Urban vegetation extraction from VHR (tri-)stereo imagery : a comparative study in two central European cities

The present study proposes a workflow to extract vegetation height for urban areas from Pléiades stereo and tri-stereo satellite imagery. The workflow was applied on a stereo image pair for Szeged, Hungary and on tri-stereo imagery for Salzburg, Austria. Digital surface models (DSMs) of the study areas were computed using the semi-global matching algorithm. Normalised digital surface models (nDSMs) were then generated. Objects of vegetation and non-vegetation were delineated based on the spectral information of the multispectral images by applying multi-resolution segmentation and support vector machine classifier. Mean object height values were then computed from the overlaid pixels of the nDSMs and assigned to the objects. Finally, the delineated vegetation was classified into six vegetation height classes based on their assigned height values by using hierarchical classification. The vegetation discrimination resulted in very high accuracy, while the vegetation height extraction was moderately accurate. The results of the vegetation height extraction provided a vertical stratification of the vegetation in the two study areas which is readily applicable for decision support purposes. The elaborated workflow will contribute to a green monitoring and valuation strategy and provide input data for an urban green accessibility study.DK W 1237N23(VLID)251709

Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data

NEMO-HD: High-Resolution Microsatellite for Earth Monitoring and Observation

The Space Flight Laboratory (SFL) at the University of Toronto Institute for Aerospace Studies, in collaboration with the Slovenian Centre of Excellence for Space Sciences and Technologies (SPACE-SI), is developing a 40 kg microsatellite for earth monitoring and observation that is capable of resolving a Ground Sampling Distance (GSD) of 2.8 m from a design altitude of 600 km. NEMO-HD (Nanosatellite for Earth Monitoring and Observation - High Definition) is the second spacecraft that is based on SFL\u27s high-performance NEMO bus and builds upon the heritage of SFL\u27s flight-proven Generic Nanosatellite Bus (GNB). NEMO-HD will carry two optical instruments: a narrow-field instrument as well as a wide-field instrument. The narrow-field instrument will be capable of resolving 2.8 m GSD in four channels corresponding to Landsat-1, 2, 3, and 4 spectral channels (450-520 nm, 520-600 nm, 630-690 nm, and 760-900 nm). The wide-field instrument will be capable of resolving 75 m GSD or better. Both instruments are capable of recording High-Definition video at 1920 by 1080 pixels. The spacecraft will be capable of performing global imaging and real-time video streaming over Slovenia and other regions where it will be in view of the ground station. In addition, the spacecraft will also be capable of performing remote observations. NEMOHD will include the standard complement of subsystems, sensors and actuators that make up a three-axis stabilized NEMO bus. NEMO-HD will be enhanced to include a 50 Mbps X-band downlink, 128 GB of on-board storage, a high-performance instrument computer, and a power system generating 31 W at end-of-life with a 130 W-h Li-ion battery. The paper provides an overview of the NEMO-HD system design