Application of ALOS and Other Satellite Data to Study

Application of ALOS and Other Satellite Data to Study Landscape Changes

Related to Petroleum Fields and Their Exploitation at the Timan-Pechorian

petroleum province JAXA PI 200

Irina Smirnova (1)

, Alexandra Rusanova (1)

(1) Institute of Remote Sensing Methods for Geology (VNIIKAM), Pulkovskoe shosse, 82, St.-Petersburg,

Russia, Phone: (7) 812 3637192, Fax: (7) 812 3637196, E-mail: [email protected]

Abstract

The final report on the project titled “Application of

ALOS Data to Study Landscape Changes Related to

Petroleum Fields and Their Exploitation at the North

West of Russia” (JAXA PI 200) is presented.

The objective of research was the study of landscape

changes above petroleum fields caused by natural factors

(neotectonic movements, subsidence, fracturing of rocks,

cryogenic processes, global warming and others), as well

as human activity, connected with petroleum fields

exploration and exploitation (disturbance and pollution

of natural environment due to drilling, accidents on wells,

oil pipelines, subsidence of the surface and others), using

ALOS and other satellite data. Some test sites located in

the northern part of the Timan-Pechorian petroleum

province were chosen for fulfilment of the project.

Satellite data acquired in different years (1985 - 2001) by

various sensors are collected and processed for these

areas. ALOS data (AVNIR2, PRISM, PALSAR),

acquired in 2006-2008 has been used to study geological

processes and landscape changes. Processing and

comparison of multitemporal satellite data were realized

on the basis of GIS software (ERDAS Imagine, ENVI

module SARScape, Map Info). Detection of changes was

made in automatic mode using the methods of

differencing, color compositing and other as well as by

visual interactive analysis. The advantage of ALOS

AVNIR, PRISM, and PALSAR data for study of

cryogenic processes, geological structures and landscape

changes has shown.

Keywords: ALOS, landscape changes, cryogenic

processes, geological structure, petroleum fields.

1. INTRODUCTION

The main objective of our research was the study of

landscape changes above petroleum fields caused by

natural factors as well as human activity using ALOS

(AVNIR, PRISM, PALSAR) and other satellite data. The

target objectives were:

to estimate ALOS data for study of geological

structure and landscape changes and compare them

with other satellite data;

to identify the effective tool for monitoring of

different landscape changes using multisensor,

multitemporal satellite data by employing different

change detection techniques;

to detect the changes caused by natural factors such

as cryogenic processes development (preferably

changes in thermokarst lakes and shore line) and

changes caused by human activity (mechanical

disturbance of a surface and pollution of lakes and

rivers connected to construction of oil pipelines and

oil terminal, drilling of wells, building of roads and

other industrial objects,) using ALOS and other

multitemporal satellite data on the test sites located

in the northern part of Timan-Pechorian petroleum

province;

to estimate level of suspended sediments

concentration in polluted lakes;

to estimate the expression of geological structures

and faults including structures controlled petroleum

traps distribution on ALOS and other satellite data .

2. GEOLOGICAL SETUP OF THE AREA

The study area is situated in the northern part of Timan-

Pechorian petroleum province (North-West of Russia) in

subarctic region (tundra and forest tundra zone). It

characterized by extreme climatic conditions and

underlined continuous permafrost with thickness ranging

from 50 to more than 200 meters that has caused wide

development of cryogenic processes such as thermokarst,

thermoerosion, frost swelling of hillocks, polygonal

grounds, slope processes and others. Quaternary deposits

are widespread in this area and consist of moraines,

glaciofluvial, fluvial, glaciolacustrine and lacustrine

sediments. Quaternary deposits sometimes mask surface

expression of deep geological structures, but distribution

of the different forms of glacial relief which clearly

distinguished on satellite images (lakes, sand hills,

moraine ridges, in particular edge of glacial deposits etc.)

as well as swamps, erosion pattern and linear landscape

elements are connected with distribution of geological

petroleum structures. Global warming can cause melting

This document is provided by JAXA.

mailto:[email protected]

of permafrost and the changes in cryogenic processes

development, which can complicate the exploitation of

petroleum fields and lead to accidents on oil and gas

pipeline. The area of the study of landscape changes and

geological processes using ALOS AVNIR and PALSAR

data has shown on Fig. 1. The results of satellite image

processing are represented for 6 test areas (Fig. 1).

Fig. 1 Test areas location

Test areas 1 and 2 are situated in the Varandey region.

Active industrial development of the territory is

conducted during more than 70 years. Recently the

industrial development of the area was essentially made

active in connection with construction of the oil terminal

"Varandey", being basic object for export of petroleum

extracted in the Timan-Pechorian petroleum province,

and new oil pipeline “Southern Khilchuou – Varandei”

coming into service in 2008. New engineering objects of

various assignments are erected: industrial,

infrastructural, linear, therefore is very important the

development of questions connected to probable negative

changes of conditions of the area. The problems of

rational development of this territory essentially are

complicated by presence of permafrost, sensitive to

external influences, first of all to global or regional

climatic changes and also to local changes connected to

man-made activity: exploitation of petroleum fields and

construction of engineering objects. Test area 1 includes

coastal zone of Barents Sea and test area 2 includes

Varandey petroleum field.

Test areas 3, 4, 5, 6 are located in the Usinsk region

includes prospective petroleum-bearing structures and

intensive exploited petroleum fields Usinskoe, Vozeiskoe

and others. The network of seismic profiles, wells, oil

and gas pipelines, roads, building and other infrastructure

are clearly distinguished on satellite images. Exploitation

of petroleum fields disturbs natural environment and

cause strengthening of intensity of cryogenic processes.

3. DATA USED

The following multispectral data was analyzed and

processed for change detection and study of cryogenic

geological processes:

─ ALOS AVNIR2 Path Num. 249, Frame Num. 2200,

2210, 2220, 2230, 2240, 2250, 2260, acquired

2006/10/09.

─ ALOS AVNIR2 Path Num. 249 Frame Num. 2190,

2200 acquired 2007/07/12

─ ALOS AVNIR2 Path Num. 245 Frame Num. 2200,

2210, 2220, 2230, 2240, 2250 (2007/06/20); Path Num.

254 Frame Num. 2190, 2200, 2210, 2220, 2230, 2240

(2007/07/05); Path Num. 257 Frame Num. 2200, 2210,

2220, 2230, 2240 (2007/07/10);

─ PRISM Path Num. 241 Frame Num. 2200, 2195, 2205,

2250, 2255, 2260 (2006/07/11),

For comparison with ALOS AVNIR2 data the following

images were used:

─ LANDSAT 4 TM acquired in August 03, 1988 and in

June 25, 1988;

─ LANDSAT 7 ETM+ acquired in July 21, 2000;

─ KFA 1000 acquired in June, 1985.

The following radar data was used for study of

geological structures and landscape:

─ ALOS PALSAR acquired in June, July and August of

2006 and 2007 (wavelength 23,5 cm - L band, FBS and

PLR modes);

─ JERS-1 SAR acquired in December of 1996 and in

August of 1997 (wavelength 23,5 cm - L band, HH

polarization);

─ RADARSAT-1 acquired in February of 2001

(wavelength 5,6 cm - C band, HH polarization, standard

beam 3).

4. METHODOLOGY

Computer processing and analysis of the data were

realized on the basis of GIS software (ERDAS Imagine,

ENVI module SARscape, Map Info) and includes:

─ creation of databases of satellite images obtained in

different years;

─ preliminary processing of satellite images (image to

image rectification, relative calibration of multitemporal

images; a speckle filtering of SAR images using Frost

filter);

─ interactive interpretation of different satellite images

with compilation of vector layers,

─ processing of multitemporal images for change

detection in automatic mode (color compositing, image

differencing, Principal Components Analysis), as well as

using visual interactive analysis;

─ creation of spectral curves of test objects using

different bands of multitemporal satellite images;

─ different methods of classification;

─ lineament analysis (extraction of lineament in

automatic mode, analysis of lineament density).

The choice of processing methods depends on research

objectives and used satellite data (radar or multispectral).

When using multitemporal satellite images for changes

detection the images should be radiometrically calibrated

in order to reduce the differences of acquisition terms

that may cause the appearance of false changes. One of


the most effective methods for this purpose is relative

radiometric calibration, i.e. that brightness values of one

image are corrected to match these of other one (serving

as a reference image). In our study ALOS AVNIR 2

image (2007) was a reference image. LANDSAT 4 TM

(1988) and 7 ETM+ (2000) were corrected in relation to

ALOS AVNIR 2 image. For radiometric calibration

unchanged reference sites having identical brightness on

all three satellite images (clear lakes with low value of

brightness, and the sand grounds with high value of

brightness) were chosen. The calibration of one image in

relation to another is made using Eq. 1.

L' = a *L + b (1)

Where L' – value of brightness of calibrated image,

L - value of brightness of initial image,

a (gains), b (offset) - coefficients of the equation.

The coefficients a and b, used in Eq. 1, are calculated

using the system of two linear equations Eqs. 2, 3

Y1 = b+aX1 (2)

Y2 = b+aX2 (3)

Where X1, X2 – values of brightness within the limits of

reference sites (sand – clear lakes) of the image which is

corrected; Y1, Y2 – values of brightness within the limits

of reference sites (sand – clear lakes) of the image to

which calibration is made.

Most simple approach for change detection in automatic

mode is the generation of RGB color composite from

pair of images (bands with equal wavelength) acquired in

different years. If color composite images (RGB) is

generated from pair of multitemporal images where R -

the image acquired later, and G and B - the image

acquired earlier, objects with increased brightness, will

have red color on the resultant image, for example, sites

of the coast accumulation and dried up lakes, polluted

lakes, roads, areas of drilling and new engineering

objects. Sites with decreased brightness that can be

connected with increase in soil moisture, a deepening of

lakes, occurrence of new lakes, sites of coast abrasion,

etc. will have blue color.

To create difference image the subtraction of earlier

image from later is carried out. On the resultant image

objects which brightness has increased will have light

color, and dark – objects which brightness has decreased.

Unchanged objects will have gray color. To receive more

precise picture of changes, brighter objects are

represented by red color, and objects which brightness

has decreased are blue.

For interpretation of PALSAR polarimetric data RGB

composition and method of Pauli de composition [1]

were used.

4. RESULTS AND DISCUSSION

4.1. Results of detection of the changes caused by

cryogenic processes.

The analysis of ALOS AVNIR 2 data acquired in July of

2007 in the northern part of Timan-Pechorian petroleum

province confirms the tendency of thermokarst lakes

drainage that has shown in our previous works which

were devoted to comparison of LANDSAT imagery

obtained in different years (in July-August of 1986-1988

and in July-August of 2000) [2], and these LANDSAT

images with ALOS AVNIR 2 data acquired in October

of 2006 [3]. Dried thermokarst lakes are situated mainly

within the limits of low seaside plains, lacustrine and

marsh landscapes composed mainly peat and sandy

sediments, and also within the large river valleys. The

increase of lake areas or formation of new lakes

practically does not occur (except the lakes, which were

formed due to man-made activity). It testifies that

processes of global warming have not find yet reflection

in changes of thermokarst lakes. In fact when frozen

ground intensively thaws, surface subsidence and

formation of new lakes should occur. On ALOS

AVNIR2 data we can observe frost swelling of hillocks

on the bottom of dried thermokarst lakes that testifies

that the ground frosting is increased (Fig. 2).

Fig. 2 ALOS AVNIR2 RGB 432 (10.09.2006). Frost

swelling of hillocks on the bottom of dried lakes

The advantage of ALOS AVNIR2 data for study of

cryogenic processes is their high spatial resolution that

allows to detect microforms of relief caused by ground

frosting, as well as microforms of relief that indicate

petroleum structures, small lakes which can caused by

permafrost melting, changes in character of vegetation

and other features, which poorly distinguished on

LANDSAT images with spatial resolution 30 meters.

4.2. Results of detection of the changes in a coastal

zone and thermokarst lakes in Varandey region.

On the test area 1 ALOS AVNIR 2 (21/07/2007) and

LANDSAT 4 ТМ (03/08/1988) have been processed for

change detection using two techniques: color

compositing and image differencing. Results of

processing on test area 1 (color composite image RGB,

where R – ALOS AVNIR2 and G, B – LANDSAT 4

ТМ) have allowed to reveal changes in a coastal zone of

sea within accumulative terrace: sites of shore abrasion

(blue color) and sites of coast accumulation, including

new spit formation, increase of the area of sand deflation

and the area of new constructions (red color).


Fig. 3 Test area 1. Color composite image. RGB: R – ALOS AVNIR2 (3 band), 2007; G and B – Landsat 4

TM (3 band), 1988. The figures with arrows specify the areas of changed objects of coastal zone. 1-10 –

numbers of changed thermokarst lakes

Fig. 4. Test area 1. Result of change classification based on difference ALOS AVNIR2 (3 band), 2007 and

Landsat 4 TM (3 band), 1988 (red – sites with increased brightness value; blue – sites with decreased

brightness value)


The area of these changed sites is calculated (Fig. 3).

Linear measurements in a coastal zone have shown, that

since 1988 up to 2007 displacement of a coastal line due

to abrasion near settlement Varandey reached 20-30 m

and 30-90 m to the east and to the west from Varandey

that corresponds to field measurements [4]. Abrasion

has been increased due to man-made activity, but near

settlement Varandey speed of abrasion was slowed

down due to construction for coast protection.

Mechanical disturbance of the surface and new

constructions also have a red color on RGB images. For

example at construction of coastal oil reservoirs the area

of disturbance has reached 1 km2 (Fig. 3).

Within the limits of lacustrine and marsh plane

significant changes of thermokarst lakes are detected

(Fig. 3). The lake 1 has dried up, lakes 3, 4, 5 (dark red

color) became shallower due to natural processes.

Activisation of thermokarst processes due to man-made

activity (blue color) is reflected in increase of surface

moisture (shores of lake 5), increase of lakes deep (lake

2). Variations of red color from dark red up to bright red

reflect a degree of lakes pollution: minimal (lake 7),

average (lake 6) and maximal (lakes 8, 9, 10) (Fig. 3).

The changes detected on difference image (Fig. 4)

obtained using image differencing method on the basis

of the same images that RGB (Fig. 3) are similar. The

classification of changes was made and brighter objects

are represented by red color, and objects which

brightness has decreased are blue (Fig. 3). But on this

image it is impossible to distinguish the dried up lakes

and polluted lakes as well as lakes, which depth (or

pollution) has changed slightly (dark red color on RGB).

On the test area 2 the satellite images received in three

dates were analyzed: LANDSAT 4 ТМ (03/08/1988),

LANDSAT 7 ЕТМ + (21/07/2000) and ALOS

AVNIR 2 (05/07/2007) (Fig. 5). The analysis of spectral

characteristics using Bands 1, 2, 3, 4 of these images

was spent to distinguish the polluted lakes from dried up

thermokarst lakes and to estimate level of suspended

sediments concentration in polluted lakes. Test objects

where spectral characteristics were measured are shown

on Figure 5.

Test objects 1-4 are lakes polluted up to 2007, which

was clear in 1988 and 2000, test object 5 is shallow lake

with insignificant increase of suspended sediments

concentration, test objects 6-8 are dried up lakes and

test object 9 is lake with salt water. The spectral curves

have been made for these objects (Fig. 6). The analysis

of the curves has shown that unchanged thermokarst

lakes have identical characteristics of spectral brightness

in images of all years, averaging in the first band - 70, in

the second - 40, in the third - 25, in the fourth - 8 units.

In the polluted lakes (test objects 1-4 –

A

B

C

Fig. 5 Test area 2. A – Landsat 4 RGB 421

(03.08.1988); B – Landsat 7 RGB 421

(21.07.2000); C – ALOS AVNIR2 RGB 421

(12.07.2007); red digits – test objects location and

their number

Fig. 6 a, b, c, d) spectral brightness on ALOS AVNIR2

(2007) in the first band increases up to 80-102, in the

second - till 51-96, in the third - till 45-90, in the fourth -

till 15-30 units, depending on a degree of pollution. Test

object 1 has minimal pollution (Fig.6 a), test object 3 –

maximal (Fig. 6 c). Thus a degree of lake pollution as a

result of man-made activity has increased approximately

in 2,5 - 3,5 times. The spectral curve of shallow lake

where suspended sediments concentration was increased

insignificantly due to natural processes is presented on

Figure 6 e (test object 5) for comparison.


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Spectral bands Spectral bands

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Fig. 6 Test area 2. Comparison of spectral curves using LANDSAT 4, 1988 (red), LANDSAT 7, 2000 (blue) and

ALOS AVNIR2, 2007 (green) for different test objects: a, b, c d – objects 1-4; e – object 5; f – object 6;

g – object 8; h – object 9


At dried up from 1988 till 2000 thermokarst lake (Fig. 6 f)

spectral brightness in 1, 2, 3 bands is increased

insignificantly but in 4 band it increases from 8 till 40-50

units and character of spectral curve is changed. This

spectral curve become similar to spectral curve of old

dried up lake, which was dry in all years (Fig. 6 g).

The results of the works in the Varandey region in more

detail were discussed in [5].

4.3. Results of detection of the changes caused by man-

made activity in the Usinsk region

Comparison of Japanese ALOS AVNIR2 (October 2006)

and Russian photographical false color image KFA 1000

with wavelength 560 - 810 nm (June 1985), which have

almost identical spatial resolution (ALOS AVNIR2 –

10 m, KFA 1000 – 8 m) was made for the test area 3 (Fig.

1). The techniques of various data fusion (color

compositing, image differencing, Principle Component

Analysis) for detection of landscape changes caused by

human activity have been estimated for this area and other

sites [6]. For example, the result of Principle Components

Analysis (test area 3) is presented on Figure 7. The

results are quite satisfactory and allow detecting new

roads, buildings, water reservoirs, new lake as objects of

black color.

Fig. 7 Test area 3. Result of PCA (ALOS

AVNIR and KFA). Image of third principal

component

The numerous changes connected with human activity are

detected using method of color compositing of

multitemporal radar images, received during 1996-2007

on the test area 4.

4.4. Results of analysis of ALOS PALSAR images for

study of geological structures

Comparative analysis of radar and multispectral data has

shown that radar data (as L band and as C band) are more

effective for structural interpretation especially in the

areas covered by forest for extraction of lineaments and

revelation of active faults and fracture zones, controlled

petroleum traps distribution. But L band (ALOS PALSAR,

JERS-1 SAR) is more prospective for geological

application due to ability of radio waves to penetrate

through a vegetative and soil cover and to reveal the

places with high moisture characterized the fault zones

and microforms of relief indicative for the geological

structures.

On Figure 8 the results of visual interactive analysis of

ALOS PALSAR (FBS mode) is presented. The main line

structures which correspond to faults and fracture zones

and boundaries between different rocks are revealed. The

most of ring structures revealed on PALSAR data are not

visible on multispectral images. These structures control

the distribution of anticlines in sedimentary cover,

including petroleum fields and prospective structures.

Extraction of lineament in automatic mode and analysis of

their density, obtained using ALOS PALSAR permits to

reveal the places with high permeability of rocks and

define prospective sites for oil discovery.

The results of the study have shown that ALOS PALSAR

data is an effective tool for geological application.

Fig. 8 Test area 5. ALOS PALSAR interpretation:

1 – main line structures, 2 – main ring structures,

3 – oil and gas fields

4.3. Results of processing of ALOS PALSAR

polarimetric data

The processing of ALOS PALSAR polarimetric data was

made for test area 6. For interpretation of PALSAR

polarimetric data RGB composition (Fig. 9) and method

of Pauli de composition (Fig. 10) were used.

The Pauli decomposition provides an interpretation of a

full polarimetric data set in terms of elementary scattering

mechanisms: sphere/plate/trihedral (single- or odd-bounce

scattering), dihedral oriented at 0° (double- or even-

bounce) and diplane oriented at 45° (qualitatively related

also to volume scattering). In general decomposition

approach is suitable for discriminating the scattering of

elementary objects.

Results of image analysis (Fig. 10) have allowed to reveal

different types of landscape and vegetation (rare forest –

red color, low trees and bushes – green color, wetland -

blue color, lakes – black color) and to estimate wetland

deep.


Fig. 9 Test area 6. ALOS PALSAR, polarimetric color

coded image (red – hh, green – hv, blue – vv)

Fig. 10 Test area 6. ALOS PALSAR.

RGB image of Pauli decomposition

5. CONCLUSION

The study was concluded as follows:

─ Computer processing of multitemporal ALOS AVNIR

2 and LANDSAT as well as different SAR data for

change detection using various techniques (color

composite RGB, image differencing Principle

Components Analysis) is effective approach.

─ The technique of color composite RGB is most simple

and fastest way for change detection. It allows detecting

and differentiating changes connected with human

activity and natural processes.

─ The technique of image differencing with

classification of changes allows to obtain more evident

picture of changes, but it results depend on size of the

chosen threshold, and different types of objects can be

carried to one class, for example, the dried up and

polluted lakes.

─ Comparison of ALOS AVNIR2 and LANDSAT data

has allow to detect the changes caused by human activity

(mechanical disturbance of a surface, pollution of lakes

and rivers and others) and changes caused by natural

factors (changes in coastal line and thermokarst lakes).

─ Analysis of spectral curves of multitemporal ALOS

AVNIR 2 and LANDSAT satellite images has allowed

estimating level of lake pollution due to human activity

and comparing it with level of suspended sediment

concentration caused by natural processes.

─ ALOS AVNIR, PALSAR and PRISM data due to

their high spatial resolution is an effective tool for study

of cryogenic processes and landscape changes.

─ ALOS PALSAR data is an effective tool for geological

application due to ability of radio waves to penetrate

through a vegetative and soil cover and to reveal the

places with high moisture characterized the fault zones

and microforms of relief indicative for the geological

structures.

.

─ ALOS PALSAR polarimetric data allows to reveal

new information to study vegetation cover especially

wetland vegetation.

6. ACKNOWLEDGEMENT

This research is conducted under the agreement of JAXA

Research Announcement titled “Application of ALOS

Data to Study Landscape Changes Related to Petroleum

Fields and Their Exploration and Exploitation” (JAXA PI

200). The authors are grateful for cooperation and

assistance provided by Japan Aerospace Exploration

Agency (JAXA) and EORC Order Desk.

7. REFERENCES

[1] S.R. Cloude and E. Pottier, “A review of target

decomposition theorems in radar polarimetry”, IEEE

Trans. GRS, vol. 34(2), pp. 498-518, Mar. 1996.


[2] I. Smirnova, A. Rusanova, and N. Smirnova,

“Processing and Interpretation of Remotely Sensed Data

based on GIS for Study of Exogenic Geological Processes

in the North-Eastern part of Timan-Pechorian Petroleum

Province”, Proceedings of III International Conference

“Remote Sensing of Natural Environment”, Minsk,

Byelorussia, 2006, pp. 166-168.

[3] I. Smirnova, A. Rusanova, “Application of ALOS and

Other Satellite Data to Study Landscape Changes Related

to Petroleum Fields and Their Exploration and

Exploitation”, Proceedings of the First Joint PI

Symposium of ALOS Data Nodes for ALOS Science

Program in Kyoto, 2007.

[4] S.A. Ogorodov, “Morphology and dynamics of coast

of the Pechora sea”, Works of Institute of Oceanology, v.3,

Varna, Bulgaria, pp. 77-86, 2001.

[5] I. Smirnova, A. Rusanova, “Monitoring of Landscape

Changes Due to Petroleum Fields Exploitation,

Construction of Oil Pipelines and Oil Terminal in the

Northern Part of the Timan-Pechorian Petroleum Province

Using Multitemporal ALOS and LANDSAT Data”,

Proceedings of ALOS PI 2008 Symposium. Island of

Rhodes, Greece, 3-7 November 2008.

[6] A. Rusanova, I. Smirnova, “Comparative Analysis and

Computer Processing of Japanese ALOS AVNIR, Russian

KFA 1000 and Radar (Japanese JERS-1 and Canadian

Radarsat) Multitemporal Satellite Data for Change

Detection”, Proceedings of the First Joint PI Symposium

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Documents

Application of ALOS and Other Satellite Data to Study