Historical analysis and visualization of the retreat of Findelengletscher, Switzerland, 1859–2010

Since the end of the Little Ice Age around 1850, glaciers in Europe have strongly retreated. Thanks to early topographic surveys in Switzerland, accurate maps are available, which enable us to trace glacier changes back in time. The earliest map for all of Switzerland that is usable for a detailed analysis is the Dufour map from around 1850 with subsequent topographic maps on a ~ 20 year interval. Despite the large public and scientific interest in glacier changes through time, this historic dataset has not yet been fully utilized for topographic change assessment or visualization of historic glacier extents. In this study, we use eleven historical topographic maps and more recent digital datasets for the region of Zermatt to analyze geometric changes (length, area and volume) of Findelengletscher as well as for creating animations of glacier evolution through time for use in public communication. All maps were georeferenced, the contour lines digitized, and digital elevation models (DEMs) created and co-registered. Additional digital data like the SRTM X-band DEM and high resolution laser scanning data were used to extend the analysis until 2010. Moreover, one independent DEM from aerial photogrammetry was used for comparison. During the period 1859–2010, Findelengletscher lost 3.5 km of its length (6.9 km in 2010), 4.42 ± 0.13 km² of its area (15.05 ± 0.45 km² in 2010) and 1.32 ± 0.52 km³ of its volume. The average rate of thickness loss is 0.45 ± 0.042 m yr− 1 for the 151 years period. Four periods with high thickness change from − 0.56 m ± 0.28 yr− 1 (1859–1881), − 0.40 ± 0.08 m yr− 1 (1937–1965), − 0.90 ± 0.31 m yr− 1 (1995–2000) and − 1.18 ± 0.02 m yr− 1 (2000–2005) have been identified. Small positive thickness changes were found for the periods 1890–1909 (+ 0.09 ± 0.46 m yr − 1) and 1988–1995 (+ 0.05 ± 0.24 m yr− 1). During its retreat with intermittent periods of advance, the glacier separated into three parts. The above changes are demonstrated through an animation (available from the supplementary material), which has been created to inform the general public

The current deglaciation of the Ortles-Cevedale massif (Eastern Italian Alps): impacts, controls and degree of imbalance.

The Ortles-Cevedale is the largest glacierized mountain group of the Italian Alps hosting 112 ice bodies, with a total area of 76.8 km2. Since the 1980\u2019s, this massif is undergoing a rapid deglaciation, as most of the mountain ranges in the European Alps. The aims of this work were: i) to quantify area and volume change of the Ortles- Cevedale glacier system from the 1980s to the 2000s; ii) to improve the knowledge of factors controlling the spatial variability of the deglaciation; and iii) to assess the degree of imbalance of individual glaciers with respect to the present climate conditions. Two inventories were created, based on Landsat5 TM scenes of 20-09-1987 and 31-08-2009. Contrast-enhanced composites (bands TM5, TM4 and TM3), aerial photos and field surveys (for the most recent period) were used to correct the automatic delineation of glaciers derived from a hard classification based on a threshold applied to a TM3/TM5 ratio image. Since Landsat scenes were acquired at the end of the ablation seasons and fresh snow was absent, the accumulation areas could be roughly determined by mapping the snow covered area. This region was identified from the difference in reflectance between snow and ice in the near infrared band of Landsat (TM4), and mapped after correcting topographic effects to determine surface reflectance. The area-averaged geodetic mass budget was then calculated for the individual glaciers by differencing two Digital Terrain Models (2000s minus 1980s, derived from LiDAR and aerial photogrammetry) and combining the result with the glacier outlines. Afterwards, we examined the mass balance data using statistical analyses (Correlation matrices, Principal Component Analysis, Cluster Analysis). This allowed us highlighting clusters of glaciers, which exhibit a similar behavior, identify the outlayers and the relative influence of the factors controlling spatial variability of the mass losses. Finally, we assessed the degree of imbalance of individual glaciers by comparing the current Accumulation Area Ratios (AAR) with the balanced-budget AAR (AAR0), the latter also accounting for the debris cover of glaciers. We found that the total area loss of the Ortles-Cevedale glaciers from 1987 to 2009 amounts to 23.5 km2, i.e. 23.4% of the initial area. On the other hand, the AAR of the entire glacier system was 0.3 in both investigated years. The overall debris cover increased from 10.5% to 16.3%. The geodetic mass balance rate was -0.7 m w.e. y1(as an average on 112 ice bodies), ranging from -0.1 to -1.7 m w.e. y1. We also found that the main controls of the differing change of single glaciers are related to their hypsometry (elevation range and slope), AAR, feeding source and debris cover. Interestingly, a significant correlation was found between AAR, AAR0 and debris cover. This information was used to assess and visualize the needed additional reduction of individual glaciers to reach equilibrium with the current size of their accumulation areas. This amounts on average to a further reduction of 40% of the current areal extent of glaciers

Estudio de caso: evaluación de generación eólica en PYMES para cumplir con la ley 27.191

El cambio climático y las nuevas políticas al respecto llevan a la necesidad de desarrollar el campo de las energías renovables. Esto es enmarcado en el caso de Argentina por la Ley 27.191, que pone objetivos claros de generación de energía mediante técnicas limpias enfocados principalmente en los grandes consumidores de energía eléctrica. Para satisfacer esta necesidad, se plantea la utilización de un parque eólico emplazado en la zona de Neuquén capital y alrededores, tomando como referencia el consumo de un galpón de empaque situado en el mismo sector, para la determinación de la energía que el parque debe brindar. Se presentan las características principales del recurso eólico, se analizan los terrenos disponibles para la instalación de las máquinas, y se determinan la ubicación y el tipo de aerogeneradores a utilizar. El estudio se enfoca en aerogeneradores en el rango de pequeña a mediana potencia, dadas las características de los vientos disponibles, y la necesidad de minimizar el impacto ambiental por la localización del parque. Una vez determinados estos factores, se procede a calcular la producción anual neta de energía del proyecto. Con los resultados obtenidos se concluye sobre la factibilidad del mismo.Climate change and new politics associated with it lead to the need for developing the enewable energies field. This is framed in the case of Argentina by Law 27.191 that states clear objectives of energy generation by clean techniques that are focused mainly in big electric energy consumers. To satisfy this need, it’s considered the use of a wind farm located in Neuquén capital and its surroundings, taking as reference the consumption of a packing shed situated in the same area, to determine the energy the farm has to fulfill. The main characteristics of the wind resource are presented, available fields for machines installation are analyzed, and the location and type of wind turbine are determined. The study is focused in turbines from small to medium power range, given the characteristics of available winds, and the need to minimize environmental impact because of the location of the farm. Once these factors are determined, net annual energy production of the project is calculated. With the results achieved, conclusions are made about the feasibility of it.Fil: Rastner, Salvador. Universidad Nacional del Comahue. Facultad de Ingeniería. Departamento de Mecánica Aplicada; Argentina

Deriving a year 2000 glacier inventory for New Zealand from the existing 2016 inventory

Due to adverse snow and cloud conditions, only a few inventories are available for the maritime glaciers in New Zealand. These are difficult to compare as different approaches and baseline data have been used to create them. In consequence, glacier fluctuations in New Zealand over the past two decades are only known for a few glaciers based on field observations. Here we present the results of a new inventory for the ‘year 2000’ (some scenes are from 2001 and 2002) that is based on glacier outlines from a recently published inventory for the year 2016 and allowed consistent change assessment for nearly 3000 glaciers over this period. The year 2000 inventory was created by manual on-screen digitizing using Landsat ETM+ satellite imagery (15 m panchromatic band) in the background and the year 2016 outlines as a starting point. Major challenges faced were late and early seasonal snow, clouds and shadow, the geo-location mismatch between Landsat and Sentinel-2 as well as the correct interpretation of ice patches and ice under debris cover. In total, we re-mapped 2967 glaciers covering an area of 885.5 km$^{2}$ in 2000, which is 91.7 km$^{2}$ (or 10.4%) more than the 793.8 km$^{2}$ mapped in 2016. Area change rates (mean rate −0.65% a$^{−1}$) increase towards smaller glaciers. Strongest area loss from 2000 to 2016 occurred at elevations ~1900 m but the highest relative loss was found below 800 m a.s.l. In total, 109 glaciers split into two or more entities and 264 had wasted away by 2016

Identifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systems

The deposition of livestock urine and feces in grazed fields results in a sizable input of available nitrogen (N) in these soils; therefore significantly increasing potential nitrogen pollution from agricultural areas in the form of nitrous oxide (N2O), ammonia (NH3), and nitrate (NO3−). Livestock deposition events contributes to high spatial variability within the field and generate uncertainties when assessing the contribution that animal waste has on nitrogen pollution pathways. This study investigated an innovative technique for identifying the spatial coverage of urine deposition in grasslands without the need for manual soil measurements. A Remotely Piloted Aircraft System (RPAS) using a twin camera system was used to identify urine patches in a 5 ha field, which had been grazed by sheep 3 weeks previous to measurements. The imagery was processed using Agisoft Photoscan (Agisoft LLC) to produce true and false color orthomosaic imagery of the entire field. Imagery of five areas (225 m2) within the field were analyzed using a custom R script. For a total of 1,125 m2 of grassland, 12.2% of the area consisted of what was classified as urine patch. A simple up-scaling method was applied to these data to calculate N2O emissions for the entire field providing an estimate of 1.3–2.0 kg N2O-N ha−1 emissions from urine and fertilizer inputs

Which glaciers are the largest in the world?

Glacier monitoring has been internationally coordinated for more than 125 years. Despite this long history, there is no authoritative answer to the popular question: ‘Which glaciers are the largest in the world?’ Here, we present the first systematic assessment of this question and identify the largest glaciers in the world – distinct from the two ice sheets in Greenland and Antarctica but including the glaciers on the Antarctic Peninsula. We identify the largest glaciers in two domains: on each of the seven geographical continents and in the 19 first-order glacier regions defined by the Global Terrestrial Network for Glaciers. Ranking glaciers by area is non-trivial. It depends on how a glacier is defined and mapped and also requires differentiating between a glacier and a glacier complex, i.e. glaciers that meet at ice divides such as ice caps and icefields. It also depends on the availability of a homogenized global glacier inventory. Using separate rankings for glaciers and glacier complexes, we find that the largest glacier complexes have areas on the order of tens of thousands of square kilometers whereas the largest glaciers are several thousands of square kilometers. The world's largest glaciers and glacier complexes are located in the Antarctic, Arctic and Patagonia

Automated detection of rock glaciers using deep learning and object-based image analysis

B Robson was supported by the Meltzer foundation and a University of Bergen grant. S MacDonell was supported by CONICYT-Programa Regional (R16A10003) and the Coquimbo Regional Government via FIC-R(2016)BIP 40000343. D. Hölbling has been supported by the Austrian Science Fund through the project MORPH (Mapping, Monitoring and Modeling the Spatio-Temporal Dynamics of Land Surface Morphology; FWF-P29461-N29). N Schaffer was financed by CONICYT-FONDECYT (3180417) and P Rastner by the ESA Dragon 4 programme (4000121469/17/I-NB).Rock glaciers are an important component of the cryosphere and are one of the most visible manifestations of permafrost. While the significance of rock glacier contribution to streamflow remains uncertain, the contribution is likely to be important for certain parts of the world. High-resolution remote sensing data has permitted the creation of rock glacier inventories for large regions. However, due to the spectral similarity between rock glaciers and the surrounding material, the creation of such inventories is typically conducted based on manual interpretation, which is both time consuming and subjective. Here, we present a novel method that combines deep learning (convolutional neural networks or CNNs) and object-based image analysis (OBIA) into one workflow based on freely available Sentinel-2 optical imagery (10 m spatial resolution), Sentinel-1 interferometric coherence data, and a digital elevation model (DEM). CNNs identify recurring patterns and textures and produce a prediction raster, or heatmap where each pixel indicates the probability that it belongs to a certain class (i.e. rock glacier) or not. By using OBIA we can segment the datasets and classify objects based on their heatmap value as well as morphological and spatial characteristics. We analysed two distinct catchments, the La Laguna catchment in the Chilean semi-arid Andes and the Poiqu catchment in the central Himalaya. In total, our method mapped 108 of the 120 rock glaciers across both catchments with a mean overestimation of 28%. Individual rock glacier polygons howevercontained false positives that are texturally similar, such as debris-flows, avalanche deposits, or fluvial material causing the user's accuracy to be moderate (63.9–68.9%) even if the producer's accuracy was higher (75.0–75.4%). We repeated our method on very-high-resolution Pléiades satellite imagery and a corresponding DEM (at 2 m resolution) for a subset of the Poiqu catchment to ascertain what difference image resolution makes. We found that working at a higher spatial resolution has little influence on the producer's accuracy (an increase of 1.0%), however the rock glaciers delineated were mapped with a greater user's accuracy (increase by 9.1% to 72.0%). By running all the processing within an object-based environment it was possible to both generate the deep learning heatmap and perform post-processing through image segmentation and object reshaping. Given the difficulties in differentiating rock glaciers using image spectra, deep learning combined with OBIA offers a promising method for automating the process of mapping rock glaciers over regional scales and lead to a reduction in the workload required in creating inventories.Publisher PDFPeer reviewe

Occurrence and characteristics of rock glaciers in the Poiqu River basin – Central Himalaya

Funding: This study was conducted within the framework of the Dragon 4 program funded by ESA (4000121469/17/I-NB) and further supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDA20100300), Swiss National Science Foundation (Grant No. IZLCZ2_169979/1) and the Hong Kong Research Grants Council (CUHK14303417 and HKPFS PF16-03859).Rock glaciers are important to study as they can be of hydrological importance and could have serious hazard potentials. Existing investigations about rock glaciers in High Mountain Asia indicate that the landforms are abundant, but information is still rare for large parts of the region. We compiled a rock glacier inventory for the Poiqu River basin, Central Himalaya. The mapping was conducted using very high-resolution Pléiades imagery and digital elevation model and imagery available from Google Earth. Rock glaciers were classified either active or inactive based on interferograms generated using ALOS-1 PALSAR data. Moreover, we developed a new method to automatically map the frontal slopes of the rock glaciers to investigate their activity. The results reveal 370 rock glaciers including 148 active and 222 inactive ones. We found nine rock glaciers damming lakes, three of which could be potentially dangerous. The overall rock glacier area is about 20.9 km which is more than 10% of the glacier area. The two largest rock glaciers cover 0.50 and 0.45 km². The rock glaciers are located at elevations between ~4000 and ~6000 m above sea level (mean elevations ~5100 m). Most of the rock glaciers face towards East and Southwest. The mean overall slope is 19.3° with the active ones being on average only slightly steeper (active: 19.7°, inactive: 19.0°). Their frontal slopes, however, are clearly steeper. The availability of very high-resolution data was key to generate a rock glacier inventory and allowed assessment of the rock glacier characteristics with high accuracy.PreprintNon peer reviewe

Earth observation to investigate occurrence, characteristics and changes of glaciers, glacial lakes and rock glaciers in Poiqu River Basin (Central Himalaya)

This research has been supported by the Dragon 4 program funded by ESA (4000121469/17/I-NB), the Swiss National Science Foundation (grant nos. IZLCZ2_169979/1 and 200021E_177652/1) and the Strategic Priority Research Program of Chinese Academy of Sciences (grant no. XDA20100300).Meltwater from the cryosphere contributes a significant fraction of the freshwater resources in the countries receiving water from the Third Pole. Within the ESA-MOST Dragon 4 project, we addressed in particular changes of glaciers and proglacial lakes and their interaction. In addition, we investigated rock glaciers in permafrost environments. Here, we focus on the detailed investigations which have been performed in the Poiqu River Basin, central Himalaya. We used in particular multi-temporal stereo satellite imagery, including high-resolution 1960/70s Corona and Hexagon spy images and contemporary Pleiades data. Sentinel-2 data was applied to assess the glacier flow. The results reveal that glacier mass loss continuously increased with a mass budget of −0.42 ± 0.11 m w.e.a−1 for the period 2004–2018. The mass loss has been primarily driven by an increase in summer temperature and is further accelerated by proglacial lakes, which have become abundant. The glacial lake area more than doubled between 1964 and 2017. The termini of glaciers that flow into lakes moved on average twice as fast as glaciers terminating on land, indicating that dynamical thinning plays an important role. Rock glaciers are abundant, covering approximately 21 km2, which was more than 10% of the glacier area (approximately 190 km2) in 2015. With ongoing glacier wastage, rock glaciers can become an increasingly important water resource.Publisher PDFPeer reviewe

Annual to seasonal glacier mass balance in High Mountain Asia derived from Pl\ue9iades stereo images: examples from the Pamir and the Tibetan Plateau

\ua9 Copyright: Glaciers are crucial sources of freshwater in particular for the arid lowlands surrounding High Mountain Asia. To better constrain glacio-hydrological models, annual, or even better, seasonal information about glacier mass changes is highly beneficial. In this study, we evaluate the suitability of very-high-resolution Pl\ue9iades digital elevation models (DEMs) to measure glacier mass balance at annual and seasonal scales in two regions of High Mountain Asia (Muztagh Ata in Eastern Pamirs and parts of western Nyainq\ueantanglha, south-central Tibetan Plateau), where recent estimates have shown contrasting glacier behaviour. The average annual mass balance in Muztagh Ata between 2019 and 2022 was -0.07ĝ€\uaf\ub1ĝ€\uaf0.20ĝ€\uafmĝ€\uafw.e.ĝ€\uafa-1, suggesting the continuation of a recent phase of slight mass loss following a prolonged period of balanced mass budgets previously observed. The mean annual mass balance in western Nyainq\ueantanglha was highly negative for the same period (-0.60ĝ€\uaf\ub1ĝ€\uaf0.15ĝ€\uafmĝ€\uafw.e.ĝ€\uafa-1), suggesting increased mass loss rates compared to the approximately previous 5 decades. The 2022 winter (+0.13ĝ€\uaf\ub1ĝ€\uaf0.24ĝ€\uafmĝ€\uafw.e.) and summer (-0.35ĝ€\uaf\ub1ĝ€\uaf0.15ĝ€\uafmĝ€\uafw.e.) mass budgets in Muztagh Ata and western Nyainq\ueantanglha (-0.03ĝ€\uaf\ub1ĝ€\uaf0.27ĝ€\uafmĝ€\uafw.e. in winter; -0.63ĝ€\uaf\ub1ĝ€\uaf0.07ĝ€\uafmĝ€\uafw.e. in summer) suggest winter- and summer-accumulation-type regimes, respectively. We support our findings by implementing the Sentinel-1-based Glacier Index to identify the firn and wet-snow areas on glaciers and characterize the accumulation type. The good match between the geodetic and Glacier Index results supports the potential of very-high-resolution Pl\ue9iades data to monitor mass balance at short timescales and improves our understanding of glacier accumulation regimes across High Mountain Asia