INTRODUCTION 1 PROBLEM

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1 COMPARING METHODS FOR REMOTE SENSING SATELLITE PROJECT VALIDATION M. Mirshams & S. Amani K.N.Toosi University of Technology Ministry of Science &Technology, Aerospace Research Institute (ARI) ABSTRACT Research, design and products of remote sensing satellites for their vast application on several industrial and scientific cases is one of the Iranian space strategy s goal then comparing several plans on quantity and quality point view become so important, a remote sensing satellite validation because of several effective factor is so hard and complex in this article we suggest a simple comparing method to compare satellite plan with each other. INTRODUCTION Remote sensing is the observation of the earth s surface with special instruments and brings together some information about the earth from far way. [1] From the first days of satellites use in remote sensing field, up to now more than hundreds satellites have been lunched in to space, these satellites are used for different purposes and for this reason they have different factors and technical characterization, some of these factors are resolutionspectral band- radiometric resolution- swath width Total mass-data transferring (send) rate- spectral band Review Time and this is very difficult to compare all of them absolutely, therefore we decided to compare multi factor with AHP (analytical hierarchy process ) method and in this method we can calculate level of all satellites that are mentioned in this article then we found out that the AHP method is very effective for our purposes and we can use this method in describing, designing and the using of a remote sensing satellite.[2][3][4] 1 PROBLEM Nowadays scientists use several different methods for the validation of remote sensing satellites or other satellites, satellite producer or organization that use satellites for some special purpose have their own method that has never been published, but occasionally some international organizations try to published some satellite validation, In 1998 the Indian IRS-1D was known as a best remote sensing satellite on resolution viewpoint. [5] It is clearly known that the validation for all factors gives such an exact and true response but on the other hand so many factors have effects on satellite action that it is impossible to collect all of them or in other words the satellite producer has only published some ordinary and low level information and they try to keep valuable information secret, then we try to collect some information from several references and use factors that could identify one satellite performance in operational mode with high insurance, these factors are: 1-Resolution 2-Radiometric resolution 3-Spectral band

com ABSTRACT Research, design and products of remote sensing satellites for their vast application on several industrial and scientific cases is one of the Iranian space strategy s goal then

2 4-Review time 5-Total mass 6-Swath width 7-Data send rate 2 USAGE OF AHP METHOD IN REMOTE SATELLITE VALUATION 2.1 First step Start with describing the goal. Here the goal is optimal selection of RS satellite in the world or plan and project that going to be done. In this way according to described AHP method levels and main factors that play a main roll in satellite assess are categorized below. According fig (1) middle level consists of the problem s main factor. In this article there are seven main factor and include (resolution-spectral resolution-radiometric resolution-swath width- review time- transient time- weight), and the end levels are which choices that here are twenty six RS satellite. [6] Factor Comparative and absolute weight calculation In Analytical hierarchy process _AHP, every level element compares with the upper level element, pair to pair and their weight known as a comparative weight. Then with complication of all comparative weights, every choice of absolute weight will be detected and this is known as absolute weight. 2.2 Second step All comparisons in the analyses of the AHP process will be done pair to pair, for example if we compare the satellite according to its resolution point view, compare the first satellite A with satellite B then extend this comparison with C and so on. You can see decide process in AHP at fig (1). For example if we want compare 26 satellites this comparison could be done with the above mentioned seven factors in the middle level of fig (1), we need to create seven matrix with a 26*26 dimension then we can derive the Comparative weight of satellite to the factor from those matrix. For example we explained a part of the first matrix (resolution). At the beginning we created a matrix where it s columns and rows be named with satellite s names then started to compare rows with columns such a compare resolution of LANDSAT 1 to LANDSAT 2 be located in (1, 1) and then compare LANDSAT 1 to LANDSAT 2 and save at (1, 2) in matrix these action be continued until latest satellite. Note: Some times quantity decrease is an advantage, then we inverse them (quantity) to do our calculation on ordinary procedure, this is true about resolution i.e. 25 m resolution is better than 30m resolution. After matrix production you have to normalized matrix and save the average of every row in a column matrix until it is be used in the next step, this 26*1 matrix acts as a Comparative weight of satellite to resolution, a similar process will be executed with a residue factor of 6 and be stored separately in 6 matrix with 26*1 dimension. In the end of second step we have 7 (26*1) matrix that will be used in the 3rd and 4 th step.

In this way according to described AHP method levels and main factors that play a main roll in satellite assess are categorized below.

3 2.3 3rd steps In this step we have to compare factors with each other and identify factors advantage respect to goal. Which of these 7 factors are the most important than the others? For this purpose, similar to second step operation to find and drive Comparative weight of the satellite to factors will be done about Comparative weight of factors to goal, but in this step our matrix has 7*7 dimensions because of our seven main factors. This matrix rows and columns are the main factors that were mentioned before. Now we have to know the advantage of one factor in respect to others, and these advantages are dictated to us by (applied science & research institute) scientists and according to the purpose of this mission. [6] In this analysis for: Resolution: value 1 Radiometric resolution (bit/pixel): value 0.7 Spectral band: value 0.7 Review time: value 1 Total mass: value 1 Swath wide: value 0.5 Data send rate: value 0.7 Above value will arrange in the Comparative weight matrix of factors to goal and then normalize the rows average store in one 7*1 matrix according th steps In this step absolute weight or nominal value of all satellites will be calculated. For this purpose the Comparative weight of factors in respect to goals (7*1 matrixes) has to be multiplied in Comparative weight of choices respect to factors (26*1 matrix). For example resolution 26*1 matrix multiple to Comparative weight of resolution in respect to our goals (.1077) and this procedure will be continued for all seven factors (resolution-spectral resolution-radiometric resolution-swath width- review time- transient time- total mass) then all seven calculated value will be summation for each satellite and become the absolute value for that satellite. For example value of LANDSAT 1 become LANDSAT 1 value= * * * * * * *0.1077= Above calculation will be done by a computational program that was written in MATLAB technical language and is available. OUTCOME - Accordingly all factor analysis, with the AHP method Indian IRS-1D, with absolute weights selected as a best satellite in our analysis. Fig (2). - The AHP method has a good performance when the comparing national RS satellite plan or future satellite constellation plan for some special purpose; if data of Iranian RS satellite is available we can calculate the value of plan respect to other countries plan with the AHP method.

matrix has 7*7 dimensions because of our seven main factors. This matrix rows and columns are the main factors that were mentioned before.

4 REFERENCES 1 base of fundamental of remote sensing, P. krack Del Val & W.B. heis translated by ali sadeg nad & habib allah sahami-defense science institute, fundamental of remote sensing, remote sensing institute of Japan, translated by Iran remote sensing center, space remote sensing and the private sector: An Essay, national Academy of public administration, Washington, D.C March A study to examine the Mechanisms to carry out the transfer of civil land remote sensing systems to the private sector, earth satellite corporation, Rockville,MD, March 28, Analytical hierarchy process, translated by Dr. H.godsi pour Tehran polytechnic university Fig. 1: block diagram of AHP method

1375 3 space remote sensing and the private sector: An Essay, national Academy of public administration, Washington, D.C March 1983.

5 0,09 0,08 0,07 0,06 0,05 0,04 0,03 0,02 0,01 0 Resursf17 Resursf03 Resurse01-3 Resurse01-N4 Resursf14 Resursf20 SPOT3 SPOT4 SPOT5 IRS1A IRS1B IRSP2 IRS1C IRSP3 IRS1D IRSP5 Resursf01 SPOT2 Fig.2: result of comparing (final) absolute weight of satellites SPOT1 Landsat7 Landsat6 Landsat5 Landsat4 Landsat3 Landsat2 Landsat1

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING. Genya SAITO, Naoki ISHITSUKA, Yoneharu MATANO, and Masatane KATO*

APPLICATION OF TERRA/ASTER DATA ON AGRICULTURE LAND MAPPING Genya SAITO*, Naoki ISHITSUKA*, Yoneharu MATANO**, and Masatane KATO*** *National Institute for Agro-Environmental Sciences 3-1-3 Kannondai Tsukuba