scholarly journals Determining the terrain characteristics related to the surface expression of subsurface water pressurization in permafrost landscapes using susceptibility modelling

2017 ◽  
Vol 11 (3) ◽  
pp. 1403-1415 ◽  
Author(s):  
Jean E. Holloway ◽  
Ashley C. A. Rudy ◽  
Scott F. Lamoureux ◽  
Paul M. Treitz
Keyword(s):  
Active Layer ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Additive Model ◽  
The Arctic ◽  
Subsurface Water ◽  
Permafrost Degradation ◽  
Topographic Wetness Index ◽  
Landscape Degradation ◽  
Terrain Characteristics

Abstract. Warming of the Arctic in recent years has led to changes in the active layer and uppermost permafrost. In particular, thick active layer formation results in more frequent thaw of the ice-rich transient layer. This addition of moisture, as well as infiltration from late season precipitation, results in high pore-water pressures (PWPs) at the base of the active layer and can potentially result in landscape degradation. To predict areas that have the potential for subsurface pressurization, we use susceptibility maps generated using a generalized additive model (GAM). As model response variables, we used active layer detachments (ALDs) and mud ejections (MEs), both formed by high PWP conditions at the Cape Bounty Arctic Watershed Observatory, Melville Island, Canada. As explanatory variables, we used the terrain characteristics elevation, slope, distance to water, topographic position index (TPI), potential incoming solar radiation (PISR), distance to water, normalized difference vegetation index (NDVI; ME model only), geology, and topographic wetness index (TWI). ALDs and MEs were accurately modelled in terms of susceptibility to disturbance across the study area. The susceptibility models demonstrate that ALDs are most probable on hill slopes with gradual to steep slopes and relatively low PISR, whereas MEs are associated with higher elevation areas, lower slope angles, and areas relatively far from water. Based on these results, this method identifies areas that may be sensitive to high PWPs and helps improve our understanding of geomorphic sensitivity to permafrost degradation.

scholarly journals Determining the terrain characteristics related to the surface expression of subsurface water pressurization in permafrost landscapes using susceptibility modelling

2016 ◽  
Author(s):  
Jean E. Holloway ◽  
Ashley C. A. Rudy ◽  
Scott F. Lamoureux ◽  
Paul Treitz
Keyword(s):  
Active Layer ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Additive Model ◽  
The Arctic ◽  
Subsurface Water ◽  
Permafrost Degradation ◽  
Topographic Wetness Index ◽  
Landscape Degradation ◽  
Terrain Characteristics

Abstract. Warming of the Arctic in recent years has led to changes in the active layer and uppermost permafrost. In particular, thick active layer formation results in more frequent thaw of the ice-rich transient layer. This addition of moisture, as well as infiltration from late season precipitation, results in high pore-water pressures (PWPs) at the base of the active layer and can potentially result in landscape degradation. To predict areas that have the potential for subsurface pressurization, we use susceptibility maps generated using a generalized additive model (GAM). As model response variables, we used active layer detachments (ALDs) and mud ejections (MEs), both formed by high PWP conditions at the Cape Bounty Arctic Watershed Observatory, Melville Island, Canada. As explanatory variables, we used the terrain characteristics elevation, slope, distance to water, topographic position index (TPI), potential incoming solar radiation (PISR), distance to water, normalized difference vegetation index (NDVI; ME model only), geology, and topographic wetness index (TWI). ALDs and MEs were accurately modelled in terms of susceptibility to disturbance across the study area. The susceptibility models demonstrate that ALDs are most probable on hill slopes with gradual to steep slopes and relatively low PISR, whereas MEs are associated with higher elevation areas, lower slope angles and in areas relatively far from water. Based on these results, this method identifies areas that may be sensitive to high PWPs, and helps improve our understanding of geomorphic sensitivity to permafrost degradation.

scholarly journals Arctic aquatic graminoid tundra responses to nutrient availability

2021 ◽  
Vol 18 (8) ◽  
pp. 2649-2662
Author(s):  
Christian G. Andresen ◽  
Vanessa L. Lougheed
Keyword(s):  
Nutrient Availability ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Hot Spot ◽  
Soil Phosphorus ◽  
The Arctic ◽  
Permafrost Degradation ◽  
Nutrient Inputs ◽  
Nutrient Pools ◽  
Environmental Controls

Abstract. Unraveling the environmental controls influencing Arctic tundra productivity is paramount for advancing our predictive understanding of the causes and consequences of warming in tundra ecosystems and associated land–atmosphere feedbacks. This study focuses on aquatic emergent tundra plants, which dominate productivity and methane fluxes in the Arctic coastal plain of Alaska. In particular, we assessed how environmental nutrient availability influences production of biomass and greenness in the dominant aquatic tundra species: Arctophila fulva and Carex aquatilis. We sampled a total of 17 sites distributed across the Barrow Peninsula and Atqasuk, Alaska, following a nutrient gradient that ranged from sites with thermokarst slumping or urban runoff to sites with relatively low nutrient inputs. Employing a multivariate analysis, we explained the relationship of soil and water nutrients to plant leaf macro- and micro-nutrients. Specifically, we identified soil phosphorus as the main limiting nutrient factor given that it was the principal driver of aboveground biomass (R2=0.34, p=0.002) and normalized difference vegetation index (NDVI) (R2=0.47, p=0.002) in both species. Plot-level spectral NDVI was a good predictor of leaf P content for both species. We found long-term increases in N, P and Ca in C. aquatilis based on historical leaf nutrient data from the 1970s of our study area. This study highlights the importance of nutrient pools and mobilization between terrestrial–aquatic systems and their potential influence on productivity and land–atmosphere carbon balance. In addition, aquatic plant NDVI spectral responses to nutrients can serve as landscape hot-spot and hot-moment indicators of landscape biogeochemical heterogeneity associated with permafrost degradation, nutrient leaching and availability.

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 Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI)

2018 ◽  
Vol 8 ◽  
pp. 91-100
Author(s):  
Belete Berhanu ◽  
Ethiopia Bisrat
Keyword(s):  
Surface Water ◽  
Water Resource ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cost Effective ◽  
Water Shortage ◽  
Sample Volume ◽  
Runoff Generation ◽  
Topographic Wetness Index ◽  
Wetness Index

Ethiopia is endowed with water and has a high runoff generation area compared to many countries, but the total stored water only goes up to approximately 36BCM. The problem of water shortage in Ethiopia emanates from the seasonality of rainfall and the lack of infrastructure for storage to capture excess runoff during flood seasons. Based on this premise, a method for a syndicate use of topography, land use and vegetation was applied to locate potential surface water storing sites. The steady-state Topographic Wetness Index (TWI) was used to represent the spatial distribution of water flow and water stagnating across the study area and the Normalized Difference Vegetation Index (NDVI) was used to detect surface water through multispectral analysis. With this approach, a number of water storing sites were identified in three categories: primary sources (water bodies based), secondary sources (Swampy/wetland based) and tertiary sources (the land based). A sample volume analysis for the 120354 water storing sites in category two, gives a 44.92BCM potential storing capacity with average depth of 4 m that improves the annual storage capacity of the country to 81BCM (8.6 % of annual renewable water sources). Finally, the research confirmed the TWI and NDVI based approach for water storing sites works without huge and complicated earth work; it is cost effective and has the potential of solving complex water resource challenges through spatial representation of water resource systems. Furthermore, the application of remote sensing captures temporal diversity and includes repetitive archives of data, enabling the monitoring of areas, even those that are inaccessible, at regular intervals.

scholarly journals Satellite Imaging-Based Residential Greenness and Accelerometry Measured Physical Activity at Midlife—Population-Based Northern Finland Birth Cohort 1966 Study

2020 ◽  
Vol 17 (24) ◽  
pp. 9202
Author(s):  
Soile Puhakka ◽  
Tiina Lankila ◽  
Riitta Pyky ◽  
Mikko Kärmeniemi ◽  
Maisa Niemelä ◽  
...  
Keyword(s):  
Physical Activity ◽  
Birth Cohort ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vigorous Physical Activity ◽  
Leisure Activities ◽  
Additive Model ◽  
Population Based ◽  
Moderate Physical Activity ◽  
Positive Health

Background: Recently, the importance of light physical activity (LPA) for health has been emphasized, and residential greenness has been positively linked to the level of LPA and a variety of positive health outcomes. However, people spend less time in green environments because of urbanization and modern sedentary leisure activities. Aims: In this population-based study, we investigated the association between objectively measured residential greenness and accelerometry measured physical activity (PA), with a special interest in LPA and gender differences. Methods: The study was based on the Northern Finland Birth Cohort 1966 (5433 members). Participants filled in a postal questionnaire and underwent clinical examinations and wore a continuous measurement of PA with wrist-worn Polar Active Activity Monitor accelerometers for two weeks. The volume of PA (metabolic equivalent of task or MET) was used to describe the participant’s total daily activity (light: 2–3.49 MET; moderate: 3.5–4.99 MET; vigorous: 5–7.99 MET; very vigorous: ≥8 MET). A geographic information system (GIS) was used to assess the features of each individual’s residential environment. The normalized difference vegetation index (NDVI) was used for the objective quantification of residential greenness. Multiple linear regression and a generalized additive model (GAM) were used to analyze the association between residential greenness and the amount of PA at different intensity levels. Results: Residential greenness (NDVI) was independently associated with LPA (unadjusted β = 174; CI = 140, 209) and moderate physical activity (MPA) (unadjusted β = 75; CI = 48, 101). In the adjusted model, residential greenness was positively and significantly associated with LPA (adjusted β = 70; CI = 26, 114). In men, residential greenness was positively and significantly associated with LPA (unadjusted β = 224; CI = 173, 275), MPA (unadjusted β = 75; CI = 48, 101), and moderate to vigorous physical activity (MVPA) (unadjusted β = 89; CI = 25, 152). In women, residential greenness was positively related to LPA (unadjusted β = 142; CI = 96, 188) and inversely associated with MPA (unadjusted β = −22; CI = −36, −8), vigorous/very vigorous physical activity (VPA/VVPA) (unadjusted β = −49; CI = −84, −14), and MVPA (unadjusted β = −71; CI = −113, −29). In the final adjusted models, residential greenness was significantly associated only with the amount of LPA in men (adjusted β = 140; CI = 75, 204). Conclusions: Residential greenness was positively associated with LPA in both genders, but the association remained significant after adjustments only in men. Residential greenness may provide a supportive environment for promoting LPA.

scholarly journals Methane Content in Ground Ice and Sediments of the Kara Sea Coast

Geosciences ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 434 ◽  
Author(s):  
Irina Streletskaya ◽  
Alexander Vasiliev ◽  
Gleb Oblogov ◽  
Dmitry Streletskiy
Keyword(s):  
Active Layer ◽  
Kara Sea ◽  
Methane Content ◽  
The Arctic ◽  
Permafrost Degradation ◽  
Microbial Oxidation ◽  
Ground Ice ◽  
Arctic Seas ◽  
Methane Concentrations ◽  
Sea Coast

Permafrost degradation of coastal and marine sediments of the Arctic Seas can result in large amounts of methane emitted to the atmosphere. The quantitative assessment of such emissions requires data on variability of methane content in various types of permafrost strata. To evaluate the methane concentrations in sediments and ground ice of the Kara Sea coast, samples were collected at a series of coastal exposures. Methane concentrations were determined for more than 400 samples taken from frozen sediments, ground ice and active layer. In frozen sediments, methane concentrations were lowest in sands and highest in marine clays. In ground ice, the highest concentrations above 500 ppmV and higher were found in massive tabular ground ice, with much lower methane concentrations in ground ice wedges. The mean isotopic composition of methane is −68.6‰ in permafrost and −63.6‰ in the active layer indicative of microbial genesis. The isotopic compositions of the active layer is enriched relative to permafrost due to microbial oxidation and become more depleted with depth. Ice-rich sediments of Kara Sea coasts, especially those with massive tabular ground ice, hold large amounts of methane making them potential sources of methane emissions under projected warming temperatures and increasing rates of coastal erosion.

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 Comparison between the Holt-Winters and SARIMA Models in the Prediction of NDVI in an Arid Region in Kenya using Pixel-wise NDVI Time Series

2021 ◽  
Vol 2 (23) ◽  
pp. 1-15
Author(s):  
Mwana Said Omar ◽  
◽  
Hajime Kawamukai
Keyword(s):  
Time Series ◽  
Arid Region ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Moving Average ◽  
Additive Model ◽  
Grid Search ◽  
Sarima Model ◽  
Ndvi Time Series ◽  
Sarima Models

Desertification is major issue in arid and semi-arid lands (ASAL) with devastating environmental and socio-economic impacts. Time series analysis was applied on 19 years’ pixel-wise monthly mean Normalized Difference Vegetation Index (NDVI) data. The aim of this study was to identify a time series model that can be used to predict NDVI at the pixel level in an arid region in Kenya. The Holt-Winters and Seasonal Auto Regressive Integrated Moving Average (SARIMA) models were developed and statistical analysis was carried out using both models on the study area. We performed a grid search to optimise and determine the best hyper parameters for the models. Results from the grid search identified the Holt-Winters model as an additive model and a SARIMA model with a trend autoregressive (AR) order of 1, a trend moving average (MA) order of 1 and a seasonal MA order of 2, with both models having a seasonal period of 12 months. It was concluded that the Holt-Winters model showed the best performance for 600 ✕ 600 pixels (MAE = 0.0744, RMSE = 0.096) compared to the SARIMA model.

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 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.

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