MAPPING SUBMERGED AQUATIC VEGETATION IN ALBEMARLE SOUND, NORTH CAROLINA, USA USING LANDSAT-8 AND SONAR DATA

被引:3
|
作者
Luo, Xuelian [1 ]
Wang, Yong [1 ,2 ,5 ]
Luczhovich, Joseph [3 ,4 ]
机构
[1] UESTC, West Hitech Zone, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China
[2] East Carolina Univ, Dept Geog Planning & Environm, Greenville, NC 27858 USA
[3] East Carolina Univ, Inst Coastal Sci & Policy, Greenville, NC 27858 USA
[4] East Carolina Univ, Dept Biol, Greenville, NC 27858 USA
[5] UESTC, Big Data Res Ctr, Inst Remote Sensing Big Data, West Hitech Zone, 2006 Xiyuan Ave, Chengdu 611731, Sichuan, Peoples R China
关键词
Coastal aquatic ecosystem; Landsat-8; North Carolina coast; Submerged aquatic vegetation (SAV); ECOSYSTEMS;
D O I
10.1109/IGARSS.2016.7729986
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As one of most valuable and vulnerable resources in coastal aquatic ecosystems, submerged aquatic vegetation (SAV) and its state have received great attention. There is an urgent need for coastal managers and researches to monitor and assess spatial and temporal distributions of the SAV rapidly. Because of the repetitive coverage, satellite hi-resolution images are proved to be efficient but not suitable in large-scale spatial and multiple temporal assessment due to the concern of cost. Thus, the objective of this research is to probe into the suitability of Landsat-8 OLI data in the mapping of SAV habitats at Albemarle Sound, North Carolina, USA. With SONAR data as in situ measurement, the overall accuracy based on the number (n) of SAV points detected the SONAR per cell was 66.7% if n >= 1, 68.3% when n >= 6, and 67.8% if n >= 10. The cell size was 15mx15m. Thus, the distribution of SAV beds was efficiently depicted using multi-temporal Landsat-8 data. The phenological changes of SAV were revealed.
引用
收藏
页码:3802 / 3805
页数:4
相关论文
共 50 条
  • [41] Mapping terrestrial groundwater-dependent ecosystems in arid Australia using Landsat-8 time-series data and singular value decomposition
    Box, Jayne Brim
    Leiper, Ian
    Nano, Catherine
    Stokeld, Danielle
    Jobson, Peter
    Tomlinson, Adrian
    Cobban, Dale
    Bond, Tim
    Randall, Debbie
    Box, Paul
    REMOTE SENSING IN ECOLOGY AND CONSERVATION, 2022, 8 (04) : 464 - 476
  • [42] Fusing Landsat-8, Sentinel-1, and Sentinel-2 Data for River Water Mapping Using Multidimensional Weighted Fusion Method
    Liu, Qihang
    Zhang, Shiqiang
    Wang, Ninglian
    Ming, Yisen
    Huang, Chang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [44] MAPPING VEGETATION AND MEASURING THE PERFORMANCE OF MACHINE LEARNING ALGORITHM IN LULC CLASSIFICATION IN THE LARGE AREA USING SENTINEL-2 AND LANDSAT-8 DATASETS OF DEHRADUN AS A TEST CASE
    Srivastava, Anubhava
    Bharadwaj, Shruti
    Dubey, Rakesh
    Sharma, Vinarma Bhushan
    Biswas, Susham
    XXIV ISPRS CONGRESS: IMAGING TODAY, FORESEEING TOMORROW, COMMISSION III, 2022, 43-B3 : 529 - 535
  • [45] Estimation of Above-Ground Mangrove Biomass Using Landsat-8 Data- Derived Vegetation Indices: A Case Study in Quang Ninh Province, Vietnam
    Hai-Hoa Nguyen
    Huy Duc Vu
    Roeder, Achim
    FOREST AND SOCIETY, 2021, 5 (02) : 506 - 525
  • [46] Lithological discrimination and mineralogical mapping using Landsat-8 OLI and ASTER remote sensing data: Igoudrane region, jbel saghro, Anti Atlas, Morocco
    Baid, Soukaina
    Tabit, Abdelhalim
    Algouti, Ahmed
    Algouti, Abdellah
    Nafouri, Imane
    Souddi, Sabir
    Aboulfaraj, Abdelfattah
    Ezzahzi, Salma
    Elghouat, Akram
    HELIYON, 2023, 9 (07)
  • [47] Inland Lakes Mapping for Monitoring Water Quality Using a Detail/Smoothing-Balanced Conditional Random Field Based on Landsat-8/Levels Data
    Wei, Lifei
    Zhang, Yu
    Huang, Can
    Wang, Zhengxiang
    Huang, Qingbin
    Yin, Feng
    Guo, Yue
    Cao, Liqin
    SENSORS, 2020, 20 (05)
  • [48] Assessing the performance of machine learning algorithms for soil salinity mapping in Google Earth Engine platform using Sentinel-2A and Landsat-8 OLI data
    Aksoy, Samet
    Yildirim, Aylin
    Gorji, Taha
    Hamzehpour, Nikou
    Tanik, Aysegul
    Sertel, Elif
    ADVANCES IN SPACE RESEARCH, 2022, 69 (02) : 1072 - 1086
  • [49] Enhanced lithological mapping of Durba-Araba basement blocks, along the eastern margin of the Central Gulf of Suez Rift, Egypt, using Landsat-8 Data
    Adel M. Seleim
    Mahmoud H. Bekiet
    Mohamed S. Hammed
    Arabian Journal of Geosciences, 2022, 15 (14)
  • [50] Understanding the potentials of early-season crop type mapping by using Landsat-8, Sentinel-1/2, and GF-1/6 data
    Wang, Cong
    Zhang, Xinyu
    Wang, Wenjing
    Wei, Haodong
    Wang, Jiayue
    Li, Zexuan
    Li, Xiuni
    Wu, Hao
    Hu, Qiong
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 224