cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/hh8fc4
title: Three new species of free-living marine nematodes (Nematoda: Enoplida) from the Clarion-Clipperton Fracture Zone (CCFZ), North Pacific

description: This dataset contains the digitized treatments in Plazi based on the original journal article Shimada, Daisuke, Takeda, Naoya, Tsune, Akira, Murakami, Chisato (2020): Three new species of free-living marine nematodes (Nematoda: Enoplida) from the Clarion-Clipperton Fracture Zone (CCFZ), North Pacific. Zootaxa 4859 (4): 507-526, DOI: https://doi.org/10.11646/zootaxa.4859.4.3
DOI: 10.6084/m9.figshare.13515194
title: Mitochondrial genome of a giant water bug Lethocerus deyrollei (Hemiptera: Belostomatidae) from South Korea

description: Four PCR primer sets designed for <i>Lethocerus deyrolli</i> in this study: one universial (<i>COX1</i> gene) and three species-specific (<i>COX1</i>, <i>COX1</i>-<i>CytB</i>, and <i>CytB</i>-<i>COX1</i>)
DOI: 10.6084/m9.figshare.13515194.v1
title: Mitochondrial genome of a giant water bug Lethocerus deyrollei (Hemiptera: Belostomatidae) from South Korea

description: Four PCR primer sets designed for <i>Lethocerus deyrolli</i> in this study: one universial (<i>COX1</i> gene) and three species-specific (<i>COX1</i>, <i>COX1</i>-<i>CytB</i>, and <i>CytB</i>-<i>COX1</i>)
DOI: 10.12760/01-2014-2-05
title: Building detection with multi-view colour infrared imagery.

description: This paper presents an automatic building detection approach exploiting colour infrared (CIR) imagery. A Digital Surface Model (DSM) is first extracted by photogrammetry with a proprietary development including multiple views. Then a Digital Terrain Model (DTM) is derived from the DSM by selecting the lowest regions with slowly varying elevation. A normalised DSM, difference of the DSM and derived DTM highlights building candidates thanks to a simple threshold. In order to reduce false positives due to trees, a vegetation mask is obtained from the NDVI of the ortho-rectified CIR image. A specific procedure was designed to handle the problematic shadow areas where the NDVI criterion often misses vegetation. The proposed building detection approach has been applied to the Vaihingen data set of the ISPRS benchmark and validated by the results of its evaluation procedure. We plan to integrate the new DTM extraction and shadow adapted vegetation mask, main contributions of this paper, to our project about change detection for database revision for the Belgian National Geographic Institute.
DOI: 10.12760/02-2014-1-17
title: Mineral mapping based on automatic detection of multiple absorption features

description: In comparison with multispectral image data, hyperspectral (HS) imagery with higher spectral resolution provides sufficient spectral resolution to describe diagnostic absorption signatures. Specific chemical bonds in materials, whether solid, liquid or gas, determine the surface reflectance and emittance, as variations in material composition often cause shifts in the position and shape of absorption bands in the spectrum. In addition, detecting the exact absorption wavelength position is a key factor not only for mineral identification but also for tracking diverse environmental processes and pathways. A couple of techniques to identify absorption parameters have been suggested, however, they are capable of a quantitative characterization of just one major absorption feature and, due to the techniques they use, limited to the SWIR region. 
In this paper, new tools are presented allowing automatic detection of multiple absorption feature parameters (absorption maximum wavelengths and depths). The tools employ methods based on a trend analysis of the spectra, while bad bands (e. g., noise, error bands) are detected at first and excluded from further analysis. The tools - e.g. called QUANTools - have been created using IDL programming language and can be used under ENVI/IDL (version 5.0 and higher). As multiple absorption features are detected within the VNIR/SWIR/TIR regions and their wavelength positions, respectively, the newly suggested method has a potential to become a new mapping technique suitable for environments with high heterogeneity and dynamics.
DOI: 10.12760/02-2014-1-16
title: Semi-automatic open source geoprocessing for change-detection in federal geodata

description: This project addresses the vast complexity of keeping federal geodata up to date according to the official regulations. Cooperating with the Hessian state agency for land management and geoinformation (Hessisches Landesamt fÜr Bodenmanagement und Geoinformation - HLBG) concepts and solutions have been developed in a two-year project. It is supposed to enhance the efficiency of the geodata update processes within state agencies. 
With the help of the concept of change detection datasets are supposed to be updated. The aim of the project is to provide a thematic layer of change indicators for the staff dealing with updating datasets. To assess the feasibility of this approach in a federal agency surrounding two exemplary datasets were defined. The long-term goal is to use semi-automatic change detection processes for increasing numbers of datasets within the agency. 
Lake boundaries as well as relevant (meaning: above a Delta z-threshold defined by the agency) elevation changes were processed. Light detection and ranging DEM (Lidar) is supposed to be kept up to date without subsequent flights. This paper describes the process of updating the lake boundaries. 
According to the needs of the state agency processing rule sets (e.g. accuracy tolerances or minimum area size) were developed. The rule sets were then implemented using the Python programming language to create geoprocessing scripts as post-processing algorithms for raster database queries, which can tackle the data amount for Hesse with its 21,000 km².
This paper presents the methods which are being used to detect objects and derive features to be used in the process of change detection. Due to the high topicality of the oriented aerial images their derivatives (photogrammetric point clouds, orthophotos) serve as the core element for the detection of change features in the more recent epoch
DOI: 10.12760/01-2014-2-04
title: Shape-texture features for the VHSR satellite images classification using the MLP neural net.

description: With the emergence of commercial satellites with on-board sensors characterized by Very High Spatial Resolution (VHSR), identification and localization of topographic features are becoming conceivable. The VHSR sensors provide images with significant amount of geometrical details that yield new kinds of information, such as shape information. On the other hand, the classification of this heterogeneous information set requires also the establishment of new techniques different from those used for low and medium spatial resolution data classification. To this end, the Multilayer Perceptron (MLP) neural network has been investigated to classify this heterogeneous set of information using a combination of different features extracted from objects, namely Quaternion Zernike moments as shape descriptor and Haralick's features as textural descriptor. The proposed approach was tested using a sub-scene of Quickbird image datasets of Algiers (northern Algeria). The results indicate a mean accuracy value of 79.99 percent using only the shape feature information, 74.89 percent by applying the textural features information and 86.23 percent by combination of shape descriptor and texture descriptor. The results of the proposed method with MLP classifier are also compared with those results obtained by k-NN and SVM classifiers, a fact which confirms the effectiveness of the suggested approach.
DOI: 10.15468/sf3rys
title: Discovery of the genus Dioedus LeConte, 1862 from China, with description of a new species (Coleoptera: Tenebrionidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Jiang, Ri-Xin, Wang, Ji-Shen, Wang, Shuo (2020): Discovery of the genus Dioedus LeConte, 1862 from China, with description of a new species (Coleoptera: Tenebrionidae). Zootaxa 4860 (1): 129-134, DOI: https://doi.org/10.11646/zootaxa.4860.1.7
DOI: 10.12760/02-2014-1-15
title: Monitoring forest cover change in boreal forests: A methodological approach

description: The purpose of this study is to develop a monitoring tool for boreal forest cover change on continental level at high resolution. The system is based on Landsat satellite imagery and has been implemented for the period 1990-2000-2010. For the identification and classification of the forest cover within a large amount of satellite imagery, a robust methodological approach combining multi-date image segmentation and cluster based supervised automated classification was chosen. Thus, an object based, automatic classification method with a regional expert validation are combined to produce regional scale land cover statistics over Russia and Mongolia. High resolution satellite imagery is used to accurately estimate land cover and land cover change for the epochs 1990-2000-2010. The overall method consists of four distinct steps: (i) automatic image preprocessing and pre-interpretation, (ii) validation by regional expert, (iii) statistic computation and (iv) accuracy assessment. The automated procedures have as main objective to unequivocally identify the objects so as to maximally reduce the post-classification interventions of manual procedures and of visual interpretation. A total of 14 different land cover classes are defined in the legend. Given the focus on forests, special attention was devoted to the differentiation of eight different forest cover types, going up to species level.
DOI: 10.12760/03-2014-07
title: HYPERSPECTRAL DIGITAL IMAGE ANALYSIS AND GEOCHEMICAL ANALYSIS OF A RARE EARTH ELEMENTS MINERALIZED INTRUSIVE COMPLEX (FEN CARBONATITE COMPLEX IN TELEMARK REGION, NORWAY)

description: Today rare earth elements are of great interest for the global economy. They are of particular importance in modern technology, such as batteries, LCD displays and catalytic converters. Hyperspectral imagers, like the Earth Observing-1 Hyperion and the future environmental mapping and analysis program (EnMAP) bear a potential to identify rare earth element enriched zones in hardly accessible terrains on Earth. Moreover, it is a brilliant technology for monitoring exploration with regard to environmental pollution and protection of local communities. Hence, a fast and accurate geological prospection algorithm using highly spectrally resolved satellite and airborne images is necessary. Since a lot of competing absorptions (e.g. vegetation, iron oxides and atmospheric water) take place in the VNIR spectral range and the shape of rare earth element absorption bands are usually similar to the shape of noise, a detection of Rare Earth Elements is hampered.
DOI: 10.12760/03-2014-06
title: AN AUTOMATED PROCESSING CHAIN FOR THE RETRIEVAL OF GEOREFERENCED REFLECTANCE DATA FROM HYPERSPECTRAL EO-1 HYPERION ACQUISITIONS

description: Spaceborne hyperspectral imaging becomes more and more important for remote sensing applications. Data acquisitions from current sensors having VNIR and SWIR detectors, like Hyperion on the EO-1 platform, and future sensors, such as EnMAP, MSMI, HISUI, Prisma or HyspIRI, require precise data preprocessing to enable the variety of applications they are designed for. Most applications require continuous spectra over the VNIR and SWIR wavelength range (e.g. geological applications) and georeferenced reflectance as data process level to be independent of illumination and sensor geometry, to reduce the influence of the atmosphere during the acquisition and to enable the integration of application related outputs information into spatially larger georeferenced information systems.
DOI: 10.12760/03-2014-05
title: Global DEMs’ accuracy improvement with respect to local DEM data

description: Today there is a great variety of DEMs: global and local. In contrast to local DEMs, the global DEMs offer extensive coverage but they are less accurate. This paper proposes the improvement of the accuracy of global DEMs locally by fitting them to more accurate local DEMs. A combination of the exhaustive search and divide-and-conquer algorithms is used to compute the planar displacement of the global DEMs which minimizes the RMSE of the elevations. The method is applied to 3 test sites all over Greece using the SRTM and the ASTER global DEMs and more accurate local DEMs, with encouraging results.
DOI: 10.12760/03-2014-04
title: Evaluating ASTER GDEM accuracy for two areas in Western Peloponnese, Greece

description: In this study the accuracy of ASTER GDEM was examined. For two areas with different geomorphologic characteristics DSM from ASTER stereo pairs were created with classical photogrammetric techniques. Those DSMs were compared with the ASTER GDEM. Points of certified elevation collected with DGPS have been used to estimate the accuracy of the DSM. The elevation difference between the two DSMs was calculated. 2D RMSE, correlation and the percentile value were also computed and the results are presented.
DOI: 10.12760/03-2014-03
title: Relief evolution monitoring using airphotos time series and GIS. A case study from Western Greece

description: Western Greece is suffering by landslides. The term landslide includes a wide range of ground movement, such as slides, falls, flows etc. mainly based on gravity with the aid of many conditioning and triggering factors. Landslides provoke enormous changes to the natural and artificial relief. The annual cost of repairing the damage amounts to millions of euros. In this paper a combined use of airphotos time series, high resolution remote sensing data and GIS for the relief evolution monitoring is presented. Analog and digital air-photos used covered a period of almost 70 years from 1945 until 2012. Classical analog airphotos covered the period from 1945 to 2000, while digital airphotos and satellite images covered the 2008-2012 period. The air photos have been orthorectified using the Leica Photogrammetry Suite. Ground control points and a high accuracy DSM were used for the orthorectification of the air photos. The 2008 digital air photo mosaic from the Greek Cadastral with a spatial resolution of 25 cm and the respective DSM was used as the base map for all the others data sets. The rms error was less than 0.5 pixel. Changes to the relief and to the artificial constructions were digitized and then implemented in an ARCGIS database. The results are presented in this paper.
DOI: 10.12760/03-2014-02
title: Spatial consequences of adopting selected criteria for wind farm siting

description: Lack of definition of spatial capacity for wind farm development in Poland and associated lack of clearly defined wind farm siting criteria resulted in the impairment of spatial order at the country scale and contributed to numerous social conflicts. In the study an attempt was made to assess the potential for wind energy development in Poland against the background of regional differences in land availability for wind farm siting. The assessment was made using selected criteria derived from analyses of environmental receptors sensitive to wind turbine impacts. The key criteria included environmental considerations such as: municipal areas, countryside settlement pattern, areas of protected nature and ecological corridors, woodlands and areas of highest landscape values. Analyses were made with the use of GIS tools to delimitate areas which should be excluded from wind farm development. Two minimal distances from the settled (build up) area were adopted as safe for siting a power generating facility, i.e. one and two km. The value of index showing the proportion of land available for wind energy development versus total country area is low and attains 2.63% when one-kilometer wide buffer zone is kept between the farm and the settled area. Whereas for a two-kilometer wide buffer zone, the above value decreases to merely 0.1%, assuming that the remaining criteria for wind farm siting, such as those concerning nature and landscape, remain the same. The country’s space availability for wind farm development will be substantially limited if precise environmental criteria for wind farm siting, based on the evaluation of settlement patterns, location of natural resources and landscape values, are introduced into the spatial planning policy in Poland. While at the same time, this would help to secure appropriate quality of human life, human health as well as the highest natural and landscape values of the country.
DOI: 10.12760/03-2014-01
title: The satellite-based products for supporting prevention and recovery of forest fires in PREFER

description: The PREFER FP7 project aims at responding to major fire prevention needs in Southern Europe. The Mediterranean area is systematically affected by uncontrolled forest fires with large impact on ecosystems, soil erosion, slope instability, desertification trends, and local economies as a whole, with a negative mid-to-long term prospect because of expected climate change. In this scenario, the need to improve the information and the intelligence support to forest fire prevention is widely recognized to be relevant. Fire prevention is still the most cost-effective strategy when compared to fire-fighting and extinguishing that are costly, local, and triggered only in response to already ongoing crises. The PREFER project intends to contribute to responding to such a pragmatic need of Southern Europe’s forests by: 1) providing timely multi-scale and multi-payload information products based on exploitation of all available spaceborne sensors; 2) offering a portfolio of EO products focused both on Pre-crisis and Post-crisis forest fire emergency cycle in the EU Mediterranean area; 3) preparing the exploitation of new spaceborne sensors available by 2020 (e.g.: Sentinels) and 4) contributing to the definition of user requirements for the new EO missions.
The paper is devoted to illustrate some of the more significant and innovative products developed by the project.
DOI: 10.12760/02-2014-1-13
title: Temporal changes in Norway spruce physiological status using hyperspectral data: A case study of mountainous forests affected by long-term acidic depositions

description: A decline in the Norway spruce forests of the Krusne Hory Mts., Czech Republic, has been reported since the early 1950's. It was attributed to the combination of severe atmospheric pollution and climatic conditions. The physiological status of the Norway spruce forests has been assessed using ground-truth data (biochemical and spectroscopic data) as well as two hyperspectral data sets acquired in 1998 (ASAS sensor, NASA Goddard Space Flight Center) and in 2013 (APEX sensor, developed by a Swiss-Belgian consortium on behalf of ESA, currently operated by VITO). The very first results coming from the analysis of the foliar chemistry indicate that the stands exhibit different physiological statuses corresponding to the pollution gradients in 1998 and 2013. Slight improvement of the Norway spruce physiological status was recorded in the eastern part of the mountains (e.g., total carotenoids to chlorophyll ratio), while the status of the western-located stands slightly worsened. These findings may correspond to a tremendous decrease in the atmospheric pollution which was most severe in the east. However, remains of the pollution can be still seen in the adverse soils conditions. Further linkages among foliar chemistry and reflectance and soil chemistry are currently under investigation.
DOI: 10.12760/01-2014-2-02
title: Extreme Learning Machine for classification of high resolution remote sensing images and its comparison with traditional Artificial Neural Networks (ANN)

description: Artificial Neural Networks (ANN) is an important technique for land cover classification of high resolution images. However, there are many inherent limitations of ANN based on Multi-Layer Perception (MLP) with back propagation such as the necessity of fine-tuning the number of input parameters and slow convergence time. Therefore, an attempt has been made to introduce and explore the potential of an Extreme Learning Machine (ELM) which deviates from iterative weight adjustment of neurons during the learning process and is extremely fast at classifying high resolution images. A detailed comparison of the ELM is made with back propagation ANN with better learning algorithms (Scaled Conjugate Gradient (SCG) and Levenberg-Marquardt (LM)) in terms of accuracy, the time required for fine tuning different parameters, and generalisation capability. A high resolution QuickBird satellite image collected over an area of Warsaw, Poland was used for the analysis. Experimental results showed that the ELM produced classification accuracy comparable to that achieved with newer state-of-the-art ANN. The benefits of employing the ELM over conventional ANN are the need of determining only one user parameter, namely the number of neurons in the network, and the significantly lower computational costs. The simplicity of needing to determine only one parameter and the extremely high speed of the ELM could be extremely helpful for different applications when fast but accurate classification is desired.
DOI: 10.12760/02-2014-1-12
title: Urban growth patterns for Bucharest, Romania: Analysis of Landsat imagery

description: Is there any spatial pattern for Bucharest urban growth that occurred during the last 25 years, after the end of Cold War? This question is answered by the results obtained through the Landsat data analysis performed in order to detect the changes produced in land use in the last 25 years for the city of Bucharest and its surroundings. The analysis is based on the four major land use classes that are generated by means of a processing methodology proposed in this paper.
DOI: 10.12760/01-2014-2-01
title: Practical example of the Supervised Vicarious Calibration (SVC) method - ValCalHyp Airborne Hyperspectral Campaign under EUFAR

description: A novel reflectance-based approach for radiometric calibration 
		and atmospheric correction of airborne hyperspectral (HRS) data, supervised vicarious calibration (SVC), 
		was proposed by Brook and Ben-Dor in 2011. The present study aimed to validate the SVC method using 
		simultaneously operated several different airborne HRS sensors that acquired data above several 
		selected sites. The general goal is thus to apply a cross-calibration approach to examine the 
		capability and stability of the SVC method. In the current study three sensors were involved in an 
		airborne campaign mission supported by EUFAR under a project entitled ValCalHyp. The AISA-Dual 
		(operated by NERC), AHS and CASI (operated by INTA) acquired data over several selected sites in the 
		south of France (Salon de Province, Marseille, Avignon and Montpellier) on 28 October 2010 between 
		13:00 and 16:00 UTC.
DOI: 10.12760/02-2014-1-11
title: Extraction of urban building heights from LiDAR data: an integrated remote sensing and GIS approach

description: Although passive remote sensing technology allows us to detect and map urban buildings and infrastructures, they have several limitations when it comes to extracting their heights. However, by using a combination of data from passive and active sensors, it is possible to overcome some of those limitations and produce highly accurate 3-D height maps of urban areas. In this paper, a combination of IKONOS and LiDAR data is used and processed through integrated remote sensing-GIS based method to extract individual building heights in the urban central part of Norman, Oklahoma. Results show that while the method extracts the location of buildings with moderately high (75%) degree of completeness, the accuracy level in estimating the area and height was lower and depends mostly on the presence of trees surrounding the buildings. Future research should focus on using the method on IKONOS and LiDAR data collected during winter seasons when the leaves of trees are not present.