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Remote Sensing And Image Interpretation

Changes in climate extremes and their impacts on the natural physical environment: An overview of the IPCC SREX report

Glacial melting in the Tibetan Plateau affects the water resources of millions of people. This study finds that—partly owing to changes in atmospheric circulations and precipitation patterns—the most intensive glacier shrinkage is in the Himalayan region, whereas glacial retreat in the Pamir Plateau region is less apparent.

Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings

Contributing Authors: J. Box (USA), D. Bromwich (USA), R. Brown (Canada), J.G. Cogley (Canada), J. Comiso (USA), M. Dyurgerov (Sweden, USA), B. Fitzharris (New Zealand), O. Frauenfeld (USA, Austria), H. Fricker (USA), G. H. Gudmundsson (UK, Iceland), C. Haas (Germany), J.O. Hagen (Norway), C. Harris (UK), L. Hinzman (USA), R. Hock (Sweden), M. Hoelzle (Switzerland), P. Huybrechts (Belgium), K. Isaksen (Norway), P. Jansson (Sweden), A. Jenkins (UK), Ian Joughin (USA), C. Kottmeier (Germany), R. Kwok (USA), S. Laxon (UK), S. Liu (China), D. MacAyeal (USA), H. Melling (Canada), A. Ohmura (Switzerland), A. Payne (UK), T. Prowse (Canada), B.H. Raup (USA), C. Raymond (USA), E. Rignot (USA), I. Rigor (USA), D. Robinson (USA), D. Rothrock (USA), S.C. Scherrer (Switzerland), S. Smith (Canada), O. Solomina (Russian Federation), D. Vaughan (UK), J. Walsh (USA), A. Worby (Australia), T. Yamada (Japan), L. Zhao (China)

Observations: Changes in Snow, Ice and Frozen Ground

Glaciers are among the best terrestrial climate indicators, an important water resource in mountains1,2 and a major contributor to global sea level rise3,4. In the Hindu Kush - Karakoram - Himalaya region (HKKH), a paucity of appropriate glacier data has prevented a comprehensive assessment of current regional mass balance5. However, there are indirect evidences of a complex pattern of glacial responses5-8 in reaction to heterogeneous climate change signals9. Here, we provide the first coherent data set of detailed glacier thickness changes over the HKKH during 2003-2009 by combining satellite laser altimetry and a global elevation model. In the eastern, central and south-western parts of the HKKH, glacier wastage is widespread with regional thinning rates up to 0.66 ± 0.09 m a-1 in the Jammu-Kashmir region. Conversely, in the Karakoram, glaciers are close to balance with only a slight thinning of 0.07 ± 0.04 m a-1. Regionally averaged thinning rates under debris-mantled ice are similar to those of clean ice despite insulation by debris covers. The 2003-2008 specific mass balance for our HKKH study region is -0.21 ± 0.05 m a-1 water equivalent (WE), significantly less negative than the global average of ~ -0.7 m a-1 WE for glaciers and ice caps4,10. This difference is mainly an effect of the balanced glacier mass budget in the Karakoram. The corresponding HKKH sea level contribution is +0.035 ± 0.009 mm a-1 amounting to 1% of the present-day sea level rise11. Our 2003-2008 mass budget of -12.8 ± 3.5 Gt a-1 is more negative than recent satellite gravimetry based estimates of -5 ± 6 Gt a-1 over 2003-2010 (ref. 12). For the mountain catchments of the Indus and Ganges basins13, the glacier imbalance contributes ~3.5% and ~2.0%, respectively, to the annual average river discharge13, and up to ~10% for the Upper Indus basin14.

Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas

. Here we present results from ongoing work where we apply an object oriented mapping algorithm developed in eCognition in order to automatically identify and digitally map avalanche deposits. The algorithm performance is compared with respect to a selected number of manually digitized avalanche outlines mapped by avalanche experts.

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Using eCognition to automatically detect and map avalanche deposits from the spring 2009 avalanche cycle in the Tatra mts., Slovakia

Using eCognition we developed an algorithm to automatically detect and map avalanche deposits in Very High Resolution (VHR) optical remote sensing imagery acquired from satellites and airplanes. The algorithm relies on a cluster-based object-oriented image interpretation approach which employs segmentation and classification methodologies to identify avalanche deposits. The algorithm is capable of detecting avalanche deposits of varying size, composition, and texture. A discrete analysis of one data set (airborne imagery collected near Davos, Switzerland) demonstrates the capability of the algorithm. By comparing the automated detection results to the manually mapped results for the same image, 33 of the 35 manually digitized slides were correctly identified by the automated method. The automated mapping approach characterized 201 667 m2, of the image as being representative of a fresh snow avalanche, roughly 8.5% of the image. Through a spatial intersection between the manually mapped avalanches and the automatically mapped avalanches, 184 432 m2, or 89%, of the automatically mapped regions are spatially linked to the manually mapped regions. The rate of false positive was less than 1% of the pixels in the image. The initial results of the algorithm are promising, future development and implementation is currently being evaluated. The ability to automatically identify the location and extent of avalanche deposits using VHR optical imagery can assist in the development of detailed regional maps of zones historically prone to avalanches. This in turn can help to validate issued avalanche warnings.

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Automated Avalanche Deposit Mappping from VHR Optical Imagery

Remote sensing is the science of obtaining information about objects or areas from a distance, without being in direct contact with the target that's being investigated. Remote sensing methods make use of emitted and reflected radiation, captured from sensors on airplanes, satellites and drones, or from ground-based systems. Remote sensing exploits the fact that the Earth's atmosphere features three main atmospheric windows, each allowing the penetration of radiation. Active and passive methods are the two main types of remote sensing, utilizing naturally sourced radiation, or radiation actively produced by instruments, respectively. For decades, geologists have employed visual observations, photographs and, subsequently, aerial images to map and understand the Earths’ surface. Today, satellite imagery is used in addition to traditional methods or, sometimes, as a replacement. Recent advances in remote-sensing technologies, especially the rapid increase in the number of satellites, and consequently, in the image acquisition frequency, enable geoscientists to explore and analyze the land surface, acquire data and generate maps and evaluate the geo-potential of any specific area on the globe, at unprecedented scales and speeds. Today, remote sensing has become an irreplaceable tool in the geosciences at large, and specifically also in geology, the latter with many applications, such as geologic and geo-structural mapping, mineral and water exploration, hydrocarbon exploration, natural hazards analysis, and geomorphology.

Remote Sensing in Geology

Glaciers, snow cover and permafrost are important storages of terrestrial fresh water and are released from the storage by melting processe having a seasonal dynamics. Their changes over time can have significant impacts on the water cycle controlling the discharge behaviour of alpine rivers and on natural disasters relating to thawing of glaciers, snow and permafrost. These effects often include downstream areas outside of the direct glacial and periglacial zone.

Glacier Changes and Permafrost Distribution

(1) Department of Geography, University of Zürich, Switzerland / currently at: Department of Geosciences, University of Oslo, Norway, (2) Department of Physical Geography, University of Würzburg, Germany, (3) Department of Geography, University of Jena, Germany, (4) Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe, University of Karlsruhe, Germany / currently at: Department of Geography, University of Zürich, Switzerland

Regula Frauenfelder

Papers

Using eCognition to automatically detect and map avalanche deposits from the spring 2009 avalanche cycle in the Tatra mts., Slovakia

Automated Avalanche Deposit Mappping from VHR Optical Imagery

Remote Sensing in Geology

Glacier Changes and Permafrost Distribution

An integrative observation of kinematics and geophysical parameters of Gianda Grischa rockglacier, Upper Engadine, Swiss Alps