This study presents a computer vision application of the structure from motion (SfM) technique in three dimensional high resolution gully monitoring in southern Morocco. Due to impractical use of terrestrial Light Detection and Ranging (LiDAR) in difficult to access gully systems, the inexpensive SfM is a promising tool for analyzing and monitoring soil loss, gully head retreat and plunge pool development following heavy rain events. Objects with known dimensions were placed around the gully scenes for scaling purposes as a workaround for ground control point (GCP) placement. Additionally, the free scaling with objects was compared to terrestrial laser scanner (TLS) data in a field laboratory in Germany. Results of the latter showed discrepancies of 5.6% in volume difference for erosion and 1.7% for accumulation between SfM and TLS. In the Moroccan research area soil loss varied between 0.58 t in an 18.65 m² narrowly stretched gully incision and 5.25 t for 17.45 m² in a widely expanded headcut area following two heavy rain events. Different techniques of data preparation were applied and the advantages of SfM for soil erosion monitoring under complex surface conditions were demonstrated.

A new instrument has been setup at the Centre de Recherche Public-Gabriel Lippmann to measure spectral emissivity values of typical earth surface samples in the 8 to 12 μm range at a spectral resolution of up to 0.25 cm⁻¹. The instrument is based on a Hyper-Cam-LW built by Telops with a modified fore-optic for vertical measurements at ground level and a platform for airborne acquisitions. A processing chain has been developed to convert calibrated radiances into emissivity spectra. Repeat measurements taken on samples of sandstone show a high repeatability of the system with a wavelength dependent standard deviation of less than 0.01 (1.25% of the mean emissivity). Evaluation of retrieved emissivity spectra indicates good agreement with reference measurements. The new instrument facilitates the assessment of the spatial variability of emissivity spectra of material surfaces—at present still largely unknown—at various scales from ground and airborne platforms and thus will provide new opportunities in environmental remote sensing.

This study evaluates the potential that lies in the photogrammetric processing of aerial images captured by unmanned aerial vehicles. UAV-Systems have gained increasing attraction during the last years. Miniaturization of electronic components often results in a reduction of quality. Especially the accuracy of the GPS/IMU navigation unit and the camera are of the utmost importance for photogrammetric evaluation of aerial images. To determine the accuracy of digital elevation models (DEMs), an experimental setup was chosen similar to the situation of data acquisition during a field campaign. A quarry was chosen to perform the experiment, because of the presence of different geomorphologic units, such as vertical walls, piles of debris, vegetation and even areas. In the experimental test field, 1042 ground control points (GCPs) were placed, used as input data for the photogrammetric processing and as high accuracy reference data for evaluating the DEMs. Further, an airborne LiDAR dataset covering the whole quarry and additional 2000 reference points, measured by total station, were used as ground truth data. The aerial images were taken using a MAVinci Sirius I – UAV equipped with a Canon 300D as imaging system. The influence of the number of GCPs on the accuracy of the indirect sensor orientation and the absolute deviation’s dependency on different parameters of the modelled DEMs was subject of the investigation. Nevertheless, the only significant factor concerning the DEMs accuracy that could be isolated was the flying height of the UAV.

This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.