Long-term Monitoring and Visualization Analysis System for ... · Long-term Monitoring and Visualization Analysis System for Permafrost Change on Qinghai-Tibet Plateau Jiuyuan Huo1,2

Long-term Monitoring and Visualization

Analysis System for Permafrost Change on

Qinghai-Tibet Plateau

Jiuyuan Huo1,2

1 Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou, China

2 Information Center, Lanzhou Jiaotong University, Lanzhou, China

Email: [email protected]

Yaonan Zhang1*

1 Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou, China

Email: yaonan@ lzb.ac.cn

Abstract—The Qinghai-Tibet Railway goes through

continuous high altitude permafrost regions on the Qinghai-

Tibet plateau. The melting of ice in permafrost will lead to

weaken the road foundation, cause the roadbed to collapse

and other adverse effects. In order to obtain the detailed

change information of the permafrost, understand climate

change process and relationship of subgrade stability and

permafrost changes, we discussed the 44 different forms of

subgrade monitoring sites established to monitor the ground

temperature and the roadbed deformation and a

visualization and analysis software of permafrost change

process to analyze the long-term monitoring data in this

paper. The system offers the basic data for further

permafrost researching and for scientific basis of subgrade

stability early warning. And it also provides a new research

idea for geo-data visualization and analysis.

Index Terms—Permafrost Change, Roadbed Stability,

Temperature Monitoring, Long-term Monitoring System,

Contour Map, Visualization Analysis

I. INTRODUCTION

Permafrost regions in the Qinghai-Tibet plateau are the

highest elevation and largest areas permafrost region in

the world within the middle and low latitudes. Permafrost

area is about 1.3 × 106 km

2, accounting for 70% of total

area of the permafrost in China, and altitude of

permafrost distribution area usually over 4000 m [1, 2].

Permafrost on the plateau is characterized by high

temperature, ranging between 0 °C and − 4.0 °C, and

consequently by a weak thermal stability. In the

background of global warming, the Tibetan Plateau

warming climate will influence the development and

distribution of permafrost. Permafrost temperature,

thickness and spatial change of distribution are the

responses climate change. Surface excavation, vegetation

eradication and embankments construction in the human

engineering activities will result in strong thermal erosion

for permafrost, change heat exchange conditions of soil

and atmosphere, and give rise to change of temperature

balance state, interfere permafrost environment and

ecological balance of natural environment. Permafrost

degradation will make the strength and frozen soil

bearing capacity lower down, damage the stability of

permafrost embankment deeply [3, 4, 5, 6, 7, 8].

Qinghai-Tibet Railway (QTR), a total length of 1937

km, are north from Xining, Qinghai, and southern to

Lhasa, Tibet. It mainly crossed the permafrost areas,

which about 4,000m to 5,000m altitude in the Qinghai-

Tibet Plateau, and has an average elevation of 4,500

meters. The QTR crossed about 550 km of permafrost

regions, including 275 km of warm permafrost regions,

221 km of ice-rich permafrost regions, and 124 km of

warm and ice-rich permafrost regions [9]. To address

thermal stability of the high temperature and high ice

content permafrost, design ideas of cooling embankment

and reducing the permafrost temperature were adopted in

the QTR to ensure the thermal stability of permafrost

under the embankment [10, 11, 12, 13, 14].

Although, the preliminary geoscience technical

investigation on permafrost along the QTR has been

initiated during the 1960s and lasted about 40 years.

Many researches have been carried out on the distribution

characteristics, mechanical characteristics, change

predictions, and many other aspects of Tibetan Plateau

permafrost study. For the complicated geological

conditions of the QTR project, the research of

maintenance and construction of QTR till has strong

meaning of exploration and practicality. How to correctly

understand, permafrost development under climate

change and engineering construction, as well as the

relationship between the stability of railway embankment

and permafrost changes have become serious issues.

An important prerequisite to guarantee the longevity of

infrastructure in permafrost regions is a sufficiently

detailed preliminary study, and the most essential step is

to determine the permafrost presence and its ice content

[15, 16]. Thus, to solve these issues, a long-term

Corresponding author: Yaonan Zhang, Department of Computer and Network, Cold and Arid Regions Environmental and Engineering

Research Institute, CAS, Lanzhou, China, 730000

JOURNAL OF COMPUTERS, VOL. 7, NO. 8, AUGUST 2012 1927

© 2012 ACADEMY PUBLISHERdoi:10.4304/jcp.7.8.1927-1934

monitoring system has been built up in permafrost

regions along the QTR, the permafrost temperature of

surrounding embankment, sedimentation and deformation

have been monitored to collect critical data [17, 18].

These data monitored by the long-term monitoring

system could help to make an accurate grasp of trends

and judgments to the embankment stability, and make a

scientific prevention and diagnosis engineering disease

early, and also provide an important guarantee to

prediction, early warning, and problem analysis of the

roadbed.

Contour map is a general designation of a series of

equivalent lines distributed on a map. It could analyze the

spatial characteristics of physical elements, and grasp the

overall features of the spatial variation. Contour map is

widely used in many, especially in the field of geography,

large amounts of data are needed to be drawn into the

contours map for analysis and research. Visual analysis of

contour map is taken to analyze the monitored data of

temperature change of road foundation under the QTR,

and to facilitate the researchers to discover scientific laws

of the permafrost change process in an intuitive manner.

Surfer mapping software is one of the widely used data

visualization applications in the study area of geoscience.

Surfer supports a variety of data formats, has powerful

functions, and results beautiful and practical drawing

results. The long-term monitoring system has produced

large amounts of data in the monitoring process,

problems of inefficiency, labor waste and effect the

progress of research to track the new trends quickly will

be resulted in the traditional way of clicking menu item to

handling data and mapping for analysis. In order to

improve the efficiency of plotting of contour maps and

provide the researchers an analysis environment,

visualization and analysis software of permafrost change

process is developed by the hybrid programming of VB

and Surfer software.

The change process and stability of permafrost within

the observed region could be understood timely and

accurately. According the analysis results, some measures

could be taken to the relevant region to protect the

stability and reliable operation of the QTR.

II. RELATED WORK

Ground temperatures and embankment deformations

monitoring have been proposed as means of detecting

changes in permafrost regions, thus, there were more

scientists take research in this field in domestic and

international.

Charles Harris presented a review of the changing state

of European permafrost. They focused on methodological

developments and data collection over the last decade or

so, including research associated with the continent-scale

network of instrumented permafrost boreholes established

between 1998 and 2001 [16]. Results obtained during the

International Polar Year (IPY) on the thermal state of

permafrost and the active layer in the Antarctic are

presented in [19]. They also discussed the development of

boreholes network for permafrost and active-layer

monitoring. Mauro Guglielmin introduced active layer

and permafrost monitoring at two sites in Northern

Victoria Land, Boulder Clay and Oasi. And automatic

and year-round recording of ground temperatures and of

the main climatic parameters was carried out [20]. The

Geological Survey of Canada (GSC) has been developing

and maintaining a network of active-layer and permafrost

thermal monitoring sites which contribute to the

Canadian Permafrost Monitoring Network and the Global

Terrestrial Network for Permafrost. The presented results

indicate that the response of permafrost temperature to

recent climate change and variability varies across the

Canadian permafrost region [21].

In the research of QTR project, many Chinese

researchers have done a lot of work. Wei Ma, et al.,

summarized characteristics of embankment deformation

based on field monitoring datasets along the QTR. And

further analyses were carried out at some typical

monitoring profiles to discuss mechanisms of these

embankment deformations [22]. Based on dynamic

triaxial test at low temperature of the frozen clay from the

Beiluhe permafrost subgrade along the QTR, Zhanyuan

Zhu et al., studied residual deformation laws and dynamic

subsidence prediction model of permafrost subgrade

under train traffic [23]. On the base of in situ engineering

tests of the crushed rock embankment, the embankment

of crushed rock slope protection and the ventilated duct

embankment in Qinghai-Tibet railway, the basic data of

actively adjusting and cooling roadbed measures in

permafrost regions have been obtained through

monitoring the ground temperature in the roadbed [24].

Although these monitoring systems have collected a

large collection of data, but there is no fast and

convenient visualization environment for researchers in

carrying out scientific research. And contour map is a

common useful tool to analyze spatial characteristics of

physical quantity elements in practice. To address the

problem and develop more scientific, more visual and

faster engineering drawing software, we use VB with

Surfer software to develop a contour map visualization

software system to analyze the change process of

permafrost underneath the embankment of QTR in this

paper.

III. LONG-TERM MONITORING SYSTEM OF

PERMAFROST REGIONS

A long-term monitoring system has been deployed

along the QTR. Through the combinations of different

types of permafrost with different engineering measures,

ground temperatures and embankment deformations at 44

monitoring sites along the 550 km of permafrost regions

from the northern boundary of permafrost distribution,

Xidatan, to the southern boundary of permafrost

distribution, Anduo, were monitored continuously [17,

18]. The monitoring sections in the sites contain all types

of permafrost along the QTR, and it provides strong

support for subgrade stability research in different

permafrost conditions. The aims of establishment the

long-term permafrost monitoring system: To monitor

regular pattern of the change of ground temperature of

permafrost in the condition of warmer climate and the

1928 JOURNAL OF COMPUTERS, VOL. 7, NO. 8, AUGUST 2012

© 2012 ACADEMY PUBLISHER

growing impact of human activities. To predict and

forecast the development trends and embankment

stability of permafrost. To monitor impact of permafrost

degradation to ecological environment and engineering

construction.

At one monitoring site, ground temperatures and

embankment deformations were monitored

simultaneously. Ground temperatures were measured by

strings of thermistors installed in boreholes [25, 26].

Embankment deformation monitoring was done manually

on a monthly basis. In this paper, focuses were mainly on

ground temperature monitoring system. Past ground

temperature monitoring data were manually collected on

the field, and it result in the high cost and less efficiency.

As the monitoring sites involves more than 500 km along

the QTR, the frequency of monitoring and continuity of

data collection will be effected in this way. To collect and

access data timely, Campbell CR3000 automatic data

collection instruments were installed on some

temperature monitoring points. Monitored data also will

be transmitted through communication network of China

Mobile Company, General Packet Radio Service (GPRS)

to achieve data center.

A. Select Monitoring Sites

Long-term permafrost monitoring system conformed to

the following principles in selecting monitoring sites.

Firstly, monitor the key and weakness sections of QTR.

Second, select the warm and ice-rich area. Finally, try to

select flat terrain success for the consideration of future

observation. Based on the above principles, the overall

geographic distribution and elevation of monitoring sites

has been selected were shown in Figure 1.

B. Monitoring Contents

To understand the heat transfer process in the railway

embankment and climate response process, different

forms of ground temperature observation systems were

set up according to different types of road embankment.

We adopted the thermal resistance as the temperature

sensor and the indoor accuracy of calibration is ±

0.05 °C.

A temperature node deployment diagram of a cross

section in a temperature monitoring field was showed in

Figure 2. The red and green points arranged in columns

and rows in the figure are the monitoring sensor nodes.

There were seven ground temperature monitoring holes

deployed in the vertical direction in a typical monitoring

section that is left nature, left slope toe, left road shoulder,

road center, right road shoulder, right slope toe, right

nature. Nature ground temperature holes were set up in

the cross section at 10 m outside of the left and right side.

The depth of temperature monitoring holes are about 20

m. Underneath the ground, in various vertical ground

temperature monitoring hole, in the first 5 m, temperature

sensor nodes were deployed at a 0.5 m interval, and

nodes were deployed at 1.0 m interval beneath 5 m. In the

roadbed, a number of temperature monitoring holes were

set up along the ground horizontal. Each hole was start

from left slope to right slope of road, and temperature

sensor node deployed at 1 m interval in the holes. And a

set of sensors were deployed along the left slope and right

slope direction, CR3000 data logger will automatically

collect data from every nodes at every 2 hours. In

addition, the left and right shoulders of embankment are

determined from Golmud to Lhasa direction that is right

slope is always north-facing and left slope is south-facing.

C. Ground Temperature Monitoring System

According to function, ground temperature monitoring

system could be divided into data collection unit, data

network transmission unit, power supply unit and visual

analysis software.

(1) Data collection unit: includes ground temperature

sensors and automatic data logger instrument. The

thermal resistance was adopted as the temperature sensor

and Campbell data logger was used for automatic data

acquisition. The frequency of data collection is two hours,

and the collected data were stored in memory card.

(2) Data transmission unit: WAVECOM GPRS

modem was deployed for remote control and data

transmission. The device exchanges data with the

CR3000 data logger through the serial port (RS232), and

sent data to data center through the GPRS network.

GPRS modem also could accept instructions from

computer of data center to remote control the CR3000

data logger.

(3) Power supply unit: a safe and reliable monitoring

system uses solar plus battery power supply scheme,

mainly by the solar panels (30W) and battery (gel battery)

form. Responsible for the wireless transmission of

10m10m

Ø

20

m

NLasa

Left nature

holes

Left slope toe

Left road shoulder

Right nature

holes

Right slope toe

Right road shoulder

Road center

Top Roadbed Bottom Roadbed

Figure 2. Distribution of ground temperature boreholes in a typical

cross section of embankment.

4100

4300

4500

4700

4900

5100

5300

Elevation (m)

Figure 1. Geographical information and elevation of monitoring sections



electricity supply concerns terminal equipment, power

and data acquisition needs to ensure the normal operation

of field monitoring equipment.

(4) Visual analysis software: Visual analysis software

for long-term monitoring system of the QTR has been

developed to facilitate effectively visual analyze the

monitoring data. Visual Basic6.0 was selected as the

development environment to embedded call Surfer 8.0 for

drawing contour maps of ground temperature. The

software will be described in detail in later chapters.

D. Descript Monitoring Data

Monitoring data of temperature sensor nodes in ground

temperature monitoring system collected by Campbell

CR3000, and its data file format shown in Table 1. The

data was collected from each temperature sensor in cross

section in the time-series, and the time series of

monitoring nodes was in the first column of the table, the

second column to the last column is the resistance value

collected by each sensor at the timestamp in the time

series. The temperature sensors could monitor the

temperature changes nearby its location and obtain the

resistance value. According to the conversion formula

and the sensor's parameters calibrated in factory, the

resistance values should be converted to temperature

values.

As Surfer software drawing contour maps, special

requirement of data format was needed. A general

requirement is the text format, containing the data items

such as the location coordinates of observation points (for

example, coordinate x, coordinate y) and attributes (for

example, ground temperature). Before drawing contour

map by Surfer, the monitored data should be converted to

this format.

IV. THE DESIGN OF VISUALIZATION SOFTWARE

A. Concept Design

The seamless and automation connection could be

established between Surfer software and VB visual

programming languages. Automation method was

adopted by Surfer 8.0 to expose its interfaces, and these

ActiveX Automation objects covers almost all the

features of Surfer. There are two tasks should be

accomplished by VB programmers in writing the

embedded program of Surfer software. First, writing a

program of the main frame under the original code model

of VB. Second, writing a visualization software module

to call Surfer software by referring Surfer Automation

API.

As shown in Figure 3, the flow chart of visual analysis

software of permafrost changes process in QTR mainly

has the following steps:

(1) First, convert the resistance values to actual

temperature values through the conversion formula and

the sensor's parameters calibrated in factory, and

transpose data file.

(2) establish coordinate system in the monitoring

section, visual define the coordinate location of each

sensor through the position of sensor's groups and

separation distance between the sensors, and generates a

standard coordinate file.

(3) Combine temperature data with coordinate file, and

produce the data file conformed to the form (coordinate x,

coordinate y, time t1 temperature, time t2 temperature...

time tn temperature).

TABLE I. A SAMPLE MONITORING RESISTANCE DATA FILE OF SECTION 3

TIME D_1 D_2 D_3 D_4

2009-9-14 16:00 1738.31 1885.548 2132.538 1997.720

2009-9-14 18:00 1741.03 1887.019 2134.200 1998.295

2009-9-14 20:00 1742.06 1888.090 2135.588 1998.999

2009-9-14 22:00 1745.68 1880.973 2126.614 1995.986

2009-9-15 0:00 1742.63 1882.845 2123.814 1996.550

2009-9-15 2:00 1741.01 1885.807 2125.805 1997.333

... ... ... ... ...

·

Conversion

Combination

Start

End

Input

Parameters File

Input Resistance

Data File

Temp Data File

(t1,t2,...tn)

Generate

Coordinate File

TimeSeries Data

(x, y, t1, …, tn)

Input Boundary

File (*.bln)

i=1

Invoke Surfer

Service

Grid Data

Grid Blank

Draw Contour

Map

i=n

i=i+1

Y

N

Display Contour

Maps

Figure 3. Flowchart of visualization analysis software for permafrost change



(4) Take the first, second and the ith column data (x, y,

ti), embedded call Surfer daemon to convert data into

Surfer .grd file format.

(5) Call Surfer daemon to generate a temperature

contour map from the .grd file generated in the third step,

and limit the range of coordinates by blank file.

Attributes such as color and axis parameters could be

automatically set in this process.

(6) Repeat the above fourth and fifth step n times to

generate all contour maps at the monitoring cross-section

at time series. Through observation and comparison of

these contour maps of permafrost region, the change and

stability of permafrost could be analyzed.

B. Visualization Software Functions

1) Convert Resistance Data to Temperature Data

According to the conversion equation and the sensor's

parameters calibrated from factory, the resistance values

monitored by sensor nodes should be converted to

temperature values. Equation (1) is the conversion

equation of resistance value to temperature value. There

are 7 parameters in the equation, Pa is parameter A, Pb is

parameter B, Pxa is parameter XA, Pyb is parameter YB,

Pzc is parameter ZC, LN is length of wire, Wr is the

resistance of wire and Rr is the resistance value measured

by sensor.

PzcPaWrRrLN

PbPyb

PaWrRrLNPbPxaT

16.273**

16.273**

2

. (1)

2) Generate Coordinates of Sensors

To draw contour maps, a plane coordinate system

should be established for each section and define the

coordinate location of each sensor. The visualization

software could visually determine coordinates of each

sensor and generate a standard coordinate file.

3) Combine Data with Coordinates

As shown in Table 2, temperature data file should be

combined with the coordinate file to generate complete

temperature data file of the monitoring section. The first

column is the name of temperature sensors, the second

column to the third columns are the coordinate x and y of

the sensor, the fourth column to the last column is the

temperature value of each sensor at the timestamp in the

time series.

4) Draw Contour Maps

After preparation of the temperature data, visualization

software could embedded call the Surfer software to draw

contour map. Complete set of temperature contour maps

would be generated at each timestamp follow time series.

An unfilled contour map and a filled contour map of

permafrost temperature within a temperature observation

section 3 of roadbed in QTR at 10:00 on September 3,

2009 were shown in Figure 4.a and Figure 4.b.

5) Display Contour Maps

Contour maps could be viewed and browsed easily and

quickly in this function. Users browse contour maps at

different interval to dynamically analyze the process of

permafrost change at different regions and at different

time.

V. MONITORING RESULTS AND ANALYSES

A. Compare Interpolation Methods of Contour Map

One of the key steps of drawing contour map of is

interpolate discrete points data into regular grid points

data, thus the selection of spatial interpolation method of

contour drawing would affect the result of contour map

rendering. Surfer 8.0 offers 12 kinds of interpolation

method that are Kriging method, Inverse Distance to a

Power method, Minimum Curvature method, Modified

Shepard's Method, Natural Neighbor method, Nearest

Neighbor method, Polynomial Regression method, Radial

Basis Function method, Triangulation with Linear

Interpolation method. Kriging method is more accurate

other interpolation methods for middle and small discrete

data. Kriging is a method of interpolation named after a

South African mining engineer named D. G. Krige [27,

28]. For the powerful interpolation functions, Kriging

method has become the preferred method to deal with (X,

Y, Z) data. Therefore, it was adopted in this paper for

contour mapping and analysis.

B. Analyses and Discussions of Permafrost Change

The development of visualization software was

accomplished in December 2010. Currently, the ground

temperature monitoring system and visualization software

work well, and a more complete long-term temperature

monitoring data has been received. In this section, we

analyzed the monitoring results of the long-term

monitoring system and made a preliminary analysis to

understand the permafrost change and the process of

freezing and thawing under the embankment of QTR.

1) Temperature Change in Monitoring Permafrost

-10 -5 0 5 10

b.Filled contour map

m

℃

-15

-9

-3

0

3

9

15

-10 -5 0 5 10

a.Unfilled contour map

-20

-15

-10

-5

0

Figure 4. Unfilled and filled contour map of ground temperature of embankment in section 3 (at 20:00 on September 14, 2009)

TABLE II. THE FINAL DATA FILE COMBINED FROM TEMPERATURE DATA AND

COORDINATE DATA OF SENSOR NODES IN SECTION 3

No. X Y 2009-9-14

16:00

2009-9-14

18:00

2009-9-14

20:00

2009-9-14

22:00

D_1 -11 -0.2 8.43 8.38 8.37 8.31

D_2 -11 -0.7 8.3 8.28 8.26 8.36

D_3 -11 -1.2 4.37 4.35 4.33 4.44

D_4 -11 -1.7 3.57 3.57 3.56 3.6

... ... ... ... ... ... ...



To analyze temperature change of permafrost in

monitoring section, we compared ground temperature of

sensors deployed in different locations of left slope toe,

left road shoulder, road center, right road shoulder, and

right slope toe of embankment at section 11.

As shown in Figure 5, results from ground temperature

monitoring at the section showed that between the

embankment and road surface, temperature of road center

was higher than the left shoulder and right shoulder,

difference of left shoulder and right shoulder temperature

was slightly. Underneath the road surface, the changes of

temperature were gradually obvious. The temperature of

left slope toe was always higher than monitoring nodes

deployed in other locations. The temperature of right

shoulder, road center and right slope toe were close to the

left slope toe, but the temperature of the right slope toe

was significantly lower than the other. Compared to other

locations, under the 3m to 12m of road surface, the

temperature of right slope toe was lower about 0.2 to 0.9

degree, but after 12m of the road surface, its temperature

was close to other locations.

As can be seen from Figure 5, at 5.0 m under the road

surface, the temperature of each location has the biggest

difference. We compared ground temperature curve of

permafrost at the depth of 5.0 m under the road surface in

Section 7 shown in Figure 6 to compare the temperature

changes. In 20 days from September 14, 2009 to October

05, 2009, in the embankment at 5.0 m, the average

temperature of Right Slope Toe of embankment at 5.0 m

underneath road was lower about 0.2 to 0.3 degree than

other locations.

Although the QTR was basically north-south, but the

monitoring sections showed the effect of “yin-yang

slope", that is the temperature of soil under the left slope

toe is higher than the temperature of soil under the right

slope toe, temperature field of soil under the embankment

is asymmetric. Previous studies showed that the "yin-

yang slope" effect of embankment would cause the rate

of sedimentation of the sunny side of embankment slope

is greater than the shady side, and lead to uneven

subgrade deformation and sunny longitudinal cracks to

give rise to effect the stability of the roadbed [29, 30].

2) Frost heave process of embankment analysis

Frost heave of embankment is the result of many

factors, such as soil conditions of embankment, moisture

changes and atmospheric temperature. The embankment

soil is internal factor of frost heave. The premise of frost

heave of embankment is the temperature field change. As

the temperature is lowered from positive temperature to

negative temperature, the embankment soil began to

freeze, and the corresponding temperature is called the

freezing temperature of soil. 0 °C was taken as the

freezing temperature in this experiment [31].

Curves of freezing depth of the QTR embankment with

time at section 11 was shown in Figure 7. It can be seen

from the figure that the freezing process of embankment

soil at different locations are different. The freezing

process of left road toe, left shoulder and road center of

the embankment soil are similar, while the right slope toe

and right shoulder have larger changes in the soil freezing

process. Through the monitoring data, the largest frozen

depth of the right slope toe is 2.45 m, while the left slope

toe is only 1.0 m. Although the embankment is in a

steady state and the deformation is small, the differences

of the long-term freezing and thawing of the left and right

slope under the embankment may cause difference

deformation in the horizontal direction and give an

adverse impact to roadbed stability.

3) Contour maps analysis of monitoring sections

-1.2-1.15

-1.1-1.05

-1-0.95

-0.9-0.85

-0.8Left Slope Toe

Left Road Shoulder

Road Center

Right Road Shoulder

Right Slope Toe

Figure 6. Ground temperatures changing with time at the depth of 5.0 m beneath left slope toe, left road shoulder, road center, right road

shoulder, and right slope toe at section 11 (20 days, from September 14,

2009 to October 05, 2009)

-2.5

-2.3

-2.1

-1.9

-1.7

-1.5

-1.3

-1.1

-0.9

-0.7

-0.5 Left SlopeToe

Left RoadShoulder

RoadCenter

RightRoadShoulderRightSlope Toe

Figure 7. Curves of freezing depth with time at section 11. (2 months, from September 14, 2009 to November 14, 2009)

-20

-15

-10

-5

0

5

-2.0 -1.0 0.0 1.0 2.0 3.0

Left Slope Toe

(1B)

Left Road

Shoulder (1D)

Road Center

(1F)

Right Road

Shoulder (1E)

Right Slope

Toe (8P)

Figure 5. Comparison of ground temperature deployed at Left Slope Toe, Left Road Shoulder, Road Center, Right Road Shoulder, and Right

Slope Toe of embankment at section 11.



The contour map of variation of freezing and thawing

process of soil under embankment at Section 3 from

September 14, 2009 to December 14, 2009 was shown in

Figure 8. It can be seen that after 13 m under the

embankment, the permafrost layer of this three-month

period has little changes and is relatively stable. But

between the road surface and 13 m under the

embankment, the permafrost temperature changes greatly.

Freezing depth was about 2.4 m in September, and it rose

to about 0 m of the embankment in December. The

temperature change of right shoulder is significantly

larger than the left shoulder, temperature of left shoulder

changed from the initial 4 degree to minus 3 degree,

while the temperature of right shoulder changed from

about 8 degree to more than minus 10 degree. Such a

drastic temperature changes would lead to the freezing

and thawing process of right side of embankment faster

and more obvious than the left side, and will result in the

embankment deformation of the road and impact the

stability of the roadbed greatly.

At 10 m to 18 m underneath the embankment in

section 3, a melt interlayer (red area under the

embankment in the Figure 8) has been produced. Melt

interlayer would promote the natural converge of water,

cause the further expansion of melt interlayer, which led

to the embankment has a persistent deformation [32].

VI. CONCLUSIONS AND FUTURE WORK

The establishment of long-term monitoring system of

permafrost along the QTR would help the researchers to

monitor the weather, frozen ground temperature and the

subgrade deformation of QTR embankment on

permafrost regions, and better understand the interaction

of permafrost and engineering as well as the impacts of

permafrost changes to the stability of the embankment.

Automation technology was adopted to combine VB

6.0 and Surfer software 8.0 to develop contour maps

visual analysis software. Practice has proved that it only

take about 300s by using the visual software to draw one

hundred high-resolution contour maps.

After comparison and analysis of contour maps of

ground temperature in monitoring section 3 drawn by

using 12 different interpolation methods, Kriging method

is more accurate in the medium and small discrete data

interpolation. Kriging interpolation method was selected

for contour mapping and analysis in this paper.

Through the analysis of temperature changes in

different locations in the monitoring section, monitoring

sections showed the effect of “yin-yang slope", that is the

temperature of soil under the left slope toe is higher than

the temperature of soil under the right slope toe,

temperature field of soil under the embankment is

asymmetric. By analyzing the curves of freezing depth of

the QTR embankment with time at section 11, it could be

found that the largest frozen depth of the right slope toe is

2.45 m, while the left slope toe is only 1.0 m. It may

cause difference deformation in the horizontal direction.

The contour maps of the monitoring sections show that

the temperature change of right shoulder is significantly

larger than the left shoulder. These issues would lead to

the freezing and thawing process of right side of

embankment faster than the left side, and will result in the

embankment deformation of the road and impact the

stability of the roadbed.

This system would provide the basic data for further

permafrost research, a scientific basis for early warning

for the stability of the embankment and new research

method for geo data visualization and analysis. But

contour map analysis is only one of the analysis methods,

three-dimension maps could be involved and attempt to

find more new scientific issues in the future.

ACKNOWLEDGMENT

This work is supported by Informationization

Foundation of Chinese Academy of Sciences (CAS),

"The E-Science Environment for Ecological and

Hydrological Model Research in Heihe River Basin"

(Grant number: 29O920C61); Project for Incubation of

Specialists in Glaciology and Geocryology of National

Natural Science Foundation of China (Grant number:

J0930003/ J0109); and Second Phase of the CAS Action-

Plan for West Development (Grant number: KZCX2-

XB2-09-03).

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Jiuyuan Huo is currently a Ph.D.

candidate in Cold and Arid Regions

Environmental and Engineering Research

Institute (CAREERI), CAS. He is also

senior engineer in Lanzhou Jiaotong

University. His technical interests include

Wireless Sensor Network, Grid Computer,

and Visualization.

Yaonan Zhang is a Professor and the

Dean of Department of Computer and

Network of CAREERI, CAS. He received

his doctorate from CAREERI in 2006. He

has led or participated in over 20 major

research projects in network, high-

performance computing, database and

others since 1986. His current research

interests include Network, High-

performance Computing, Grid, and E-Science.



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Long-term Monitoring and Visualization Analysis System for ... · Long-term Monitoring and Visualization Analysis System for Permafrost Change on Qinghai-Tibet Plateau Jiuyuan Huo1,2