2007 IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates

DETERMINATION OF EARTH SURFACE FROM TRMM SATELLITEIMAGES

Ali R. Al Suwaidi, Ali Dawood, Khalid Mubarak, Ghaith Matar andHamad Al Hammadi

Communication Engineering DepartmentEtisalat University College, Sharjah, UAE

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ABSTRACT

The Precipitation Radar (PR), on board of theTRMM satellite, provides many information andmeasurements related to the weather above the earth.Images are produced from reflectivity measurement ofdifferent particles and materials. Determination of earthsurface level is required when investigating detectionmethods using TRMM PR data, such as detection of oiland underground water below the earth surface. In thispaper, two techniques were proposed for detecting exactearth location from TRMM satellite rays reflectivity. Firsttechnique is based on satellite reflectivity images and thesecond one is based on the reflectivity data itself Theformer performed better than the latter in estimating theearth surface level. This finding can facilitate oil andunderground water detection.

Index Terms -satellite, TRMM, geolocation, normalsample, samples (bins), exact earth location, imageprocessing, classification.

1. INTRODUCTION

A successful mission called the Tropical RainMeasuring Mission (TRMM), was a joint project between(NASA) and (NASDA). The Precipitation Radar (PR), onboard the satellite, is the first weather radar to bedeployed in space and is one of several instruments beingused to provide a three-dimensional structure of rainfallby measuring the radar reflectivity of the cloud systemand the attenuation of a signal as it passes through theprecipitation.

The main advantage of such a system is its globalcoverage. These measurements include large ocean areaswhere our knowledge of precipitation is poor. Importantapplications of this project are immediate practicalbenefits to agricultural, water resources management, andflood warnings [1], [2], [3], [4].

The PR electronically scans from right to left, lookingin the flight direction across the ground track of thesatellite every 0.6 seconds, with horizontal resolution atthe ground of 5km and swath width of 215km. Each PRscan contains of 49 rays, ray at 25 called the nadir and theother rays called off nadir. Nadir and off nadir rays canbe sampled above and below the earth surface [4], [5].

Most TRMM data products are written usingHierarchical Data Format (HDF).

1.1. PR level - 1B

The PR Level-lB product, IB-21, PR Power,contains calibrated PR powers in three dimensional arrayswhose dimensions are scans, ray, and range bin. Power iswritten in three arrays: normal sample, surfaceoversample, and rain oversample. The vertical spacing is250 m for the normal sample. If the surface oversampleand rain oversample are combined with the normalsample, the result is 125 in vertical spacing in limitedregions [5].

1.2. PR level- 1C

The PR Level-IC product, 1 C-21, PR Reflectivity,has the same format as IB-21, with 3 changes: thevariable in the Normal Sample, Surface Oversample, andRain Oversample is reflectivity (dBZ) in lC-21 [5].

1.3. PR level - 2A

The PR Level-2A products are 2A-21, 2A-23 and2A-25. 2A-25, PR Profile, produces an estimate ofvertical rainfall rate profile for each radar beam. Therainfall rate estimate is given at each resolution cell of thePR radar [5].

2. SYSTEM OVERVIEW

This system is used to determine exact earth locationfrom TRMM PR data then processes these data intoimages. This system consists of the following elements:

1. TRMM satellite: record information about thecovered areas.

2. Computer: normally a PC running Windows.It runs the system using MATLAB software.

TRMM satellite is sending microwave towards theearth and then receiving the reflected waves. Thesereflected waves containing the information about theobjects that in the way of the waves and then TRMMsatellite process these information and store it as a HDFfiles.

1-4244-1236-6/07/$25.00 © 2007 IEEE 580

MATLAB codes were used to convert HDF filesformat to Binary format in order to study and plot imagesof the coverage area. Also M\ATLAB can be used as an

image processing tool to process the images that plottedby using TRMM data.

3. ORBIT PATH (GEOLOCATION)

The geolocation is defined as the earth location ofthe beam center per angle bins at the altitude of the earthellipsoid. This is recorded as longitude and latitude.Positive number of latitude indicates north latitude, andpositive number of longitude indicates east longitude [5].

Each orbit has 9150 scans and the duration of eachscan is 0.6 second. The duration of one orbit is 5490swhile the duration of one day is 86400s. In this case thereare 15 - 16 orbits per day over the globe for TRMMsatellite as illustrated in figure 1. Figure 2 illustrates thegeolocation of only one orbit over the globe; while figure3 shows the orbit number 29549 covers part of the UAE.

F Land!One Day Orbis| Nadi (ray = 25)!

Figure 1: One day orbits for nadir (ray = 25) in 20thJanuary 2007.

One Orbits per Day

Land* Nadir (ray = 25)* Off-Nadir (ray = 1)* Off-Nadir (ray = 49)

80-

20 .__ _ ~

-20 _ / T -- -

-60__----

- - - - - - - - - - - - - - - - - -

s

-150 -100 -50 0 50 100 150Longitude

Figure 2: Geolocation of orbit number 29549 over theglobe.

COrbit No, 2954930 < lLn

29 ______I - N-dir (ra,y = 25)\ I - O~~~~~~C:ff-Na,dir (ra,y = 1 )

28 - _C_I __ ff-Na,dir (ra,y = 49)

27 L-

-- - - - - - - - - - - - - - =-- - -

500 52 54 5ei 58 ecLoCngitude

Figure 3: Orbit No. 29549 over the UAE.

Figure 4 and 5 shows the 3D plot for latitude andlongitude of this specific orbit respectively. In thesefigures the latitude and longitude were plotted as a

function of scan and ray numbers.

Latit u de of Orbil No. 2-E49 in 3-D

20 .----

-2 0~~ ~~~~~...............

--4_

20ScnnNo. ] ° Ray

Figure 4: 3-D Latitude.

20D----

-'° I-- -- --

D .---20D ----

1000D

!moD0

Scan No.

-ongt ij de of Orbit \M o. 28549 ir 3-C

_50

40~~~~~

U---- - 0------. RE'00

20 -1--sO

0 tdy

Figure 5: 3-D Longitude.

4. SCAN GEOMATERY AND EARTH SURFACE

As mentioned in previous part each orbit consists of9150 scans. Each scan generates 49 rays toward the earth.Each ray consists of 140 bins starting from the satellitegoing towards the earth. The ray which consists of 140bins has 80 bins above the earth surface and 60 binsbelow the earth surface. Moreover, the altitude ofTRMMsatellite is 402.5 kilometers. Figure 6 shows earthlocation, bins starting location, and 49 rays.

Bin Starting as a function of Rays

0 5 10 15 20 25 30 35 40 45Rays

Figure 6: Bins starting and earth surface.

5 50

581

-20

-3'O

L 0o

F -10

_-20

-30

6C0 - - - -- - - - - i-

/-6 - - t-- 2-- - Y- - -Xf

--m

. ....

ED

a1)

-i

ao)

CZ

5. MEASURED REFLECTIVITY AND EXACTEARTH LOCATION

The normal sample PR received powers are recorded.These data stored in the array of 49 rays * 140 samples.

The figure below shows a vertical profile ofmeasured reflectivity Z m for data taken over the UAE onthe 20th of January, 2003. The distance between any twobins is 0.25 km.

Measured Reflecti\Aty Zm in dBz

20F

40

aT)zEz

n

60

80

100

120

35

30

25

_20

.* 155 10 15 20 25 30 35 40 45

Ray

Figure 7: Measured reflectivity representation for scannumber 5789.

The exact earth location can be determines as themaximum reflectivity in each ray. Figure 8 illustrateswhich sample represents the exact earth location.

images, assign each color to different number, and finallyget the indices of the maximum number (represent the binnumber after scaling it).

Measured Reflecti\Aty Zrn in dBz

Ez

5 10 15 20 25 30 35 40 45Ray

Figure 9: Measured reflectivity representation for scannumber 5789 (zoomed in).

Two methods were used in this field in order todecide which one is better (based on error percentage).

6.1. Specific color to specific number

In the first method each specific color that representscertain reflectivity should be assigned as differentnumber, for example pure red assigned to number 8.Figure 10 shows the error percentage of this method (forscan number 5789).

Error percentage for scan no. 5789

75

a80

E

z

m 85

90

0 5 10 15 20 25 30 35 40 45Ray

0

20

.' 40m

60

80

50

Figure 8: Exact earth location representing by binnumber for scan number 5789.

6. IMAGE PROCESSING

Exact earth location should be found using imageprocessing in order to compare it with the measuredreflectivity images. The reason of this is to find thepercentage of error between the real data and the image.

First of all the area that contained continuousreflectivity should be zoomed in (illustrated in figure 9)in order to processes this image easily then save it as bmpimage. Then MATLAB code should be used to read these

0 5 10 15 20 25 30 35 40 45 50Rays

Figure 10: Image processing (specific color as a specificnumber).

Error percentage of this method can be calculated byusing the following equation:|real bin values- map bin valuei

real_bin valuesError percentage of the first method:

13963 - 4027*6 100 1.9197%3963

582

_ ~~I

_I _- _ ~~~I

_ _

Exact earth location

0 + Exact earth surfaceMapped earth surface

- - Error percentage

mo

--.j

-1- -1

W.-__j

wiffir_gffi.-I

6.2. Range of colors to specific number

In this method the range of colors should be assignedas different number, for example from dark to pure redassigned to number 8. For the same scan figure 11illustrates the result of this method.

Error percentage for scan no. 5789-20

2020

Exact earth surfaceMapped earth surface

240 -Oe Error percentage

60

80

0 5 10 15 2 5 3 5 4 5 5

0 5 10 15 20 25 30 35 40 45 50Rays

Figure 11: Image processing (range of colors as aspecific number).

Error percentage of this method can be calculated byusing equation (1). Error percentage of the secondmethod:

3963 - 3956 1___________ 100 =0.88370%3963

7. CLASSIFICATION

7.1. Data mining

Data mining is a practical topic and involves learningin a practical sense. Our main interest is in techniques forfinding and describing structural patterns in data to makepredictions from it. The data will take the form of a set ofexamples. Consequently, the output will take the form ofpredictions about new examples. On the other hand, theoutput may also include an actual description of astructure that can be used to classify unknown examplesto explain the decision. It is also helpful to supply anexplicit representation of the knowledge that is acquired[6].7.3. Classification results

Classification was used for determination of earthsurface as a second way added to the image processing.Moreover, software called "Weka" was the classificationsoftware used for determining the earth surface. Thefollowing figure shows a summary of the classificationresults using the method J48. The results are showing thepercentage of the correctly classified instances and theincorrectly classified instances. Although the percentageof the correctly classified instances is high, but this is notacceptable because of the following; the availableattributes are two: the reflectivity value in dB andwhether it is ground or not. Moreover, the reflectivitiesare divided in two classes, either ground or non-ground.

The problem is that the class of non-groundreflectivies is much higher than the ground class becausethere are 1201 instances, 49 out of the 1201 are groundreflectivities and the all the remaining is non-ground.=== Summary ===

Correctly Classified Instances 116697.0858 %Incorrectly Classified Instances 352.9142 %

Confusion Matrixa b <-- classified as

15 34 a = 1.001 1151 b = 0.00

Figure 12: Summary of classification results.

8. CONCLUSIONS

We can conclude the following from the previoussections:

* Each orbit for TRMM satellite in one day has adifferent path than others orbits (covers differentareas).

* The maximum measured reflectivity in each rayrepresents the exact earth location.

* Percentage of error varies between different scannumbers.

* Classification is useful when there are equalinstances for both classes.

In general exact earth surface can be found frommeasured reflectivity file (normalsample) in IC21 dataproduct. MATLAB software can be used as an imageprocessing tools. Different methods in image processingcan be used in order to determine exact earth location andthe best method depends on the efficiency (errorpercentage) of each method. The more efficiency we get,the best the method we use. On the other hand,classification methods could be used also for determiningexact earth surface using different classification methodswhich are provided by the "Weka" software.

9. REFERENCES

[1] Khalid A. Mubarak, "3dB Thickness of Bright Band", 4thInternational Conference on Computing, Communications andControl Technologies (CCCT 2006), Orlando, USA, July 20-23,2006.

[2] B. Zafar, K. Mubarak, V. Chandrasekar, "Evaluation ofPrecipitation Type Determination from TRMM Observation,"Proceedings for the Conference on Geoscience and RemoteSensing - IGARSS 2003, Toulouse, France, July 21-25, 2003.

[3] K. Mubarak, A. Dawood, "Identification of height offreezing using TRMM satellite," International Conference onCommunications, Computer and Power (ICCCP 2007) Muscat,February 19-21, 2007.

[4] Dennis Roddy, "Satellite Communications", ThirdEdition, McGraw-Hill, 2001.

[5] TRMM Precipitation Radar Manual, Version 6, January1 th , 2005.

[6] Ian H. Witten & Eibe Frank, "Data Mining", SecondEdition, 2005.

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