Detecting and mapping vegetation distribution on the Antarctic Peninsula from remote sensing data

被引:0
|
作者
P. T. Fretwell
P. Convey
A. H. Fleming
H. J. Peat
K. A. Hughes
机构
[1] British Antarctic Survey,
[2] NERC,undefined
来源
Polar Biology | 2011年 / 34卷
关键词
Remote sensing; Vegetation mapping; Climate change; Regional warming; NDVI; Antarctica;
D O I
暂无
中图分类号
学科分类号
摘要
We present the first regional map of vegetation of anywhere on the Antarctic continent based on remote sensing (RS) data. We have used a normalized difference vegetation index (NDVI) for the examination of Landsat ETM data on the Antarctic Peninsula. The results show that 44.6 km2 (0.086%) of the study area (74,468 km2) is classed with a probability of vegetation of over 50%. The NDVI analysis is ground-truthed against vegetation surveys in Ryder Bay on the Antarctic Peninsula, and the results have been corrected for several factors influencing low NDVI readings in this environment. This methodology has been applied to 13 Landsat scenes covering Graham Land in the Northern part of the Antarctic Peninsula to examine the distribution of vegetation in the region. The Antarctic Peninsula region is important, as it has shown rapid warming of over 3°C during the past 50 years, and predictions indicate accelerated future warming. A baseline survey of the amount and distribution of vegetation is required against which to monitor future change. The results give a comprehensive coverage and allow us to present the first remote sensing-based vegetation map in Antarctica. However, initial results point to the need for further investigation of apparent errors resulting from geology on bare ground.
引用
收藏
页码:273 / 281
页数:8
相关论文
共 50 条
  • [21] Remote sensing of vegetation surrogates for regolith landform mapping
    Benger, SN
    IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES, 2003, : 3320 - 3322
  • [22] Comparison of remote sensing techniques for alien vegetation mapping
    Rowlinson, L
    Summerton, M
    Ahmed, F
    PROCEEDINGS OF THE 1998 SOUTH AFRICAN SYMPOSIUM ON COMMUNICATIONS AND SIGNAL PROCESSING: COMSIG '98, 1998, : 475 - 476
  • [23] Experimental vegetation mapping study using remote sensing
    Sellin, Vanessa
    Magnanon, Sylvie
    Gourmelon, Francoise
    Debaine, Francoise
    Nabucet, Jean
    CYBERGEO-EUROPEAN JOURNAL OF GEOGRAPHY, 2015,
  • [24] Mapping large-scale distribution of submerged aquatic vegetation coverage using remote sensing
    Yuan, Lin
    Zhang, Li-Quan
    ECOLOGICAL INFORMATICS, 2008, 3 (03) : 245 - 251
  • [25] Spatial video remote sensing for urban vegetation mapping using vegetation indices
    Luka Rumora
    Ivan Majić
    Mario Miler
    Damir Medak
    Urban Ecosystems, 2021, 24 : 21 - 33
  • [26] Spatial video remote sensing for urban vegetation mapping using vegetation indices
    Rumora, Luka
    Majic, Ivan
    Miler, Mario
    Medak, Damir
    URBAN ECOSYSTEMS, 2021, 24 (01) : 21 - 33
  • [27] Mapping Global Bamboo Forest Distribution Using Multisource Remote Sensing Data
    Du, Huaqiang
    Mao, Fangjie
    Li, Xuejian
    Zhou, Guomo
    Xu, Xiaojun
    Han, Ning
    Sun, Shaobo
    Gao, Guolong
    Cui, Lu
    Li, Yangguang
    Zhu, Dien
    Liu, Yuli
    Chen, Liang
    Fan, Weiliang
    Li, Pingheng
    Shi, Yongjun
    Zhou, Yufeng
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (05) : 1458 - 1471
  • [28] Spectroscopic remote sensing for material identification, vegetation characterization, and mapping
    Kokaly, Raymond F.
    ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XVIII, 2012, 8390
  • [29] Evaluating the Potential of Vegetation Indices in Detecting Drought Impact Using Remote Sensing Data in a Mediterranean Pinewood
    Cucca, Benedetta
    Recanatesi, Fabio
    Ripa, Maria Nicolina
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2020, PT V, 2020, 12253 : 50 - 62
  • [30] Landslide susceptibility mapping by remote sensing and geomorphological data: case studies on the Sorrentina Peninsula (Southern Italy)
    Spinetti, Claudia
    Bisson, Marina
    Tolomei, Cristiano
    Colini, Laura
    Galvani, Alessandro
    Moro, Marco
    Saroli, Michele
    Sepe, Vincenzo
    GISCIENCE & REMOTE SENSING, 2019, 56 (06) : 940 - 965