Rudiger Gens

Circumpolar Arctic Tundra Vegetation Change Is Linked to Sea Ice Decline

Abstract Linkages between diminishing Arctic sea ice and changes in Arctic terrestrial ecosystems have not been previously demonstrated. Here, the authors use a newly available Arctic Normalized Difference Vegetation Index (NDVI) dataset (a measure of vegetation photosynthetic capacity) to document coherent temporal relationships between near-coastal sea ice, summer tundra land surface temperatures, and vegetation productivity. The authors find that, during the period of satellite observations (1982–2008), sea ice within 50 km of the coast during the period of early summer ice breakup declined an average of 25% for the Arctic as a whole, with much larger changes in the East Siberian Sea to Chukchi Sea sectors (>44% decline). The changes in sea ice conditions are most directly relevant and have the strongest effect on the villages and ecosystems immediately adjacent to the coast, but the terrestrial effects of sea ice changes also extend far inland. Low-elevation (<300 m) tundra summer land temperatures, a...

SAR interferometry : issues, techniques, applications

Abstract Data from interferometric synthetic aperture radar (INSAR) can provide three-dimensional information by using the phase as an additional information source derived from the complex radar data. In this paper, the issues, techniques and applications of SAR interferometry are reviewed. After a brief historical review, the geometric implementations of SAR interferometry are described. The general processing techniques are summarized and an introduction to various phase unwrapping techniques is given. Besides the differential use of SAR interferometry, the review focuses on parameters such as baseline, decorrelation and motion compensation which have a limiting influence on the quality of the data. After evaluating the various existing and potential applications using SAR interferometric techniques such as topographic mapping, digital elevation modelling, slope measurement, change detection, classification, ocean currents, polar research, seismic events and volcanic hazards, the paper concludes with s...

Remote sensing of coastlines: detection, extraction and monitoring

This paper reviews the current status of the use of remote sensing for the detection, extraction and monitoring of coastlines. The review takes the US system as an example. However, the issues at hand can be applied to any other part of the world. Visual interpretation of airborne remote sensing data is still widely and popularly used for coastal delineation. However, a variety of remote sensing data and techniques are available to detect, extract and monitor the coastline. The developed techniques have reached a level of maturity such that they are applied in operational settings.

Climate Divisions for Alaska Based on Objective Methods

AbstractAlaska encompasses several climate types because of its vast size, high-latitude location, proximity to oceans, and complex topography. There is a great need to understand how climate varies regionally for climatic research and forecasting applications. Although climate-type zones have been established for Alaska on the basis of seasonal climatological mean behavior, there has been little attempt to construct climate divisions that identify regions with consistently homogeneous climatic variability. In this study, cluster analysis was applied to monthly-average temperature data from 1977 to 2010 at a robust set of weather stations to develop climate divisions for the state. Mean-adjusted Advanced Very High Resolution Radiometer surface temperature estimates were employed to fill in missing temperature data when possible. Thirteen climate divisions were identified on the basis of the cluster analysis and were subsequently refined using local expert knowledge. Divisional boundary lines were drawn th...

Two-dimensional phase unwrapping for radar interferometry: developments and new challenges

The growing interest in the applications of synthetic aperture radar (SAR) interferometry led to an increasing demand for reliable phase unwrapping techniques. Research efforts have been spent on the understanding of the principles in order to develop more robust algorithms with improved computational characteristics. Numerous algorithms have been proposed to solve the two-dimensional phase unwrapping problem. This paper reviews the basic concepts of phase unwrapping and gives an overview on the major processing strategies for solving the problem. It presents the developments in phase unwrapping with special reference to SAR interferometry and indicates the trends and new challenges in this field.

Data fusion for investigating land subsidence and coal fire hazards in a coal mining area

Coal mining areas all over the world are often threatened by serious environmental hazards such as the occurrence of coal fires, land subsidence, etc. Coal fires burn away the natural non-renewable coal resources, locally raise the temperature of the area, emit polluting gases such as oxides of carbon, sulphur and nitrogen, and when present underground are even the cause of land subsidence. Mining-induced subsidences, on the other hand, cause horizontal and vertical movements in the land surface, and open cracks and fissures that serve as inlets for oxygen, which in turn aggravate the problem of coal fires. These inter-related phenomena often render the mining areas unfit for human inhabitation and the commercial exploitation of coal nearly impossible in some parts. In this study, satellite data acquired in three regions of the electromagnetic spectrum, namely optical, thermal and microwave, along with field data, are used to identify the areas affected by coal fires and land subsidence in a coalfield in north-west China. Data fusion techniques are used for an integrated analysis of this complex problem.

Monitoring coal fires using multi-temporal night-time thermal images in a coalfield in north-west China

China has the largest coal resources in the world but these are seriously endangered by coal fires. Though the problem of coal fires is long standing and not only limited to China, little has been done for regular monitoring of these fires. This Letter proposes the use of multi-temporal night-time thermal images acquired from Landsat Thematic Mapper band 6 for establishing a coal fire monitoring system for a coalfield in north-west China. Other images and map data are fused with the thermal images to provide a comprehensive picture of the fires through the years. Finally the fires are classified into different categories based on multi-temporal changes.

Timing of retrogressive thaw slump initiation in the Noatak Basin, northwest Alaska, USA

In the North American low arctic, increased retrogressive thaw slump frequency and headwall retreat rates have been linked with climate warming trends since the midtwentieth century, but specific weather drivers of slump initiation timing are less clear. We examined relationships among retrogressive thaw slump initiation and annual air temperature, precipitation, and snow cover using time series of satellite imagery and weather station data in northwest Alaska. Synthetic aperture RADAR and optical imagery were used to examine retrogressive thaw slump initiation between 1997 and 2010. Over 80% of the slump features examined in this study first appear within a 13 month span from late June 2004 to July 2005. Remote weather station data show that 2004 and 2005 are among several years exhibiting above average thawing indices and average summer temperatures between 1992 and 2011. However, 2004 is distinct from the rest of the record, with unusually warm temperatures primarily occurring early in the thaw season between April and early June, and including two intense precipitation events in May. Regional weather reported by the NOAA National Weather Service also reflects these local findings. Snowmelt timing in 2004 corresponded with warmer air temperatures and precipitation between April and May, exposing the ground surface more than 2 weeks earlier than average for 2001–2012 within the Noatak Basin. Future rates of thaw slump initiation may be linked with changing trends in the timing of weather, in addition to general climate warming.

Improving PolSAR Land Cover Classification With Radiometric Correction of the Coherency Matrix

The brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. For polarimetric SAR (PolSAR) imagery being used for purposes of land cover classification, this radiometric variability is shown to affect the outcome of a Wishart unsupervised classification in areas of moderate topography. The intent of this paper is to investigate the impact of applying a radiometric correction to the PolSAR coherency matrix for a region of boreal forest in interior Alaska. The gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product that is radiometrically “flat.” This paper follows two paths, one with and one without radiometric correction, to investigate the impact upon classification accuracy. Using a Landsat-derived land cover reference, the radiometric correction is shown to bring about significant qualitative and quantitative improvements in the land cover map. Confusion matrix analysis confirms the accuracy for most classes and shows a 15% improvement in the classification of the deciduous forest class.

The influence of input parameters on SAR interferometric processing and its implication on the calibration of SAR interferometric data

Synthetic Aperture Radar (SAR) interferometry is a field of rapid development. The processing of SAR interferometric data is complex and influenced, in particular, by the input parameters. A sensitivity study of these input parameters and issues relating to the calibration of SAR interferometric data is presented. The pulse repetition frequency has been identified as a critical parameter during the SAR interferometric processing which, in case of inconsistencies in the CEOS standard data format, leads to erroneous results.