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Impact Analysis of Coal Mining on Land Use and Land Cover at Panadhro area of Kachchh using Remote Sensing and GIS

Joshi Kajal* and Dharaiya Nishith

Department of Life Sciences, Hemchandracharya North Gujarat University, Patan (Gujarat) 384265, India

* corresponding author, email: [email protected]

Abstract

Land use and land cover is very important factor to understand the relation between the human activities and the environment. Land cover change is a major key note of global environment change. The development of any region is dependent on the urbanization and industrialization; however development sometime shows adverse impact on environment resulting in loss of biological wealth of an ecosystem. Panadhro and the surrounding villages like Fulara and Khanot of Kachchh district are abundant of coal minerals. There are lots of changes in Land Use Land Cover (LULC) because of the exploration of the minerals in this area. Remote Sensing (RS) and Geographic Information System (GIS) are very effective tools for analysis of land use and land cover changes at a regional level. This research explains the use of RS and GIS technology for the detection of LULC changes in the study area. Image classification has been done by ERDAS imagine. It is observed that LULC changes have been detected in last 13 years mainly in the open land followed by the agriculture land.  The study has been pointed out the various effects of coal mining activities on the land use.

Keywords: Change detection, Supervised classification, Kachchh, Mining

1. Introduction

Human activities bring the change in land use which affects all the components of the environment, but the effects of these changes are very slow and not measurable quickly by a normal person (Nagarajan and Poongothai 2011). Land cover may be defined as the biophysical earth surface, while land use is often shaped by human, socio-economic and political influences on the land. It is essential to major the land use land cover (LULC) changes. Remote sensing (RS) and geographic information system (GIS) are used for the LULC change detection (Diallo et. al., 2009). Land use refers to human activities and the varied uses which are carried on over land and land cover refers to natural vegetation, water bodies, rock/soil, artificial cover and others noticed on the land classification (Yanli et. al., 2012). Information like maps and statistical data of land use land cover is essential for the planning, management and further utilization or conservation of land. According to Reis (2008) humans have misused the innate environment. Increasing population growth, industrialization, urbanization and some other factors affect the LULC of a particular area. The information generated on landscape change and configuration help to analyze global ecological and environmental change. Population growth and human activities like mining in Panadhro, Fulara and Khanot villages of Kachchh district, Gujarat- India are responsible for the LULC change and environmental degradation (Kaul and Sopan, 2012). Because of the population growth there is loss of agriculture land. Coal mining plays a fundamental role in the development and progress of this region, but it has some adverse impact on humans and environment. Panadhro of Kachchh district has ample amount of coal minerals (Singh et. al., 2011). There is a lot of changes in LULC because of the exploration of coal minerals and it adversely affect to the environment of that region (Chitade and Katyar, 2010). Remote sensing (RS), integrated with geographic information system (GIS), provides an effective tool for analysis of land use and land cover changes at a landscape level. Remote sensing as a direct adjunct to field, playing an important role to study and assess the natural resources (Abbas et. al., 2010). By understanding the dynamics of land use development in the past, managing the current situation with modern GIS tools, and modeling the future, one is able to develop plans for multiple uses of natural resources and nature conservation (Prakasam, 2010). Anthropogenic changes in land use and land cover are often assumed to be identical; they are rather quite different (Sreenivasulu et. al., 2013). The main objective of this study is to evaluate and quantify land use land cover changes in Pandharo village and surrounding areas due to coal mining in last 13 years using the LISS III satellite image and its classification.

2. Materials and Methods

Figure 1: Map showing the study site Pandharo

The study was conducted in Panadhro (Latitude 23.6825, Longitude 68.7709) and the surrounding villages Fulara and Khanot of Kachchh district, on the north western part of Gujarat. The climatic condition in this region is considered to be of semi arid type. Extreme temperature both in summer and winter are felt. The minimum and maximum temperatures recorded are 15.4 0C in winter and 50.16 0C in summer respectively. The average temperature of this region is about 32 0C. Rainfall is extremely scanty and is active from June to September with annual average rainfall of 29.2 cm. The Panadhro village has population of around 10,000 as per the population census 2011, out of which around 3000 people are working in coal mines.

Figure 2: Pandhro coal mining site (Photo by K. Joshi)

Panadhro is famous for its lignite mines, which were developed in early 1970s and are run by Gujarat Mineral Development Corporation (GMDC) Limited (Singh et. al., 2011). The town of S. K. Varmanagar developed after Panadhro mines were discovered is just a few kilometers away and fulfills the daily needs of mining community. The first unit of mines was commissioned in 1974 and operated by GMDC. The lease area of this lignite mine is about 1151 Ha. The total exploration area is 11.33 km2. Lignite and limestone are mined using hydraulic excavators and dumper combination along with ancillary equipment such as dozer, water sprinkler motor grader etc. from this area. The product lignite coal is directly used in Akrimota thermal power station and Kuchchh lignite thermal power station. According to an estimate made by the experts this mine has deposits of around one million tonnes of lignite which would be explored by the GMDC on commercial basis on the lines of the work done at Panandhro since last three decades. Panandhro lignite mines have in all 10 million tonnes of underground lignite reserves while 90 million tonnes have been so far dug and sold to the industries in and outside Gujarat.

In this study, LISS-III satellite images of year 2000 and 2013 were used and explored through supervised classification in ERDAS'' imagine (Alsaaideh et. al., 2011). Supervised classification is a significant tool for the process derives statistical relationships between the input and the ground truth habitats (Basana and Wodeyar, 2013). The images are obtained from Bhaskaracharya Institute for Space Applications and Geo-Informatics (BISAG) and National Remote Sensing Centre (NRSC), Hyderabad. Ground truthing was done by collecting GPS points for confirmation and georeferencing (Phukan et. al., 2013, Varadharajan et. al., 2012). Change Detection between both the images for all the land use and land cover classes were computed. Among different classification algorithms, maximum likelihood was used for supervised classification by taking 50 training areas for five major LULC class categories (10 training points for each LULC class) (Temesgen et. al. 2014). The LULC classes include Agricultural Land, Built Up area, Open/Waste Land, Water bodies and Mining area (Table 1). ERDAS Imagine'' 9.1 and Arc GIS'' 9.2 were used for satellite image processing and LULC change analysis (Tiwari and Saxena 2011). Digital land use land cover classification through supervised classification method was performed for the LULC classification. Recoding method is also done for converting pixel value into proper class. Area statistics of each land use category is calculated in hectors in attribute table in ERDAS Imagine 9.1 as suggested by Abate (2011) (Table 2). The rate of change was calculated for each LULC class using following formula given by Temesgen et. al. (2014).

Rate of change (ha/year) = (A-B)/C

Where:  A = Recent area of LULC in ha,

B = Previous area of LULC in ha,

C = Time interval between A and B in years

Table 1: Description of Land Use Land Cover Classes

Land Use Land Cover Class Description

Agricultural land Areas allotted to rain fed and irrigated cultivation, including fallow plots, agricultural land mixed with some bushes, trees and the scattered rural settlements included within the cultivated fields.

Built up area Areas that have been populated with residential, commercial, transportation facilities, settlements, roads and tourist places

Open/Wastelands Area of thin soil, sand or mountainous or hilly areas, almost has no vegetation cover or degraded agricultural lands.

Water bodies Areas covered by manmade small dams, seasonal water bodies and permanent water bodies (streams, rivers, lakes, reservoirs and sea).

Mining area Areas that have been allotted for the open cast mining

After Abate (2011), Temesgen et. al. (2014), Diallo et. al. (2009), Solaimani et. al. (2010)

The classified images were edited on the basis of the ground truth data collected from the field and then final classified maps were prepared with assessing classification accuracy using accuracy assessment tool of ERDAS'' where LULC maps were used in raster format. By applying random points in accuracy assessment window we received accuracy report containing overall classification accuracy (Dwivedi et. al., 2015). Image analysis operations have been carried out using GIS and finally the changes in various LULC classes are obtained using post classification comparison method. Error matrix and KAPPA analysis were done for accuracy assessment classification. The final map was prepared after the ground truth and changes were estimated in GIS (Tiwari and Khanduri, 2011). The output was analyzed for land cover degradation and interpreted with ancillary data collected from various government agencies. The results obtained were used in order to assess the stress of land use on ecosystem for the better natural resource management.

3. Results and Discussion

The study depicts that, Panadhro has undergone a huge change in various land use categories from 2000 to 2013. The land use assessment depicts that the total area of 11238.2 ha in the year 2000 was classified into agricultural land (24.60 %), built up area (2.56 %), open/waste land (67.07 %) and water body (5.77 %).  While in 2013, no change were detected in agriculture land and built up area; however open lands are reduced by 7.14%. Moreover 7.19 % of the land was converted in mining area which was not detected in 2000. The land use difference has been shown in Figure 1. Table 2 illustrates the LULC change in Panadhro in 2000 to 2013.

Figure 3: Satellite images and classified images of year 2000 and 2013

Table 2: Land Use Land Cover Changes in Panadhro from 2000 to 2013

Sr. No. Land Use Land Cover Class 2000 LULC Area 2013 LULC Area Change in ha

(2000-2013) Rate of Change  (ha/year)

Ha % Ha %

1 Agricultural Land 2764.5 24.60 2764.5 24.60 0 0

2 Built Up area 287.4 2.56 287.4 2.56 0 0

3 Open/Wastelands 7537.2 67.07 6734.8 59.93 -802.4 -61.72

4 Water bodies 649.1 5.77 642.9 5.72 -6.2 -0.48

5 Mining area 0 0 808.6 7.19 808.6 62.20

Total 11238.2 100 11238.2 100 0 0

The overall accuracy of classification methodology is 89.7% and 90.5% and KAPPA statistics is 0.87 and 0.88 respectively for the 2000 and 2013 images. The major land use in Panadhro and surrounding area of Kachchh is agricultural land, open land, water bodies and settlements. But the land under the open category has experienced a declining trend in the past thirteen years. Here water bodies decrease and open land converted to mining area. Table 2 depicts that almost all the mining areas are converted from the open land. There is a risk of decline in the extent of land under agriculture and built up in the near future. Changes in land use and land cover tend to affect greatly to the local biodiversity and the ecosystem. It is observed that because of changes in vegetation and water bodies, pollution level has increased extremely in the surrounding area and during the recent years it has attained the critical level (Beniwal et. al., 2015). The results also reveal that there is a need to monitor the LULC changes at regular interval to prepare the land use plan for the sustainable development. The geological experts of GMDC have found huge stock of lignite at Umarsar village near Panadhro spread in 2100 ha which has brightened new hope for industries in Kuchchh using lignite as fuel (Mengistu and Salami, 2007). This area will also undergo the same situations as the Panadhro, which can be regulated through regular monitoring of LULC change using the techniques described in this research so that a suitable land management plan can be proposed for such areas affected by mining activities.

4. Conclusion

The changes measured using remote sensing and GIS technologies shows critical adverse and undesirable environmental impacts. Therefore an effective sustainable land management policies and practices are required in the mining sites to avoid the environmental stress and promote sustainable development. The increase in the area under the mining may lead to a lot of environmental and ecological issues. As a sum up it could be stated that Panadhro area is now under the threat of change in land use. As the area is close to the Kachchh biosphere reserve it requires immediate attention. There is a need to take effective measures to protect the land especially open lands and water bodies in Kachchh region where the mining is now flourishing as an important industry.

Acknowledgments

The authors are thankful to Department of Science and Technology (DST), Government of India for the financial assistance. Thanks are also due to BISAG for providing the satellite images and image analysis.  Head, Department of Life Sciences, HNG University is duly acknowledged for providing the necessary facilities for the research work.

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