Application of geomorphons for analysing changes in the morphology of a proglacial valley (case study: The Scott River, SW Svalbard)

Gawrysiak, Leszek; Kociuba, Waldemar

doi:10.1016/j.geomorph.2020.107449

Cited by 16 publications

(13 citation statements)

References 67 publications

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“…Then, both DEMs, the original post-excavation slag hill and side slopes, and the one representing a reclamation situation, were used to produce a DEM of Difference (DoD). The DoD method was used to measure earthquake deformation [25], quantify flood deposits [26], and analyze changes in the morphology of a proglacial valley [27]. The DoD approach is to subtract an old DEM from the new DEM, taking into account the uncertainty of the DEMs, which included measurement errors, sampling bias, and uncertainties due to interpolation methods, among others [28].…”

Section: Quantification Of Slope Change and Dem Of Differencementioning

confidence: 99%

Monitoring Extractive Activity-Induced Surface Subsidence in Highland and Alpine Opencast Coal Mining Areas with Multi-Source Data

Wang

Bai

et al. 2022

Remote Sensing

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Mining developments in alpine coal mining areas result in slow or rapid ground subsidence, which can lead to melting and collapse of permafrost. This paper integrated unmanned aerial vehicle (UAV) images and satellite-based SAR interferometry images to monitor intensive surface mining subsidence during reclamation. Digital Surface Model (DSM) acquired from UAV images was first used to evaluate the changes of the reclamation scheme on the microtopography carried out by slope and the Digital Elevation Model (DEM) of difference (DoD). The monitoring results showed that the slope had been reduced from over 30 degrees to under 15 degrees after the terrain had been reshaped. The DoD map revealed the distribution of main extraction areas and landfill areas. To further monitor the surface subsidence after local terrain adjustment, the Permanent Scatterer Interferometry (PS-InSAR) method was used to reveal the surface subsidence characteristics of the mine site before and after reclamation. The maximum cumulative subsidence ranged from −772.3 to 1183 mm based on 21 Sentinel-1A images in three years. Within a year of terrain reshaping, uplift and subsidence still occurred at hills and pit side slopes, following the nearly equal subsidence rate. The experimental results showed that the slope reshaping and vegetation recovery had a limited impact on the reduction of the ground subsidence in a short period. Therefore, on this basis, a combination of UAV and PS-InSAR methods can be used to continue monitoring time series subsidence in alpine mines.

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Section: Quantification Of Slope Change and Dem Of Differencementioning

confidence: 99%

Monitoring Extractive Activity-Induced Surface Subsidence in Highland and Alpine Opencast Coal Mining Areas with Multi-Source Data

Wang

Bai

et al. 2022

Remote Sensing

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“…To address the misclassification problem due to topography effects, we accounted for complex landforms in mountainous areas based on the geomorphon concept [21][22][23][24] to circumvent the ill-posed calculus of taking spatial derivatives from noisy topography data. We employed the SRTM digital elevation model (DEM) [25] derived from satellite SAR data to calculate geomorphons.…”

Section: Mappingmentioning

confidence: 99%

“…Regarding the advances in the new method, we highlight (1) the advantage of utilizing the two-dimensional (2-D) space of VV-VH for building structure mapping to robustly resolve the issue of radar backscatter incidence and azimuth angle dependence; (2) the ability of consistent time-series Sentinel-1 SAR to identify persistent buildings in a multitude of environmental conditions across the rural-urban continuum; (3) the utilization of multiple SAR signature interactions between trees and water surface to correct for building misclassification; (4) the use of the geomorphon concept and its applications [21][22][23][24] to account for effects of complex topography; and (5) the SAR ability to detect stationary structures or installations that are maintained on sea surfaces. Finally, in the discussion and conclusion, we note future research extensions with multiple international SAR datasets to support the Paris Agreement on climate change, through the potential improvement in the estimation of FFCO2 emission using data products of persistent building structures to represent true settlements.…”

Section: Introductionmentioning

confidence: 99%

Building Structure Mapping on Level Terrains and Sea Surfaces in Vietnam

et al. 2021

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Mapping building structures is crucial for environmental change and impact assessment, and is especially important to accurately estimate fossil fuel CO2 emissions from human settlements. In this regard, the objective of this study is to develop novel and robust methods using time-series data acquired from Sentinel-1 synthetic aperture radar (SAR) to identify and map persistent building structures from coastal plains to high plateaus, as well as on the sea surface. From annual composites of SAR data in the two-dimensional VV-VH polarization space, we determined the VV-VH domain for detecting building structures, whose persistence was defined based on the number of times that a pixel was identified as a building in time-series data. Moreover, the algorithm accounted for misclassified buildings due to water-tree interactions in radar signatures and due to topography effects in complex mountainous landforms. The methods were tested in five cities (Bạc Liêu, Cà Mau, Sóc Trăng, Tân An, and Phan Thiết) in Vietnam located in different socio-environmental regions with a range of urban configurations. Using in-situ data and field observations, we validated the methods and found that the results were accurate, with an average false negative rate of 10.9% and average false positive rate of 6.4% for building detection. The algorithm could also detect small houses in rural settlements and in small islands such as in Hòn Sơn and Hòn Tre. Over sea surfaces, the algorithm effectively identified lines of power poles connecting islands to the mainland, guard shacks in marine blood clam farms in Kiên Giang, individual wind towers in the off-shore wind farm in Bạc Liêu, and oilrigs in the Vũng Tàu oil fields. The new approach was developed to be robust against variations in SAR incidence and azimuth angles. The results demonstrated the potential use of satellite dual-polarization SAR to identify persistent building structures annually across rural–urban landscapes and on sea surfaces with different environmental conditions.

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“…Geomorphon analysis [32], a technique that we employ in this research, is a machine vision terrain classifier of rasterized terrain models. Geomorphons have been often used to represent and even predict geomorphological and hydrological changes in river valleys [33][34][35][36]. In the form of input to a physically based hydrological model, geomorphons were successfully represented in the spatially distributed hydrological parameters of the upper reaches of a montane watershed in Brazil [33].…”

Section: Core Of Cranberry Gladesmentioning

confidence: 99%

Beaver-Driven Peatland Ecotone Dynamics: Impoundment Detection Using Lidar and Geomorphon Analysis

Swift

Kennedy

2021

Land

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This investigation focused on remotely detecting beaver impoundments and dams along the boreal-like peatland ecotones enmeshing Cranberry Glades Botanical Area, a National Natural Landmark in mountainous West Virginia, USA. Beaver (Castor spp.) are renowned for their role as ecosystem engineers. They can alter local hydrology, change the ratios of meadow to woodland, act as buffers against drought and wildfire, and influence important climate parameters such as carbon retention and methanogenesis. The Cranberry Glades (~1000 m a.s.l.) occupy ~300 ha, including ~40 ha of regionally rare, open peatlands. Given the likely historical role of beaver activity in the formation and maintenance of peatland conditions at Cranberry Glades, monitoring of recent activity may be useful in predicting future changes. We analyzed remotely sensed data to identify and reconstruct shifting patterns of surface hydrology associated with beaver ponds and dams and developed a novel application of geomorphons to detect them, aided by exploitation of absences and errors in Lidar data. We also quantified decadal-timescale dynamics of beaver activity by tallying detectable active impoundments between 1990–2020, revealing active/fallow cycles and changing numbers of impoundments per unit area of suitable riparian habitat. This research presents both a practical approach to monitoring beaver activity through analysis of publicly available data and a spatiotemporal reconstruction of three decades of beaver activity at this rare and imperiled “Arctic Island” of the southern High Alleghenies.

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Application of geomorphons for analysing changes in the morphology of a proglacial valley (case study: The Scott River, SW Svalbard)

Cited by 16 publications

References 67 publications

Monitoring Extractive Activity-Induced Surface Subsidence in Highland and Alpine Opencast Coal Mining Areas with Multi-Source Data

Monitoring Extractive Activity-Induced Surface Subsidence in Highland and Alpine Opencast Coal Mining Areas with Multi-Source Data

Building Structure Mapping on Level Terrains and Sea Surfaces in Vietnam

Beaver-Driven Peatland Ecotone Dynamics: Impoundment Detection Using Lidar and Geomorphon Analysis

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