Holger Daedelow

Automated Generation of Value-Added Products for the Validation of Remote Sensing Information Based on In-Situ Data

Available in-situ (IS) data are an essential prerequisite for the validation of remote sensing (RS) data and information products. Due to the fact that IS data supply is very labour- and cost-intensive, ground-truth data acquisition needs to be operational and automated. Moreover, measurements should be taken simultaneously to data acquisition by operational RS systems. To be able to deliver representative and validated IS data applied to the validation of complimentary operational RS data, locations of measurement stations will have to be optimised to be representative for a particular geographical space. This paper presents a novel approach to provide complementary IS data simultaneously to RS data acquisition. It outlines the installation and operation of an automated IS measurement network for environmental parameters in the DEMMIN (Durable Environmental Multidisciplinary Monitoring Information Network) test site. To process the data, an operational processing chain has been implemented and used for IS data volumes. IS data measurements are evaluated to establish a basis for generating and validating value-added RS products.

High Temperature Fire Experiment for TET-1 and Landsat 8 in Test Site DEMMIN (Germany)

In 2012, the German Aerospace Center (DLR) launched the small satellite TET-1 (Experimental Technology Carrier) as a test platform for new satellite technologies and as a carrier for the Multi-Spectral Camera System (MSC) with five spectral bands (Green, Red, Near Infrared, Middle Infrared, and Thermal Infrared). The MSC has been designed to provide quantitative parameters (e.g. fire radiative power, burned area) observing high-temperature events. The detection of such events provides information for operational support to fire brigades, to change detection of hotspots, to assess CO2 emissions of burning vegetation, and, finally, contributes to the monitoring programs that support climate models. In order to investigate the sensitivity and accuracy of the MSC system, a calibration and validation fire campaign was developed and executed, to derive characteristic signal changes of corresponding pixels in the MWIR and LWIR bands. The planning and execution of the validation campaign and the results are presented.