Seasonal change monitoring and mapping of coastal vegetation types along Midnapur-Balasore Coast, Bay of Bengal using multi-temporal landsat data

被引:10
|
作者
Jana A. [1 ,2 ]
Maiti S. [2 ]
Biswas A. [3 ]
机构
[1] NRDMS Centre, Office of the District Magistrate, Administrative Building, Purba Medinipur, Tamluk, 721636, WB
[2] Department of Geology and Geophysics, Indian Institute of Technology Kharagpur, Kharagpur, 721302, WB
[3] Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal, 462066, MP
关键词
Coastal vegetation; Midnapur-Balasore coast; NDVI (normalized differential vegetation index); Remote sensing; RGB-NDVI; Seasonal change;
D O I
10.1007/s40808-015-0062-x
中图分类号
学科分类号
摘要
The present study highlights the application of satellite remote sensing in seasonal change monitoring and mapping of coastal vegetation types along Midnapur-Balasore coast, Bay of Bengal, using multi-temporal satellite images of Landsat ETM+ of 2000, 2001 and 2002 of pre-monsoon and post-monsoon seasons. Two types of image analysis techniques were applied in this study to identify different species of coastal vegetations, health and their areal extent. RGB-NDVI was computed to detect and monitor the changes of vegetation health during pre and post-monsoon period. Another technique is supervised digital classification was used for mapping of different coastal vegetations and to determine their spatial extent of the study area. Five major coastal vegetation types were delineated using satellite data viz., dune vegetation, mangroves, salt marsh, agricultural lands and other vegetations. An attempt has been made to analyze seasonal change monitoring and mapping of different coastal vegetations communities including mangroves, salt marsh, and dune vegetation from 2000 to 2002 using Landsat 7 ETM+ data. From 2000 to 2002 it is observed that the areal extent of salt marsh and dune vegetation is changed seasonally along each littoral cell. It is increased during post-monsoon season and decrease during pre-monsoon season. In this period, the gain of 704.34 ha area of salt marsh and 2153.88 ha area of dune vegetations cover was noticed. During post-monsoon period the mangrove vegetation covers along all littoral cells have increased this may be due to supply of huge amount of sediment and increase of salinity condition after monsoon. But over the entire 3 years period from pre-monsoon 2000 to post-monsoon 2002 the net change was negative, which was quantified as 61.83 ha. The depletion of mangroves may be due to high anthropogenic pressure, commercial aquaculture, highly eroding nature of the coast and tidal activities. The NDVI derived from ETM+ images provide useful information to monitor coastal vegetation changes, especially the natural plants growing on sand dunes, mangroves and salt marsh vegetations. The analysis of NDVI variations showed the qualitative information about the vegetation. On the other hand classified image provide quantitative information about the coastal vegetation. © 2015, Springer International Publishing Switzerland.
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  • [1] Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform
    Aghababaei, Masoumeh
    Ebrahimi, Ataollah
    Naghipour, Ali Asghar
    Asadi, Esmaeil
    Verrelst, Jochem
    [J]. REMOTE SENSING, 2021, 13 (22)
  • [2] FOREST MAPPING AND MONITORING IN TASMANIA USING MULTI-TEMPORAL LANDSAT AND ALOS-PALSAR DATA
    Lehmann, E. A.
    Zhou, Z. -S.
    Caccetta, P.
    Milne, A.
    Mitchell, A.
    Lowell, K.
    Held, A.
    [J]. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 6431 - 6434
  • [3] Shoreline change monitoring for coastal zone management using multi-temporal Landsat data in Mahi River estuary, Gujarat State
    Patel, Krunal
    Jain, Rajmal
    Patel, Ajay N.
    Kalubarme, Manik H.
    [J]. APPLIED GEOMATICS, 2021, 13 (03) : 333 - 347
  • [4] Shoreline change monitoring for coastal zone management using multi-temporal Landsat data in Mahi River estuary, Gujarat State
    Krunal Patel
    Rajmal Jain
    Ajay N. Patel
    Manik H. Kalubarme
    [J]. Applied Geomatics, 2021, 13 : 333 - 347
  • [5] Shoreline change assessment for various types of coasts using multi-temporal Landsat imagery of the east coast of South Korea
    Choung, Yun-Jae
    Jo, Myung-Hee
    [J]. REMOTE SENSING LETTERS, 2016, 7 (01) : 91 - 100
  • [6] Dynamic monitoring of land use change in Loess Plateau using multi-temporal Landsat TM data
    Hou, XY
    Liu, JY
    Gao, ZQ
    Zhuang, DF
    Yu, XF
    [J]. REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY, 2004, 5544 : 380 - 389
  • [7] Monitoring Land Use and Land Cover Change in the Source Region of the Yangtze River Using Multi-Temporal Landsat Data
    Hu, Guangyin
    Dong, Zhibao
    Lu, Junfeng
    Yan, Changzhen
    [J]. 2011 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND CONTROL (ICECC), 2011, : 340 - 343
  • [8] Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data
    Miller, JD
    Yool, SR
    [J]. REMOTE SENSING OF ENVIRONMENT, 2002, 82 (2-3) : 481 - 496
  • [9] Monitoring of Chilika Lake mouth dynamics and quantifying rate of shoreline change using 30 m multi-temporal Landsat data
    Vivek, G.
    Goswami, Santonu
    Samal, R. N.
    Choudhury, S. B.
    [J]. DATA IN BRIEF, 2019, 22 : 595 - 600