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    Exploring 16 years changing dynamics for land use/land cover in Pearl City (Thoothukudi) with spatial technology

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    https://www.riss.kr/link?id=A105096128

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Land use land cover (LU/LC) changes over the period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. The virtual assessment of LU/LC changes between 2000 and 2016 is carried out in Pearl City (Thoothukudi) using Remote-Sensing data and GIS tool. This change detection is done by 15 m resolution cloud-free Advanced Spaceborne Thermal Emission and Reflection Radiometer data captured during the year 2000 and 2016. The dynamic changes depict the major land use features like settlements, saltpan, crop land, vegetation, barren and water body from satellite data through supervised classifications of a maximum likelihood algorithm.
    The classified images highlight a series of constructive results in settlement (4.30%), vegetation (4.00%), saltpan (0.24%) and pessimistic results in barren land (-7.68%), crop land (-0.64%) and water body (-0.23%) respectively. The study recommends that urbanization of settlement land usage is highly mobilized in Thoothukudi coastal areas.
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    Land use land cover (LU/LC) changes over the period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. The virtual assessment of LU/LC changes between 2000 and ...

    Land use land cover (LU/LC) changes over the period are essential to understand the development of human activities within a region to define the impact of anthropogenic and natural activities. The virtual assessment of LU/LC changes between 2000 and 2016 is carried out in Pearl City (Thoothukudi) using Remote-Sensing data and GIS tool. This change detection is done by 15 m resolution cloud-free Advanced Spaceborne Thermal Emission and Reflection Radiometer data captured during the year 2000 and 2016. The dynamic changes depict the major land use features like settlements, saltpan, crop land, vegetation, barren and water body from satellite data through supervised classifications of a maximum likelihood algorithm.
    The classified images highlight a series of constructive results in settlement (4.30%), vegetation (4.00%), saltpan (0.24%) and pessimistic results in barren land (-7.68%), crop land (-0.64%) and water body (-0.23%) respectively. The study recommends that urbanization of settlement land usage is highly mobilized in Thoothukudi coastal areas.

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    참고문헌 (Reference)

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    1 Yu¨ksel, A., "Using ASTER imagery in land use/cover classification of eastern Mediterranean landscapes according to CORINE land cover project" 8 (8): 1237-1251, 2008

    2 Selvam, S., "Use of remote sensing and GIS techniques for land use and land cover mapping of Tuticorin Coast, Tamil Nadu" 2 (2): 233-241, 2012

    3 Houghton, R. A., "The US carbon budget : Contributions from land-use change" 285 (285): 574-578, 1999

    4 Landgrebe, D. A., "Signal theory methods in multispectral remote sensing" Wiley 508-, 2003

    5 Houghton, R. A., "Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000" 55 (55): 378-390, 2003

    6 Paudel, B., "Review of studies on land use and land cover change in Nepal" 13 (13): 643-660, 2016

    7 Giri, C. P., "Remote sensing of land use and land cover: Principles and applications" CRC Press 2012

    8 Wang, Y., "Remote sensing of coastal environments" CRC Press 2009

    9 Wilkie, D. S., "Remote sensing imagery for natural resources monitoring: A guide for first-time users" Columbia University Press 1996

    10 Richards, J. A., "Remote sensing digital image analysis (Vol. 3)" Springer 1999

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    12 Rajesh, S. V. J. S. S., "Pennar (Somasila) to Cauvery (Grand Anicut) inter basin water transfer impact assessment on land use/land cover environment" 9 (9): 393-, 2017

    13 Khan, M. M. H., "Natural disasters and landuse/land-cover change in the southwest coastal areas of Bangladesh" 15 (15): 241-250, 2015

    14 Rawat, J. S., "Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India" 18 (18): 77-84, 2015

    15 Kumaravel, S., "Monitoring land cover changes in the parts of east cost of Tamilnadu and Pondicherry Union Territory using geospatial technology" 2 (2): 2013

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    17 Nagamani, K., "Land use/land cover in pondicherry using remote sensing and GIS" 15-17, 2003

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    19 Townshend, J., "Land remote sensing and global environmental change, Remote sensing and digital image processing Vol. 11" Springer 835-856, 2011

    20 Lu, D., "Land cover classification in a complex urban-rural landscape with QuickBird imagery" 76 (76): 1159-1168, 2010

    21 Otukei, J. R., "Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms" 12 : S27-S31, 2010

    22 Meyer, W. B., "Human population growth and global land-use/cover change" 23 : 39-61, 1992

    23 Lambin, E. F., "Global land use change, economic globalization, and the looming land scarcity" 108 (108): 3465-3472, 2011

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    25 Thenkabail, P. S., "Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data" 95 (95): 317-341, 2005

    26 Erle, E., "Encyclopedia of earth" Environmental Information Coalition, National Council for Science and the Environment 2007

    27 Jamal, J. A., "Dynamic land use/cover change modelling:Geosimulation and multiagent-based modelling" Springer Science & Business Media 2011

    28 Ninomiya, Y., "Detecting lithology with Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) multispectral thermal infrared ‘‘radianceat-sensor’’ data" 99 (99): 127-139, 2005

    29 He, C., "Detecting land-use/land-cover change in rural–urban fringe areas using extended change-vector analysis" 13 (13): 572-585, 2011

    30 Kesgin, B., "Comparison of pixel-based and object-based classification methods in detecting land use/land cover dynamics" IOS Press 173-, 2009

    31 Waske, B., "Classifier ensembles for land cover mapping using multitemporal SAR imagery" 64 (64): 450-457, 2009

    32 Ramankutty, N., "Characterizing patterns of global land use: An analysis of global croplands data" 12 (12): 667-685, 1998

    33 Lu, D., "Change detection techniques" 25 (25): 2365-2401, 2004

    34 Samanta, S., "Change detection of land use and land cover over a period of 20 years in Papua New Guinea" 8 (8): 138-, 2016

    35 Oyinloye, M. A. A., "Application of IKONOS satellite images in monitoring of urban landuse change in Ikeja, GRA, Lagos, Nigeria" 2 (2): 1-10, 2013

    36 Dean, A. M., "An evaluation of per-parcel land cover mapping using maximum likelihood class probabilities" 24 (24): 2905-2920, 2003

    37 Soundranayagam, J. P., "An analysis of land use pattern in the industrial development city using high resolution satellite imagery" 21 (21): 79-88, 2011

    38 Anderson, J. R., "A land use and land cover classification system for use with remote sensor data (Vol. 964)" US Government Printing Office 1976

    39 Szuster, B. W., "A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones" 31 (31): 525-532, 2011

    40 Tehrany, M. S., "A comparative assessment between object and pixel-based classification approaches for land use/land cover mapping using SPOT 5imagery" 29 (29): 351-369, 2014

    41 Giri, C., "A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets" 94 (94): 123-132, 2005

    42 Rosenfield, G. H., "A coefficient of agreement as a measure of thematic classification accuracy" 52 (52): 223-227, 1986

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