The Fully Automatic Optical Processing System Catena at DLR

Krauss, Thomas F.; d’Angelo, Pablo; Schneider, Mathias; Gstaiger, Veronika

doi:10.5194/isprsarchives-xl-1-w1-177-2013

Cited by 41 publications

(27 citation statements)

References 2 publications

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“…Their respective location is indicated as black frames in Figure 1. The RapidEye images were orthorectified and atmospherically corrected using the automated processing chain CATENA developed and maintained by the German Aerospace Center [27]. CATENA relies on the physical model implemented in the ATCOR software to eliminate atmospheric effects [28].…”

Section: The Rapideye Datamentioning

confidence: 99%

Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

et al. 2015

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Image time series of high temporal and spatial resolution capture land surface dynamics of heterogeneous landscapes. We applied the ESTARFM (Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model) algorithm to multi-spectral images covering two semi-arid heterogeneous rangeland study sites located in South Africa. MODIS 250 m resolution and RapidEye 5 m resolution images were fused to produce synthetic RapidEye images, from June 2011 to July 2012. We evaluated the performance of the algorithm by comparing predicted surface reflectance values to real RapidEye images. Our results show that ESTARFM predictions are accurate, with a coefficient of determination for the red band 0.80 < R 2 < 0.92, and for the near-infrared band 0.83 < R 2 < 0.93, a mean relative bias between 6% and 12% for the red band and 4% to 9% in the near-infrared band. OPEN ACCESSRemote Sens. 2015, 7 6511Heterogeneous vegetation at sub-MODIS resolution is captured adequately: A comparison of NDVI time series derived from RapidEye and ESTARFM data shows that the characteristic phenological dynamics of different vegetation types are reproduced well. We conclude that the ESTARFM algorithm allows us to produce synthetic remote sensing images at high spatial combined with high temporal resolution and so provides valuable information on vegetation dynamics in semi-arid, heterogeneous rangeland landscapes.

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Section: The Rapideye Datamentioning

confidence: 99%

Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

et al. 2015

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“…Before being processed all of the images are converted from the original JPEG 2000 file format to the DLR internal XDIBIAS (Krauß, 2013) Difference images between the adjusted mosaicked images and the reference images were produced in order to evaluate the results not only by visual means. Quality and stability of the results are evaluated by means of a per-band global root-meansquare deviation and mean error.…”

Section: Methodsmentioning

confidence: 99%

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

Langheinrich

Fischer

Probeck

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The growing number of available optical remote sensing data providing large spatial and temporal coverage enables the coherent and gapless observation of the earth's surface on the scale of whole countries or continents. To produce datasets of that size, individual satellite scenes have to be stitched together forming so-called mosaics. Here the problem arises that the different images feature varying radiometric properties depending on the momentary acquisition conditions. The interpretation of optical remote sensing data is to a great extent based on the analysis of the spectral composition of an observed surface reflection. Therefore the normalization of all images included in a large image mosaic is necessary to ensure consistent results concerning the application of procedures to the whole dataset. In this work an algorithm is described which enables the automated spectral harmonization of satellite images to a reference scene. As the stable and satisfying functionality of the proposed algorithm was already put to operational use to process a high number of SPOT-4/-5, IRS LISS-III and Landsat-5 scenes in the frame of the European Environment Agency's Copernicus/GMES Initial Operations (GIO) High-Resolution Layer (HRL) mapping of the HRL Forest for 20 Western, Central and (South)Eastern European countries, it is further evaluated on its reliability concerning the application to newer Sentinel-2 multispectral imaging products. The results show that the algorithm is comparably efficient for the processing of satellite image data from sources other than the sensor configurations it was originally designed for.

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“…Five different software packages were used: The processing system CATENA, developed by the DLR Remote Sensing Technology Institute, was deployed for various steps of pre-processing (Krauß et al, 2013). The GIS software ESRI ArcGIS 10 was used for all GIS related steps.…”

Section: Methodsmentioning

confidence: 99%

Creation of a High-Resolution Product Clc2006_backdating by a Backward Look From the Digital Land Cover Model DLM-De2009 to 2006 - A Contribution to the German Corine Land Cover 2012 Project Within a Bottom-Up Approach

Keil

Esch

Feigenspan

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:For the update 2012 of CORINE Land Cover, in Germany a new approach has been developed in order to profit from the higher accuracies of the national topographic database. In agreement between the Federal Environment Agency (UBA) and the Federal Agency for Cartography and Geodesy (BKG), CLC2012 has been derived from an updated digital landscape model DLM-DE, which is based on the Official Topographical Cartographic Information System ATKIS of the land survey authorities. The DLM-DE 2009 created by the BKG served as the base for the update 2012 in the national and EU context, both under the responsibility of the BKG.In addition to the updated CLC2012, a second product, the layer "CLC_Change" (2006)(2007)(2008)(2009)(2010)(2011)(2012)

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The Fully Automatic Optical Processing System Catena at DLR

Cited by 41 publications

References 2 publications

Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

Using RapidEye and MODIS Data Fusion to Monitor Vegetation Dynamics in Semi-Arid Rangelands in South Africa

An Enhanced Algorithm for Automatic Radiometric Harmonization of High-Resolution Optical Satellite Imagery Using Pseudoinvariant Features and Linear Regression

Creation of a High-Resolution Product Clc2006_backdating by a Backward Look From the Digital Land Cover Model DLM-De2009 to 2006 - A Contribution to the German Corine Land Cover 2012 Project Within a Bottom-Up Approach

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