Land use Dynamics and Landscape Patterns Assessment using Geoinformatics Techniques in Raniganj Coalfield, India

 

Amit Sarkar

PhD Research Scholar, Department of Geography, University of Calcutta, Kolkata-700019, India

*Corresponding Author E-mail:  iamitsarkar91@gmail.com

 

Abstract:

In recent time land use land cover changes in human influenced area have been a breakthrough for research (Steven, 1987). Degradation and extensive loss of various land cover during open cast mining operation are hoped. In Raniganj coalfield, the continuous opencast mining activities were being done since 1960 for overburden and coal production purposes. Due to rapid interaction of mining aids like dragline, dumper and dozer with bare surface destruction and alteration of land use are happened. Eventually these land use converted into other land uses in due course of time. Therefore it is urgent necessary to understand and compute the environmental influence of open cast coal mining on landscape pattern in and around Raniganj coalfield area. The researcher strives to asses and interpret the pattern of land use change due to opencast coal mining in Sodepur, Salanpur, Sripur, Satgram, Pandaveswer, Kunstoria, Kajora, Kenda,  Sonepur Bazari, Bankola and Jhanjra areas of Raniganj coalfield using remotely sensed data (Sarkar, A., 2017).

 

KEY WORDS: Raniganj coalfield, open cast mining, , supervised image classification.

 

 


INTRODUCTION:

Opencast mining adversely causes widespread environmental decay especially land alteration and mutation. In order to compute the LULC changes since last five decades five spatial maps are prepared with ten different classes using supervised image classification method followed by maximum likelihood algorithm in ERDAS Imagine software. Agricultural area is declining from 55253.65 hectare in 1973 to 44858.6 hectare in 2015 and exhibits a negative growth rate. On the other hand, urban area sharply indicates the inverse trend. The area is increased from 3552.24 hectare in 1973 to 19648.72 hectare in 2015.

 

2. Research Area:

Raniganj coalfield is the birth place of coal mining in India is located in Burdwan district of West Bengal. About 95% of the total area of the coalfield is covered by four districts (Burdwan 71%, Birbhum 9%, Bankura 8% and Purulia 7%) of West Bengal. It is almost elliptical in shape and covers an area of about 1530 sq km. included within latitudes 23° 30Ꞌ N to 23° 52Ꞌ N and longitudes 86° 38Ꞌ E to 87° 23Ꞌ E.  The coalfield has an east-west stretch of 75 km and north-south stretch of 35 km. This coalfield mainly consists 10 seams viz R-I to R-X where R – denotes to Raniganj formation and roman one is the bottom most seam whereas roman ten is the top most seam. Number of running OCP is 17 and abandoned is 21. The area presents a nearly flat topography with broad undulation. Mean elevation is 98.45m (ECL, 2015).

 

 


Figure 1: Location of research are (Source:CMPDI and ECL)

 

3. MATERIALS AND METHODS:

To perceive the impression of anthropogenic actions on landscapes following methods has been used—

 

3.1 Remote Sensing and Other Data Sources:

The satellite data were gathered from USGS Earth Explorer portal.  Five temporal satellite images are applied for preparation of land use maps from 1973 to 2015. Six individual topographic maps on 1:50000 scales are gathered namely 73M/1, 73M/2, 73M/5, 73M/6, 73I/13 and 73I/14 from Survey of India to built the base layer of the satellite data. Details of the satellite data are given below in table 1.

 

Table 1: Details of remote sensing satellite data

Year

Acquisition Date

Path/Row

Spatial Resolution

Description

Projection

1973

18th & 20th March

149/44 & 150/43

60 m

Landsat MSS

World Geological Survey 84/ UTM, Zone 45

1992

15th March

139/44

30 m

Landsat 5 (TM)

2002

19th March

139/44

30 m

Landsat 7 (TM)

2010

25th March

139/44

30 m

Landsat 7 (TM)

2015

15th March

139/44

30 m

Landsat 8 (ETM+)

 

3.2 Data Processing:

Entire tasks are done from spatial and spectral enhancement menu of image interpreter tab in ERDAS Imagine software. Contrast stretching and tail trimming algorithms are performed to improve the visual interpretability of the image. Colour space transformation RGB to IHS function and the reverse IHS to RGB functions are applied for the year 2002 and 2010 to enhance the image information. To extract the entire research area for the year 1973 image stretching is performed using mosaic tool from data preparation tab.

 

3.3 Classification Scheme:

Firstly satellite images are visually interpreted. Signatures are collected using AOI tool from multiple areas throughout the image for a single class. Later these signatures are merged which belong to the same class and renamed after a land use class. In this manner ten distinctive LULC classes are captured. Signature alarm and contingency matrix is also used to evaluate signatures that have been created from AOI. After all these evaluations, supervised classification is applied with distance file from classification tab followed by signature editor menu bar; select Classify/supervised to perform a supervised classification. The distance file is used for post classification purposes. Option dialog is also utilized to define the statistical information like minimum, maximum, mean and standard deviation for the signature so that the signatures in the output thematic raster layer have this statistical information. Under parametric decision rule, Maximum likelihood is selected. Post classification filtering is applied from the viewer menu bar, select Raster/filtering/statistical filtering (Median filter) to remove unwanted discrete pixels from the thematic maps and to producing homogeneous region permanently (Sarkar, A., 2017). The classified maps of 1973, 1992, 2002, 2010 and 2015 are shown in figure 2, 3 and 4 respectively.

 

 

Figure 2: Landscapes map of 1973 and 1992 (clock wise), Raniganj coalfield

 

 

Figure 3: Landscapes map of 2002 and 2010 (clock wise), Raniganj coalfield

 

 

Figure 4: Landscapes map of 2015, Raniganj coalfield3.4 Ground Truth and Training Data:

Ground  truth  data  has  been  collected  through extensive  filed  survey  during  May  2015  and  December 2016 for better understanding of the LULC map shown in figure 5.

 

Figure 5: Ground truth verification waypoints map, Raniganj coalfield

 

A GPS device was employed across the entire study region representing all land cover classes for in-situ collection of ground truth geographic coordinates and locations; land use and land cover attributes, species information, and other general notes using stratified random sampling method. Google Earth has also been used extensively for collecting and plotting 950 ground truth data (Sarkar, A., 2017).

 

3.5 Accuracy Assessment:

First of all reference pixels are randomly selected. Then accuracy is measured for each classification using a confusion matrix. 720 ground truth points are overlain on the land use land cover maps and the land cover value is extracted. After values are extracted a confusion matrix is generated for accuracy assessment. The confusion matrix is used for the following—

 

Table 2: Algorithms for accuracy assessment, Raniganj coalfield

Overall Accuracy

                      Total number of correctly classified pixels (diagonal)

                     —————————————————————— × 100

                                       Total number of reference pixel

User Accuracy

                       Number of correctly classified pixels in each category

                  ———————————————————————— × 100

                  Total number of classified pixels in that category (row total)

 

Producer Accuracy

                               Number of correctly classified pixels in each category

                        ————————————————————————— × 100

                        Total number of classified pixels in that category (column total)

 

Kappa Coefficient (T)

Total Sample × Total Corrected Sample) ˗ ∑ (Column total × Row total)

—————————————————————————————

                                Total Sample2 ˗ ∑ (Column total × Row total)

Table 3: Confusion matrix for accuracy assessment of LULC map 1973, Raniganj coalfield

Classified Data

Reference Data

Users

accuracy

(%)

LULC Classes

   F           AL           FL            R            RS         WB           E            L              U            EL        Total

F

AL

FL

R

RS

WB

E

L

U

EL

Total

1120

65             32                              3                           21

1241

1356

1057

629

606

510

408

486

1593

552

8408

90.24

92.18

87.04

76.31

86.47

93.0

69.85

86.63

91.46

98.73

15

45

11

6

15

18

5

 

1235

1250

65               4              5               7            6                           2               2

21

12

3

25

30

23

5

 

1434

920

                                   34                          37

5

42

25

3

 

 

 

1092

480

    9           102           10

9

8

6

 

 

 

507

524

16                                            6

4

 

 

 

 

545

425

                  8

19

 

 

 

603

285

                  6              4

4

 

 

326

421

20

 

 

466

1467

 

7

1508

545

551

Producer Accuracy (%)

90.69     87.17      84.25       94.67      96.15       70.48      87.42       90.34      97.28      98.91

Overall Accuracy: 88.46%

Kappa Coefficient: 0.81

Table 4: Confusion matrix for accuracy assessment of LULC map 1992, Raniganj coalfield

Classified Data

Reference Data

Users

accuracy (%)

LULC Classes

F           AL           FL            R            RS         WB           E            L               U            EL        Total

F

AL

FL

R

RS

WB

E

L

U

EL

Total

1420

32             36                              5                          23

1516

1146

1052

760

901

530

481

567

1438

466

8850

93.67

89.01

86.12

80.26

91.68

86.42

68.61

87.83

99.09

98.28

 

21

54

2

4

8

20

9

 

1538

1020

65              6            8                11            8                           2              5

31

15

4

21

36

15

4

 

1178

906

                                   36                          25

5

42

22

5

 

 

 

1081

610

9                98          21

5

8

6

 

 

 

635

826

15                                             5

6

 

 

 

 

854

458

             7

34

 

 

 

652

389

                  3               8

9

 

 

450

498

25

 

 

523

1425

 

8

1468

458

471

Producer Accuracy (%)

 92.32     86.59      86.9        83.81         96.72   69.60         86.44       95.22    97.07         97.24

Overall Accuracy: 88.14%

Kappa Coefficient: 0.86

 

 

 

 

Table 5: Confusion matrix for accuracy assessment of LULC map 2002, Raniganj coalfield

Classified Data

Reference Data

Users

accuracy

(%)

LULC Classes

F           AL           FL            R            RS         WB           E            L               U            EL        Total

F

AL

FL

R

RS

WB

E

L

U

EL

Total

1725

52            29                                8                          25

1839

1337

1059

789

749

689

467

548

1398

594

9469

93.80

92.00

85.74

79.21

92.12

87.23

82.44

85.58

96.92

99.16

25

69

11

4

5

21

36

 

1896

1230

50              10            12                4             3                           2             1

25

32

4

32

20

15

7

 

1417

908

                                   32                          25

5

25

36

4

 

 

 

1057

625

9                102           5

2

5

9

 

 

 

651

690

21                                           3

5

 

 

 

 

724

601

             5

36

 

 

 

796

385

                  7             6

7

 

 

425

469

36

 

 

519

1355

 

5

1408

589

596

Producer Accuracy (%)

 90.98      86.80     85.90        96.00    95.30        75.50       90.59      90.37       96.24       98.83

Overall Accuracy: 90.04%

Kappa Coefficient: 0.88

 

 

 

Table 6: Confusion matrix for accuracy assessment of LULC map 2010, Raniganj coalfield

Classified Data

Reference Data

Users

accuracy

(%)

LULC Classes

   F           AL           FL            R            RS         WB           E            L               U            EL        Total                     

F

AL

FL

R

RS

WB

E

L

U

EL

Total

1654

59            36                                6                          25

1780

1397

1257

592

973

502

382

653

1451

591

9578

92.92

88.40

89.10

71.24

87.98

84.66

74.60

90.20

98.28

98.48

29

42

11

13

2

7

13

 

1771

1235

68               11             21            3             9                         8               13

25

16

3

14

30

29

12

 

1423

1120

                                   24                         46

2

42

36

13

 

 

 

1317

421

15               102          25

12

9

8

 

 

 

461

856

35                                           12

6

 

 

 

 

904

425

                10

36

 

 

 

625

285

                  1              2

8

 

 

352

589

20

 

 

645

1426

 

9

1476

582

597

Producer Accuracy (%)

93.39    86.79        85.04     91.32       94.69         68         80.97       91.32       96.61      97.49

Overall Accuracy: 88.424%

Kappa Coefficient: 0.84

 

 

 

 

 

Table 7: Confusion matrix for accuracy assessment of LULC map 2015, Raniganj coalfield

Classified Data

Reference Data

Users

accuracy (%)

LULC Classes

F        AL        FL           R           RS           WB            E            L               U            EL         Total

F

AL

FL

R

RS

WB

E

L

U

EL

Total

1612

48             21                                4                          17

1702

1290

1146

695

740

544

408

466

1593

702

9286

94.7

91.5

88.0

75.3

96.8

93.0

77.2

90.8

95.5

97.2

20

56

9

5

9

13

8

 

1732

1180

57               5             7                8             5                           5               3

19

20

2

17

35

25

8

 

1354

1008

                                   29                          34

3

36

28

7

 

 

 

1160

523

9                124           10

8

2

4

 

 

 

542

716

12                                             2

2

 

 

 

 

734

506

             4

23

 

 

 

677

315

                  2               5

6

 

 

355

423

20

 

 

437

1522

 

3

1603

682

692

Producer Accuracy (%)

 93.1         87.1          86.9        96.5         97.5         74.7         88.7         96.8         94.9         98.6

Overall Accuracy: 90.74%

Kappa Coefficient: 0.92

 

3.6 Microsoft Excel:

To display the proportion of area of different land use Pie diagram and simple bar graph are prepared in Microsoft excel using the data gathered from LULC maps. To compute the percent area and rate of land use change the below mentioned algorithms are used —

Area (%) = individual class area / total area * 100

Rate of land use change (%) =

((present LULC value – previous LULC value) / previous LULC value) * (1 / 10) * 100

Prediction of future values in excel is calculated from layout tab/trend line option. Here exponential trend line is prepared with three periods forward forecasting algorithm.

 

4. RESULT AND DISCUSSION:

In order to detect the transformation and current status of land use land cover in Raniganj coalfield area different spatial map of 1973, 1992, 2002, 2010 and 2015 is analyzed. Land use land cover is classified into ten classes— forest, agricultural land, fallow land, river, river sand, water body, exposure, lagoon, urban and excavated land. Areal proportion of different land use is displayed in figure 5, 6 and 7. Forest displayed an acute decline in their areal extent from 38143.1 hectare in 1973 to 22096.8 hectare in 2015. Agriculture dominates among all land uses, but the area is declining continuously from 55253.65 hectare in 1973 to 44858.6 hectare in 2015. River is almost at the stage of elimination, which comes down from l 4327.42 hectare in 1973 to 717.75 hectare in 2015. The areal coverage of water body is minimum and also decreasing in a rapid rate from 925.82 hectare in 1973 to 712.71 hectare in 2015.  After these analysises it is clear that there is gradual decrease of dense or open forest, agricultural land, water body and river. In due course of time considerable portion of forest and agricultural land is converted  into open cast quarry, construction, mining lagoon, road and fallow land.

 

 

 

Figure 6: Land use land cover distribution in 1973 and 1992 (clock wise), Raniganj coalfield

 

 

Figure 7: Land use land cover distribution in 2002 and 2010(clock wise), Raniganj coalfield

 

During the ground truth survey it was noticed that in Satgram, Pandaveswar, Kunstoria, Kajora, Bankola, Jhanjraand Sonepur Bazari area most of the forest and agricultural land is lost due opencast miing activities including land excavation, construction of new houses and buildings, mining  quarry  located in the South, East and Western part of the area. Rapid growth of population and urbanization accelerate the land use land cover changes. These are being accelerated due to open cast mining activities. As an outcome there is a loss of 16046.2 hectare forest, 10394.4 hectare agriculturall and and 3609.25 hectare river land and 213.11 hectare water body.

 

There is an increase of 10586.48 hectare fallow land, 4704.32 hectare river sand, 16095.76 hectare urban and 6499.47 hectare excavated land. Fallow land is the second largest land cover in the study area which is continuously increasing from 35256.52 hectare in 1973 to 45843.2 hectare in 2015. During opencast mining virgin land is being extracted to meet the coal. The virgin land can be either forest or agriculture. After abandonment of mining operation this land turned into fallow land. For instance there is a vast transformation of forest and agriculture into fallow land located in the South East and North West parts of the research area i.e. at Purusattampur, Sripur and Dabor area. Initially this area is renowned for mining activity. Therefore it is assumed that opencast mining is increasing decade by decade which leads to more quarry land, mining lagoon and mining exposure land. Quarry land is being created at the time of digging of land to extract coal and overburden. When extraction and production of coal is exhausted mined  areas  are  left  abandoned, which  in  due  course  of  time  are  covered  mostly  with vegetation and water. Mining lagoon is that waterlogged abandoned opencast project. Contrary exposure is the vegeted land. Dense forest, agriculture and water body of Sodepur, Mahalaxmi, Slanpur and Sonepur Bazari area converted to excavated land or quarry or mining lagoon located in the Western, Central and southern part of the study area. Mining quarry which increas from 7264.53 hectare in 1973 to 13764.6 hectare in 2015. Mining lagoon which increases from 692.27 hectare in 1973 to 1678.69 hectare in 2015. Exposure land is increased from 3917.34 hectare in 1973 to 5232.68 hectare in 2015 respectively.

 

River sand acutely increasded due to ceasation of river, rising population pressure, agricultural activity on river bed etc. Some segments of Damodar and Ajay river turned into river sand. It is increasded from 4165.68 hectare in 1973 to 8870.67 hectare in 2015. Durgapur and Asansol are two mighty cities in this area. These two cities are industrially advanced especially based on coal. Therefore this area is urbanizing in rapid rate. Urban land is increasded from 3552.24 hectare in 1973 to 19648.72 hetare in 2015. South, central and Western parts of this area is acutely  urbanizing. These area are Barakar, Dishergarh, Sanctoria, Panjabi more, etc. In Purusattampur,  Dalmiya,  Kenda and Shibpur abandoned quarry and mining overburden is transformed into sparse forest, fallow land, settlement  located  in  the  eastern and South western parts of the study area of the study area.

 

Figure 8: Land use land cover distribution in 2015, Raniganj coalfield

 

Percentage of area and trend and rate of land use change is computed and shown in figure 9 and figure 10 respectively. From which it is understood that there is subsequent decrease and increase in land uses. Forest was 25% in 1973 but it decreased into 13.52%   in 2015.  Highly affected forest cover is mostly transformed into fallow, agriculture and quarry. The rate of decrease in forest was found to rise from -2% during 1973 and1992 to -2.16% during 2010 and 2015. Initially from 1973 to 1992 agriculture is increased 36.21% to 38.58% at the rate of 1% due to transformation of forest land into it. After 1992 this land use is continuously decreasing from 38.58% in 1992 to 24.89% in 2010 at a rate of -2.12%. In last five years agriculture exhibits tiny increase 24.89% in 2010 to 27.45% in 2015 with a rate of 1.59%. Therefore it can be said that agriculture retains its own land and moderately affected. During 1973 to 2002 fallow land was decreased from 23.24% to 21.62%. Later fallow land is increased rapidly from 21.62% in 2002 to 28.05% in 2015 with a rate of 1.92%. Mostly forest and quarry was transformed into fallow.

 

 

Figure 9: Percentage area of various land use land cover in 1973 to 2015, Raniganj Coalfield

 

Percentage of river is continuously declined from 3% in 1973 to 0.43% in 2015. Most of river land was transformed into river sand at a rate of -5.42% in 1992 to 2002. River sand was 3.12% in 1973 but it increased to 5.42% in 2015. River sand changed at the rate of 7.10% in 1992 to 2002 but it reduced to 1.02% in 2010 to 2015 and was transformed into crop area, river water and fallow area. Water body was 1.02% in 1973 and declined into 0.43% in 2015 at the rate of -2% in 1973 to 1992. Later the rate of change comes in about 0.52%. Exposure, lagoon and excavated land are the outcome of opencast coal mining and have been discussed earlier. These land uses were increasing since 1973. Exposure land was 3% in 1992 and 6.19% in 2002. After that the areal cover declined to 3.20% in 2015. The rate of change was 7% in 1973 to 1992 and -4.53% in 2010 to 2015. Mining lagoon has inclined almost 0.2% in 1973 to 1.03% in 2015. The rate of change was 3.14% in 1973 to 1992. Area of excavated land was 5.02% in 1973, it increased to 9.47% in 1992 but later it declined to 8.42% in 2015. The rate of change was 5% in 1973 to 1992 and 2.68% in 2010 to 2015. Urban land was 2.14% in 1973 but it increased to 12.02% in 2015. The increase rate of urbanization was mainly due to transformation of fallow land into urban and construction of buildings. The acute rate of urbanization was 15% in 1973 to 1992 and 18.80% in 1992 to 2002. After 2002 the rate of urbanization was declined into 2.27% in 2010 to 2015.

 

 

Figure 10: Rate of change in land use categories in 1973 to 2015, Raniganj Coalfield

 

The open cast mining affects the land use and land cover of Raniganj coalfield area decade by decade in an accelerating rate. To know these impacts in near future, forecasting of trends of land uses are computed using 3 periods forward forecasting algorithm with R squared value. The trend and predicted individual land uses in the form of exponential curve are shown in figure 11, 12, 13, 14 and 15. Test results shows that rate of reduction of forest and agricultural land will follow negative trend between 2016 and 2018.

 

 

Figure 11: Trend analysis and prediction of forest & agriculture in 1973 to 2018 (clock wise), Raniganj Coalfield

 

Compare to agriculture, the forest area will be reduced more with greater rate of -2.16% in terms of the change in annual percentage. It is predicted that area of river and water body will also be reduced at the rate of now. Fallow land and river sand will be increased at the rate of above 1.16% and 1.02% respectively in terms of the change in annual percentage. Exposure, lagoon and excavated areas are expected to increase slightly at their present rate of change. The most important forecasting is about the urban land.

 

 

Figure 12: Trend analysis and prediction of fallow & river in 1973 to 2018 (clock wise), Raniganj Coalfield

 

 

Figure 13: Trend analysis and prediction of river sand & water body in 1973 to 2018 (clock wise) Raniganj Coalfield

 

 

Figure 14: Trend analysis and prediction of exposure & lagoon in 1973 to 2018 (clock wise), Raniganj Coalfield

 

It is predicted that the urban land will increase acutely with greater rate of 2.26% in terms of the change in annual percentage. The increase in urban land is mainly based on reductions in forest and agriculture. The rate at which the urban area will increase from 2015 to 2018 is lower than during 1973 to 2002 in terms of the change in annual percentage. Highly developed economy and high human population density will also caused more urbanization in Raniganj area. It should be remembered that the forecasting system in excel is an art not a science. Therefore the computed prediction is also just gives us a concept not actual value. From the above discussion about the trend analysis and forecasting of land use land cover in Raniganj coalfield area from 1973 to 2018 it can be said that opencast mining activity adversely affects the landscape.

 

 

Figure 15: Trend analysis and prediction of urban & excavated land in 1973 to 2018 (clock wise), Raniganj Coalfield

6. CONCLUSION:

The land use land cover analysis showed an increase in the non forest area that is increase in man-made land use. From the above result and discussion  it can be concluded that opencast mining  has  disastrous to these above discussed land uses. If the rate of land use transformation is occured with the present rate it certainly leads to deforestation,  destruction of fertile soil and more mine abandoned land. It is observed that because of changes in land use and land cover  pattern in Raniganj coalfield area Shibpur, Pandaveswar, Damaliya and Purusattampur, Sonepur Bazari, Khottadih, Bomjemehri and Dalurband area is affected vastly. In order to reduce the impact of mining activitry on landscape scientific approach  during and after mining  activities has to be taken like proper backfilling, storage of top soil seperately, forestation and monitoring the spoil ersion from dumped overburden. Land use  land cover degradation which is associated to opencast mining project and developmental project in Raniganj coaal field area are bringing a cronic challenge to the landscape. Due to larger size of the study area it is very difficult to allocate the land uses adequately at small scale. Furthermore, the accuracy through visually interpreted process is not good enough. These are the limitations of this study (Rao, P. 2014).

 

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Received on 27.04.2018       Modified on 29.05.2018

Accepted on 21.06.2018      ©A&V Publications All right reserved

Research J. Science and Tech. 2019; 11(1):27-37.

DOI: 10.5958/2349-2988.2019.00004.4