skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Remote Sensing of Tundra Ecosystems Using High Spectral Resolution Reflectance: Opportunities and Challenges
Abstract Observing the environment in the vast regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including National Aeronautics and Space Administration’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low‐stature plants and very fine‐scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long‐term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi‐scale spectroscopy, from lab studies to satellites that enable frequent and continuous long‐term monitoring, to inform statistical and biophysical approaches to model vegetation dynamics.  more » « less
Award ID(s):
1836898
PAR ID:
10374910
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Journal of Geophysical Research: Biogeosciences
Volume:
127
Issue:
2
ISSN:
2169-8953
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Chen, Jing M (Ed.)
    The Arctic is warming faster than anywhere else on Earth, placing tundra ecosystems at the forefront of global climate change. Plant biomass is a fundamental ecosystem attribute that is sensitive to changes in climate, closely tied to ecological function, and crucial for constraining ecosystem carbon dynamics. However, the amount, functional composition, and distribution of plant biomass are only coarsely quantified across the Arctic. Therefore, we developed the first moderate resolution (30 m) maps of live aboveground plant biomass (g m− 2) and woody plant dominance (%) for the Arctic tundra biome, including the mountainous Oro Arctic. We modeled biomass for the year 2020 using a new synthesis dataset of field biomass harvest measurements, Landsat satellite seasonal synthetic composites, ancillary geospatial data, and machine learning models. Additionally, we quantified pixel-wise uncertainty in biomass predictions using Monte Carlo simulations and validated the models using a robust, spatially blocked and nested cross-validation procedure. Observed plant and woody plant biomass values ranged from 0 to ~6000 g m− 2 (mean ≈350 g m− 2), while predicted values ranged from 0 to ~4000 g m− 2 (mean ≈275 g m− 2), resulting in model validation root-mean-squared-error (RMSE) ≈400 g m− 2 and R2 ≈ 0.6. Our maps not only capture large-scale patterns of plant biomass and woody plant dominance across the Arctic that are linked to climatic variation (e.g., thawing degree days), but also illustrate how fine-scale patterns are shaped by local surface hydrology, topography, and past disturbance. By providing data on plant biomass across Arctic tundra ecosystems at the highest resolution to date, our maps can significantly advance research and inform decision-making on topics ranging from Arctic vegetation monitoring and wildlife conservation to carbon accounting and land surface modeling 
    more » « less
  2. Tundra vegetation productivity and composition are responding rapidly to climatic changes in the Arctic. These changes can, in turn, mitigate or amplify permafrost thaw. In this Review, we synthesize remotely sensed and field-observed vegetation change across the tundra biome, and outline how these shifts could influence permafrost thaw. Permafrost ice content appears to be an important control on local vegetation changes; woody vegetation generally increases in ice-poor uplands, whereas replacement of woody vegetation by (aquatic) graminoids following abrupt permafrost thaw is more frequent in ice-rich Arctic lowlands. These locally observed vegetation changes contribute to regional satellite-observed greening trends, although the interpretation of greening and browning is complicated. Increases in vegetation cover and height generally mitigate permafrost thaw in summer, yet, increase annual soil temperatures through snow-related winter soil warming effects. Strong vegetation–soil feedbacks currently alleviate the consequences of thaw-related disturbances. However, if the increasing scale and frequency of disturbances in a warming Arctic exceeds the capacity for vegetation and permafrost recovery, changes to Arctic ecosystems could be irreversible. To better disentangle vegetation– soil– permafrost interactions, ecological field studies remain crucial, but require better integration with geophysical assessments. 
    more » « less
  3. Abstract Arctic warming can influence tundra ecosystem function with consequences for climate feedbacks, wildlife and human communities. Yet ecological change across the Arctic tundra biome remains poorly quantified due to field measurement limitations and reliance on coarse-resolution satellite data. Here, we assess decadal changes in Arctic tundra greenness using time series from the 30 m resolution Landsat satellites. From 1985 to 2016 tundra greenness increased (greening) at ~37.3% of sampling sites and decreased (browning) at ~4.7% of sampling sites. Greening occurred most often at warm sampling sites with increased summer air temperature, soil temperature, and soil moisture, while browning occurred most often at cold sampling sites that cooled and dried. Tundra greenness was positively correlated with graminoid, shrub, and ecosystem productivity measured at field sites. Our results support the hypothesis that summer warming stimulated plant productivity across much, but not all, of the Arctic tundra biome during recent decades. 
    more » « less
  4. Cumulative impact assessments (CIAs) for new Arctic oilfields have not adequately addressed the potential landscape impacts of climate change or the indirect impacts of infrastructure in areas with ice-rich permafrost (IRP) (e.g., Raynolds et al. 2020). The main goals of this paper are: (1) trace the history of remote sensing for assessing past cumulative impacts in the Prudhoe Bay Oilfield (PBO), Alaska; (2) discuss some promising new remote-sensing and modeling tools; and (3) point toward improved capability to predict future changes. We first define IRP and cumulative impacts (CIs) and distinguish direct impacts (footprint) of infrastructure from the indirect impacts that follow construction. Aerial photographs (U.S. Navy 1948–1949) provided images of PBO landscapes before development occurred. The oil industry initiated annual high-resolution aerial-photograph missions of the PBO in 1968. In the same year, the International Biological Program (IBP) Tundra Biome started geoecological investigations that used these images to map landforms, soils, and vegetation of the PBO (Walker et al. 1980). The maps were later adapted to GIS approaches in three highly impacted 25-km2 areas of the PBO, which included several years of changes to tundra areas adjacent to infrastructure (Walker et al. 1987). The National Research Council later updated these three landscape-scale maps to 2001 and contracted the oil companies and Quantum Spatial Inc. to produce a regional-scale historical analysis of the network of roads, pipelines and other forms of infrastructure in all the North Slope Oilfields (NRC 2003). The regional- and landscape-scale maps used for NRC analysis were updated again in 2010 when unexpected rapid expansion of ice-wedge thermokarst was detected (Raynolds et al. 2014, 2016). Up to this time, CIAs of the PBO relied on aerial photographs and maps produced by the oil industry. The spatial resolution of available satellite-based remote-sensing data was insufficient to discern the details of periglacial landforms (e.g., ice-wedge polygons and nonsorted circles) or of roads, pipelines, or changes to land surfaces adjacent to infrastructure. Industry-sponsored studies that used remote-sensing products included studies of oil-pipeline spills, reserve-pits leaks (e.g., Jorgenson et al. 1995), off-road vehicles trails, and recovery following removal of gravel pads. Highlighted studies for this talk include a new NSF project that is part of the NSF Navigating the New Arctic initiative that is using integrated ground-based studies, advanced remote-sensing tools, and improved modeling approaches to examine climate- and infrastructure-related changes (Walker et al. 2022, Bergstedt 2022). Other projects that use PBO datasets for calibration, include an analysis of long-term impacts from a catastrophic flood (Shur et al. 2016, Zwieback et al. 2021) and studies that are using massive amounts of high-resolution imagery and pattern-recognition tools to detect and map ice-wedge polygons, water bodies, and infrastructure across the circumpolar Arctic (Bartsch et al. 2020; Witherrana et al. 2021). These tools combined with improved modeling approaches that bridge the gap between regional and engineering scales (e.g., Deimling et al. 2021) promise to greatly improve our ability to predict and monitor future infrastructure and landscape changes in areas with IRP. 
    more » « less
  5. Abstract Changes in vegetation productivity based on normalized difference vegetation index (NDVI) have been reported from Arctic regions. Most studies use very coarse spatial resolution remote sensing data that cannot isolate landscape level factors. For example, on Yamal Peninsula in West Siberia enhanced willow growth has been linked to widespread landslide activity, but the effect of landslides on regional NDVI dynamics is unknown. Here we apply a novel satellite-based NDVI analysis to investigate the vegetation regeneration patterns of active-layer detachments following a major landslide event in 1989. We analyzed time series data of Landsat and very high-resolution (VHR) imagery from QuickBird-2 and WorldView-2 and 3 characterizing a study area of ca. 35 km2. Landsat revealed that natural regeneration of low Arctic tundra progressed rapidly during the first two decades after the landslide event. However, during the past decade, the difference between landslide shear surfaces and surrounding areas remained relatively unchanged despite the advance of vegetation succession. Time series also revealed that NDVI generally declined since 2013 within the study area. The VHR imagery allowed detection of NDVI change ‘hot-spots’ that included temporary degradation of vegetation cover, as well as new and expanding thaw slumps, which were too small to be detected from Landsat satellite data. Our study demonstrates that landslides can have pronounced and long-lasting impacts on tundra vegetation. Thermokarst landslides and associated impacts on vegetation will likely become increasingly common in NW Siberia and other Arctic regions with continued warming. 
    more » « less