Seeing the System from Above: The Use and Potential of Remote Sensing for Studying Ecosystem Dynamics

被引:0
作者
Cornelius Senf
机构
[1] Technical University of Munich,
[2] School of Life Sciences,undefined
[3] Ecosystem Dynamics and Forest Management Group,undefined
来源
Ecosystems | 2022年 / 25卷
关键词
remote sensing; satellite; geospatial; imagery; airborne; drone;
D O I
暂无
中图分类号
学科分类号
摘要
Remote sensing techniques are increasingly used for studying ecosystem dynamics, delivering spatially explicit information on the properties of Earth over large spatial and multi-decadal temporal extents. Yet, there is still a gap between the more technology-driven development of novel remote sensing techniques and their applications for studying ecosystem dynamics. Here, I review the existing literature to explore how addressing these gaps might enable recent methods to overcome longstanding challenges in ecological research. First, I trace the emergence of remote sensing as a major tool for understanding ecosystem dynamics. Second, I examine recent developments in the field of remote sensing that are of particular importance for studying ecosystem dynamics. Third, I consider opportunities and challenges for emerging open data and software policies and suggest that remote sensing is at its most powerful when it is theoretically motivated and rigorously ground-truthed. I close with an outlook on four exciting new research frontiers that will define remote sensing ecology in the upcoming decade.
引用
收藏
页码:1719 / 1737
页数:18
相关论文
共 1038 条
[21]  
Daskalova GN(2019)Uncovering ecological patterns with convolutional neural networks Trends in Ecology & Evolution 34 734-1205
[22]  
Atkins JW(2020)Terrestrial laser scanning in forest ecology: Expanding the horizon Remote Sensing of Environment 251 112102-2365
[23]  
Stovall AEL(2007)Hyperspectral remote sensing of canopy biodiversity in Hawaiian Lowland Rainforests Ecosystems 10 536-587
[24]  
Alberto Silva C(2001)Detecting vegetation leaf water content using reflectance in the optical domain Remote Sensing of Environment 77 22-263
[25]  
Bae S(2015)Risk perception and the public acceptance of drones Risk Analysis 35 1167-664
[26]  
Levick SR(2004)Landsat’s role in ecological applications of remote sensing BioScience 54 535-143
[27]  
Heidrich L(2002)Characterizing 23 Years (1972–95) of stand replacement disturbance in Western Oregon forests with Landsat imagery Ecosystems 5 122-691
[28]  
Magdon P(2014)Recovery and resilience of tropical forests after disturbance Nature Communications 5 3906-610
[29]  
Leutner BF(2016)Copernicus high-resolution layers for land cover classification in Italy Journal of Maps 12 1195-17
[30]  
Wöllauer S(2010)Assessing changes in forest fragmentation following infestation using time series Landsat imagery Forest Ecology and Management 259 2355-7081