scholarly journals Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review

2021 ◽  
Vol 13 (6) ◽  
pp. 1217
Author(s):  
Marius Philipp ◽  
Andreas Dietz ◽  
Sebastian Buchelt ◽  
Claudia Kuenzer
Keyword(s):  
Remote Sensing ◽  
Greenhouse Gas ◽  
Satellite Remote Sensing ◽  
Surface Deformation ◽  
Greenhouse Gas Emission ◽  
Thermal State ◽  
Carbon Sink ◽  
Google Earth ◽  
Permafrost Degradation ◽  
Frozen Ground

Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.) and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet) will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.

scholarly journals Progress and Challenges in Studying Regional Permafrost in the Tibetan Plateau Using Satellite Remote Sensing and Models

2020 ◽  
Vol 8 ◽  
Author(s):  
Huiru Jiang ◽  
Guanheng Zheng ◽  
Yonghong Yi ◽  
Deliang Chen ◽  
Wenjiang Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Tibetan Plateau ◽  
Satellite Remote Sensing ◽  
Surface Deformation ◽  
Microwave Remote Sensing ◽  
Local Scale ◽  
The Tibetan Plateau ◽  
Freeze Thaw ◽  
Plateau Area

Recent climate change has induced widespread soil thawing and permafrost degradation in the Tibetan Plateau. Significant advances have been made in better characterizing Tibetan Plateau soil freeze/thaw dynamics, and their interaction with local-scale ecohydrological processes. However, factors such as sparse networks of in-situ sites and short observational period still limit our understanding of the Tibetan Plateau permafrost. Satellite-based optical and infrared remote sensing can provide information on land surface conditions at high spatial resolution, allowing for better representation of spatial heterogeneity in the Tibetan Plateau and further infer the related permafrost states. Being able to operate at “all-weather” conditions, microwave remote sensing has been widely used to retrieve surface soil moisture, freeze/thaw state, and surface deformation, that are critical to understand the Tibetan Plateau permafrost state and changes. However, coarse resolution (>10 km) of current passive microwave sensors can add large uncertainties to the above retrievals in the Tibetan Plateau area with high topographic relief. In addition, current microwave remote sensing methods are limited to detections in the upper soil layer within a few centimetres. On the other hand, algorithms that can link surface properties and soil freeze/thaw indices to permafrost properties at regional scale still need improvements. For example, most methods using InSAR (interferometric synthetic aperture radar) derived surface deformation to estimate active layer thickness either ignore the effects of vertical variability of soil water content and soil properties, or use site-specific soil moisture profiles. This can introduce non-negligible errors when upscaled to the broader Tibetan Plateau area. Integrating satellite remote sensing retrievals with process models will allow for more accurate representation of Tibetan Plateau permafrost conditions. However, such applications are still limiting due to a number of factors, including large uncertainties in current satellite products in the Tibetan Plateau area, and mismatch between model input data needs and information provided by current satellite sensors. Novel approaches to combine diverse datasets with models through model initialization, parameterization and data assimilation are needed to address the above challenges. Finally, we call for expansion of local-scale observational network, to obtain more information on deep soil temperature and moisture, soil organic carbon content, and ground ice content.

A geospatial web portal for sharing and analyzing greenhouse gas data derived from satellite remote sensing images

2013 ◽  
Vol 7 (3) ◽  
pp. 295-309 ◽  
Author(s):  
Hao Lin ◽  
Bailang Yu ◽  
Zuoqi Chen ◽  
Yingjie Hu ◽  
Yan Huang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Greenhouse Gas ◽  
Satellite Remote Sensing ◽  
Web Portal ◽  
Remote Sensing Images

Application of Satellite Remote Sensing Techniques to Frozen Ground Studies

2004 ◽  
Vol 28 (3) ◽  
pp. 163-196 ◽  
Author(s):  
Tingjun Zhang ◽  
Roger G. Barry ◽  
Richard L. Armstrong
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Frozen Ground ◽  
Remote Sensing Techniques

scholarly journals Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine

2018 ◽  
Vol 10 (8) ◽  
pp. 1226 ◽  
Author(s):  
Kelsey E. Nyland ◽  
Grant E. Gunn ◽  
Nikolay I. Shiklomanov ◽  
Ryan N. Engstrom ◽  
Dmitry A. Streletskiy
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Cover Change ◽  
Environmental Modeling ◽  
Google Earth ◽  
The Arctic ◽  
Permafrost Degradation ◽  
Yenisei River ◽  
River Region ◽  
Google Earth Engine

Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has been challenging due to persistent cloud and snow cover issues and the spectrally similar land cover types. Google Earth Engine (GEE) represents a powerful tool to efficiently investigate these changes using a large repository of available optical imagery. This work examines land cover change in the Lower Yenisei River region of arctic central Siberia and exemplifies the application of GEE using the random forest classification algorithm for Landsat dense stacks spanning the 32-year period from 1985 to 2017, referencing 1641 images in total. The semiautomated methodology presented here classifies the study area on a per-pixel basis utilizing the complete Landsat record available for the region by only drawing from minimally cloud- and snow-affected pixels. Climatic changes observed within the study area’s natural environments show a statistically significant steady greening (~21,000 km2 transition from tundra to taiga) and a slight decrease (~700 km2) in the abundance of large lakes, indicative of substantial permafrost degradation. The results of this work provide an effective semiautomated classification strategy for remote sensing in permafrost regions and map products that can be applied to future regional environmental modeling of the Lower Yenisei River region.

Monitoring land use change in the Lake Taupo catchment between 1975, 1990 and 2002 using satellite remote sensing data

2007 ◽  
pp. 17-22
Author(s):  
H. Lilienthal ◽  
A. Brauer ◽  
K. Betteridge ◽  
E. Schnug
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Native Vegetation ◽  
Lake Water Quality ◽  
Livestock Farming ◽  
Slow Decline

Conversion of native vegetation into farmed grassland in the Lake Taupo catchment commenced in the late 1950s. The lake's iconic value is being threatened by the slow decline in lake water quality that has become apparent since the 1970s. Keywords: satellite remote sensing, nitrate leaching, land use change, livestock farming, land management

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