scholarly journals Disturbance Mapping in Arctic Tundra Improved by a Planning Workflow for Drone Studies: Advancing Tools for Future Ecosystem Monitoring

2021 ◽  
Vol 13 (21) ◽  
pp. 4466
Author(s):  
Isabell Eischeid ◽  
Eeva M. Soininen ◽  
Jakob J. Assmann ◽  
Rolf A. Ims ◽  
Jesper Madsen ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Predictive Ability ◽  
Ground Cover ◽  
Arctic Tundra ◽  
The Arctic ◽  
Ecosystem Monitoring ◽  
Selection Of Variables ◽  
State Changes ◽  
Study Sites

The Arctic is under great pressure due to climate change. Drones are increasingly used as a tool in ecology and may be especially valuable in rapidly changing and remote landscapes, as can be found in the Arctic. For effective applications of drones, decisions of both ecological and technical character are needed. Here, we provide our method planning workflow for generating ground-cover maps with drones for ecological monitoring purposes. The workflow includes the selection of variables, layer resolutions, ground-cover classes and the development and validation of models. We implemented this workflow in a case study of the Arctic tundra to develop vegetation maps, including disturbed vegetation, at three study sites in Svalbard. For each site, we generated a high-resolution map of tundra vegetation using supervised random forest (RF) classifiers based on four spectral bands, the normalized difference vegetation index (NDVI) and three types of terrain variables—all derived from drone imagery. Our classifiers distinguished up to 15 different ground-cover classes, including two classes that identify vegetation state changes due to disturbance caused by herbivory (i.e., goose grubbing) and winter damage (i.e., ‘rain-on-snow’ and thaw-freeze). Areas classified as goose grubbing or winter damage had lower NDVI values than their undisturbed counterparts. The predictive ability of site-specific RF models was good (macro-F1 scores between 83% and 85%), but the area of the grubbing class was overestimated in parts of the moss tundra. A direct transfer of the models between study sites was not possible (macro-F1 scores under 50%). We show that drone image analysis can be an asset for studying future vegetation state changes on local scales in Arctic tundra ecosystems and encourage ecologists to use our tailored workflow to integrate drone mapping into long-term monitoring programs.

scholarly journals Remote sensing assessment of glacial loss and vegetation change from 1989 to 2016: Pond Inlet, Nunavut

2021 ◽  
Author(s):  
Ruby R. Pennell
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Relevant Literature ◽  
Arctic Tundra ◽  
The Arctic ◽  
Landscape Changes ◽  
Storm Events ◽  
Time Period ◽  
Induced Changes

The climate change phenomenon occurring across the globe is having an increasingly alarming effect on Canada’s Arctic. Warming temperatures can have wide spanning impacts ranging from more rain and storm events, to increasing runoff, thawing permafrost, sea ice decline, melting glaciers, ecosystem disruption, and more. The purpose of this MRP was to assess the climate-induced landscape changes, including glacial loss and vegetation change, in Pond Inlet, Nunavut. A time series analysis was performed using the intervals 1989-1997, 1997-2005, and 2005-2016. The two methods for monitoring change were 1) the Normalized Difference Snow Index (NDSI) to detect glacial change, and 2) the Normalized Difference Vegetation Index (NDVI) to detect vegetation change, both utilizing threshold and masking techniques to increase accuracy. It was found that the percent of glacial loss and vegetation change in Pond Inlet had consistently increased throughout each time period. The area of glacial loss grew through each period to a maximum of 376 km2 of glacial loss in the last decade. Similarly, the area of the Arctic tundra that experienced vegetation change increased in each time period to a maximum of 660 km2 in the last decade. This vegetation change was characterized by overall increasing values of NDVI, revealing that many sections of the Arctic tundra in Pond Inlet were increasing in biomass. However, case study analysis revealed pixel clustering around the lower vegetation class thresholds used to classify change, indicating that shifts between these vegetation classes were likely exaggerated. Shifts between the higher vegetation classes were significant, and were what contributed to the most change in the last decade. The observations of higher glacial melt and increases in biomass are occurring in parallel with the increasing temperatures in Pond Inlet. Relevant literature in the Arctic agrees with the findings of this MRP that there are significant trends of glacial loss and vegetation greening and many studies attribute this directly to climate warming. The results of this study provide the necessary background with regards to landscape changes which could be used in future field studies investigating the climate induced changes in Pond Inlet. This study also demonstrates that significant landscape modifications have occurred in the recent decades and there is a strong need for continued research and monitoring of climate induced changes.

scholarly journals Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence

2019 ◽  
Vol 11 (12) ◽  
pp. 1460 ◽  
Author(s):  
Dongjie Fu ◽  
Fenzhen Su ◽  
Juan Wang ◽  
Yijie Sui
Keyword(s):  
Satellite Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Gross Primary Production ◽  
Remote Sensing Data ◽  
Arctic Region ◽  
Arctic Tundra ◽  
The Arctic ◽  
Global Inventory ◽  
The Arctic Region

A general greening trend in the Arctic tundra biome has been indicated by satellite remote sensing data over recent decades. However, since 2011, there have been signs of browning trends in many parts of the region. Previous research on tundra greenness across the Arctic region has relied on the satellite-derived normalized difference vegetation index (NDVI). In this research, we initially used spatially downscaled solar-induced fluorescence (SIF) data to analyze the spatiotemporal variation of Arctic tundra greenness (2007–2013). The results derived from the SIF data were also compared with those from two NDVIs (the Global Inventory Modeling and Mapping Studies NDVI3g and MOD13Q1 NDVI), and the eddy-covariance (EC) observed gross primary production (GPP). It was found that most parts of the Arctic tundra below 75° N were browning (–0.0098 mW/m2/sr/nm/year, where sr is steradian and nm is nanometer) using SIF, whereas spatially and temporally heterogeneous trends (greening or browning) were obtained based on the two NDVI products. This research has further demonstrated that SIF data can provide an alternative direct proxy for Arctic tundra greenness.

scholarly journals Remote sensing assessment of glacial loss and vegetation change from 1989 to 2016: Pond Inlet, Nunavut

2021 ◽  
Author(s):  
Ruby R. Pennell
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Relevant Literature ◽  
Arctic Tundra ◽  
The Arctic ◽  
Landscape Changes ◽  
Storm Events ◽  
Time Period ◽  
Induced Changes

The climate change phenomenon occurring across the globe is having an increasingly alarming effect on Canada’s Arctic. Warming temperatures can have wide spanning impacts ranging from more rain and storm events, to increasing runoff, thawing permafrost, sea ice decline, melting glaciers, ecosystem disruption, and more. The purpose of this MRP was to assess the climate-induced landscape changes, including glacial loss and vegetation change, in Pond Inlet, Nunavut. A time series analysis was performed using the intervals 1989-1997, 1997-2005, and 2005-2016. The two methods for monitoring change were 1) the Normalized Difference Snow Index (NDSI) to detect glacial change, and 2) the Normalized Difference Vegetation Index (NDVI) to detect vegetation change, both utilizing threshold and masking techniques to increase accuracy. It was found that the percent of glacial loss and vegetation change in Pond Inlet had consistently increased throughout each time period. The area of glacial loss grew through each period to a maximum of 376 km2 of glacial loss in the last decade. Similarly, the area of the Arctic tundra that experienced vegetation change increased in each time period to a maximum of 660 km2 in the last decade. This vegetation change was characterized by overall increasing values of NDVI, revealing that many sections of the Arctic tundra in Pond Inlet were increasing in biomass. However, case study analysis revealed pixel clustering around the lower vegetation class thresholds used to classify change, indicating that shifts between these vegetation classes were likely exaggerated. Shifts between the higher vegetation classes were significant, and were what contributed to the most change in the last decade. The observations of higher glacial melt and increases in biomass are occurring in parallel with the increasing temperatures in Pond Inlet. Relevant literature in the Arctic agrees with the findings of this MRP that there are significant trends of glacial loss and vegetation greening and many studies attribute this directly to climate warming. The results of this study provide the necessary background with regards to landscape changes which could be used in future field studies investigating the climate induced changes in Pond Inlet. This study also demonstrates that significant landscape modifications have occurred in the recent decades and there is a strong need for continued research and monitoring of climate induced changes.

Positive response of tree productivity to warming is reversed by increased tree density at the Arctic tundra-taiga ecotone

2021 ◽  
Author(s):  
Xanthe Walker ◽  
Heather D. Alexander ◽  
Logan Berner ◽  
Melissa A Boyd ◽  
Michael M. Loranty ◽  
...  
Keyword(s):  
Tree Growth ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arctic Tundra ◽  
Tree Density ◽  
The Arctic ◽  
Growth Responses ◽  
Annual Variations ◽  
Stand Productivity ◽  
Active Layers

The transition zone between the northern boreal forest and the arctic tundra, known as the tundra-taiga ecotone (TTE) has undergone rapid warming in recent decades. In response to this warming, tree density, growth, and stand productivity are expected to increase. Increases in tree density have the potential to negate the positive impacts of warming on tree growth through a reduction in the active layer and an increase in competitive interactions. We assessed the effects of tree density on tree growth and climate-growth responses of Cajander larch (<i>Larix cajanderi</i>) and on trends in the normalized difference vegetation index (NDVI) in the TTE of Northeast Siberia. We examined 19 mature forest stands that all established after a fire in 1940 and ranged in tree density from 300 to 37,000 stems ha-1. High density stands with shallow active layers had lower tree growth, higher stand productivity, and more negative growth responses to growing season temperatures compared to low density stands with deep active layers. Variation in stand productivity across the density gradient was not captured by Landsat derived NDVI, but NDVI did capture annual variations in stand productivity. Our results suggest that the expected increases in tree density following fires at the TTE may effectively limit tree growth and that NDVI is unlikely to capture increasing productivity associated with changes in tree density.

scholarly journals Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

2020 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Manuel Ángel Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando José Aguilar ◽  
Dilek Koc-San ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Remote Sensing Techniques ◽  
Image Pairs ◽  
Study Sites ◽  
High Level ◽  
Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

Decreased photosynthetic efficiency in plant species exposed to multiple airborne pollutants along the Russian-Norwegian border

2000 ◽  
Vol 78 (8) ◽  
pp. 1021-1033 ◽  
Author(s):  
Ann Marie Odasz-Albrigtsen ◽  
Hans Tømmervik ◽  
Patrick Murphy
Keyword(s):  
Chlorophyll Fluorescence ◽  
Plant Species ◽  
Photosynthetic Efficiency ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Plant Cover ◽  
Mixed Forest ◽  
Airborne Pollutants ◽  
Fluorescence Measurements ◽  
Study Sites

Photosynthetic efficiency was estimated by chlorophyll fluorescence measurements (Fv/Fm) in 11 plant species growing along a steep gradient of airborne pollution along the Russian-Norwegian border (70°N, 30°E). Photosynthetic efficiency was positively correlated with environmental variables including annual temperature and a maritime gradient and was negatively correlated with the airborne concentrations of Cu, Ni, and SO2 from the Cu-Ni smelters. Photosynthetic efficiency in six plant species from the mixed forest, but not pine (Pinus sylvestris L.), and three species from the birch forest was inversely correlated with SO2 and the concentrations of Ni and Cu in lichens. Measurement of fluorescence in these species was a sensitive indicator of pollutant impact. Plant cover at the 16 study sites and the photosynthetic efficiency of five target species correlated with normalized difference vegetation index (NDVI) values. This study demonstrated that it is possible to detect relations among field-measured ecophysiological responses in plants, levels of airborne pollutants, and satellite remote-sensed data.Key words: chlorophyll fluorescence, smelters, sulfur dioxide, nickel, copper, normalized difference vegetation index (NDVI).

scholarly journals Fire-induced changes in soil and vegetation in the forest-tundra of Western Siberia

2020 ◽  
Vol 223 ◽  
pp. 03001
Author(s):  
Oleg Sizov ◽  
Leya Brodt ◽  
Andrey Soromotin ◽  
Nikolay Prikhodko ◽  
Ramona Heim
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Western Siberia ◽  
The Arctic ◽  
Fire Scars ◽  
Forest Tundra ◽  
The North ◽  
Tundra Vegetation ◽  
Lichen Cover ◽  
The Face

Wildfires are one of the main factors for landscape change in tundra ecosystems. In the absence of external mechanical impacts, tundra plant communities are relatively stable, even in the face of climatic changes. In our study, lichen cover was degraded on burnt tundra sites, which increased the permafrost thaw depth from 100 to 190 cm. In old fire scars (burnt 1980 – 1990) of the forest-tundra, vegetation cover was dominated by trees and shrubs. The soil temperature on burnt forest-tundra sites was higher in comparison to conditions of the unburnt control sites and permafrost was was not found at a depth of 2-2,3m. Dynamics of the Normalized Difference Vegetation index (NDVI) from 1986-2020 reveal that immediately after fires, vegetation recovered and biomass increased due to the development of Betula nana shrubs. In old fire scars of the forest-tundra (burnt 1980-1990), a significant increase in NDVI values was evident, in contrast to the unburnt tundra vegetation where this trend was less pronounced. We conclude that "greening" in the north of Western Siberia may occur due to fire-induced transformation processes. The role of wildfires in the advance of the treeline to the north, driven by climate change and active economic development of the Arctic, will gradually increase in future.

scholarly journals Vegetation dynamics in Alpine glacier forelands tackled from space

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea Fischer ◽  
Thomas Fickert ◽  
Gabriele Schwaizer ◽  
Gernot Patzelt ◽  
Günther Groß
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Ground Cover ◽  
Plant Succession ◽  
Ice Age ◽  
Hazard Management ◽  
Alpine Glacier ◽  
Glacier Terminus ◽  
Vegetation Sampling

Abstract Monitoring of plant succession in glacier forelands has so far been restricted to field sampling. In this study, in situ vegetation sampling along a chronosequence between Little Ice Age (LIA) maximum extent and the recent glacier terminus at Jamtalferner in the Austrian Alps is compared to time series of the Normalized Difference Vegetation Index (NDVI) calculated from 13 Landsat scenes (1985–2016). The glacier terminus positions at 16 dates between the LIA maximum and 2015 were analysed from historical maps, orthophotos and LiDAR images. We sampled plots of different ages since deglaciation, from very recent to approx. 150 years: after 100 years, roughly 80% of the ground is covered by plants and ground cover does not increase significantly thereafter. The number of species increases from 10–20 species on young sites to 40–50 species after 100 years. The NDVI increases with the time of exposure from a mean of 0.11 for 1985–1991 to 0.20 in 2009 and 0.27 in 2016. As the increase in ground cover is clearly reproduced by the NDVI (R² ground cover/NDVI 0.84) – even for sparsely vegetated areas –, we see a great potential of satellite-borne NDVI to perform regional characterizations of glacier forelands for hydrological, ecological and hazard management-related applications.

scholarly journals Vegetation phenology in Greenland and links to cryospheric change

2018 ◽  
Vol 59 (77) ◽  
pp. 59-68 ◽  
Author(s):  
Jeffery A. Thompson ◽  
Lora S. Koenig
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Greenland Ice Sheet ◽  
The Arctic ◽  
Growing Degree Days ◽  
Degree Days ◽  
Hydrologic Change ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cryospheric Change ◽  
Dry Out

ABSTRACTRecent greening of vegetation across the Arctic is associated with warming temperatures, hydrologic change and shorter snow-covered periods. Here we investigated trends for a subset of arctic vegetation on the island of Greenland. Vegetation in Greenland is unique due to its close proximity to the Greenland Ice Sheet and its proportionally large connection to the Greenlandic population through the hunting of grazing animals. The aim of this study was to determine whether or not longer snow-free periods (SFPs) were causing Greenlandic vegetation to dry out and become less productive. If vegetation was drying out, a subsequent aim of the study was to determine how widespread the drying was across Greenland. We utilized a 15-year time-series obtained by the MODerate Resolution Imaging Spectroradiometer (MODIS) to analyze the Greenland vegetation by deriving descriptors corresponding with the SFP, the number of cumulative growing degree-days and the time-integrated Normalized Difference Vegetation Index. While the productivity of most vegetated areas increased in response to longer growing periods, there were localized regions that exhibited signs consistent with the drying hypothesis. In these areas, vegetation productivity decreased in response to longer SFPs and more accumulated growing degree-days.

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