cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.12760/02-2014-1-10
title: RGBI images with UAV and off-the-shelf compact cameras: an investigation of linear sensor characteristics

description: UAVs are able to close the gap between ground-based (total station, Global Navigation Satellite System - GNSS) and airborne data acquisition. Usually, cameras in the visible range of light are used for this purpose. Until now, only a few sensors have been commercially available for the capturing of non-visible wavelengths, e.g., of the near infrared for vegetation analysis. Almost all common camera sensors can be used and be modified through small interventions for the near infrared to make a RGBI (red, green, blue, near infrared) sensor head. Vegetation parameters like NDVI can be calculated from this data. 
At the Frankfurt University of Applied Sciences, a sensor head has been developed to collect RGBI data. The sensor head consists of two Sigma DP2 FOVEON-sensor cameras. One of them is modified for the near infrared. This sensor head is mounted to an octocopter UAV with a maximum take-off weight of 3.5 kg. The cameras are triggered simultaneously. In the post-processing, the image channels are registered to each other by a self-developed software script and a radiometric adjustment based on reference targets in the field is carried out. The resulting multispectral images are processed to multispectral orthophoto mosaics in standard photogrammetric software. A spectrometer and various test panels are available for the investigation of linear characteristics of the cameras. 
This paper briefly presents the construction of the sensor head. In particular, the radiometric characteristics of the sensor should be considered. The Sigma cameras have a poor colour separation due to the installed FOVEON sensors. This is balanced by the algorithms implemented in the raw data software Sigma PhotoPro, offered by the manufacturer. However, the linear sensor characteristic is destroyed by gamma correction and white balance. Freely available raw data converters can process the Sigma data without these photographic corrections and preserve the linear characteristic, but the image quality suffers from the poor spectral separation.
DOI: 10.12760/02-2014-1-09
title: Use of Unmanned Aircraft Systems (UAS) in a multi-scale vegetation index study of Arctic plant communities in Adventdalen on Svalbard

description: Use of Unmanned Aircraft Systems (UAS) gives the opportunity to carry out research with a reduced environmental footprint. Unmanned aircraft, including both fixed wing and multi rotor types (helicopters) allow us to collect very high resolution image data for vegetation mapping without the need for any personnel walking into the site and thereby potentially disturbing the sensitive Arctic ecosystems. The main aim of this project was to explore the feasibility of UAS-based vegetation mapping and extraction of vegetation indices (NDVI) for a range of different Arctic plant communities including dense marshes, moss tundra communities and different tundra heaths. The study area of Adventdalen valley on Svalbard, Arctic Norway, is located at 71.2 degree N 16 degree E and experiences a dry Arctic climate with a mean July temperature of about 6 degree C. The UAS was a fixed wing aircraft instrumented with a Red, Green, Blue (RGB) compact camera and a Normalized Difference Vegetation Index (NDVI) camera taking pictures from 100 metres altitude with highest ground resolution of 2.5 cm capable of mapping 2-3 square km per flight. The study area's two main plant communities; the Arctic bell heath and a graminoid rich Polar Willow heath were easily detected both in the NDVI and RGB images. In addition, wet moss tundra and mires were separated from the heath communities. In the NDVI image the moss-dominated mires were difficult to separate from the graminoid dominated mires in most cases, but they were well separable in RGB colour space. Also in situ NDVI measurements by a handheld passive proximal sensor were simultaneously done during the flight campaign. These measurements were analysed in order to correlate the species level NDVI and community level NDVI measurements with the NDVI images acquired at a variety of spatial resolutions by the UAS. The analysis shows that NDVIs of four main plant species at in situ leaf and community levels were significantly correlated. The correlation between the surface (in situ) NDVI community level and the UAS NDVI community level acquired from 100 metres above the surface of four main plant communities was higher, and these two scales are considered to be best for extraction of NDVI observations in Arctic areas like Svalbard.
DOI: 10.12760/02-2014-1-08
title: Applying spectral unmixing to determine surface water parameters in mining environment

description: Water has been traditionally monitored by in situ measurements taking point samples at regular intervals. From an optical perspective, in addition to pure water itself, the optical properties of surface waters are mainly influenced by three constituents: phytoplankton, suspended sediment, and coloured dissolved organic matter (CDOM). Although imaging spectroscopy can serve as a modern method to monitor polluted surface waters, only a limited number of studies have been published on this topic. In our study, we tested the feasibility of mapping the properties of surface waters affected by long-term mining activities using airborne multi-flight-line HyMap hyperspectral (HS) datasets. An approach using fundamental water image end-members to map relative abundances of selected parameters of surface waters (dissolved Fe, dissolved organic carbon DOC, non-dissolved particles) was tested and ground truth (eight monitored ponds) was then used to validate the results of spectral mapping. Although the detected end-members did not implicitly have to be absolutely pure, they represented the most extreme water types within the studied area. Correlations between the studied water parameters and three fractional images were detected (dissolved Fe: R2=0.74, undissolved particles: R2=0.57, DOC: R2=0.42); these images were further used to create semi-automatic maps.
DOI: 10.12760/02-2014-1-07
title: A tool for predicting diurnal soil albedo variation in Poland and Israel

description: Results of studies on the effects of soil surface roughness on the diurnal broadband blue-sky albedo variation of cultivated and uncultivated soils conducted so far in Poland and Israel indicated that the spectral reflectance behaviour of so genetically different soils such as those developed in these countries is similar enough to use the same procedure to predict the albedo variation for all the soils together. This paper discusses this variation using data generated by equations describing the overall albedo level of these soils taking into account only the organic carbon and carbonates content and the slope of their diurnal albedo increase in the function of the solar zenith angle, disregarding other properties of the soils.
DOI: 10.12760/02-2014-1-06
title: Wetland Leaf Area Index modelling with field and satellite hyperspectral data

description: Leaf Area Index (LAI) is an important variable in environmental processes modelling. Already several approaches were proposed to model wetlands LAI with remote sensing data. However, none of these methods was based on upscaling the field spectral reflectance measurements, which is a matter of this paper. In this study, we used combined measurements of spectral reflectance (350-2500 nm) and LAI to establish a regression model of LAI. The spectral reflectance was   resampled to the spectral resolution of a satellite hyperspectral sensor (CHRIS-PROBA) beforehand and then used to calculate NDVI-based spectral indices. From the set of spectral indices the one with the strongest correlation with LAI was chosen for the regression. Finally, the regression was applied to the CHRIS satellite images and the results were analysed within the scope of different wetland communities of the study area. The results show that the optimal regression model gives statistically different LAI values for the majority of different ground truth plant communities, rivers and urban areas.
DOI: 10.12760/01-2013-2-06
title: Spatio-temporal constraints for emissivity and surface temperature retrieval: Preliminary results and comparisons for SEVIRI and IASI observation

description: Infrared instrumentation on geostationary satellites is now rapidly approaching the spectral quality and accuracy of modern sensors flying on polar platforms. Currently, the core of EUMETSAT geostationary meteorological programme is the Meteosat Second Generation (MSG). However, EUMETSAT is preparing for the Meteosat Third Generation (MTG). The capability of geostationary satellites to resolve the diurnal cycle and hence to provide time-resolved sequences or times series of observations is a source of information which could suitably constrain the derivation of geophysical parameters.
Nowadays, also because of lack of time continuity, when dealing with observations from polar platforms, the problem of deriving geophysical parameters is normally solved by considering each single observation as independent of past and future events. For historical reason, the same approach is currently pursued with geostationary observations, which are still being dealt with as they were with polar observations.
In this study we show some preliminary results on emissivity and surface temperature retrieval for SEVIRI observations, using the Kalman filter methodology (KF) and compare the retrievals with those obtained using IASI observations co-localized with SEVIRI ones using the times accumulation approach (Optimal Estimation OE). The Sahara desert was chosen as target area, and both SEVIRI and IASI data (infrared radiances and cloud mask) were acquired. The time period considered is that of July 2010 (the whole month). ECMWF analyses for the same date and target area have also been acquired, which comprise Ts, T(p), O(p), Q(p) for the canonical hours 0:00, 6:00, 12:00 and 18:00. Moreover, for the purpose of developing a suitable background for emissivity, the Global Infrared Land Surface Emissivity database developed at CIMSS, University of Wisconsin, derived by MODIS observations was used and was available from the year 2003 till 2011.
Concerning the performance of the two methodologies, the retrieval of skin temperature is almost equivalent. The agreement between OE and KF is fairly good if compared with ECMWF analysis for sea surface, while for land surface, OE and KF agree fairly well with ECMWF during the night, but at midday ECMWF shows a cold bias of 10 K and more. For emissivity the comparison with the UW/BFEMIS database for the same date and location is fairly good for both methods.
DOI: 10.12760/02-2014-1-05
title: Use of a Lidar high resolution Digital Elevation Model for risk stability analysis

description: Remote sensing data offer an accurate source of information to the administration. Walloon administration develops its capacities in using Earth Observation data to respond to the EU request of characterizing the risks related to closed and/or abandoned mining sites. This paper compares two Digital Elevation Models (DEM) derived either from aerial photos or from a LiDAR (Light Detection And Ranging) scanner in their capabilities of characterizing unstable land cover and risks of landslides for Walloon coal waste heaps.
A first inventory of Walloon facilities at risk provided to EU authorities identified geotechnical failure as being one of the major risks linked to coal mine waste heaps. The risk of geotechnical failure was quantified using a geotechnical factor of safety computed on a pixel basis using the topography of the facility. The topography was extracted from a regional-scale DEM with a spatial resolution of 10 m (ERRUISSOL model, information on http://geoportail.wallonie.be). Since the first inventory, a new DEM dataset using LiDAR scanner has been acquired by the Walloon Region. This paper compares both datasets in their ability to quantify the risk of slope instability on five specific heaps. 
The DEM from LiDAR data offers a resolution of 1 m. It leads to significant differences in the spatial and statistical distributions of slopes, as compared to the regional 10 m-resolution DEM. To test this spatial effect, the resolution of the LiDAR DEM has been averaged by pixel aggregation to 2/4/8 and 10 m-resolution for direct comparison with the ERRUISSOL DEM. In all cases, the application of the geotechnical factor of safety criterion based on the high-resolution LiDAR DEM leads to larger portions of heap surfaces at risk of geotechnical failure. In the next months, this method will be proposed to the Walloon administration for application to all facilities considered at risk by the first inventory to improve the characterization of the risk of geotechnical failure, and confirm or not the risk.
DOI: 10.12760/02-2014-1-04
title: PROSAIL model for reflectance simulations of mountainous non-forest communities

description: Monitoring vegetation cover, especially in mountain and protected areas is an important issue. The analyses were conducted in Krkonose Mountains in the Krkonose National Park, Czech Republic. Heterogeneous non-forest mountain communities were analysed. The aim of the study was to check the possibility of using the Radiative Transfer Model to simulate the reflectance of very diverse mountain non-forest communities. In field measurements, biophysical parameters were collected and calculated to input parameters to the PROSAIL model. At the same time a reference spectrum was acquired. Then, the PROSAIL model was used to simulate the spectrum for each polygon. The accuracy was tested using Root Mean Square Error (RMSE) and normalised Root Mean Square Error (nRMSE) values for comparison with the reference spectrum. The average RMSE value for the whole analysed range was equal 0.129. The biggest errors were noticed in the near infrared (0.242) and the smallest in the 400-600 nm range (0.017). Generally, all noticed RMSE and nRMSE values are very diverse and quite big. The acquired results show that PROSAIL can be used to simulate the reflectance, but the model has to be adjusted, especially in the near infrared range.
DOI: 10.12760/02-2014-1-03
title: Data processing of Russian forest fire remote monitoring systems

description: Sustainable forestry and forest fire management are not possible in Russia without using remote monitoring data, because the territory under forest fire risk is huge. There are three main remote monitoring systems in Russia. The aim of the study is to consider data of two systems and to suggest some methods for comparison. Different SQL and geospatial queries were used for the systems to be compared. The results obtained demonstrate that there are some considerable contradictions between these systems. To overcome these problems advanced processing remote monitoring datasets were used and some kinds of advanced processing methods are suggested. A fuzzy logic was applied to match the fires reported by different systems. The fuzzy logic model is considered in detail in this paper. The result of this data processing can be the basis to develop future fire forecasting systems and decision support systems. The proposed methods of comparative analysis and additional processing of the data provided by the monitoring systems meant to improve input data quality in various modelling and forecasting applications.
DOI: 10.12760/02-2014-1-02
title: Quantitative modelling of urban changes using multi-temporal Digital Elevation Models

description: The construction of multi-temporal data sets for the modelling and documentation of urban environments has gained a large interest in the last few years. The growing availability of remote sensing data and sophisticated software tools has enabled the construction of Digital Elevation Models (DEMs) with various spatial and temporal resolutions. For this research, multiple scanned airborne images of the inner city of Ghent (Belgium) were processed for the calculation of DEMs using a conventional digital photogrammetric workflow. The aerial images were acquired during four campaigns: 1965, 1977, 1987 and 1990. All resulting image-based DEMs were compared with a DEM acquired with Airborne Laser Scanning (ALS) from 2009. This comparison allowed a model adjustment by minimizing the systematic shift between the data sets. In order to distinct built-up, destroyed or unchanged buildings over time, a threshold of 2.5 m was applied on the resulting vertically shifted points. Finally, a connected component analysis allowed the removal of outliers in the data. The resulting points were evaluated against a 2D digital cadastre map, which enabled a quantitative determination of difference in urban topography. The procedure to detect these changes, as well as the potentials and challenges of this technique, are discussed in this contribution.
DOI: 10.12760/01-2014-1-03
title: A review of INTA AHS PAF

description: The INTA AHS system has been operational since 2004, having performed over 60 flight campaigns throughout Europe up to the present time. The system is formed by an airborne scanner (AHS), a navigation system, calibration equipment, and a specific processing chain that have been implemented within the INTA airborne data Processing and Archiving Facility (PAF). In this chain, raw data (level 0 product) is transformed to at-sensor radiance (level 1b) and later to georeferenced at-sensor radiance (level 1c). Other processing levels, as atmospherically corrected reflectance, temperature or emissivity (L2b / L2c), can also be produced. The resulting image products are delivered together with radiometric statistics, metadata and quality descriptors according to EUFAR HyQuaPro recommendations. In this paper, details about this processing chain are given. The paper also describes the procedure for in-flight geometric calibration (internal orientation calibration and boresight estimation). Finally, an evaluation of the product accuracy (radiometric, spectral and geometric) is presented, using imagery from different AHS campaigns.
DOI: 10.15468/64hm7a
title: Review of the aberrant spider wasp genus Irenangelus Schulz (Pompilidae Ceropalinae) from the Indian subcontinent with the description of a new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Binoy, C., Wahis, Raymond, Kumar, P. Girish (2020): Review of the aberrant spider wasp genus Irenangelus Schulz (Pompilidae Ceropalinae) from the Indian subcontinent with the description of a new species. Zootaxa 4860 (2): 257-266, DOI: https://doi.org/10.11646/zootaxa.4860.2.7
DOI: 10.12760/02-2014-1-01
title: A new method for artefact-free estimation of surface slope from bathymetric Lidar data

description: When estimating the slope and aspect of a natural surface obtained by bathymetric Lidar scanning, discrepancies in the elevation data from neighbouring strips often cause artefacts. In this paper, a novel algorithm for slope estimation avoiding this kind of artefacts is presented. The algorithm is based on filtering the point data in the region of overlap using a set of scan angle based thresholds. Each threshold yields a data set with different selection of points from the neighbouring strips. Gradient estimates based on these data sets are then combined by either averaging or applying a trimmed mean type operation to obtain the artefact-free slope estimate. The algorithm is developed using bathymetric Lidar data and the obtained slope estimate of the seabed is used for the correction of the Lidar waveform data. The developed method is applicable in a wide range of situations where overlapping data from different sources need to be combined.
DOI: 10.6084/m9.figshare.13172246
title: 2020 01 03 VID00028 Analysis and Results

description: Typo on date has been corrected.<br>Slide presentation with frame-by-frame, context, and discussion with unambiguous detection and identification of at least two anomalous large non-human primates.<br>For transparency, includes the Java program used for custom frame-by-frame image stabilization, the anchor point data file, and a close up of the anchor point.<br><br>NOTE: The unrelated final GoPro segment from 3 January 2020 is also stored in this folder. See 2020 01 03 Field Notes for the first four segments. Then see 2020 01 09 Field Notes for GoPro video of the next hike starting from a location near to where this video drops off. The full set of GoPro videos provide a wide angle view of the areas surveyed along the primary route taken repeatedly in gathering data on the animals' behavioral patterns.
DOI: 10.6084/m9.figshare.13172246.v2
title: 2020 01 03 VID00028 Analysis and Results

description: Slide presentation with frame-by-frame, context, and discussion with unambiguous detection and identification of at least two anomalous large non-human primates.<br>For transparency, includes the Java program used for custom frame-by-frame image stabilization, the anchor point data file, and a close up of the anchor point.<br><br>NOTE: The unrelated final GoPro segment from 3 January 2020 is also stored in this folder. See 2020 01 03 Field Notes for the first four segments. Then see 2020 01 09 Field Notes for GoPro video of the next hike starting from a location near to where this video drops off. The full set of GoPro videos provide a wide angle view of the areas surveyed along the primary route taken repeatedly in gathering data on the animals' behavioral patterns.
DOI: 10.12760/01-2014-1-02
title: An application of the Perpendicular Moisture Index for the prediction of fire hazard

description: Various factors contribute to forest fire hazard, and among them vegetation moisture is the one that dictates susceptibility to fire ignition and propagation. The scientific community has developed a number of spectral indices based on remote sensing measurements in the optical domain for the assessment of vegetation equivalent water thickness (EWT), which is defined as the mass of liquid water per unit of leaf surface. However, fire models rely on the live fuel moisture content (LFMC) as a measure of vegetation moisture. LFMC is defined as the ratio of the mass of the liquid water in a fresh leaf over the mass of oven dry leaf, and spectral indices proposed so far fail in capturing LFMC variability. Recently, the perpendicular moisture index (PMI), based on MODIS, was pro-posed to overcome this limitation and provide a direct measure of LFMC. The aim of this research was to understand the potential and limitations of the PMI in predicting fire hazard, towards its ap-plication in a practical context. To this purpose, a data set of more than 7,700 fires recorded in Campania (13,595 km2), Italy, between 2000 and 2008 was compared with PMI derived from MODIS images. Results show that there is no relationship between PMI and fire size, whereas a linear correlation was found between the spectral index and fire rate of spread.
DOI: 10.12760/01-2013-2-09
title: Method for calibrating the image from a mixel camera based solely on the acquired hyperspectral data

description: The mixel camera combines a new type of hardware component - an array of light mixing chambers - with a mathematical method that restores captured hyperspectral data with large keystone to its keystone-free form. When it is no longer necessary to correct keystone in hardware, the requirements to the optical design become much less stringent, and the mixel camera can therefore collect about four times more light than most traditional high-resolution cameras. However, for the mathematical data restoring method to function correctly, the geometry of the camera - such as the relative position of the image sensor and the slit - should be known with a small fraction of a pixel precision. Due to quite small sensor pixel size, it may be very challenging to make the camera so rigid mechanically that previously obtained calibration data remain valid for a long enough period. We will in this paper show how the captured hyperspectral data from the scene of interest, i.e., an unknown natural scene, can be used to give sufficiently precise calibration.