Jan Kropáček

Glacier mass changes on the Tibetan Plateau 2003-2009 derived from ICESat laser altimetry measurements

Glacier mass changes are a valuable indicator of climate variability and monsoon oscillation on the underexplored Tibetan Plateau. In this study data from the Ice Cloud and Elevation Satellite (ICESat) is employed to estimate elevation and mass changes of glaciers on the Tibetan Plateau between 2003 and 2009. In order to get a representative sample size of ICESat measurements, glaciers on the Tibetan Plateau were grouped into eight climatically homogeneous sub-regions. Most negative mass budgets of ? 0.77 ? 0.35?m?w.e.?a?1 were found for the Qilian Mountains and eastern Kunlun Mountains while a mass gain of + 0.37 ? 0.25?m?w.e.?a?1 was found in the westerly-dominated north-central part of the Tibetan Plateau. A total annual mass budget of ? 15.6 ? 10.1?Gt?a?1 was estimated for the eight sub-regions sufficiently covered by ICESat data which represents ?80% of the glacier area on the Tibetan Plateau. 13.9 ? 8.9?Gt?a?1 (or 0.04 ? 0.02?mm?a?1 sea-level equivalent) of the total mass budget contributed ?directly? to the global sea-level rise while 1.7 ? 1.9?Gt?a?1 drained into endorheic basins on the plateau.

Object-oriented and textural image classification of the Siberia GBFM radar mosaic combined with MERIS imagery for continental scale land cover mapping

Boreal forests and wetlands play an important role in the climate system, in particular through biosphere–atmosphere flux exchanges. They are an important pool of carbon and their role as sink or source of greenhouse gases is not fully understood. Accurate mapping of the vegetation of Siberia can therefore contribute to a better understanding of these processes at regional scale and of their effects on the climate through regional biosphere modeling. The potential of the combination of radar data with medium‐resolution optical data to obtain regional‐scale land cover mapping is investigated using multi‐spectral imagery from the MERIS sensor at 300 m resolution and a high resolution radar mosaic (pixel spacing of 100 m) covering Western and Eastern Siberia compiled in the framework of the Global Boreal Forest Mapping project. For this purpose, capabilities of oriented‐object image analysis associated to wavelet multi‐resolution techniques are investigated. Results show that wavelet multi‐resolution textures bring relevant additional information for land cover classification. Suggestions are made for the implementation of an object‐based wavelet multi‐resolution texture estimator.

Temporal and Spatial Aspects of Snow Distribution in the Nam Co Basin on the Tibetan Plateau from MODIS Data

Large areas of the Tibetan plateau are only covered by a sparse network of ground snow sampling stations, while the snow cover is highly heterogeneously distributed due to wind, topography etc. Nevertheless, the snow accumulation and spatial patterns play an important role in the hydrological cycle. It releases moisture during the dry spring period before the onset of the monsoon season. Widely used MODIS snow cover products have been available globally since 2002. The understanding of the temporal and spatial distribution of snow cover in a given region calls for a comprehensive data representation method. In this paper a method to visualize both spatial and temporal aspects of snow cover distribution from MODIS 8-day composite data is presented. It is based on RGB display of the snow cover data which is grouped according to season. The RGB syntheses of snow cover distribution (RSD) were generated for the Nam Co Basin in the central part of the Tibetan Plateau during the years of 2002–2009. An alternating pattern of monsoon and autumn snow cover was identified in the western part of the basin which corresponds to the biennial character of the variations of the Indian monsoon. Monsoon snow cover was found in RSD images for the years 2002, 2004 and 2008 whereas in years 2003 and 2009 the autumn snow cover is dominant. The eastern part of the basin does not follow this general pattern since it is affected by the so called “lake effect”, which is a snow fall induced by the passing of dry and cold westerlies over the lake surface during the winter months. The years 2002, 2006 and 2007 were identified as years with a particularly strong lake effect from the RSD images. Areas with permanent snow cover and areas that were snow free were both found to be relatively stable. Comparison of the lake effect at Nam Co with nearby Siling Co, where the lake effect is smaller or absent, suggests that the presence of an effective barrier on the opposite side of the lake is a prerequisite for the occurrence of the strong lake effect.

Estimation of Mass Balance of the Grosser Aletschgletscher, Swiss Alps, from ICESat Laser Altimetry Data and Digital Elevation Models

Traditional glaciological mass balance measurements of mountain glaciers are a demanding and cost intensive task. In this study, we combine data from the Ice Cloud and Elevation Satellite (ICESat) acquired between 2003 and 2009 with air and space borne Digital Elevation Models (DEMs) in order to derive surface elevation changes of the Grosser Aletschgletscher in the Swiss Alps. Three different areas of the glacier are covered by one nominal ICESat track, allowing us to investigate the performance of the approach under different conditions in terms of ICESat data coverage, and surface characteristics. In order to test the sensitivity of the derived trend in surface lowering, several variables were tested. Employing correction for perennial snow accumulation, footprint selection and adequate reference DEM, we estimated a mean mass balance of −0.92 ± 0.18 m w.e. a−1. for the whole glacier in the studied time period. The resulting mass balance was validated by a comparison with another geodetic approach based on the subtraction of two DEMs for the years 1999 and 2009. It appears that the processing parameters need to be selected depending on the amount of available ICESat measurements, quality of the elevation reference and character of the glacier surface.

Reactivation of mass movements in Dessie graben, the example of an active landslide area in the Ethiopian Highlands

Dessie town is located in a tectonic depression along the western rift margin with a young, high energy relief. Study area is known for numerous landslides in the past. These landslides are of different types, from shallow soil creeping to huge deep-seated landslides with appreciable consequences. Landslides endanger the quickly growing regional centre of Dessie and its infrastructure. Four typical recent landslides have been selected and studied in detail using both remote sensing and field observations from 2013. The described reactivation and new landslide events have been caused by a combination of natural influences and anthropogenic activities. Since seasonal rainfall is the main external triggering factor, precipitation data from Dessie weather station were analysed. The degree of negative human impact on slope instability was also discussed. Endangered zones and the actual risk in the studied localities were identified, and adequate measures were proposed.

Geo-referencing of continental-scale JERS-1 SAR mosaics based on matching homologous features with a digital elevation model: theory and practice

An effective method for a posteriori ortho-rectification of continental-scale synthetic aperture radar (SAR) mosaics using a digital elevation model (DEM) has been developed. The method is based on homologous feature matching between the DEM and a simulated SAR image. The simulated image is derived from the radar-viewing geometry, topographic information and contextual information provided by the Shuttle Radar Topography Mission (SRTM), shorelines and water bodies database (SWBD) and GeoCover Landsat mosaics. Two large L-band SAR mosaics (the global boreal forest mapping (GBFM) Siberia mosaic and the global rain forest mapping (GRFM) Africa mosaic), assembled from the Japanese Earth Resources Satellite-1 (JERS-1) data, were accurately geo-referenced and ortho-rectified. The GRFM Africa mosaic was also radiometrically corrected for topographic effects. The accurate co-registration with the DEM allows for improved classification methods based on the combination of SAR backscatter with terrain features. Comparison of the revised GBFM and GRFM mosaics with a forthcoming set of continental-scale mosaics assembled from the Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radar (PALSAR) data will offer a unique possibility for change detection studies over the Tropical and Boreal forest zones with a temporal spacing of some 10 years.

Generation and Use of Topographic Features for Improving the Classification of the Regional Scale GBFM Siberia SAR Mosaic

Information on terrain features like slope, orientation and convexity may be very useful for thematic interpretation of single band satellite radar data. Accuracy of the co-registration is the key issue. The map-projected GBFM radar mosaic of Siberia has been co-registered with a digital elevation model, using a cross-correlation technique in the Fourier domain. The mosaic was produced in the framework of the Global Boreal Forest Mapping Project, an initiative of the Japan Agency for Space Exploration (JAXA), and is based on JERS-1 synthetic aperture radar (SAR) data acquired in years 1997-8. The SRTM digital elevation data (90 m horizontal resolution) have been used for areas up to 60 degrees of latitude and the USGS GTOPO30 elevation data (500 m horizontal resolution) for the rest of the area. Since SAR and DEM data-sets capture completely different features of the landscape and SAR imagery is affected by geometric and radiometric (shadow and layover) distortions due to elevation and local terrain slope, automatic matching by homologous features of the radar image to the DEM image is not possible. Due to the unavailability of SRTM data at the time of the mosaic processing and, in any event, due to computational constraints (the mosaic is composed of some 400 SAR strip-images covering 135 000 km2 each) the classical geo-coding procedure using slant range data had to be ruled out. The a-posteriori solution entailed the simulation of the radar reflectivity dependency on the local incidence angle based on available DEM and radar viewing geometry. The radar mosaic was then matched with the simulated image. The cross-correlation moving window was composed of mutually overlapping squares (60 by 60 pixels) in a regular grid with 20 pixel spacing between the centers. The co-registration gives good level of correlation not only for mountainous areas but also for hilly ones. High correlation occurs also in flat areas with pronounced hydrological features like river courses and lake shores that are reflected in SRTM as fine-detail features. The density of control points was on average 1400 points per 100 square kilometers. The geometric effect of topography (like shortening of the slopes oriented towards the radar) has been then corrected by inversion of the same model which had been used for generating the simulated image. Radar backscattering coefficient dependency on local incidence angle was modeled and corrected by a simple inverse sine function model. The corrected radar image was then fed to a classification algorithm together with layers extracted from the DEM, such as slope and convexity. Preliminary thematic classification results confirm that geometric and radiometric corrections afforded by this technique greatly improve the classification accuracy.

COMBINED METHOD FOR RISK ASSESSMENT OF MASS MOVEMENT AND EROSION SUSCEPTIBILITY IN THE ETHIOPIAN HIGHLANDS

The Ethiopian Plateau and the Rift Valley typically display various symptoms of intensive erosion, mass movement and land degradation, which have arisen in response to rapid changes in land cover in an area of high dynamics of relief development. In order to assess the risk of these symptoms of intensive erosion and mass movement it is necessary to apply a method for the evaluation of non-linear systems. Therefore, our aim was to develop a combined method for evaluating the risk of landslides or erosion using complex system theory. This combined integrated method has been tested on two selected localities with landslide hazards on the border of the Ethiopian Highlands and the Main Ethiopian Rift. The method is suitable for a prompt risk evaluation and swift decision making.