Hello everyone and welcome to the eleventh lecture of this course which is Introduction
to Remote sensing In this particular discussion we are going to have discussion on image interpretation
and especially we would like to focus on geological land forms rock types and structures Because
think that once the data has being acquired by a satellite and sensor than it has to be
use for some purposes One example I am going to show here how various land forms which
are present on the surface of the earth then we identify and discern very easily using
satellite image
Remember that when we were discussing the advantages of a remote sensing data one of
the example it is said about the synoptic view Especially for geological mapping or
things related to the earth sciences When we go on the ground we see a very small area
and we are not vantage point That means we see very small area just standing on the ground
but when we use the satellite data then we are having because of this remote sensing
technology we are having a synoptic view and that providing a data or information about
a large area Information like in our case suppose if I am interested to study the lands
forms then large numbers of land forms are available
This example is of course is a mosaic in the background it is digital illumination model
is there top of it the land set ETM plus images have been draped here and you are seeing a
complete seamless mosaic part of India Especially I would like to focus on major land forms
which you can identify where easily or anyone who doesn’t have even the background of
remote sensing or background of geology or sciences can still identify and because of
this 3D prospective view of available through this tele-elevation model or even with single
satellite image even the depth perception comes because of the presence of the shadow
and orientation of shadow
With the reference related to the viewer we get the depth perception So here we can identify
the mountain chain which is the Himalayan Mountain very easily and if we are having
some information some further knowledge we can say these are the highest part of Himalayan
Mountain system which are snow and ice covered so we are having snow as well as glaciers
part above that and this is the Tibetans plateau is there and on that we can see lot of lakes
including our Mansarovar lake as well
Then we come to the south of this Himalayan we can identify other large land forms like
for example the river system the Ganga’s river is there the Yamuna river is there the
Brahmaputra river which basically originates from Tibet it is called Tsangpo in Tibet and
enters in India through Assam states largely and it goes in the bay of Bengal And even
because of digital elevation method in the background so even you have seen some information
about the land forms which are present in the sea itself
And specially this north 90 degree range as well it become the (ah) plateau part of India
then we see the different Vindhya ranges and also Aravali’s are there and Vindhya’s
are there Satpura are there Vindhyans are there Satpura are there all kind of mountain
system river valleys everything becomes easily identified
This image is from Google earth where products have been generated we can zoom it and identify
objects including the desert part of our Indian desert as well as some part of Pakistan and
with agriculture land you can also identify part of Punjab and Haryana and Western UP
which you can see some part including Pakistan On the eastern side what we see different
geological structures We will see the zoom part of it and how the arrangements of different
land forms which are projects
This is because remote sensing is providing data in multispectral so we see thing in color
Remote sensing is also providing data so we can create digital elevation models so we
can get the depth perception and also remote sensing is providing data to large area after
doing image processing and making mosaic we can see large numbers of various types of
land forms identify very easily and that things So like mountains plane’s we can identify
valleys we can identify lakes we can identify desert we can identify glaciers I have already
mentioned this part we can identify N’s one This is not exhaustible this identification
of things keep going
The only problem with the remote sensing of earth is that because earth is having atmosphere
sometimes we are having clouds and because of this over cast we do not get a high quality
satellite image if we compare the satellite image of Mars where we don’t have much atmosphere
very thing atmosphere and therefore satellite images are very clear you can identify each
and every type almost every type of landforms on surface of Mars like using images of Mangalyan
The zoom part is like for north east India as you can see there is series of these antiform
and synform plunging folds are there and same time you can see Sundarban area the Brahmaputra
is coming You can see the concentration of the sediment and that extend and so and so
for You can identify as many as landform which are present in the particular part of the
earth very easily
Like for example I will give example of north east India there is series of Host and grievance
and plunging folds are present here this is radar image this is image from Landsar ETM
Mosaic and if we combine this two our interpretation and our analysis will improve further So we
will be able to identify more type of land forms but if we use in a separate form then
our limitation become
And finally you can reconstruct some models shown the lines which are nothing but the
antique lines which are a symmetric and are shown here and we can decent and we can create
the model for further understand Because your purpose in not just only understanding but
further exploration maybe exploration for water maybe exploration for wild and gas and
this part is having quite of these resources So that is why the analysis interpretation
of different landforms becomes very very important
To identify images reconstruct model and try to understand what is beneath the surface
though most of the satellite data accept radar data in case of desert area might penetrate
may penetrate up to few meters in a dried sand but otherwise remote sensing provide
on the sufficient information Information about the surface of the earth whatever the
feature are present whether geological structures land forms vegetations and water bodies glaciers
snow peaks and covered peaks and so on so for this
But using the help of this earth signs of geology you can create a model which can give
us depth information as well what is beneath that and then this things finally this things
can be confirmed by using geophysical method which can give you surface information So
what is happening nowadays any area which have to be explode for anything for mineral
for natural resources even for natural disaster even for oil or gas whatever first people
resort of satellite images and they try to extract as much as possible the information
from this satellite images
So remember that statement a picture a normal picture tells thousand words whereas a satellite
image tells 10 thousand words So that is the advantage that we not only we identify the
landforms not only we identify different features or objects present on the earth but we try
to infer the information We look that how this landform has formed what would be the
conditions of the surface and if I am looking for ground water then there I can find the
ground water and if I am looking for oil which is in a very special circumstances I can find
in special geological arrangement then still I can infer that one Nowadays for all kind
of surveys or investigation which involve the land surface of the earth first people
will resort satellite images including natural disaster conditions
Some examples I am showing here that how asymmetric anticlines antiforms can be identified and
then infer and then we can estimate how things are in the depth So syncline are looking synforms
are looking there seems through the satellite series of lines but they are basically part
of synform whether it is (systa) symmetrical or asymmetrical we can still see we can get
information very easily through satellite images and we can reconstruct some models
So in a 2D surface this is how it looks but we can construct the 2D surface and see that
this construction has been done using satellite image and in the background we having digital
elevation model and that model too has been derived from satellite data either using your
stereo pair data or using SAR interoferomatric technique So there are several digital elevation
models which have been derived from satellite ( ) based on remote sensing either stereo
or SAR interoferomatric all are available free of cost for that part of the world
So we can infer we can make our understanding about different landforms different features
which are present on the earth implying including in the background the modern digital elevation
model as shown in this example So on surface you see features like this in the surface
you see features something like this you can create 3D surface or prospective using digital
elevation model and draping over satellite image like this and then finally you can make
a model to make full understanding not only on the surface but subsurface conditions as
well
So that makes exploration of oil gas petroleum anything is much easier and reliable This
started with a simply surface information then got digital elevation model and then
some understanding about some geological area and then finally reconstruction of a model
So this complete detail about things Now we want further detail more confirmation more
reliable information than geophysical and experiments can be done geophysical prospective
can be done geophysical techniques can be done when we apply to make things more reliable
Similarly here what we are seen that how a river crossed all these geological features
specially these plunging anticline and so on So we can based on this we also infer the
age of the fluvial system compared to the geological structure This is cut across that
means these structure was later formed river was there and we can infer so many other
So first data acquisition from satellite data then come analysis interpretation inferences
and basically the replications So this how the sequence goes So just images are not sufficient
these has to be analyze this has to be interpritate And based on the interpretation along with
some other data may you know GIF forms you put that along with other data sense and you
try to infer the structure the self surfacing information the surface information and so
on for so
So this is how the geological landforms can be indentified again examples of part of Pakistan
because we have less vegetation and therefore all these geological landforms are very very
clearly visible Gas reservoirs are distributed in antiforms or anticline a giant gas field
wires are covered in this northern part of the structure here in this part of the structure
So the initial investigation nowadays as I have mentioned always now is starting with
the satellite data so if one is looking for oil gas or any other thing it is the best
way to starting this thing
Similarly this folds could traps for natural gas and oil that’s why they are important
this landforms the geological landforms which we are seeing there interpretation and there
understanding about such surface conditions can give clues about availability of natural
resources
Again this is about the Zagros mountain fold belt of (satellite) Iran where you can see
that there are many several plunging anticline and syncline are there and these area are
also having the potential of providing oil and gas
And same with this Zagros field another high resolution images 3D prospective is also there
so you can get better idea about different landforms that are present Maybe some idea
about the sub surface conditions and may be some idea about the available natural resources
of surface condition
And like dome structure you get dome structures are also useful for certain kind of resources
Similarly like this is volcano and this is volcanic neck where you can see easily and
then the lava which has come and important thing to note here this is for composite and
see the growth of vegetation the lava in few years time get converted into very highly
fertile soil and therefore the vegetation you can see Because false color composite
as discussed earlier the infra red channel is assign red color and in infrared channel
then vegetation is having highest reflectance and therefore in false color composite or
standard color false color composite the FCC vegetation will appear green it will be high
dense or healthy vegetation will appear in false color composite in red and that is why
you are seeing
So in infrared channel it is having highest reflectance but in false color composite it
will appear red So this how the interpretation has to be done That you are seeing the vegetation
in red color which is very healthy and fertile land this what so if there is water available
soil is very good and people will go around and do agriculture there
So many volcanoes where the water is available the land becomes very fertile Though if they
are dormant or extent volcanoes it is very good and one of the example from India is
the Deccan tribe it is the large basaltic tariff which covers large part of Maharashtra
and Madhya Pradesh the soil is again black cotton soil again very fertile land
And this is desert landforms which you are seeing sundews of different types of dews
you are seeing and different dews of Namibia Africa say longitudinal beans which are you
know longer lines which you are seeing here sand dunes parallel to the area of wind out
directions even identify based on this orientation landforms the prevalent wind direction So
one is the image another one is the analysis interpretation and then the inferences Inference
here you can make what is prevalent to the direction as well
This is the desert part the image is from Google earth which is having various land
set images on the background you are having digital elevation model as you can see this
Haryana Punjab is full of this true color image therefore you are seeing vegetation
in green then you are having desert part hardly there is any vegetation in the part of Rajasthan
up to the Indo Pakistan border On the other side there is some desert part there but this
Indus river valley you are having good vegetation they are similar to what we are having in
Punjab So desert land forms can also be identified and also you are seeing some part of this
Kutch
This is ground of feature of ground part of sand dunes how they look on the ground and
on satellite images And the images are taken from the top so they look different
This Great Dyke of Zimbabwe it is very long Dyke approximately 2.46 billion approximate
billion years value will matter deposits So if you are having satellite image if that
area is not explored one can go through the data and can identify the data going the field
take the sample and analyze the data and one may find if value will matter data Here it
has been found which is having platinum and chromium and say all over the Great Dyke area
This is a glacier land form Malaspina Glacier Alaska and this is very unique feature on
the surface of the earth where glacier not as a kind of value glacier it is a kind of
alluvial fan kind of glacier in a circular body There are some value kind of glaciers
are also seen So not only light images you can identify landforms of deserts area or
mountain but you can also identify glacier landforms fluvial landforms and several other
types of landforms are there This is very famous glacier of Alaska Malaspina In glacier
you can also see false color composite you can also see the lower part the growth of
vegetation forest and then water bodies glaciated lakes and other features can also be seen
and sea part is also there interference between land sea can also be identified
This is a 3D prospective view of the glacier Malaspina Alaska glacier valley glacier you
can identify But this is a unique feature which make a fan shape kind of glacier because
this like alluvial fan but a glacier because suddenly it is leaving the mountains coming
in the plain area but still it is very cold so the ice is there snow is there therefore
it looks like a fan but it is a glacier not typical value glacier as shown here
I have been mentioning that remote sensing data especially nowadays is available from
1972 Landsat MSS till 2016 complete time series is available from different censors on board
of different satellite All these archives are now almost available free of cost on net
and therefore time series analysis can be done chain detection analysis can be done
and this example is on that
And a very famous Gangotri glacier where our river Ganges start it originates as you can
see this not based on satellite data information based on some topographic maps and some other
ground information that the glacier the snout of the glacier the beginning of the glacier
the mouth of the glacier was here in 1780 but once we entered here and now this is the
era of satellite data and what we see that it has retreated to this extend and you can
also see the scale
So roughly about three or four kilometers up it has gone it has retreated and it is
the situation in 2001 this information in 2001 has of course come through satellite
information If we get a another one say latest 2016 this retreat might be observed here So
if we get the successive images at time series data first of all what we can see how a landform
is changing maybe a glaciated landform maybe a desert landform of fluvial landform doesn’t
matter so one thing how things have been changed this thing can be done through the times series
or chain detection analysis and what is the speed the velocity of and how quickly things
have been changing
And it is not necessary that things will change as they have been changing like between 1780
to 1935 The change may be faster or lower depending of the metrological conditions or
weather conditions if we talk only about the glaciers or landforms but there are changes
which are sudden like related with earthquake There are changes which occur within few seconds
these changes too can be detected by using employing a pre earthquake image and post
earthquake image
Remember when I was discussing the advantages of remote sensing data not only it provides
the synoptic view not only it provides the digital data not only it provides the regular
basis but it also provides the unbiased basis so here the manual input or human input might
be biased but based on the satellite data this is more reliable information or inputs
which are coming or which are making the understanding about this information about the glaciers
Maybe a fluvial system how a river are shifting a particular river at a particular section
how it is shifting with time and how this land forms are changing What is the speed
of changing one So by looking the past and the changes and the way things have changes
we can also think about the project we can project to the future So if you say this Gangotri
glacier the change continues and if we know that how things have changed in past we can
also project in future this is now might appear somewhere here
That prediction and that modeling can also be done after learning through time series
data about say any landform or say any changing feature on the surface of the earth So that
is the advantage that the desert are increasing or reducing a glacier or glaciated part of
Himalaya is increasing number of glaciers are increasing or reducing or fluvial system
more flooding are occurring
Everything can be assessed through the time series data their speed can also be assessed
that how the things are changing And then we can do some modeling we can predict that
how in near future things will change So based on this unreliable synoptic digital data and
not many such studies can be done
And another example of this you sees this fluvial landform Fluvial landforms are again
very important specially from sediment transport point of view or even normal transport point
of view from ground water recharge point of view and also others like vegetations growth
algae growth and so many other things are there because this keeps changing So another
natural disaster that is flooding so from flooding point of view the study of such fluvial
land forms are important If we are having time series data as of now today then we have
45 years of data we can see how things have been changed in past specially with the fluvial
system
Similarly I am now giving example of our own Indian system this is the Ganges this is the
Yamuna this is Allahabad where there is Sangam and see these palaeo channels there remaining
of extent courses of rivers of Yamuna and Ganges so that means what they are telling
that few years back Yamuna was flowing somewhere here few years back Ganga was flowing here
It is shifting how much it will shift in future or whether it will come back
This can be analyzed it is being analyzed by employing time series remote sensing data
not only for Ganga Yamuna Brahmaputra almost all rivers which are having migrating characteristics
and they are changing fluvial landforms can be studied and even if we are having much
older data we can tell that in which year the river Yamuna was flowing in this part
And these are all have different name palaeo channels oxford lake so these are the palaeo
channels Yamuna this is Oxford lake that is water after sometime it will become dry and
so on so forth This fluvial system will keep changing the study is very important that
we can assess the flood potential in this area
This is the Brahmaputra this is braided channel of Brahmaputra and several other streams and
rivers are also meeting in Brahmaputra and Brahmaputra almost every year is bringing
flood high sediments because of high erosion in Himalaya and high concentration of sediments
are coming and the channels are braided there is no single channel and it is in a wide valley
creates havoc every year due to flooding Palaeo channels are there people have studied that
how Brahmaputra has moved from one place to another and even can predict how in future
things will move in a fluvial system So that is the advantage of having remote sensing
data if you go there stand on a point you don’t see that such a synoptic point view
of Brahmaputra you thinking will be very narrow in that sense
Another very good fluvial feature which is called the sorrow of Bihar which is a Kosi
river you would be surprise to know that about 250 years ago this Kosi river was flowing
in this part that means on the eastern side and in this 250 years later and now it is
flowing here so this has made a world largest alluvial fan it has been moving and moving
but it has a limit after it cannot go in west part So one day it will come start coming
back again and year almost every year it is bringing flood and it is creating lot of problems
in Bihar Another thing we have study that using satellite data we can study that how
it has migrated What was the speed and what it start coming back and these courses are
changing or not
All these things can be studied through satellite images so that’s the advantage of having
remote sensing specially I have focused on geological land form feature that we see very
quickly on satellite images specially like product of Google Earth or some other and
then we start interpretation and of course we can make some inferences if we are having
old data arc eye or time series data how things have been changed in past and also we can
predict about future we can model the things that how thing will change in future So thank
you very much