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PubMed | European Commission, James Hutton Institute, Research and Conservation Division, University of Queensland and 86 more.
Type: | Journal: Global change biology | Year: 2016

The first International Peat Congress (IPC) held in the tropics - in Kuching (Malaysia) - brought together over 1000 international peatland scientists and industrial partners from across the world (International Peat Congress with over 1000 participants!, 2016). The congress covered all aspects of peatland ecosystems and their management, with a strong focus on the environmental, societal and economic challenges associated with contemporary large-scale agricultural conversion of tropical peat. This article is protected by copyright. All rights reserved.


Atwood E.C.,Ludwig Maximilians University of Munich | Atwood E.C.,RSS Remote Sensing Solutions GmbH | Englhart S.,RSS Remote Sensing Solutions GmbH | Lorenz E.,German Aerospace Center | And 4 more authors.
PLoS ONE | Year: 2016

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future. © 2016 Atwood et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Low F.,German Aerospace Center | Navratil P.,RSS Remote Sensing Solutions GmbH | Kotte K.,University of Heidelberg | Scholer H.F.,University of Heidelberg | Bubenzer O.,University of Cologne
Environmental Monitoring and Assessment | Year: 2013

With the recession of the Aral Sea in Central Asia, once the world's fourth largest lake, a huge new saline desert emerged which is nowadays called the Aralkum. Saline soils in the Aralkum are a major source for dust and salt storms in the region. The aim of this study was to analyze the spatio-temporal land cover change dynamics in the Aralkum and discuss potential implications for the recent and future dust and salt storm activity in the region. MODIS satellite time series were classified from 2000-2008 and change of land cover was quantified. The Aral Sea desiccation accelerated between 2004 and 2008. The area of sandy surfaces and salt soils, which bear the greatest dust and salt storm generation potential increased by more than 36 %. In parts of the Aralkum desalinization of soils was found to take place within 4-8 years. The implication of the ongoing regression of the Aral Sea is that the expansion of saline surfaces will continue. Knowing the spatio-temporal dynamics of both the location and the surface characteristics of the source areas for dust and salt storms allows drawing conclusions about the potential hazard degree of the dust load. The remote-sensing-based land cover assessment presented in this study could be coupled with existing knowledge on the location of source areas for an early estimation of trends in shifting dust composition. Opportunities, limits, and requirements of satellite-based land cover classification and change detection in the Aralkum are discussed. © 2013 Springer Science+Business Media Dordrecht.


Konecny K.,Ludwig Maximilians University of Munich | Konecny K.,RSS Remote Sensing Solutions GmbH | Ballhorn U.,RSS Remote Sensing Solutions GmbH | Navratil P.,RSS Remote Sensing Solutions GmbH | And 7 more authors.
Global Change Biology | Year: 2016

Tropical peatland fires play a significant role in the context of global warming through emissions of substantial amounts of greenhouse gases. However, the state of knowledge on carbon loss from these fires is still poorly developed with few studies reporting the associated mass of peat consumed. Furthermore, spatial and temporal variations in burn depth have not been previously quantified. This study presents the first spatially explicit investigation of fire-driven tropical peat loss and its variability. An extensive airborne Light Detection and Ranging data set was used to develop a prefire peat surface modelling methodology, enabling the spatially differentiated quantification of burned area depth over the entire burned area. We observe a strong interdependence between burned area depth, fire frequency and distance to drainage canals. For the first time, we show that relative burned area depth decreases over the first four fire events and is constant thereafter. Based on our results, we revise existing peat and carbon loss estimates for recurrent fires in drained tropical peatlands. We suggest values for the dry mass of peat fuel consumed that are 206 t ha-1 for initial fires, reducing to 115 t ha-1 for second, 69 t ha-1 for third and 23 t ha-1 for successive fires, which are 58-7% of the current IPCC Tier 1 default value for all fires. In our study area, this results in carbon losses of 114, 64, 38 and 13 t C ha-1 for first to fourth fires, respectively. Furthermore, we show that with increasing proximity to drainage canals both burned area depth and the probability of recurrent fires increase and present equations explaining burned area depth as a function of distance to drainage canal. This improved knowledge enables a more accurate approach to emissions accounting and will support IPCC Tier 2 reporting of fire emissions. © 2016 John Wiley & Sons Ltd.


Ballhorn U.,RSS Remote Sensing Solutions GmbH | Jubanski J.,RSS Remote Sensing Solutions GmbH | Kronseder K.,RSS Remote Sensing Solutions GmbH | Kronseder K.,Ludwig Maximilians University of Munich | And 2 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2012

We estimated forest Above Ground Biomass (AGB) of tropical peat swamp forests in the Indonesian province of Central Kalimantan through correlating airborne Light Detection And Ranging (LiDAR) data to forest inventory data. Two LiDAR point cloud metrics, the Quadratic Mean Canopy profile Height (QMCH) and the Centroid Height (CH), were correlated to the field derived AGB estimates. The regression models could be improved through the use of the LiDAR point densities as input. The highest coefficient of determination was achieved for CH (R2= 0.88; n= 52). Surveying with a LiDAR point density between 2-4 points per square meter (pt/m2) resulted in the best cost-benefit ratio. It was also shown that impact from logging and the associated AGB losses dating back more than 10 years could still be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat based AGB estimate showed an overestimation of 60.8% in a 3.0 million ha study area. © 2012 IEEE.

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