150 research outputs found

    Supraglacial rivers on the northwest Greenland Ice Sheet, Devon Ice Cap, and Barnes Ice Cap mapped using Sentinel-2 imagery

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    Supraglacial rivers set efficacy and time lags by which surface meltwater is routed to the englacial, subglacial, and proglacial portions of ice masses. However, these hydrologic features remain poorly studied mainly because they are too narrow (typically <30 m) to be reliably delineated in conventional moderate-resolution satellite images (e.g., 30 m Landsat-8 imagery). This study demonstrates the utility of 10 m Sentinel-2 Multi-Spectral Instrument images to map supraglacial rivers on the northwest Greenland Ice Sheet, Devon Ice Cap, and Barnes Ice Cap, covering a total area of ∼10,000 km2. Sentinel-2 and Landsat-8 both capture overall supraglacial drainage patterns, but Sentinel-2 images are superior to Landsat-8 images for delineating narrow and continuous supraglacial rivers. Sentinel-2 mapping across the three study areas reveals a variety of supraglacial drainage patterns. In northwest Greenland near Inglefield Land, subparallel supraglacial rivers up to 55 km long drain meltwater directly off the ice sheet onto the proglacial zone. On the Devon and the Barnes ice caps, shorter supraglacial rivers (up to 15–30 km long) are commonly interrupted by moulins, which drain internally drained catchments on the ice surface to subglacial systems. We conclude that Sentinel-2 offers strong potential for investigating supraglacial meltwater drainage patterns and improving our understanding of the hydrological conditions of ice masses globally

    Oil-Palm Plantation Identification from Satellite Images Using Google Earth Engine

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    Oil-palm plantation is a crucial determinant for land-use planning and agricultural studies. Remote sensing techniques have elevated limitations of the on-site survey as computerized imaging is much efficient and economical. This paper presents a ubiquitous application of Gabor analysis for extracting oil-palm plantation from satellite images. The proposed system was built on the cloud-based Google Earth Engine. Herein, THEOS images were convoluted with Gabor kernels, and both K-Means and SVM then learned their responses for comparison. Experimental results showed that SVM could better identify the plantation areas with precision, recall, and accuracy of 92.98%, 88.96%, and 94.24% respectively

    Diverse supraglacial drainage patterns on the Devon ice Cap, Arctic Canada

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    The Devon Ice Cap (DIC) is one of the largest ice masses in the Canadian Arctic. Each summer, extensive supraglacial river networks develop on the DIC surface and route large volumes of meltwater from ice caps to the ocean. Mapping their extent and understanding their temporal evolution are important for validating runoff routing and melt volumes predicted by regional climate models (RCMs). We use 10 m Sentinel-2 images captured on 28 July and 10/11 August 2016 to map supraglacial rivers across the entire DIC (12,100 km2). Both dendritic and parallel supraglacial drainage patterns are found, with a total length of 44,941 km and a mean drainage density (Dd ) of 3.71 km−1. As the melt season progresses, Dd increases and supraglacial rivers form at progressively higher elevations. There is a positive correlation between RCM-derived surface runoff and satellite-mapped Dd , suggesting that supraglacial drainage density is primarily controlled by surface runoff

    Characteristics of Supraglacial Channels and Drainage Networks on Antarctic Ice Shelves

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    Supraglacial channels that flow on ice shelves can store and transport large volumes of meltwater to various locations (e.g., moulins, lakes, crevasses) during the melt season, so they play an important role in glacial hydrology and ice shelf stability. However, the current understanding of supraglacial channels is limited, especially the underlying processes and the controls on their development and variability. This study uses multiple remotely sensed data including satellite imagery and Digital Elevation Models (DEMs) to measure supraglacial channels in Antarctica. Five contrasting ice shelves around the margin of the Antarctic Ice Sheet are chosen as the study sites – Bach, Nansen, Nivlisen, Riiser-Larsen and Roi Baudouin ice shelves. Supraglacial lakes and channels are mapped by automatic delineation method during the melt season in 2020 and 2022, and key fluvial metrics are calculated, e.g., number, length, width, depth, sinuosity, bifurcation ratio, orientation, slopes and drainage density. Extensive supraglacial lakes and channels were observed on all five Antarctic ice shelves during the peak of the melt season and most were interconnected to form a total of 119 channel networks at different scales. The results demonstrate that: (ⅰ) supraglacial channel networks often occurred in areas with low elevations and near grounding lines, (ⅱ) supraglacial channel networks on different ice shelves exhibited different drainage patterns and hydromorphic characteristics, (ⅲ) the surface topography and structural glaciology of ice shelves affected the distribution of the supraglacial channel network. Future work could focus on long-term observation of supraglacial channels and exploring the applicability of terrestrial river-related research methods (e.g., hydrological modelling) to supraglacial channels

    Remote Sensing

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    This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

    Surface meltwater runoff routing through a coupled supraglacial-proglacial drainage system, Inglefield Land, northwest Greenland

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    The northwest Greenland Ice Sheet (NW GrIS) is rapidly losing mass, and its ablation zone has expanded over the past two decades. Numerous supraglacial streams flowing directly over the NW GrIS surface drain a large lobe of grounded ice at Inglefield Land, into the proglacial Minturn River and the Nares Strait. Owing to the absence of moulins and crevasses, this continuous supraglacial-proglacial drainage system regulates the evacuation of surface meltwater from the ice sheet to the ocean. We examine this Inglefield Land coupled supraglacial-proglacial drainage system during the 2016–2019 melt seasons (July to August), using 137 Sentinel-2 and Landsat-8 visible/near-infrared satellite images. Two surface water metrics (supraglacial meltwater area fraction Am and proglacial river effective width We) are used to track spatio-temporal variations of surface meltwater moving through this drainage system. Satellite-derived Am and We are also compared with daily surface runoff simulations from the MAR v3.11 and MERRA-2 climate/SMB models, to estimate meltwater routing lag times and assess model performance. Satellite-derived Am and We are highly correlated (r2 = 0.85, p < 0.01), indicating that the coupled supraglacial-proglacial drainage system evacuates meltwater directly from the ice surface to the ocean with negligible subglacial storage or delays. Both remotely sensed metrics are positively correlated with modeled runoff, especially MAR (r2 = 0.81 and 0.77 for Am and We, vs. 0.66 and 0.64 for MERRA-2). Lagged MAR runoff (2 days, r2 = 0.87 and 0.82) match both metrics better than simultaneous MAR runoff and the optimal time lag for both metrics are 2 d. We conclude that 1) unlike the southwest GrIS, the coupled supraglacial-proglacial drainage system at Inglefield Land routes surface meltwater runoff directly off the ice surface to the proglacial zone, with virtually no subglacial capture of runoff by moulins; 2) most of the ∼2 d transit time occurs on the ice surface rather than in the proglacial zone; and 3) multi-temporal satellite imaging facilitates holistic, source-to-sink tracking of NW GrIS meltwater from the ice surface to the global ocean

    Image Segmentation and Content Based Image Retrieval

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    Robust Modular Feature-Based Terrain-Aided Visual Navigation and Mapping

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    The visual feature-based Terrain-Aided Navigation (TAN) system presented in this thesis addresses the problem of constraining inertial drift introduced into the location estimate of Unmanned Aerial Vehicles (UAVs) in GPS-denied environment. The presented TAN system utilises salient visual features representing semantic or human-interpretable objects (roads, forest and water boundaries) from onboard aerial imagery and associates them to a database of reference features created a-priori, through application of the same feature detection algorithms to satellite imagery. Correlation of the detected features with the reference features via a series of the robust data association steps allows a localisation solution to be achieved with a finite absolute bound precision defined by the certainty of the reference dataset. The feature-based Visual Navigation System (VNS) presented in this thesis was originally developed for a navigation application using simulated multi-year satellite image datasets. The extension of the system application into the mapping domain, in turn, has been based on the real (not simulated) flight data and imagery. In the mapping study the full potential of the system, being a versatile tool for enhancing the accuracy of the information derived from the aerial imagery has been demonstrated. Not only have the visual features, such as road networks, shorelines and water bodies, been used to obtain a position ’fix’, they have also been used in reverse for accurate mapping of vehicles detected on the roads into an inertial space with improved precision. Combined correction of the geo-coding errors and improved aircraft localisation formed a robust solution to the defense mapping application. A system of the proposed design will provide a complete independent navigation solution to an autonomous UAV and additionally give it object tracking capability

    Crevasse density, orientation and temporal variability at Narsap Sermia, Greenland

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    Mass loss from iceberg calving at marine-terminating glaciers is one of the largest and most poorly constrained contributors to sea-level rise. However, our understanding of the processes controlling ice fracturing and crevasse evolution is incomplete. Here, we use Gabor filter banks to automatically map crevasse density and orientation through time on a ~150 km2 terminus region of Narsap Sermia, an outlet glacier of the southwest Greenland ice sheet. We find that Narsap Sermia is dominated by transverse (flow-perpendicular) crevasses near the ice front and longitudinal (flow-aligned) crevasses across its central region. Measured crevasse orientation varies on sub-annual timescales by more than 45∘^\circ in response to seasonal velocity changes, and also on multi-annual timescales in response to broader dynamic changes and glacier retreat. Our results show a gradual up-glacier propagation of the zone of flow-transverse crevassing coincident with frontal retreat and acceleration occurring in 2020/21, in addition to sub-annual crevasse changes primarily in transition zones between longitudinal to transverse crevasse orientation. This provides new insight into the dynamics of crevassing at large marine-terminating glaciers and a potential approach for the rapid identification of glacier dynamic change from a single pair of satellite images
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