SPLIT REMOTE SENSING SUMMER SCHOOL 2015
SPLIT REMOTE SENSING SUMMER SCHOOL 2015
Dr. Martin Isenburg: Hands-on Course to LiDAR processing with LAStools
Dr. Isenburg will start with short and lively introduction talk on LiDAR processing with examples of different projects such as the Canary Islands (Spain) where the vegetation-penetrating lasers uncovered elevation differences of up to 25 meters between the official government maps and reality, flood mapping in the Philippines, archaeological finds in Polish forests, and mapping biomass in Thailand, or other recent laser adventures.
This is followed by a hands-on workshop during which attendees will perform the core steps of a LiDAR processing workflow on their own Windows laptops using the software and data provided. This workshop will touch upon parts of (1) LiDAR quality checking, (2) LiDAR preparation (tiling, classifying, cleaning), (3) manual editing of LiDAR files, (4) LiDAR derivative creation (DTM/DSM/contour/slope maps/CHM/…), and – if time permits – (5) some full-waveform LiDAR exploration with PulseWaves.
Dr. Claudia Notarnicola: Retrieving biophysical parameters from remotely sensed imagery: methods and applications to environmental security issues
The retrieval of biophysical parameters (soil moisture, leaf area index, snow properties, etc…) from remotely sensed data represents a challenging and important research field within the remote sensing community. The information on spatial and temporal distribution of these parameters plays a central role in many applications as they represent the starting point to address key environmental issues such as water availability, sustainable agriculture and natural hazards from local to global scale.
Moreover, the availability of new satellite sensors (such as the Sentinel family) increases the necessity to develop even more accurate and robust estimation methods thus improving the monitoring of these variables.
The retrieval process of these parameters from satellite images (optical and radar) is typically a challenging task and it falls in the category of ill-posed problem. This means that beyond the non-linearity of the relationship between input features (sensor measurements) and the target variables (soil moisture, biomass, etc.), more than one combination of soil characteristics may lead to the same electromagnetic response at the sensor. Moreover, given a scene of interest, each system will provide information on a different aspect of the phenomena at the ground (e.g., the spatial patterns or the temporal dynamic) and could be also affected on different extents by different disturbing factors.
This suggests the importance of a synergic use of multiple available remote sensing systems (from satellite to drone based sensors) for a comprehensive, accurate and robust understanding and monitoring of the natural processes at the ground. On the other side the proper selection of the retrieval approach is a key issue.
In this context, the seminar will present currently available techniques for the retrieval of biophysical parameters from remotely sensed data addressing inversion of physical-based models, parametric and non-parametric approaches such as Bayesian procedure, Neural Networks, Support Vector Regression and Ensemble techniques.
Each approach will be presented in specific applications indicating advantages, disadvantages and perspectives for the upcoming missions such as Sentinel 1 and 2. In addition the synergic use of different sensors (optical and radar) will be specifically addressed in the context of the retrieval process.
A practical session will be dedicated to test the some retrieval techniques on existing data sets acquired from both satellite and drone based sensors. This session will deal with:
– Data collection and sensitivity analysis
– Feature selection
– Training& test of the different techniques
– Validation of the results.
GEOSENSE – Vassilis Polychronos: Drones used for surveying, GIS and remote sensing
The scope of this session is to present the use of UAS (Unmanned Aerial Systems) in modern field work. Using a drone can vastly reduce the time spent collecting accurate data like raster orthomosaics with resolution down to 2cm per pixel, 3D point clouds and reflectance maps.
We will demonstrate the total workflow of such a mission including:
1. Flight planning
2. Setting on-site GCP’s
3. Flight and Image capture
4. Import and image processing
5. Generation of othomosaics and 3D point clouds
Further discussion will follow upon the use of different camera payloads like NIR, RedEdge, Multispectral and Thermal and the use of each for certain purposes like soil property and moisture analysis, crop health analysis, erosion analysis plant physiology etc.
Dr.Selim Aksoy: Pattern Recognition Techniques for Remote Sensing
The constant increase in the amount of remotely sensed images as well as the urgent need for the extraction of useful information from such data sets have made the development of new pattern recognition techniques a popular research topic for several decades. The complexity of the image content with high spectral as well as high spatial resolution necessitates a good understanding of both the advantages and the limitations of the available methods. In this session, we will cover fundamental topics in statistical pattern recognition such as Bayesian decision theory, parametric and non-parametric density estimation, feature reduction and selection, non-Bayesian classification, and unsupervised learning and clustering. We will also discuss quantitative performance evaluation methods.
Dr. Olga Sykioti: HIS indicators and methods for the vegetation status assessment using ENVI software
Dr. Olga Sykioti will start with an introduction of principles of spectroscopy, with emphasis in reflectance imaging spectroscopy. Following, she will present basic notions in hyperspectral remote sensing and specific techniques and methods used in vegetation studies (i.e. absorption features, spectral indices, spectral unmixing). The above will be completed with a dedicated hands-on workshop during which attendees will perform the required image processing steps (including basic data manipulation) for the assessment of forest health status. An example of satellite Hyperion/EO-1 hyperspectral imagery will be used to identify areas of dying conifers resulting from insect damage. Attendees will learn how to process the imagery and how to create various different vegetation indices that exploit specific wavelength ranges to highlight areas of stressed vegetation.
Dr. Konstantinos Papatheodorou: Remote Sensing applications in geology and groundwater protection
Geology is one of the first scientific fields that have been supported by RS implementation and a lot of research and applied work has been conducted and reported. Certain applications regarding mapping geologic formations, mapping lineaments and fault identification, tracing groundwater flow paths through geologic formation using ancillary data are scheduled for the presentation. The presentation will include RS data processing techniques in conjunction with GIS modelling techniques in order to provide the total workflow in the field of ground water protection and management.
Dr. Kyriacos Themistocleous: In-situ measurements with a portable spectroradiometer and data analysis
The field collection of reflectance spectra of different materials is often referred to as ground truth data collection. The field collection using a portable spectroradiometer is important for interpreting unknown properties of different materials, as well as for validating sensor performance. A one-day field trip to the Taxiarchis forest (1 h 30 min driving from the University) will be organized to collect spectral signatures from the various natural materials. In the afternoon, during the in-class session, we will analyse the collected data and explore different applications of hyperspectral data.