This document provides information on a group assignment submitted by 16 students for their Introduction to Remote Sensing course. It includes the group number, course details, student names and registration numbers, and the assignment questions. The assignment involves describing the TRMM satellite's owner and location, orbital characteristics, identifying its onboard sensors and providing details on each sensor's specifications and functioning.

1. FACULTY OF AGRICULTURE
DEPARTMENT OF AGRICULTURE ENGINEERING AND LAND PLANNING
PROGRAM: BSC. IRRIGATION AND WATER RESOURCES ENGINEERING
COURSE TITLE: INTRODUCTION TO REMOTE SENSING
GROUP NO: 04
CODE: LRM 111
GROUP WORK
DATE OF SUBMISSION: 16 JAN 2017
INSTRUCTOR: Prof D N Kimaro
NAME REGISTRATION NUMBER
OMARY OMARY B IWR/D/2016/0048
DAUDI SAID JAFARY IWR/D/2016/0010
MWENDA JOEL BENO IWR/D/2016/0042
BAWILI RAMADHANI IWR/D/2016/0007
NGEIYAMU EMMANUEL MUCHUNGUZI IWR/E/2015/0053
DOTO MUSA GESE IWR/D/2016/0011
YASSON ANDREA BEZAEL IWR/D/2016/0059
AMANZI ABUBAKARY IWR/D/2016/0003
ISAYA ALLY IWR/E/2016/0082
SHEHIZA JULITHA DICKSON IWR/D/2016/0054
MROKI REHEMA NAFTAL IWR/D/2016/0037
CHRISPIN GEBRA SHAO IWR/D/2016/0008
KWEKA DANIEL ENOCK IWR/D/2016/0023
MONYO ISMAIL BAKARI IWR/E/2016/0084
KAPINGA FREDRICK FRANCIS IWR/D/2016/0017
ZAMBI CHARLES IWR/D/2016/0064

2. ASSIGNMENT 01
(i) The one who is owning and managing TRMM satellite is Japan Aerospace Exploration
Agency (JAXA) in collaboration with National Aeronautic And Space
Administration(NASA) of USA.
It is located at Tanegashima Space Center in Japan.
TRMM Satellite
ii. TRMM Orbital Characteristics
Launch date- Inclination Orbit Mean
motion
Pedigree Apogee
November 27,
1997
35 to theᵒ
equator
Circular(non-
sun-
synchronous)
16.364 174km 176KM

3. (iii) identification and naming of the sensors on board TRMM satellite
•
a) Cloud and Earth Radiant Energy Sensor (CERES)

4. CERES will measure the energy at the top of the atmosphere, as well as estimate energy levels
within the atmosphere and at the Earth’s surface.
The Clouds and the Earth’s Radiant Energy System (CERES) instrument is one of five
instruments that is being flown aboard the Tropical Rainfall Measuring Mission (TRMM)
observatory.
The data from the CERES instrument was used to study the energy exchanged between the Sun;
the Earth’s atmosphere, surface and clouds; and space.
b) Lightning Imaging Sensor (LIS)
Lightning Imaging Sensor is a small, highly sophisticated instrument that detects and
locates lightning over the tropical region of the globe
The Lightning Imaging Sensor is a small, highly sophisticated instrument that detects and
locates lightning over the tropical region of the globe.
Looking down from a vantage point aboard the Tropical Rainfall Measuring Mission (TRMM)
observatory, 250 miles (402 kilometers) above the Earth, the sensor provides information that
could lead to future advanced lightning sensors capable of significantly improving weather "now
casting."
Using a vantage point in space, the Lightning Imaging Sensor promises to expand scientists'
capabilities for surveying lightning and thunderstorm activity on a global scale. It will help pave
the way for future geostationary lightning mappers.
From their stationary position in orbit, these future lightning sensors would provide continuous
coverage of the continental United States, nearby oceans and parts of Central America.
Researchers hope that future sensors will deliver day and night lightning information to a
forecaster's work-station within 30 seconds of occurrence — providing an invaluable tool for
storm "nowcasting" as well as for issuing severe storm warnings.
The lightning detector is a compact combination of optical and electronic elements including a
staring imager capable of locating and detecting lightning within individual storms.
The imager's field of view allows the sensor to observe a point on the Earth or a cloud for 80
seconds, a sufficient time to estimate the flashing rate, which tells researchers whether a storm is
growing or decaying.
The sensor provides information on cloud characteristics, storm dynamics, and seasonal as well
as yearly variability of thunderstorms.

5. The Lightning Imaging Sensor will be three times more sensitive than a predecessor instrument
known as the Optical Transient Detector — a lightning detector already orbiting the Earth.
The sensor studies both day and night cloud-to-ground, cloud-to-cloud and intra-cloud lightning
and its distribution around the globe.
The staring imager is made of an expanded optics lens system which provides a wide field of
view and a narrow-band filter which minimizes background light.
A highspeed, charge-coupled device detection array behaves similarly to the retina of the human
eye by creating an image of the lightning event and the background scene.
A real-time event processor then extracts the signal, thus determining when a lightning flash
occurs.
The optics lens system allows lightning detection even in the presence of bright, sunlit clouds.
Weak lightning signals that occur during the day are hard to detect because of background
illumination.
This system will remove the background signal, enabling the detection of 90 percent of all
lightning strikes.
Data recorded includes the time of a lightning event, its radiant energy — how bright the
lightning flash is — and an estimate of the lightning location.
The Lightning Imaging Sensor is approximately eight inches in diameter and 14 inches high,
while the supporting electronics package is about the size of a standard typewriter.
Together, the two modules weigh approximately 46 pounds and use about 25 watts of power.
c) Visible Infrared Radiometer (VIRS)

6. . The Visible and Infrared Scanner (VIRS) is one of the primary instruments aboard the Tropical
Rainfall Measuring Mission (TRMM) observatory.
VIRS is one of the three instruments in the rain-measuring package and serves as a very indirect
indicator of rainfall.
It also ties in TRMM measurements with other measurements that are made routinely using the
meteorological Polar Orbiting Environmental Satellites POES) and those that are made using the
Geostationary Operational Environmental Satellites (GOES) operated by the United States.
VIRS, as its name implies, senses radiation coming up from the Earth in five spectral regions,
ranging from visible to infrared, or 0.63 to 12 micrometers.
VIRS is included in the primary instrument package for two reasons. First is its ability to
delineate rainfall.

7. The second, and even more important reason, is to serve as a transfer standard to other
measurements that are made routinely using POES and GOES satellites.
The intensity of the radiation in the various spectral regions (or bands) can be used to determine
the brightness (visible and near infrared) or temperature (infrared) of the source.
If the sky is clear, the temperature will correspond to that of the surface of the Earth, and if there
are clouds, the temperature will tend to be that of the cloud tops. Colder temperatures will
produce greater intensities in the shorter wavelength bands, and warmer temperatures will
produce greater intensities in the longer wavelength bands.
Since colder clouds occur at higher altitudes the measured temperatures are useful as indicators
of cloud heights, and the highest clouds can be associated with the presence of rain.
A variety of techniques use the Infrared (IR) images to estimate precipitation. Higher cloud tops
are positively correlated with precipitation for convective clouds (generally thunderstorms)
which dominate tropical (and therefore global) precipitation accumulations.
One notable exception to this rule of thumb are the high cirrus clouds that generally flow out of
thunderstorms.
These cirrus clouds are high and therefore "cold" in the infrared observations but they do not
rain.
To differentiate these cirrus clouds from water clouds (cumulonimbus), a technique which
involves comparing the two infrared channels at 10.8 and 12.0 micrometers can be employed.
Nonetheless, IR techniques usually have significant errors for instantaneous rainfall estimates.
The strength of the IR observations lies in the ability to monitor the clouds continuously from
geostationary altitude.
By comparing the visible and infrared observations on the Tropical Rainfall Measuring Mission
with the rainfall estimates of the TRMM Microwave Imager and Precipitation Radar, it is hoped
that much more can be learned about the relationship of the cloud tops as seen from
geostationary orbit.
VIRS uses a rotating mirror to scan across the track of the TRMM observatory, thus sweeping
out a region 833 kilometers wide as the observatory proceeds along its orbit.

8. Looking straight down (nadir), VIRS can pick out individual cloud features as small as 2.4
kilometers.
VIRS Sensor Characteristics
Observation Band 0.63µm; 1.6µm; 3.75µm; 10.8µm and 12µm
Horizontal Resolution 2 km(nadir)
Swath Width About 833 km
Scan Mode Cross-Track Scan
d) TRMM Microwave Imager (TMI)
The Tropical Rainfall Measuring Mission’s (TRMM) Microwave Imager (TMI) is a passive
microwave sensor designed to provide quantitative rainfall information over a wide swath under
the TRMM satellite.
By carefully measuring the minute amounts of microwave energy emitted by the Earth and its
atmosphere, TMI is able to quantify the water vapor, the cloud water, and the rainfall intensity in
the atmosphere.
It is a relatively small instrument that consumes little power. This combined with the wide swath
and the good, quantitative information regarding rainfall make TMI the "workhorse" of the rain-
measuring package on Tropical Rainfall Measuring Mission.
Measuring Rainfall with Microwaves
Calculating rainfall rates from TMI requires some fairly complicated calculations. The basis of
these calculations is in Planck’s radiation law, which describes how much energy a body radiates
given its temperature.

9. Water surfaces such as oceans and lakes have an additional property which is very important.
The surfaces emit only about one half the microwave energy specified by Planck’s law and
therefore appear to have only about half the real temperature of the surface.
Water surfaces therefore look very "cold" to a passive microwave radiometer. Raindrops on the
other hand, appear to have a temperature that equal their real temperature.
They appear warm to a passive microwave radiometer and therefore offer a contrast against
"cold" water surfaces.
The more raindrops, the warmer the whole scene appears, and research over the last three
decades now make it possible to obtain fairly accurate rainfall rates based on the temperature of
the microwave scene.
Land is very different from oceans in terms of the emitted microwave radiation, appearing to
have about 90 percent of its real temperature.
In this case, there is little contrast to observe the "warm" raindrops. Certain properties of rainfall,
however, still can be inferred.
The high frequency microwaves (85.5 GHz) measured by TMI are strongly scattered by ice
present in many raining clouds. This reduces the microwave signal at the satellite and offers a
contrast against the warm land background.
e) Precipitation Radar (PR)
The Precipitation Radar was the first spaceborne instrument designed to provide three-
dimensional maps of storm structure.
These measurements yield invaluable information on the intensity and distribution of the rain, on
the rain type, on the storm depth and on the height at which the snow melts into rain.

10. The estimates of the heat released into the atmosphere at different heights based on these
measurements can be used to improve models of the global atmospheric circulation.
The Precipitation Radar has a horizontal resolution at the ground of about 3.1 miles (five
kilometers) and a swath width of 154 miles (247 kilometers).
One of its most important features is its ability to provide vertical profiles of the rain and snow
from the surface up to a height of about 12 miles (20 kilometers).
The Precipitation Radar is able to detect fairly light rain rates down to about .027 inches (0.7
millimeters) per hour. At intense rain rates, where the attenuation effects can be strong, new
methods of data processing have been developed that help correct for this effect.
The Precipitation Radar is able to separate out rain echoes for vertical sample sizes of about 820
feet (250 meters) when looking straight down. It carries out all these measurements while using
only 224 watts of electric power—the power of just a few household light bulbs.
The Precipitation Radar was built by the National Space Development Agency (JAXA) of Japan
as part of its contribution to the joint US/Japan Tropical Rainfall Measuring Mission (TRMM)
Sensor Specifications Characteristics
Microwave Radiometer (TMI) Radar (PR)
Visible and Infrared
Radiometer (VIRS)
Frequencies
10.7, 19.3, 21.3, 37.0, and 85.5 GHz
(dual-polarized except for 21.3:
vertical only)
13.8 GHz13.8
0.63, 1.601.6, 3,.715.6,
1,03.8.7, 5, and 12 μm1
Resolution
11 km X 8 km field of view at 37
GHz
5-km footprint and
250- m vertical
resolution
2.5-km resolution
Scanning Conically scanning (530 inc.) Cross-track scanning Cross-track scanning
Swath
Width
880-km swath 250-km swath 830-km swath

11. .
ASSIGNMENT 02
RADIOMETRIC CORRECTIONS
Definition:
removal of sensor or atmospheric 'noise', to more accurately represent ground conditions -
improve image ‘fidelity’: These corrections allow more accurate assessment of ground surface
properties and facilitate comparison be- tween images acquired at different times or for different
areas.
i) detector response calibration
As we have discussed before, Landsat MSS has 6 detectors at each band, TM has 16 and SPOT
HRVs have 3000 or 6000 detectors. The differences between the SPOT sensors and Landsat
sensors are that each SPOT detector collects one column of an image while each detector of
Landsat sensors corresponds to many lines of an image (Figure 5.1).

12. The problem is that no detector functions the same way as others. If the problem becomes
serious, we will observe banding or striping on the image.
There are two types of approach to overcome the detector response problems:
absolute calibration and
relative calibration absolute calibration
In this mode, we attempt to establish a relationship between the image grey level and the actual
incoming reflectance or the radiation. A reference source is needed for this mode and this source
ranges from laboratory light, to on-board light, to the actual ground reflectance or radiation.
For CASI, each detector is calibrated by the manufacturer in the laboratory. For the Landsat
MSS, a calibration wedge with 6 different grey levels is used. For the Landsat TM, three lamps,
which have 8 brightness combinations, are used.
In any case, a linear response is assumed for each detector
vo = a ï vi + b
vo - observed reading
vi - known source reading
e.g. for an 8-bit image 0 < vo < 255 .
Least squares method is used to derive a and b
A least squares linear fitting is applied to these detector responses.Once each detector is
calibrated, the calibrated image data (digital numbers) can be converted into radiances or spectral
reflectances. For the case of converting digital numbers of an 8 bit image into radiances, we have
relative calibration

13. Even though data may have been absolutely calibrated, an image may still have problems caused
by sensor malfunctioning. For example, in some of the early Landsat-1, 2, 3 images, there may
be lines which have been dropped out. No response for that particular detector can be found. In
other cases, there are still striping problems. This happens to both MSS and TM images. The
striping problem is most obvious when an image is acquired over water body where the actual
spectral reflectance from one part to another are similar.
When six detectors of the Landsat MSS are seeing the same
water target, their responds should be the same.
ii) De-stripping refers to the process of adding essential details in an image.
iii) Removal of missing scan lines refers to the process of removing missing
horizontal lines traced across a cathode-ray tube by an electron beam which
form part of an image.
iv) Random noise removal
is the process of removing noise from a signal. All recording devices, both analog and digital,
have traits that make them susceptible to noise. Noise can be random or white noise with no
coherence, or coherent noise introduced by the device's mechanism or processing algorithms.
BEFORE AFTER

14. Before and after removal of noise in an image
v) Vignetting removal
is the addition of an image's brightness or saturation at the periphery compared to the image
center.

15. ASSIGNIMENT : 3
Differences between LIDAR and RADAR
Radar is an object-detection system that uses radio waves to determine the
range, angle, or velocity of objects. while LIDAR (also called LIDAR,
LIDAR, and LADAR) is a surveying method that measures distance to a
target by illuminating that target with a laser light.
• RADAR uses radio waves while LIDAR uses light rays, the lasers to be
more precise.
• Size and the position of the object can be identified fairly by RADAR, while
LIDAR can give accurate surface measurements.
• RADAR uses antennae for transmission and reception of the signals, while
LIDAR uses CCD optics and lasers for transmission and reception.
SIMILARITIES BETWEEN LIDAR AND RADAR
1`. Both are detecting systems fitted in satellites for obtaining ground information

16. 2. Both uses electromagnetic energy for their detection, where radar system detect radio wave
and liar system detect laser light of the infrared region of electromagnetic spectrum application
of liar in geomorphology and forestry
ii) LASER SCANNING
Definition:
Laser Scanning - Laser Scanning is the process of shining a structured laser line over the surface
of an object in order to collect 3-dimensional data. The surface data is captured by a camera
sensor mounted in the laser scanner which records accurate dense 3D points in space.
iii) application of lidar technology in forestry and geomophology
FORESTRY
1. Forest structure analysis. Todd et al analyzed the relationship between horizontal and vertical
distributions of light transmittance and foliage distributions using LIDAR in a sugar maple stand
in northern Ontario, Canada. Weller et al described an approach to estimating forest structure
parameters, including foliage projected cover and tree height, in southeast Queensland using
laser profiler data. Lovell et al. evaluated the capabilities of ground-based and airborne laser
systems for estimation of height, cover, and vertical foliage profile in New South Wales,
Australia. Lim et al used LIDAR data to estimate biophysical properties, including 1) maximum
tree height,
2. Individual tree analysis. Popescu et al utilized LIDAR and multispectral optical data to
identify individual trees and measure crown diameters for the purpose of estimating plot-level

17. volume and biomass in the eastern United States. Leckie et al used a combination of
multispectral and LIDAR data to improve automated recognition of individual tree crowns.
4. Forest Planning and Management: LIDAR is widely used in the forest industry to plan and
mange. It is used to measure vertical structure of forest canopy and also used to measure and
understand canopy bulk density and canopy base height. Other uses of the LIDAR in the forest
industry is the measurement of the peak height to estimate its root expansion.
5. Forest Fire Management: LIDAR is becoming widely popular in forest fire management. Fire
department is transforming from reactive to proactive fire management. LIDAR image helps to
monitor the possible fire area which is called fuel mapping (fire behavior model). On this article
author discuss, how British Colombia is using LIDAR information for the fire management.
6. Precision Forestry: Precision Forestry is define as planning and operating the site specific
forest area to increase the productivity of wood quality, reduce cost and increase profits, and
maintain the environment quality. LIDAR and aerial photo is used to perform precision forestry.
Article on “LIDAR Applications in Precision Forestry” talks in detail about its uses.
GEORMOPHOLOGY
1. Flood Model: LIDAR provides very accurate information. River is very sensitive and few
meter of change in information can bring disastrous or loss of properties. So LIDAR is used to

18. create high resolution and accurate surface model of the river. These extracted LIDAR
information can be used for the 3D simulation for better planning of the structures or buildings
on the river bank.
2. Watershed and Stream Delineation:
DEM generated from LIDAR is used to create watershed area and stream line delineation. High
and accurate DEM is the major input to create this and GIS software is used to create it. This
way you can calculate watershed for the particular water channels and find out stream channel
for over land
3. Management of Coastline: LIDAR data of the coastline surface and under the water
surface can be combined by researches to analyze the waves behavior and area covered by them.
If these da
ta are captured periodically then marine scientist can understand the coastline erosion
occurrence.
Glacier Volume Changes: : LIDAR is used to calculate the glacier change over the period.
LIDAR image are taken in time series to see the change happening. For example, LIDAR image
was taken of Iceland from 2007-2009 and project was completed on 2012. These captured data
will help scientist to know the amount of volume change.
4. Dune Monitoring: LIDAR is used to monitor the dune activities. It includes change in size and
shape, vegetation, rate of change and other related dune activities.
iv) APPLICATIONS OF LIDAR IN AGRICULTURE
1. LIDAR can be used to create three dimensional digital models of a farm and from these

19. produce incredible accurate maps of the natural resources. For example it can be used to map the
water flow, define the water catchments, locate all the trees in an orchard, show the water flow
direction at the base of each tree and show the division between water flowing down the tree line
or across the tree line.
2. LIDAR allows us to observe, measure and map out the variations in slope, aspect and
elevation (Appendix 1) and use the results to modify management practices to address
limitations to production.
3. Maps of soil erosion risk can be generated using LIDAR and the RUSLE (The Revised
Universal Soil Loss Equation)
Drainage Management Plans can use the results to design control measures to minimise the
impact of intensive rainfall events.
4. As LIDAR is essentially a survey tool, it can be used to generate accurate farm maps and then
integrate the data with other government digital datasets.
5. LIDAR helps the farmer to find the area that uses costly fertilizer. LIDAR can be used to
create elevation map of the farmland that can be converted to create slope and sunlight exposure
area map. Both the layer information can be used to create high, medium and low crop
production area. Extracted information will help farmer to save on the costly fertilizer.
v) GEOLOGICAL APPLICATIONS
1. WEATHERING
The ability to assess the impact of weathering on slope stability is important to prevent the
eventual failure on rock formations and mining excavations by determining the expected lifetime
of the slope. LIDAR sensors to examine materials enable the ability to capture weathering effects
that is otherwise difficult to determine visually.

20. 2. Material Classification
Relative reflectance enables discernment of material types from several scan positions. This
capability is demonstrated in Figure 8, which depicts a coal mine high wall scanned with a Riegl
VZ-400 terrestrial laser scanner from a range of 160 meters. The coal seam is visible due to the
high contrast between coal (dark blue and the rock layer above it (yellow), Figure 8. Since, coal
is back in the visible light spectrum it absorbs light, and a value represented by dark blue is
-20dB. Pfenningbauer et.al (2010), calculate 100% reflective target returns 0dB and a dark gray
diffuse target would result in -10dB, therefore it maybe concluded that a value of - 20dB for coal
fits this trend. Figure 4, is the colorized mesh of the same area, shows some black areas in the
data but, the boundaries are not clearly defined due to shadowing, a weakness with
photogrammetry, (Tonon 2006)
3 In geology the combination of LIDAR aircraft and GPS has evolved so much it is used finding
the fault and measuring the uplift. The combination of above technology was used to find the
Seattle fault in the Washington State, USA. NASA satellite called ICESAT that has LIDAR
sensor is used to monitor glaciers and perform coastal change analysis.

21. •
REFERENCES
>TRMM Data Downloads & Documentation
>HOME Page( in the internet TRMM Satellite)
>NASA HOMEPAGE
>SUA REMOTE SENSING COMPENDIUM- PROF D N Kimaro