Interpretation of Remote Sensing Imagery

The process of interpretation and analysis of remote sensing data is based on extracting meaningful information from satellite imagery. The quality of visual interpretation depends on the resolvability and recognisability of the main visual characteristics of each photo or images. The current process of image analysis is based on digital processing limited by used satellite or airborne sensors.

MULTISPECTRAL AND MOBILE MAPPING ISPRS WG III/5 DATA SET: FIRST ANALYSIS OF THE DATASET IMPACT

Light Detection and Ranging (LiDAR) technology is playing a major role in different applications. Indeed, the possibility of exploiting either 3D geometric features and radiometric information makes LiDAR suitable for a wide range of practical domains. LiDAR proved also being quite flexible in terms of platforms where it can be implemented for the acquisition, spanning from airborne sensors up to car-based and hand-held instruments. Due to the rapid expansion of research concerning LiDAR intensity, the ISPRS WG III/5 launched in 2017 an initiative aimed at providing free access to LiDAR data acquired by modern multispectral ALS sensors as well as MLS data. The two datasets, MLS Data Set 1 – (“Sun Prairie”), and Multispectral LiDAR Data Set 2 – (“Tobermory”), were provided by Teledyne Optech Company (Canada) and were made freely available to researchers upon request. This paper is presenting the first results of this initiative in terms of applications, application domains and topics tackled by applicants. The relevance of this data set is also evaluated through a bibliometric analysis considering both Scopus and Web of Science indexed databases to analyse the main directions where the scientific research, the technical development and the application interest is moving to.

RGB Spectral Indices for the Analysis of Soil Protection by Vegetation Cover against Erosive Processes

The vegetation cover plays a fundamental role in protecting the soil from erosive processes. Many researchers have developed investigations for the calculation of the RUSLE C Factor, with the use of operating bands in the near infrared. With the current advances in Geospatial Technologies, there are a good number of RGB airborne sensors in Unmanned Aerial Vehicles (UVA). The objective of this chapter is to evaluate some RGB indexes, proposed in the literature, for the protection of the soil from erosive processes by vegetation cover, in a region with a high agricultural vocation. The methodology consisted of capturing RGB images in an area of the Ecuadorian coastal region and calculating in thematic indices, within the visible one, which offer the possibility of quickly differentiating vegetation from other types of coverage on the ground. The evaluation allowed to define which indexes present the best results and adaptation to the type of crop or plant mass mapped, and to propose their use for zoning of risk of erosion under the agro-ecological conditions of the study area.

Minimum Redundancy Array—A Baseline Optimization Strategy for Urban SAR Tomography

Synthetic aperture radar (SAR) tomography (TomoSAR) is able to separate multiple scatterers layovered inside the same resolution cell in high-resolution SAR images of urban scenarios, usually with a large number of orbits, making it an expensive and unfeasible task for many practical applications. Targeting at finding out the minimum number of images necessary for tomographic reconstruction, this paper innovatively applies minimum redundancy array (MRA) for tomographic baseline array optimization. Monte Carlo simulations are conducted by means of Two-step Iterative Shrinkage/Thresholding (TWIST) and Truncated Singular Value Decomposition (TSVD) to fully evaluate the tomographic performance of MRA orbits in terms of detection rates, Cramer Rao Lower Bounds, as well as resistance against sidelobes. Experiments on COSMO-SkyMed and TerraSAR-X/TanDEM-X data are also conducted in this paper. The results from simulations and experiments on real data have both demonstrated that introducing MRA for baseline optimization in SAR tomography can benefit from the dramatic reduction of necessary orbit numbers, if the recently proposed TWIST method is used for tomographic reconstruction. Although the simulation and experiments in this manuscript are carried out using spaceborne data, the outcome of this paper can also give examples for airborne TomoSAR when designing flight orbits using airborne sensors.

A Hyperspectral Bidirectional Reflectance Model for Land Surface

A hyperspectral bidirectional reflectance (HSBR) model for land surface has been developed in this work. The HSBR model includes a very diverse land surface bidirectional reflectance distribution function (BRDF) database with ~40,000 spectra. The BRDF database is saved as Ross-Li parameters, which can generate hyperspectral reflectance spectra at different sensor and solar observation geometries. The HSBR model also provides an improved method for generating hyperspectral surface reflectance using multiband satellite measurements. It is shown that the land surface reflective spectrum can be easily simulated using BRDF parameters or reflectance at few preselected wavelengths. The HSBR model is validated using the U.S. Geological Survey (USGS) vegetation database and the AVIRIS reflectance product. The simulated reflective spectra fit the measurements very well with standard deviations normally smaller than 0.01 in the unit of reflectivity. The HSBR model could be used to significantly improve the quality of the reflectance products of satellite and airborne sensors. It also plays important role for intercalibration among space-based instruments and other land surface related applications.

Automation for Safety and Precision in Flight Testing

The first flight of any new aircraft remains a potentially dangerous event. Test pilots face many unknowns when a prototype leaves the ground for the first time. In a time when remotely piloted and autonomous aircraft fly every day, the question about using their technologies to avoid losing a test pilot arises. This study investigates the advantages of using a machine to test another machine. It also discusses the disadvantages of relying on airborne sensors instead of using the test pilot’s cognitive capabilities and judgment. The analysis of collected flight testing data suggests that aircraft handling qualities may be more precisely tested adding specific automation. However, remote control and autonomous flight testing bring new safety constraints that cannot be ignored.