the total system, which is a convolution of the response of filter, detector and optics. With future sensors using built-in interference

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filters on the detector chip as in the case of NASA’s

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EO-1 Advanced Land Imager , the flexibility of filter realisation may have some limitations. Nevertheless, this guarantees least out-of-band contributions.

It is suggested that for spectral bands, the follow-ing parameters are specified:

- Central wavelength - Bandwidth

- Percentage of out-of-band response

Let us now look at the temporal resolution. For

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LANDSAT 1–3, any part of the globe except around

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the poles could be imaged every 18 days. The images so taken have the same instrument view-an-gle for any location, which is important so that BDRF differences do not influence the data. With the launch of SPOT, the term ‘‘revisit capability’’ was added. This novel concept is an excellent idea to image a particular place at shorter intervals than the temporal resolution of 26 days by across-track tilting of the sensor. The revisit capability should not be

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misconstrued to temporal resolution called also

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peat coverage or repeat cycle . The revisit of a location is carried out at the cost of not acquiring data over some other locations. Can we ever have a coverage of the whole globe within a specified time duration, as was possible with LANDSAT, if the revisit capability is exercised?

It is suggested that the sensor manufacturers give both repeat and revisit periods. If the sensor pointing cannot be changed, the repeat and revisit periods will be same.

Summarising, sensor designers should, among other things, specify the following:

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1. Instantaneous Geometric Field of View IGFOV

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2. Radiometrically accurate IFOV RAIFOV

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3. Ground Sample Distance GSD 4. MTF at IGFOV

5. Number of bits per pixel 6. Saturation radiance

11. Percentage of out-of-band response

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12. Radiometric accuracy: a absolute, and b rela-tive

13. Revisit period at latitude 08and 408

( ) G. JosephrISPRS Journal of Photogrammetry & Remote Sensing 55 2000 9–12

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The first three parameters above should be given for along-track and across-track. The above specifi-cation refers to the sensor level, but of course, the end user is also concerned with the product specifi-cations, like location accuracy, distortions, etc. Since these parameters are usually well addressed, this topic will not be dealt with here.

In the context of increasing relevance and depen-dence on fusion of data from various sensors, we should identify a set of sensor parameters, which, if standardised globally, would ensure maximal re-trieval of information. Let us make transparent the intrinsic capabilities of the sensors, and let the users make their choice depending on their needs. As President of the ISPRS Technical Commission I ‘‘Sensors, Platforms and Imagery’’, I solicit your suggestionsrcomments on the points raised above,

so that I can consolidate the views of the remote sensing community to generate an ISPRS-sponsored proposal for standards on sensor specifications. The next step should be to formulate standard procedures for measurement of each of these parameters.

References

NASA SP 335, 1973. Advanced scanners and imaging systems for earth observation. Working Group Report, NASArGSFC. Norwood, V.T., 1974. Balance between resolution and

signal-to-noise ratio in scanner design for earth resources systems. In: Proc. SPIE ‘‘Scanners and Imagery Systems for Earth Obser-vation’’, Vol. 51, pp. 37–42.

Palmer, J.M., 1984. Effective bandwidths for LANDSAT-4 and LANDSAT-D multispectral scanner and thematic mapper sub-systems. IEEE Transactions on Geoscience and Remote

Sens-Ž .