Quantifying sponge communities from shallow to mesophotic depths using orthorectified imagery

被引:3
|
作者
Lesser, Michael P. [1 ,2 ]
Slattery, Marc [3 ]
Macartney, Keir J. [4 ]
机构
[1] Univ New Hampshire, Dept Mol Cellular & Biomed Sci, Durham, NH 03824 USA
[2] Univ New Hampshire, Sch Marine Sci & Ocean Engn, Durham, NH 03824 USA
[3] Univ Mississippi, Dept Biomol Sci, University, MS 38677 USA
[4] Univ Texas Rio Grande Valley, Sch Earth Environm & Marine Sci, Port Isabel, TX 78958 USA
基金
美国国家科学基金会;
关键词
Mesophotic; ROV; AUV; Geometric distortion; Photogrammetry; Imagery; Plotless design; BENTHIC COVER; CORAL-REEFS; ECOLOGY; HABITAT; COUNT;
D O I
10.1007/s00227-023-04258-5
中图分类号
Q17 [水生生物学];
学科分类号
071004 ;
摘要
Mesophotic coral reefs are estimated to represent up to 80% of the total areal coverage for coral reefs worldwide. Quantifying mesophotic coral reef community structure and function, at multiple spatial and temporal scales, and the ability to monitor these attributes repeatedly and accurately, is an ecological priority. Recent discussions on the relative merits of remotely operated vehicles and autonomous underwater vehicles (ROVs and AUVs, respectively) versus the use of technical divers using quadrats or photoquadrats to obtain quantitative imagery undervalues the distinct and important complimentary roles that both approaches bring to the study of mesophotic coral reefs. However, all platforms must adhere to fundamental photogrammetry principles to accomplish the goal of accurate and repeatable surveys of coral reefs. Here we show that quantifying the projected surface area of sponge populations for a tropical coral reef on Puerto Rico using ROV imagery, not originally collected for ecological characterizations, requires specific screening guidelines to ensure the images are orthogonal and processed to obtain orthorectified images for the quantification of benthic communities. This is required to minimize multiple sources of error that could confound quantitative estimates of percent cover, biomass, and/or abundance of benthic taxa on shallow and mesophotic coral reefs using plot, or plotless, designs.
引用
收藏
页数:10
相关论文
共 38 条
  • [31] Quantifying 3D coral reef structural complexity from 2D drone imagery using artificial intelligence
    Suan, Aviv
    Franceschini, Simone
    Madin, Joushua
    Madin, Elizabeth
    ECOLOGICAL INFORMATICS, 2025, 85
  • [32] Quantifying Sub-Pixel Surface Water Coverage in Urban Environments Using Low-Albedo Fraction from Landsat Imagery
    Sun, Weiwei
    Du, Bo
    Xiong, Shaolong
    REMOTE SENSING, 2017, 9 (05):
  • [33] Can chlorophyll-a in meso-oligotrophic shallow waters be estimated using statistical approaches and empirical models from MODIS imagery?
    Munar, Andres Mauricio
    Cavalcanti, Jose Rafael
    Bravo, Juan Martin
    Lelinho Da Motta Marques, David Manuel
    Fragoso Junior, Carlos Ruberto
    RBRH-REVISTA BRASILEIRA DE RECURSOS HIDRICOS, 2018, 23
  • [34] Quantifying the heat flux and outflow rate of hot springs using airborne thermal imagery: Case study from Pilgrim Hot Springs, Alaska
    Haselwimmer, Christian
    Prakash, Anupma
    Holdmann, Gwen
    REMOTE SENSING OF ENVIRONMENT, 2013, 136 : 37 - 46
  • [35] Novel Learning of Bathymetry from Landsat 9 Imagery Using Machine Learning, Feature Extraction and Meta-Heuristic Optimization in a Shallow Turbid Lagoon
    Tran, Hang Thi Thuy
    Nguyen, Quang Hao
    Pham, Ty Huu
    Ngo, Giang Thi Huong
    Pham, Nho Tran Dinh
    Pham, Tung Gia
    Tran, Chau Thi Minh
    Ha, Thang Nam
    GEOSCIENCES, 2024, 14 (05)
  • [36] Large-scale land use/land cover extraction from Landsat imagery using feature relationships matrix based deep-shallow learning
    Dou, Peng
    Shen, Huanfeng
    Huang, Chunlin
    Li, Zhiwei
    Mao, Yujun
    Li, Xinghua
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 129
  • [37] Mapping plant communities within quasi‐circular vegetation patches using tasseled cap brightness, greenness, and topsoil grain size index derived from GF-1 imagery
    Qingsheng Liu
    Chong Huang
    He Li
    Earth Science Informatics, 2021, 14 : 975 - 984
  • [38] Mapping plant communities within quasi-circular vegetation patches using tasseled cap brightness, greenness, and topsoil grain size index derived from GF-1 imagery
    Liu, Qingsheng
    Huang, Chong
    Li, He
    EARTH SCIENCE INFORMATICS, 2021, 14 (02) : 975 - 984