and GIS Methods in Moyna Block, Purba Medinipur District,. West Bengal. Manojit Mondal, Research Scholar, Department of Geography, Ranchi University, ...
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
Changing Pattern of Land Utilization: Using Remote Sensing and GIS Methods in Moyna Block, Purba Medinipur District, West Bengal Manojit Mondal, Research Scholar, Department of Geography, Ranchi University, Ranchi, India Chandan Karan, Research Scholar, Department of Geography, Ranchi University, Ranchi, India Dr. Jitendra Shukla, Associat Professor, Department of Geography, Ranchi University, Ranchi, India
Abstract The prime objective of this paper is to identify and map the land use and land cover changes (LULCC) within Moyna block, India, on during the period from 1990 to 2001 and to explore their contemporary economic significances. In the present study Landsat 4, 5 Thematic Mapper (TM) data is used. The TM sensor collects surface reflectance data in the visible and near infrared (bands 1-5, 7), and the thermal infrared (band 6) portions of the electromagnetic spectrum. Spatial resolution of the TM data is 30 meters per pixel. The classification has identified ten land use classes: Built up area , Barren and unculturable wasteland , Forest area , Agricultural fallow land , Sand , Surface water body , Moist fallow land , Pastures and other grazing land , Land under miscellaneous tree grooves, rural settlements and Crop land . According to the analysis of LULC changes in the study area, there were major changes in open surface waterbody, crop land and agriculture fallow land. We assessed land use change with increase of the study area 1025.25 hectors (4.42%) is the surface waterbody. Moreover, approximately 27% of the study site is covered with agricultural fallow land and land under miscellaneous tree and groves and rural settlement. The results of this research are going to provide reference for trend of land use change and management in this area. Keywords: Land use and land cover changes (LULCC), Landsat, Thematic Mapper (TM), Land Utilization, ERDAS Imagine software
Introduction The land is a basic natural resource that holds the key to the survival of mankind and sustainable development in rural area. Land includes soil, water, vegetation and the microclimate, and provides humanity with the essential life support systems and it meets our ever-increasing demand for food, fodder, energy, settlements, and industries etc. (Lalljee and Facknath, 2008)1. The rapid rise in population, industrialization, and urbanization has brought considerable change world wide in land cover and land use pattern. It changes may be grouped into main two categories, viz, land conversion and modification. Land conversion is refers to change from one land use to another, i.e. removing a crop field for construction of industries. Modification refers to change in land attributes while maintaining the land use, e.g. an agricultural field being converted to fishing. Pattern of a region is an outcome of natural and socioeconomic factors and their utilization by man in time and space. Land is becoming a scarce resource due to immense agricultural and demographic pressures. Cunningham, Cunningham and Siago (2005)2 have noted that rapidly increasing human populations and expanding agricultural activities have brought about extensive land use changes throughout the world. Hence, information on land use and possibilities for their optimal use is essential for the selection, planning and implementation of land use schemes to meet the increasing demands for
www.borjournals.com
basic human needs and welfare. This information also assists in monitoring the dynamics of land use resulting out of changing demands of increasing population. Though human beings have been modifying land to obtain food, shelter and other essentials of life for thousands of years, current rates, extents and intensities of such modifications are far greater than ever in history and continue undocumented. This has driven unprecedented changes in ecosystems and environmental processes at local and regional scales. Monitoring and mediating the negative consequences of land use changes while sustaining the production of essential resources has therefore become a major priority of researchers and policy makers around the world. Location: Moyna (community development block) is an administrative division in Tamluk subdivision of Purba Medinipur district in the Indian state of West Bengal. Moyna and Nandakumar police stations serve this block3. Headquarters of this block is at Mayna. Goasafat is a census town in this block. Moyna drainage basin is situated on north-west part of Purba Medinipur district in West Bengal, India4. The basin are is extended from 22° 9' "N to 22° 18' "N latitude and 87° 42' E to 87° 51' E longitude, covered with an area of 154.51 km2 (Fig. 1). The basin area is bounded by the river Kossai and Chandia from the east and west respectively. River Chandia and Keleghai are on the south and the Baksi canal is located on the north of the basin5.
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
87
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
Data Sources and Methodology: In the present study Landsat 4, 5 Thematic Mapper (TM) data is used. The TM sensor collects surface reflectance data in the visible and near infrared (bands 1-5, 7), and the thermal infrared (band 6) portions of the electromagnetic spectrum. Spatial resolution of the TM data is 30 meters per pixel. Subsets of satellite images were rectified first for their inherent geometric errors using digital topographic maps in Universal Transverse Mercator coordinate system obtained as above as the reference material. Landsat Thematic Mapper (TM) image was first registered to the digital topographic maps using distinctive features such as road intersections and stream confluences that are also clearly visible in the image. A first-degree Rotation Scaling and Translation transformation function and the Nearest Neighbor resampling method were applied. This resampling method uses the nearest pixel without any interpolation to create the warped image (Richards, 1994). A total of 18 points were used for registration of TM image. The total root mean square (RMS) error for the each image was approximately less than 5 meters. Change detection has been applied in different application areas ranging from monitoring general land cover change using multi-temporal imageries to anomaly detection on hazardous waste sites (Jensen et al. 2005)6. One of the most common applications of change detection is determining urban land use change and assessing urban sprawl. This would assist urban planners and decision makers to implement sound solution for environmental management. A number of approaches have emerged and applied in various studies to determine the spatial extent of land cover changes. It is also reviewed that different methods of detection produce different change maps (Araya and Cabral 2008)7. The selection of an appropriate technique depends on knowledge of the algorithms and characteristic features of the study area (Elnazir et al. 2004), and accurate registration of the satellite input data. Change detection approaches based on expert systems, artificial networks, fuzzy sets and objectoriented methods are also vailable in different software
www.borjournals.com
ISSN No: 2319-5606
platforms (Jensen et al. 2005)8. In addition, various researchers (Berkavoa 2007)9 have attempted to group change detection methods into different broad categories based on the data transformation procedures and the analysis of techniques applied. According to (Berkavoa 2007), for example, change detection can be divided into two main groups: pre-classification and postclassification methods. The following section discusses some of the techniques that are available in various software platforms. Accuracy Assessments Accuracy Assessments are performed on classified images to determine how well the classification process accomplished the task. For all classifications an accuracy assessment was done by generating stratified random points for the classified images, using the accuracy assessment application in ERDAS Imagine software. To determine the accuracy of classification, a sample of testing pixels is selected on the classified images and their class identity is compared with the reference data (ground truth). The choice of a suitable sampling scheme and the determination of an appropriate sample size for testing data play a key role in the assessment of classification accuracy (Arora and Agarwal, 2002)10. The Overall accuracy was defined as the total number of correctly classified pixels divided by the total number of reference pixels (total number of sample points) (Rogan et al. 2002)11. Kappa coefficient was defined as a statistical measure of accuracy that ranges between 0 and 1, it measures how much better the classification is compared to randomly assigning class values to each pixel. Morphological Unit (Physiography, Drainage, Soil, Climate and Vegetation) The relief of the Moyna drainage basin is varying from 3 to 6 m. It is a typical trough which is fairly elongated and roughly triangular in shape. The tough deep depressions are found in the village like Baital Chack, Charandas Chak, Lalugeria, Maturichak, etc. Southern part of the basin is deeper rather than the northern part. Settlements area and embankment is representing relief variation at the micro level12.
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
88
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
LOCATION MAP OF STUDY AREA
The surface soil is sandy loam and clayey. Soil conditions of this block are maximum practical clay. Soil health are respect clay 7000 hectors , clay loam 1000 hectors, sandy soil 500 hectors sandy loam 500 hectors and others loam 1900 hectors13. Natural vegetation of this block is covering mainly mixed forest Vis mango, jam, combo etc. The Moyna drainage basin is characterized by the year wise rainfall variation, showed the vagaries of tropical monsoon climate. The mean annual temperature is around 28.5 ° C, and the average summer (May) and winter (December) temperatures varying from 45° C and
www.borjournals.com
13 ° C respectively. The mean annual rainfall is about 1850 mm14. The seasonal fluctuations of rainfall over the study area have a grate impact on the water discharge with in the Kansai and Chandia river which is directly influenced to the overtopping process of embankment breaching during the rainy season (e.g., July- August). Natura vegetation of Moyna block has been deciduous mix forest. These areas vegetation are cover very low percentage and also social forestry are spared local ad-
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
89
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ministrative areas. Mainly trees are Mango, Blackberry, Palm, eucalyptus, Bamboo, Litchi, and Jackfruit etc15. Socio-Cultural Unit (Population distribution & density , Population growth, Caste structure, Religious structure, Literacy and Economic activities of people) Population of Moyna block are very compact density. As per 1981 census, Moyna block had a total population of 139224. As per 2001 census, Moyna block had a total population of 196,503, out of which 101,890 were males and 94,613 were females. Moyna block registered a
ISSN No: 2319-5606
population growth of 12.73 per cent during the 19912001 decade. Decadal growth for the combined Midnapore district was 14.87 per cent. Decadal growth in West Bengal was 17.84 per cent. Religion structure of Moyna block are approximately same type of Purba Medinipur district. There are 91.25 % of the hindu religious, 8.68 % of the Islamic religious and 0.97 5 of others religious people are living in the Moyna block. Literacy rate are very high of this block. There are literacy rate represent 85.43 % on 2011 census, 92.56% of male and 78.25% female respectively16, 17.
Figure 1 Population growth of Moyna block. Year
Persons 2001 2011
Table 1 Workers structure of Moyna block 2001 and 2011. Marginal workers Non-workers
Main workers
47800 44085
Males
Females
43007 39336
4793 4749
Persons 30022 42728
Males 11737 27269
Females 18285 15459
Persons 118680 140114
Males
Females
47175 51384
71505 88730
Sources: Census of India, 2001,2011.
Figure 2 Workers strucure of Moyna block on 2001and 2011
www.borjournals.com
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
90
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
The forest land and agricultural fallow land in the study area gradually decreased. The total forest area has been recorded as 989.01 hectares (4.26%) in 1990, 822.33 hectares (3.54%) in 2002 and 905.22 hectares (3.90%) in 2011. The results showed during the period from 20022011, there is slightly increased of forest area (82.89 hectares). Consequently, the analysis also portrayed 83.79 hectares of forest area has been decreased during the entire study period.
Discussion and Result: Dynamic change of Land Utilization on Moyna block (1991, 2002 and 2011 land use change) Land use characteristics of Mayna block is represented in Table . Land use/Land cover characteristics of Mayna block has been categorised into ten different classes that built up area, barren and unculturable wasteland, forest area, agricultural fallow land, sand, surface water body, moist fallow land, pastures and other grazing land, land under miscellaneous tree grooves, rural settlements, crop land. The result showed most of the study area (> 48%) is covered with the surface waterbody. Moreover, approximately 27% of the study site is covered with agricultural fallow land and land under miscellaneous tree and groves and rural settlement.
On the other hand, there is a continuous decrease of agricultural fallow land in the study area from 1990-2011. In 1990, the total agricultural fallow land was 3243.44 hectares (13.98%) and 1822.32 hectares (7.86%) area has been recorded in 2011. However, the area of change is maximum during the period between 2002 and 2011 (992.49 hectares). In Mayna block, a total of 1421.12 hectares area of agricultural fallow land has been decreased during the entire study period.
Built up area in the study area is increased day by day in Mayna block. In 1990, only 0.02% area has been mapped in Mayna block, while the percent of area has been increased up to 0.15% in 2011. A total of 29.95 hectares area has been increased during the period from 1990 to 2011.
Surface water body in Mayna block is one of the important land cover characteristics as most of the land is used for pisiculture. The results showed there is increasing trend of surface waterbody in the study area. It may be due to the development of pisiculture of agricultural fallow land. In 1990, the area of Surface water body in the study area was 11257.71 hectares (48.53%), while it is increased upto 12283.26 hectares (52.95%) in 2011. The result of the analysis also showed there is a increasing trend of moist fallow in the study area that may also be used for pisiculture seasonally.
Barren and unculturable wasteland in the study area is decreasing in trend. This includes land not taken up for cultivation in the past, but not cultivated for varying reasons during the last five years or more in succession including the current year. A total of 137.63 Hectares area has been decreased during the period between 1990 and 2011. Land under miscellaneous tree grooves, rural settlements includes all cultivable land which is not included in crop/agricultural fallow land but is put to some agricultural use. Land under thatching grasses, bamboo bushes and other groves for fuel are not included under ‘Orchards’ are classified under this category. In 1990, 3228.44 hectare (13.42%) area has been mapped of the total geographical area and it is increased up to 3589.61 hectares (15.47%) in 2011. The analysis showed 361.17 hectares area has been increased during the entire study period in Mayna block.
The result of this study is showing that there is overall increase (590.81 hectares) of crop land during the period between 1990 and 2011. 11.19% (2596.41 hectares) crop land was recorded in 1990, whereas, 13.74% (3187.22 hectares) was recorded in 2011. However, there is decreasing trend of pastures and other grazing land in the study area that may go to convert into wet land and crop land due to intensive pressure of human population.
Table no. 2. Land use/land cover class and their percent of distribution in Mayna Block Land use/land cover class
1990
Built up area
5.58
0.02
11.1313
0.05
35.1
0.15
Barren and unculturable wasteland
443.64
1.91
394.7777
1.70
306.01
1.32
Forest area
989.01
4.26
822.33
3.54
905.22
3.90
Agricultural fallow land
3243.44
13.98
2814.81
12.13
1822.32
7.86
Sand
61.65
0.27
139.34
0.60
137.16
0.59
Surface water body
11257.71
48.53
11500.83
49.58
12283.26
52.95
Moist fallow land
495.81
2.14
569.9826
2.46
576.16
2.48
www.borjournals.com
Percent
2002
Percent
2011
Percent
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
91
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
Pastures and other grazing land Land under miscellaneous grooves, rural settlements Crop land
ISSN No: 2319-5606
875.52
3.77
531.4185
2.29
355.68
1.53
3228.44
13.92
3366.26
14.51
3589.61
15.47
2596.41
11.19
3046.325
13.13
3187.22
13.74
tree
Figure 3 Percent of land use/land cover characteristics in Mayna block Table No. 3. Land use/land cover change area during the period between 1990 to 2011 in Mayna Block Land use/land cover characteristics Built up area Barren and unculturable wasteland Forest area Agricultural fallow land Sand Surface waterbody Moist fallow land Pastures and other grazing land Land under miscellaneous tree grooves, rural settlements Crop land
www.borjournals.com
1990-2002
2002-2011
1990-2011
5.5513 -48.8623 -166.68 -428.63 77.69 243.12 74.1726 -344.102 137.82 449.915
23.9687 -88.7677 82.89 -992.49 -2.18 782.43 6.1774 -175.739 223.35 140.895
29.52 -137.63 -83.79 -1421.12 75.51 1025.55 80.35 -519.84 361.17 590.81
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
92
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
Figure 4 . Land use/land cover change area during the period between 1990 to2011 in Mayna Block
Figure 5 Dynamic of land use/ land cover map of Moyna block (1991-2011) Accuracy assessment In order to evaluate the land cover map of 1990, 2002 and 2011, error matrix has been prepared for a total of 50 sample points for each year. The error matrix is given in Table . The producer accuracy and user accuracy for
www.borjournals.com
each land cover class has been given in Table , selected by stratified random sampling technique. The overall accuracy for 1990, 2002 and 2011 were 90.00%, 88.00% and 88.00% respectively.
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
93
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
Table no. 4. Accuracy assessment report of land use/land cover classes in Mayna block Class Name Reference Classified Number Producers Users AcTotals Totals Correct Accuracy curacy 1990 Moist fallow land 4 3 3 75.00% 100.00% Pastures and other grazing land 2 2 2 100.00% 100.00% Sand 12 13 11 91.67% 84.62% Crop land 6 6 6 100.00% 100.00% Land under miscellaneous tree 7 8 6 85.71% 75.00% grooves, rural settlements Agricultural fallow land 8 7 7 87.50% 100.00% Surface waterbody 3 3 3 100.00% 100.00% Barren and unculturable wasteland 3 3 3 100.00% 100.00% Forest area 4 3 3 75.00% 100.00% Built up area 1 2 1 100.00% 50.00% Totals 50 50 45 Overall Classification Accuracy = 90.00% 2002 Sand 0 0 0 ----Pastures and other grazing land 0 0 0 ----Forest area 1 1 1 100.00% 100.00% Crop land 4 5 4 100.00% 80.00% Surface waterbody 11 13 11 100.00% 84.62% Land under miscellaneous tree 4 2 2 50.00% 100.00% grooves, rural settlements Moist fallow la 1 1 1 100.00% 100.00% Barren and unculturable wasteland 0 0 0 ----Built up area 0 0 0 ----Agricultural fallow land 4 3 3 75.00% 100.00% Totals 25 25 22 Overall Classification Accuracy = 88.00% 2011 Built up area 3 2 2 66.67% 100.00% Barren and unculturable wasteland 2 2 2 100.00% 100.00% Forest area 4 3 3 75.00% 100.00% Crop land 4 4 4 100.00% 100.00% Sand 2 2 2 100.00% 100.00% Surface waterbody 14 15 13 93.75% 88.24% Moist fallow land 4 3 3 75.00% 100.00% Pastures and other grazing land 2 3 2 100.00% 66.67% Land under miscellaneous tree 7 9 7 100.00% 77.78% grooves, rural settlements Agricultural fallow land 8 7 6 75.00% 85.71% Totals 50 50 44 Overall Classification Accuracy = 88.00% Kappa statistics in 2011 for Built up area, Barren and unculturable wasteland, Forest area, Crop land, Sand ,Surface waterbody, Moist fallow land, Pasture and other grazing land, Land under miscellaneous tree groves, rural settlement, Agricultural fallow land are 1.00, 1.00, 1.00, 1.00, 1.00, 0.83, 1.00, 0.65, 0.74, 0.831 respectively while overall accuracy is 85.39% and in 2002, Kappa statistics for Sand , Pasture and other grazing
www.borjournals.com
land, Forest area, Crop land, Surface waterbody, Land under miscellaneous tree groves and rural settlement, Moist fallow land, Barren and unculturable wasteland, Built up area, Agricultural fallow land are 0.00 0.00, 1.00, 0.76, 0.73, 1.00, 1.00, 0.00, 0.00, and 1.00 respectively and overall accuracy for 2002 is 82.95% (Table ). The overall Kappa statistics in 1990 was 88.36%
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
94
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
ISSN No: 2319-5606
Table 5 Calculation of Kappa statistics of land use/land cover classes in Mayna block during the period from 1990 to 2011. Class Name
KAPPA (K^) STATISTICS
1990 Moist fallow land Pastures and other grazing land Sand Crop land Land under miscellaneous tree groves, rural settlement Agricultural fallow land Surface waterbody Barren and unculturable wasteland Forest area Built up area Overall Kappa Statistics = 0.8836 2002 Sand Pasture and other grazing land Forest area Crop land Surface waterbody Land under miscellaneous tree groves and rural settlement Moist fallow land Barren and unculturable wasteland Built up area Agricultural fallow land Overall Kappa Statistics = 0.8295 2011 Built up area Barren and unculturable wasteland Forest area Crop land Sand Surface waterbody Moist fallow land Pasture and other grazing land Land under miscellaneous tree groves, rural settlement Agricultural fallow land Overall Kappa Statistics = 0.8539
Conclusion: Land use and land cover change is the resultant function of relationships between geological structure, soil types, surface elevation, slope, drainage density, haphazard embankments, depth of ground water, human activities, and so forth, from the spatial as well as environmental perspective. In the people Moyna block dependence on the cultivation activities. There are many hydromorphological favourable conditions for the onset of water-logged situation. Using different methods, aiming to change the traditional landuse pattern, people trans-
www.borjournals.com
1.00 1.00 0.80 1.00 0.71 1.00 1.00 1.00 1.00 0.49
0.00 0.00 1.00 0.76 0.73 1.00 1.00 0.00 0.00 1.00
1.00 1.00 1.00 1.00 1.00 0.83 1.00 0.65 0.74 0.83
ferred waterlogged problem into economically benefited instrument. So, people are chosen the pisciculture of surface water-body land.
References: [1] B. Lalljee, S. Facknath. 2008. Land Use, chapter, A study of the historical and present day changes in land use profile, and their driving forces in Mauritius.: pages 231 – 256; Concept Publishing Company, New Delhi, India.
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
95
Journal of Engineering Computers & Applied Sciences(JECAS) Volume 4, No.3, March 2015
[2] Saigo B. (2005). Nigeria. W. P & Cunningham M.A. Global Environmental Issues National Open University of & Environmental Science: A. Global Concern. [3] Moyna (community development block) http://en.wikipedia.org/wiki/Moyna_%28comm unity_development_block%29 [4] Purba Medinipur - ADMINISTRATIVE SETUP East Midnapore www.midnapore.in/district-info/purbamedinipur. [5] Hunter W. W. 1877. A Statistical Account of Bengal, vol. XVII. London. pp. -5. [6] Jensen, J. R. (2005): Introductory digital image processing: a remote sensing perspective. John R. Jensen. 3rd ed., Pearson Education Inc., Upper Saddle River. [7] Araya, Y. and Cabral, P (2008). Urban land cover change detection analysis using GIS and remote sensing: a case study of Asmara, Eritrea (peer-reviewed paper). [8] Berkavoa, V. (2007). Application of Remote Sensing and GIS for Change Detection from Various Data Type of Remote Sensing [9] Arora, M K and Mathur, S. 2002. Multi-source Classification Using Artificial Neural Network in a Rugged Terrain. Geocarto International, 16(3), 37-44.
ISSN No: 2319-5606
multitemporal vegetation change using Thematic Mapper imagery. Remote Sens. Environ., 80(1): 143-156. [11] Abhay Sankar Sahu. 2014.A Study on Moyna Basin Water-Logged Areas (India) Using Remote Sensing and GIS Methods and Their Contemporary Economic Significance. Hindawi Publishing Corporation Geography Journal Volume 2014, Article ID 401324, 9 pages http://dx.doi.org/10.1155/2014/401324 [12] COMPREHENSIVE DISTRICT AGRICULTURE PLAN FOR PURBA MEDINIPUR DISTRICT, WEST BENGAL (FINAL REPORT). XIth PLAN PERIOD, Submitted to The District Magistrate Purba Medinipur, West Bengal. [13] District Statistical Hand Book. Purba Medinipur, 2004, 2007, 2008, 2009, 2010 & 2011. Bureau of Applied Economics and Statistics, Govt. of West Bengal. [14] Estimation of area and production of principal crop in West Bengal (2008-09), Evaluation wing , Directorate of Agriculture, Govt. West Bengal. 2010. [15] District Human Development Report : Purba Medinipur, Development & Planning Department, Government of West Bengal, First Published, May, 2011. [16] Census of India, 2011.
[10] Rogan, J., Franklin, J. & Roberts, D.A. (2002) A comparison of methods for monitoring
www.borjournals.com
© 2012 The Author © Blue Ocean Research Journals 2012 Open Access Journals Blue Ocean Research Journals
96
