LAND USE CLASSIFICATION AND LAND COVER ASSESSMENT USING ACCURACY MATRIX FOR DHAMTARI DISTRICT, CHHATTISGARH, INDIA
Keywords:
Accuracy assessment, Land classification, Kappa coefficient, Land change, Chhattisgarh, Land coverAbstract
The land use land cover change monitoring is vital for planning, developing and managing of any region. The main aim of this study is to monitor Land use and land Cover (LULC) changes of Dhamtari district of Chhattisgarh for the periods of 1999-2004, 2004-2009, 2009-2014, and 2014-2020. Landsat-8 and Landsat-5 data were used to generate LC map. The imageries were then used for supervised classification using maximum likelihood technique to prepare LULC maps. The change map of study area is for a time period of 1999-2020. This change map shows the change of one class to other. Five major classes viz; agriculture, barren land, forest area, urban area and water bodies have been identified. The forest and agriculture class are dominant in the study area. The LULC in the study area has experienced intricate changes over past two decades. The accuracy was assessed using google imageries and field verification, 200 random points were selected to verify the LULC map. The results Shows, agriculture, Forest, Urban area have increased by 25.60% (1037.9Km2), 42.60% (1728.2Km2), 23.60% (958Km2) while barren land and water bodies have decreased by 4.80% (194.2Km2) and 3.50% (141.6Km2) respectively. The average changes occurred in each class in last two decade from 1999-2020 are agriculture land 22%, barren land 22%, Forest 38%, urban land 15%, and water bodies changes to 3%. The results from the study will help the policy makers to understand the change trend and land management in the Dhamtari District.
References
Akhssas, A., Azougay, A., Rezqi, H., Oujidi, M., Baba, K., Bahi, L., Benradi, F., Cherkaoui, E., Khamar, M., Lahmili, A., Menzhi, M., Nounah, A., and Ouadif, L. (2020). The use of a geographic information system to study geotechnical problems in urban areas. E3S Web of Conferences., 150.
Akyürek, D., Koç, Ö., Akbaba, E. M., and Sunar, F. (2018). Land use/land cover change detection using multi-temporal satellite dataset: a case study in istanbul new airport. In: ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLII-3/W4., 17-22.
Al-Maliki, L.A.J., Al-Mamoori, S.K., El-Tawel, K., Hussain, H. M., Al-Ansari, N., and Jawad Al Ali, M. (2018). Bearing capacity map for an-najaf and kufa cities using gis. Engineering., 10(05):262-269.
ALDAHWI, S.H.A., ALI, A., and ALABDULLAH, S.F. (2018). Redistribution of al-adhamiyah land use by assessment of the geotechnical properties using gis technique. J. of Eng. Sci. and Technol., 13(10(2018)):3,369-3,380.
Arunyawat, S. and Shrestha, R. (2016). Assessing land use change and its impact on ecosystem services in northern thailand. Sustainability., 8(8).
Aziz, M. and Ahmed, T. (2017). Spatial interpolation of geotechnical data: A case study for Multan City, Pakistan. Geomechanics and Eng., 13(3):475-488.
Bernard, B., Aron, M., Loy, T., Muhamud, N.W., and Benard, S. (2020). The impact of refugee settlements on land use changes and vegetation degradation in West Nile Sub-region, Uganda. Geocarto International., 1-19.
Bhat, P.A., Shafiq, M.u., Mir, A.A., and Ahmed, P. (2017). Urban sprawl and its impact on landuse/land cover dynamics of Dehradun City, India. Int. J. of Sustainable Built Environment., 6(2):513-521.
Bokaie, M., Zarkesh, M.K., Arasteh, P.D., and Hosseini, A. (2016). Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use/ Land Cover in Tehran. Sustainable Cities and Society., 23:94-104.
Chen, L., Li, M., Huang, F., and Xu, S. (2013). Relationships of LST to NDBI and NDVI in Wuhan City based on Landsat ETM+image. 2013 6th International Congress on Image and Signal Processing (CISP).
Chirachawala, C., Shrestha, S., Babel, M.S., Virdis, S.G.P., and Wichakul, S. (2020). Evaluation of global land use/land cover products for hydrologic simulation in the Upper Yom River Basin, Thailand. Sci Total Environ., 708
Corner, R.J., Dewan, A.M., and Chakma, S. (2014). Monitoring and prediction of land-use and land-cover (LULC) change. In: A. Dewan and R. Corner (Eds.), Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health, p. 75-97.
Das, N., Mondal, P., Sutradhar, S., and Ghosh, R. (2021). Assessment of variation of land use/land cover and its impact on land surface temperature of Asansol subdivision. The Egyptian J. of Remote Sensing and Space Science., 24(1):131-149.
Dawoud, W., Adib, M.E., Reddy, G.K., Ramanathan, R.S., Hatipoglu, B., Demirkan, M., and Cinkilic, C. (2016). Development of a Comprehensive Geotechnical Information Management System for Municipal Use. In: Geo-Chicago 2016, p. 353-361.
Debnath, J., Das, N., Ahmed, I., and Bhowmik, M. (2017). Channel migration and its impact on land use/land cover using RS and GIS: A study on Khowai River of Tripura, North-East India. The Egyptian J. of Remote Sensing and Space Sci., 20(2):197-210.
Demissie, F., Yeshitila, K., Kindu, M., and Schneider, T. (2017). Land use/Land cover changes and their causes in Libokemkem District of South Gonder, Ethiopia. Remote Sensing Applications: Society and Environment., 8:224-230.
Díaz-Díaz, L.M., Pando, L., Arias, D., and López-Fernández, C. (2017). Geotechnical map of a coastal and industrialized urban area (Avilés, NW Spain). J. of Maps., 13(2):777-786.
Dong, M., Hu, H., Xu, R., and Gong, X. (2017). A GIS-based quantitative geo-environmental evaluation for land-use development in an urban area: Shunyi New City, Beijing, China. Bulletin of Eng. Geology and the Environment., 77(3):1,203-1,215.
Dutta, S. and Guchhait, S.K. (2020). Assessment of land use land cover dynamics and urban growth of Kanksa Block. In Paschim Barddhaman District, West Bengal. GeoJournal.
El-Tantawi, A.M., Bao, A., Chang, C., and Liu, Y. (2019). Monitoring and predicting land use/cover changes in the Aksu-Tarim River Basin, Xinjiang-China (1990-2030). Environ Monit Assess., 191(8):480.
Fonseka, H.P.U., Zhang, H., Sun, Y., Su, H., Lin, H., and Lin, Y. (2019). Urbanization and Its Impacts on Land Surface Temperature in Colombo Metropolitan Area, Sri Lanka, from 1988 to 2016. Remote Sensing., 11(8):957.
Foody, G.M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment., 80(1): 185-201.
Fu, P. and Weng, Q. (2016). A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery. Remote Sensing of Environment., 175:205-214.
Ghosh, S., Chatterjee, N.D., and Dinda, S. (2019). Relation between urban biophysical composition and dynamics of land surface temperature in the Kolkata metropolitan area: a GIS and statistical based analysis for sustainable planning. Modeling Earth Systems and Environment., 5(1):307-329.
Hishe, S., Bewket, W., Nyssen, J., and Lyimo, J. (2019). Analysing past land use land cover change and CA-Markov-based future modelling in the Middle Suluh Valley, Northern Ethiopia. Geocarto Int., 35(3):225-255.
Hussain, S., Mubeen, M., Ahmad, A., Akram, W., Hammad, H. M., Ali, M., Masood, N., Amin, A., Farid, H. U., Sultana, S. R., Fahad, S., Wang, D., and Nasim, W. (2020). Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan. Env. Sci. and Pollution Research, 27(32):39,676-39,692.
Ibrahim, N. and Yunus, M.Z.M. (2019). Bridge monitoring and management system using GIS. IOP Conference Series: Materials Sci. and Eng., 527:012076.
Imran Basha, U., Suresh, U., Sudarsana Raju, G., Rajasekhar, M., Veeraswamy, G., and Balaji, E. (2018). Landuse and landcover analysis using remote sensing and gis: a case study in somavathi river In: Anantapur District, Andhra Pradesh, India. Nature Environment and Pollution Technology., 17(3):1,029-1,033
Islam, K., Jashimuddin, M., Nath, B., and Nath, T.K. (2018). Land use classification and change detection by using multi-temporal remotely sensed imagery: The case of Chunati wildlife sanctuary, Bangladesh. The Egyptian J. of Remote Sensing and Space Sci., 21(1):37-47.
Jelil Niang, A., Hermas, E., Alharbi, O., and Al-Shaery, A. (2020). Monitoring landscape changes and spatial urban expansion using multi-source remote sensing imagery in Al-Aziziyah Valley, Makkah, KSA. The Egyptian J. of Remote Sensing and Space Sci., 23(1):89-96.
Kaichang, D., Deren, L., and Deyi, L. (2012). Remote sensing image classification with GIS data based on spatial data mining techniques. Geo-spatial Information Science., 3(4):30-35.
Kaliraj, S., Chandrasekar, N., Ramachandran, K.K., Srinivas, Y., and Saravanan, S. (2017). Coastal landuse and land cover change and transformations of Kanyakumari coast, India using remote sensing and GIS. The Egyptian J. of Remote Sensing and Space Sci., 20(2):169-185.
Kindu, M., Schneider, T., Teketay, D., and Knoke, T. (2013). Land use/land cover change analysis using object-based classification approach in munessa-shashemene landscape of the ethiopian highlands. Remote Sensing., 5(5):2,411-2,435.
Kumar, D. (2021). Urban objects detection from C-band synthetic aperture radar (SAR) satellite images through simulating filter properties. Scientific Reports., 11(1):6,241.
Liping, C., Yujun, S., and Saeed, S. (2018). Monitoring and predicting land use and land cover changes using remote sensing and GIS techniques-A case study of a hilly area, Jiangle. China. PLoS One., 13(7):e0200493.
Liu, T. and Yang, X. (2015). Monitoring land changes in an urban area using satellite imagery, GIS and landscape metrics. Applied Geography., 56:42-54.
Lu, D., Mausel, P., Brondízio, E., and Moran, E. (2010). Change detection techniques. Int. J. of Remote Sensing., 25(12):2,365-2,401.
Magesh, N.S. and Chandrasekar, N. (2017). Driving forces behind land transformations in the Tamiraparani sub-basin, South India. Remote Sensing Applications: Society and Environment., 8:12-19.
Mahamud, M.A., Samat, N., Tan, M.L., Chan, N.W., and Tew, Y.L. (2019). Prediction of Future Land Use Land Cover Changes of Kelantan, Malaysia. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLII-4/W16., 379-384.
Marondedze, A.K. and Schütt, B. (2019). Dynamics of land use and land cover changes in harare, zimbabwe: a case study on the linkage between drivers and the axis of urban expansion. Land., 8(10).
Mas, J.F., Lemoine-Rodríguez, R., González-López, R., López-Sánchez, J., Piña-Garduño, A., and Herrera-Flores, E. (2017). Land use/land cover change detection combining automatic processing and visual interpretation. European J. of Remote Sensing., 50(1):626-635.
Mashi, S.A. and Shuaibu, H.S. (2017). People and sustainable land management: assessment of stakeholders knowledge of the nature of landuse/cover change in Abuja, Nigeria. Geo J., 83(3):545-562.
Minta, M., Kibret, K., Thorne, P., Nigussie, T., and Nigatu, L. (2018). Land use and land cover dynamics in Dendi-Jeldu hilly-mountainous areas in the central Ethiopian highlands. Geoderma., 314:27-36.
Mishra, P.K., Rai, A., and Rai, S.C. (2020). Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India. The Egyptian J. of Remote Sensing and Space Sci., 23(2):133-143.
Misra, M. and Kumar, D. (2020). A hybrid indexing approach for sustainable smart cities development. J. of the Indian Society of Remote Sensing., 48(11):1,639-1,643.
Misra, M., Kumar, D., and Shekhar, S. (2020). Assessing machine learning based supervised classifiers for built-up impervious surface area extraction from sentinel-2 images. Urban Forestry and Urban Greening., 53:126,714.
Mohamed, S.A. and El-Raey, M.E. (2019). Land cover classification and change detection analysis of Qaroun and Wadi El-Rayyan lakes using multi-temporal remotely sensed imagery. Environ Monit Assess., 191(4):229.
