10th Asian Regional Conference of IAEG (2015)

Analysis of the Sediment Production Characteristics by the Satellite Image- Case Study in Tanzania Hiroshi OGAWA(1), Hiroyuki KATHURO(1),Yoshihiro MOTOKI(1),Kiyotaka ONO(2)Kazuo ISONO(2), Masahiro YAMAGUCHI(3) , Eisuke TACHIBANA(3)(1) Nippon Koei Corporation, Japan, E-mail:a4257＠n-koei.co.jp(2) Remote Sensing Technology Center, Japan,(3) Japan International Cooperation Agency, Japan
Abstract
The satellite image analysis is thought to be the effective measure for thetopographical analysis in the area which cannot use the aerial photograph because ofvarious conditions. This poster session is the case study for the sediment production
analysis by satellite analysis and field investigation.
The Central Railway Line in the United Republic of Tanzania which maintransportation in Tanzania has been repeatedly damaged by floods and the sediment
discharge. Railway passes wide basins that belong to Great Rift Valley (eastern part). The
flood-prone area is in this basin. The target area (approximately 6600km2) is located in thisbasin. This area belongs to the savanna climate region which has the wet season and dryone. As for the geological feature, rock consists of Paleoproterozoic. Gabbro covers gneiss
and metamorphic rock as bedrock widely. After the 1970s, cultivation campaign waslaunched in Tanzania for the production of food. Therefore, the cultivated lands expandedon the upper pediments. The result was increased surface erosion in the area. Furthermore,overgrazing assisted this condition.
This time, we tried to use the satellite optical image (Rapid-Eye, SPOT) for theanalysis of the sediment production. The land cover could be classified into five colors
which show the difference of the sediment production. Furthermore, we made thetopographical and the slope classification maps using ALOS with DEM data. In addition,
we could confirm the river channel changes using the Synthetic Aperture Radar (SAR)
image. We could get the sediment producing characteristics effectively of the target area by
a series of satellite image analysis. We are confirmed that the satellite image analysis is theeffective on vast area without enough surface data.
Keywords: Satellite image analysis, Sediment production, Optical satellite image, SAR,
River channel changeUganda

1. Introduction
The Japan International Cooperation
Agency (JICA) has recognized theimportance of rehabilitating the Central
Railway Line based on the results of theJICA-funded “Comprehensive Transportand Trade System Development Master
Plan in Tanzania” (2011–14). The
Japanese Government subsequently
conducted “The Study on the Central
Corridor Railway Revitalization andEnergy Efficiency Project” (2013–14),
which identified that the flood prone area
between Kilosa and Gulwe could be thebiggest bottleneck of the entire Central
Railway Line, and thus recommended
that flood protection measures be acandidate for Japanese assistance.

Central Railway
TAZARA
Main StationRwanda

Station378 Mwanza

Kenya

438 Arusha

Burundi197 Shinyanga

Taveta130 Isaka
1251 Kigoma
963 Kaliua

210 Mpanda

115 Singida
840 Tabora

0 Tanga

Tanzania

0Study Area

DRC

Dar es Salaam

107 Kidatu

Tunduma

SCALE 1: 2000000
1000100Fig.1.1. Study Area and railway

1200300 Kilometers10th Asian Regional Conference of IAEG (2015)

2. Field characteristic
2.1. Topography
The watershed spreads out from the southeast to
the northwest direction. Mountains over 2,000 m
above sea level are distributed throughout thewatershed. However, aside from this, most of thiswatershed consists of vast plains.
According to Fig.2.3, Dodoma area is covered bya group of Cambisols. On the other hand, Mpwapwa,Kongwa, and the other areas are almost covered byLuvisols (as per the classification system of the Foodand Agriculture Organization, or FAO). Cambisols
and Luvisols are suitable soils for agriculture.
The topography of Tanzania is governed by theformation of the Rift Valley and the processes of theformation of topography. The formation of mountains
is closely associated with the activity of magma, aspreviously mentioned. Next, the process of
topographical change is associated with weatheringand erosion.

Fig.2.1. River System Map

Riverbed Profile
2000

1800

MdukweMkondoa

LumumaSikoko1600

Little Kinyasungwe

Great Kinyasungwe

MaswalaMuvumaElevation (m)Kidibo1400

Mangweta

Hodwiku

1200

Mzase
1000

800

600

400
0

50,000100,000

150,000

200,000

Distance (m)Fig.2.2. Riverbed Profile in the Target Area
The process of topographicalchange is divided into three stages.

i)Young age
The originaltopographyii)

Mature age
The mountain isformed, and erosion
is actively takingplace.

Main fieldiii) Old age
Peneplain spreads,
monadnocks areseen in places

Fig.2.3. Map of Soil Groups in the Wami/Ruvu Basin

2250,00010th Asian Regional Conference of IAEG (2015)

2.2 Geology
Tanzania is underlain mainly by Archaean andProterozoic rocks, mostly exhibiting ages of greaterthan two billion years (>2,000 Ma; 106 years). The
Archaean rocks date from 2,500 Ma to 2,800 Ma andform the Tanzania Craton, a component of theAfrican Plate, one of the world’s largest slabs ofcontinental crust.

The geological interpretation map is shown in
Fig2.4. According to this map, as for the watershedon the upstream side of Kilosa,Meta-igneous
andsedimentary(Pa),Meta-sediments,orthogneiss,granulite(Pu),
Migmatite, and granite (gs) are distributed.

M: Morogoro
K: Kilosa
G: Gulwe

Main field
G
M

K

Fig.2.4. Geological Interpretation Map of the Wami/Ruvu Watershed
Source: JICA Wami/Ruvu Basin Study Report 20133.

Study on Seasonal Changes of surfacelow
using Satellite Photographs
Tab.3.1. Characteristics of Different Sensors
3.1 Summary of the satellite analysis
SensorRadar
OpticalThe general characteristics ofAdvantage
It can observe both day and night andIt can acquire the images similar tothe satellite photographs are as
under bad weather conditions.
the views from an airplane. Therefore,
the results can be easily interpreted.
shown in Fig3.1. Tab.3.1. shows
Disadvantage The images are not easily interpreted.
It cannot observe under bad weather
advantage and disadvantage ofconditions, or at night, unless strong
the optical sensors and the radar.
light sources are given.
Image
Synthetic Aperture Radar (SAR)
has the advantage of being
unaffected by weather conditions.
Tab3.1. shows the differences intheir resulting images.
Ortho-rectified (foreshortening)
PALSAR imagery, 2006/12/30 (JST)Visible and infrared
remote sensing

Ortho-rectified AVNIR-2 imagery(true color), 2006/12/30 10:15 (JST)Microwave
remote sensing

Thermal infrared
remote sensing

SensorAntenna

Reflect sources

Sun light

TargetTargetRADAR

Reflectance of sun light
Reflectance from the light
Spectral radiation
Electromagnetic fieldvector

VioletVisibleInfrared

Thermal Infrared

Wave length
Microwave radar simulation

SensorCameraDetector
Microwave sensor

Fig.3.1.. Differences of Sensors

310th Asian Regional Conference of IAEG (2015)

3.2 Land Cover Classification by Satellite PhotoAnalysis
According to the site investigation, the sediment
discharge from the upstream areas of the Gulwe
Bridge to the downstream areas is judged as not
obvious, except for wash loads. Therefore, thesediment productivity between Kilosa and Gulwe isstudied further below:
Generally, the type of land cover will indicate thetendency of sediment discharge (or lack thereof). For
example, in forested areas, sediment does not flow outeasily, because of the high-vegetation cover.
As previously mentioned, the stage of topography
in this area is the old age. Because of this, slope
failures are generally not observed in this area. On theother hand, the cultivated land allows sediment toflow out easily, as the ground lacks vegetation and isexposed to the rainfall. The Mzase, Kidibo andMaswala areas, which have expanding cultivatedlands and overgrazing, exhibit this situation.
Fig.3.2. shows the optical image of the target area
produced by RapidEYE, which was photographed in2013. The optical image is the same tone as it isvisible to the human eye. According to Fig.3.2, a dark
tone corresponds to forest zones, a slightly less dark
tone exists around the forest, and a reddish-browntone corresponds to zones where the sedimentproductivity is high.

Spot (2007) Source: JICA Study Team

Rapid-EYE (2013)Source: JICA Study Team

Gulwe

Fig.3.3. Photos by Image Analysis

KideteFig.3.2. Optical Image(RapidEYE 2013)
Source: JICA Study Team

KilosaThe tone classification of the target area wasconducted based on the optical image. As a result, theimage was classified into five color tones: Green,Yellow Green, Orange, Light Blue and White(Fig.3.3.).

4The Spot image, whose resolution is
10 m, was photographed during 2007
(before the flood of December 2009).
The Rapid image, whose resolution is
5 m, was photographed between 2013
and 2014 (after the flood of December2011).
According to the site survey, areas
corresponding to the orange color zone
are often seen at the zone where gabbro
has been weathered, and areas
corresponding to the blue colored zone
are often seen in areas in which themetamorphic rocks and gneiss have been
weathered.
Considering the field reconnaissance,
the color tones of the image are classified
as shown in Tab.3.2. Fig.3.4. shows thecondition of the typical sites of eachcolor.

10th Asian Regional Conference of IAEG (2015)

Tab.3.2. Tone Classification of the Image

OrangeLight BlueWhite

3.3 Study of Sediment Yield by Satellite Photo
Analysis(1) Reclassification based on the Characteristics ofLand Cover
Orange color zones, in which the sedimentproductivity is high, are seen also in the forest zone,such as in the Mdkuwe watershed. However, theorange color of the forest zone is presumed to befundamentally different from the orange color ofcultivated land, such as the Maswala watershed. In
other words, the sediment productivity of the orange
color in the forest zone is judged to be lower than thatof the cultivated land. Similarly, the light blue zones
in the upstream of Maswala are assumed to bedifferent from the other sites, such as swamp zones.
Therefore, considering the characteristics of thesediment productivity based on the fieldreconnaissance, each color is classified as shown in
Tab.3.3.
Tab.3.3. Classification of Tributaries by Sediment
Productivity Source: JICA Study Team

Characteristics of Distribution Area
Dense Forest Area
Bush or Cultivated Land Area

ColorGreen
Yellow
Green

Mainly Weathered Lock Area of Mafic Igneous(main land use: Village, Cultivated Land)
Mainly Weathered Lock Area of Metamorphic
Rock and Gneiss (main land use: Village,Cultivated Land and Swamp)
Mainly Sediment Deposition Area (main landuse: Swamp, Cultivated Land)

Source: JICA Study Team

category
BranchClassification
GreenYellow Green
OrangeLight BlueWhiteFig.3.4. Condition of Typical Sites ofColored Areas

Sediment Productivity
HighLow
Mzase
Mangweta
LumumaMangweta
Kidib
MdukweMaswalaMkondoa
SikokoMuvuma(all watersheds have low productivity)

○
○
○
○

○
○
○
○

○

○
○
○

(2) Difference of the Productivity by Slope
On the riverbed, there is bed load transport (asGradientopposed to suspended load, transition).Fig.3.5.shows
The gradients of the slope and riverbed are
the distribution of the slopes less than three degrees.
important factors in sediment transportation ability.
According to this figure, the following points can be
Tab.3.4. shows the general sediment movement
made:pattern according to the gradients. According to thisi) Vast plains are distributed in the Msagali, infigure, the following things can be pointed out.
the upstream area of Gulwe.
There are almost no slope failures in mountains ofii) Slopes less than three degrees arethis target area. Therefore, the sediment production
distributed in the Mzase, Kidibo, andarea is judged to be the pediment area. The sediment
Maswala.
productivity of slopes of less than three degrees isiii) However, in the mountainous areas between
low. The movement of material on these gentle slopes
the Kilosa and Kidete, slopes less than three
is of a material which is less than that of sand. The
degrees are basically not present.
material in the sediment production zone of the target
area is the same.
Tab.3.4. Sediment Movement Form Productivity
Riverbed Gradientθ<1/300-1/200

θ<2-3deg (1/30-1/20)

θ<5-10deg (1/7-1/6)

15deg(1/4)<=θ

Occurrence area

Plain / SwampPediment

Foot of Mountain

Mountain Slope

Erosion Form

(River Bank/ RiverbedErosion)

Sheet Erosion(River Bank/ RiverbedErosion)

Sheet Erosion(River Bank/ RiverbedErosion)

Landslide /Slope Failure

Zone ofFlow /Deposition

Flow / Deposition Zone

Flow / Deposition Zone

Flow / Deposition Zone

Flow Zone

Flow Formin the River

Bed Load Transport(Bed Load / Suspended
Load /Wash Load)

Bed Load Transport(Bed Load / Suspended
Load /Wash Load)

Riverbed Material*(Except Wash Load)

Sand, Granule, (Pebble)(Sorting Process)Silt, Sand, Granule, Pebble(Sorting Process)*Refer to Riverbed Material Aanlysis

5Debris FlowFine material, Sand,Gravel, Cobble, (Boulder)(Sorting Process)Fine material, Sand, Gravel,Cobble, Boulder

10th Asian Regional Conference of IAEG (2015).
The result of image analysis by RapidEYE is total
sediment yield from the tributaries to the main river isabout 680,000 m3, and about 910,000 m3 with theaddition of the remaining watershed area.
Additionally, the sediment discharge can be divided
into upstream downstream areas, with Kidete as aboundary, considering the riverbed slope.
We guess the high value for specific sediment
discharge (m3/km2/year) in the upstream incomparison with the downstream.
4.

Conclusion and presence theme
This presentation is a interim report ofcountermeasure project. In the case of investigation
area is wide, it’s too difficult for analysis in thelimited term of project. This presentation area has
different colors by geological basement. In such area,
we can classify subarea by optics image analysis. The
calculation of Sediment Yield will have muchimproved. Now, we try to analyze correct volume
more proper than this presentation. In the dry land,satellite analysis is effective on Quantitativeinterpretationofthesedimentproduction
characteristics.

θ≦3°

Fig.3.5. Distribution of Slopes less thanThree Degrees (3°)(3) Try to calculate of Sediment Yield
Calculation of the sediment yield is calculated asfollows:i)

The sediment yield is calculated based on
the existing document about dam deposition(refer to Tab3.5.).
ii) However, annual erosion depth should beconsidered as characteristic of eachwatershed.
iii) The value based on the data of dam
deposition is average. Practically, each value
has a wide range, so erosion depth should beconsidered at about this range.
This erosion depth is included in river erosion.
Tab.3.5. Erosion Depth based on theExisting Document

Tab.3.6. Annual Erosion Depth6