Peter Strobl

Data Fusion of Different Spatial Resolution Remote Sensing Images Applied to Forest-Type Mapping

A data fusion method for land cover (LC) classification is proposed that combines remote sensing data at a fine and a coarse spatial resolution. It is a two-step approach, based on the assumption that some of the LC classes can be merged into a more generalized LC class. Step one creates a generalized LC map, using only the information available at the fine spatial resolution. In the second step, a new classifier refines the generalized LC classes to create distinct subclasses of its parent class, using the generalized LC map as a mask. This classifier uses all image information (bands) available at both fine and coarse spatial resolutions. We followed a simple data fusion technique by stacking the individual image bands into a multidimensional vector. The advantage of the proposed approach is that the spatial detail of the generalized LC classes is retained in the final LC map. The method has been designed for operational LC mapping over large areas. Within this paper, it is shown that the proposed data fusion approach increased the robustness of forest-type mapping within Europe. Robustness is particularly important when creating continental LC maps at fine spatial resolution. These maps become more popular now that remote sensing data at fine resolution are easier to access.

Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)

Fires are an integral component of ecosystem dynamics in European landscapes. However, uncontrolled fires cause large environmental and economic damages, especially in the Mediterranean region. On average, about 65000 fires occur in Europe every year, burning approximately half a million ha of wildland and forest areas; most of the burnt area, over 85%, is in the European Mediterranean region. Trends in number of fires and burnt areas in the Mediterranean region are presented in Fig. 1.

APEX: current status of the airborne dispersive pushbroom imaging spectrometer

Over the past few years, a joint Swiss/Belgium ESA initiative resulted in a project to build a precursor mission of future spaceborne imaging spectrometers, namely APEX (Airborne Prism Experiment). APEX is designed to be an airborne dispersive pushbroom imaging spectrometer operating in the solar reflected wavelength range between 4000 and 2500 nm. The system is optimized for land applications including limnology, snow, and soil, amongst others. The instrument is optimized with various steps taken to allow for absolute calibrated radiance measurements. This includes the use of a pre- and post-data acquisition internal calibration facility as well as a laboratory calibration and a performance model serving as a stable reference. The instrument is currently in its breadboarding phase, including some new results with respect to detector development and design optimization for imaging spectrometers. In the same APEX framework, a complete processing and archiving facility (PAF) is developed. The PAF not only includes imaging spectrometer data processing up to physical units, but also geometric and atmospheric correction for each scene, as well as calibration data input. The PAF software includes an Internet based web-server and provides interfaces to data users as well as instrument operators and programmers. The software design, the tools and its life cycle are discussed as well.

Laboratory calibration and inflight validation of the Digital Airborne Imaging Spectrometer DAIS 7915

In the past various authors pointed out, that the value of imaging spectrometer data is closely related to the accuracy with which the data are calibrated to represent physical parameters. the AVIRIS team at JPL gave good examples on how the calibration can be performed in the laboratory and how its accuracy can be evaluated independently by means of an in-flight calibration/validation experiment. The first part of this paper presents the laboratory instrumentation and measurements that were brought into place at the German Aerospace Research Establishment (DLR) to calibrate the DAIS 7915 sensor. Some estimates of the accuracy of these measurements are given to allow the derivation of an overall precision of the laboratory calibration. It is the purpose of an in-flight calibration and validation campaign to check the validity of the laboratory calibration for data acquired under in-flight conditions. In a joint experiment of DLR and the Remote Sensing Laboratories of the University of Zurich the DAIS instrument flew a standard test site in the center of Switzerland in summer 1996. In parallel to this overflight a number of ground reference measurements are acquired. The influence of the atmosphere is accounted for using the MODTRAN radiative transfer code. Sample spectra for different in-flight calibration targets are displayed.

Forest Fires in the European Mediterranean Region: Mapping and Analysis of Burned Areas

Approximately 60,000 fires occur in the European Mediterranean region every year. On average, they burn approximately half a million ha of forest areas. The mapping of areas burned by forest fires is of critical importance for the analysis of fire impact and for the monitoring of fire recurrence and vegetation recovery in affected areas. An important contribution of remote sensing in wildfire monitoring is the mapping and analysis of burnt areas. Areas affected by forest fires present a distinct spectral response in the optical and infrared part of the electromagnetic spectrum, which allows the mapping of these surfaces with the use of passive satellite remote sensors. On the side of active sensors, the synthetic aperture radar is also used for this purpose, especially in boreal regions, where continuous cloud cover prevents the use of optical sensors. Although remote sensing of burnt areas in the Mediterranean region has a long history, the operational implementation of remote sensing methods in national or regional Administrations is fairly new. The need of specialized personnel, dedicated hardware and software for image processing, and the lack of automation of the classification methods has prevented its operational implementation until recently. A large contribution to the success in the current use of remote sensing for burned area mapping is due to the increased processing capacity of modern computers and the ever increasing availability of remotely sensed imagery from a large variety of sensors, from the low spatial resolution in the order of km to the very high spatial detailed imagery in the order of cm. The choice of imagery depends, obviously, on the application at regional or local scale, and the frequency for which updates of fire perimeters are needed. The current chapter reviews the application of remote sensing for burned area mapping and its use in the Mediterranean region for operational fire monitoring. Additionally, it provides insights on future opportunities for the improvement of existing mechanisms, the acquisition and processing of satellite imagery, and the analysis of burnt areas.

Cumulative Sum Charts - A Novel Technique for Processing Daily Time Series of MODIS Data for Burnt Area Mapping in Portugal

Portugal has experienced severe forest fires in the recent years. European Commission (EC) requires accurate burned area assessment for Portugal every year. Satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) were found to be the most appropriate for the task. In this paper we describe an algorithm for burned area mapping in Portugal. The algorithm utilizes daily time series data from both Aqua and Terra for the whole fire season from 1.5.2005 till 31.10.2005. Robust approach to detect land cover change due to the forest fire was developed. Algorithm robustness absorbs the effects of sun-target-satellite viewing geometry, presence of residual clouds, atmospheric effects and missing data. A change due the forest fire is detected and supported by the confidence measures. A validation of the final burned area maps is performed against visual interpretation of single date MODIS scene and Landsat-derived fire maps. The visual interpretation results in 278,490 ha of burned area versus 278,801 ha assessed by the algorithm for whole Portugal. Landsat-derived maps for several big burned patches reveals 61,571 ha while algorithm based measurement results in 59772 ha of the burned forest. For its high reliability, the extension of usage of the algorithm for the whole Mediterranean area of European Union is under investigation.

Increasing Robustness of Postclassification Change Detection Using Time Series of Land Cover Maps

The monitoring of land cover requires that stable land cover classes be distinguished from changes over time. Within this paper, a postclassification method is presented that provides land cover change information, based on a time series of land cover maps. The method applies a kernel filter to sequential land cover maps. Under some basic assumptions, it shows robustness against classification errors. Despite seasonality, land cover changes often occur at a low temporal frequency (e.g., maximum once every 5-10 years). If land cover maps are available more frequently, some of the information will become redundant (oversampling). The proposed method uses this redundancy for tolerating (nonsystematic) misclassifications. In order to demonstrate the benefits and limitations of the proposed method, analytical expressions have been derived. When compared to a simple postclassification comparison, one of the key strengths of the proposed approach is that it is able to improve both the overall and users accuracy of change, while also maintaining the same level of producers accuracy. As a case study, MODerate Resolution Imaging Spectroradiometer remote sensing data from 2006-2010 were classified into forest (F)/nonforest (NF) at pan-European scale. Promising results were obtained for detecting forest loss due to natural disasters. Quality was assessed using burnt area maps in southern Europe and a forest damage report after a windstorm in France. Results indicated a considerable reduction of change detection errors, confirming the theoretical results.

Preprocessing for the digital airborne imaging spectrometer DAIS 7915

The digital airborne imaging spectrometer DAIS 7915 is a new hyperspectral scanner developed for scientific and commercial applications. The design of the sensor makes a dedicated preprocessing necessary, prior to any data evaluation. Therefore, a facility is being developed at DLR to fulfill the needs of operational preprocessing. Besides that this facility is used for continuous quality control to support the hardware team in improving the performance of the instrument. The implementation of the software and the algorithms currently used are presented in this paper.

Increasing Spatial Detail of Burned Scar Maps Using IRS‑AWiFS Data for Mediterranean Europe

Abstract: A two stage burned scar detection approach is applied to produce a burned scar map for Mediterranean Europe using IRS-AWiFS imagery acquired at the end of the 2009 fire season. The first stage identified burned scar seeds based on a learning algorithm (Artificial Neural Network) coupled with a bootstrap aggregation process. The second stage implemented a region growing process to extend the area of the burned scars. Several ancillary datasets were used for the accuracy assessment and a final visual check was performed to refine the burned scar product. Training data for the learning algorithm were obtained from MODIS-based polygons, which were generated by the Rapid Damage Assessment module of the European Forest Fire Information System. The map produced from this research is the first attempt to increase the spatial detail of current burned scar maps for the Mediterranean region. The map has been analyzed and compared to existing burned area polygons from the European Forest Fire Information System. The comparison showed that the IRS-AWiFS-based burned scar map improved the delineation of burn scars; in addition the process identified a number of small burned scars that were not detected on lower resolution sensor data. Nonetheless, the results do not clearly support the improved capability for the detection of smaller burned scars. A number of reasons can be provided for the under-detection of burned scars, these include: the lack of a full coverage and cloud free imagery, the time lag between forest fires and image acquisition date and the occurrence of fires after the image acquisition dates. On the other hand, the limited

ARES: A new reflective / emissive Imaging Spectrometer for Terrestrial Applications

A new airborne imaging spectrometer introduced: the ARES (Airborne Reflective Emissive Spectrometer) to be built by Integrated Spectronics, Sydney, Australia, financed by DLR German Aerospace Center and the GFZ GeoResearch Center Potsdam, Germany, and will be available to the scientific community from 2003/2004 on. The ARES sensor will provide 160 channels in the solar reflective region (0.45-2.45 μm) and the thermal region (8-13 μm). It will consists of two separate coregistered optical systems for the reflective and thermal part of the spectrum. The spectral resolution is intended to be between 12 and 15 nm in the solar wavelength range and should reach 150nm in the thermal. ARES will be used mainly for environmental applications in terrestrial ecosystems. The thematic focus is thought to be on soil sciences, geology, agriculture and forestry. Limnologic applications should be possible but will not play a key role in the thematic applications. For all above mentioned key application scenarios the spectral response of soils, rocks, and vegetation as well as their mixtures contain the valuable information to be extracted and quantified. The radiometric requirements for the instrument have been modelled based on realistic application scenarios and account for the most demanding requirements of the three application fields: a spectral bandwidth of 15 nm in the 0.45-1.8 μm region, and 12 nm in the 2 - 2.45 μm region. The required noise equivalent radiance is 0.005, 0.003, and 0.003 mWcm-2sr-1μm-1 for the spectral regions 0.45-1 μm, 1 - 1.8 μm, and 2 - 2.45 μm, respectively.