cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17026/dans-2ch-qsu5
title: Estimating Fire Background Temperature at a Geostationary Scale—An Evaluation of Contextual Methods for AHI-8

description: An integral part of any remotely sensed fire detection and attribution method is an estimation of the target pixel’s background temperature. This temperature cannot be measured directly independent of fire radiation, so indirect methods must be used to create an estimate of this background value. The most commonly used method of background temperature estimation is through derivation from the surrounding obscuration-free pixels available in the same image, in a contextual estimation process. This method of contextual estimation performs well in cloud-free conditions and in areas with homogeneous landscape characteristics, but increasingly complex sets of rules are required when contextual coverage is not optimal. The effects of alterations to the search radius and sample size on the accuracy of contextually derived brightness temperature are heretofore unexplored. This study makes use of imagery from the AHI-8 geostationary satellite to examine contextual estimators for deriving background temperature, at a range of contextual window sizes and percentages of valid contextual information. Results show that while contextual estimation provides accurate temperatures for pixels with no contextual obscuration, significant deterioration of results occurs when even a small portion of the target pixel’s surroundings are obscured. To maintain the temperature estimation accuracy, the use of no less than 65% of a target pixel’s total contextual coverage is recommended. The study also examines the use of expanding window sizes and their effect on temperature estimation. Results show that the accuracy of temperature estimation decreases significantly when expanding the examined window, with a 50% increase in temperature variability when using a larger window size than 5×5 pixels, whilst generally providing limited gains in the total number of temperature estimates (between 0.4%–4.4% of all pixels examined). The work also presents a number of case study regions taken from the AHI-8 disk in more depth, and examines the causes of excess temperature variation over a range of topographic and land cover conditions.
DOI: 10.17026/dans-26r-wte6
title: Evaluating the Performance of a Random Forest Kernel for Land Cover Classification

description: In this research, we evaluate the pros and cons of using an RF-based kernel (RFK) in an SVM compared to using the conventional Radial Basis Function (RBF) kernel and standard RF classifier. A time series of seven multispectralWorldView-2 images acquired over Sukumba (Mali) and a single hyperspectral AVIRIS image acquired over Salinas Valley (CA, USA) are used to illustrate the analyses
DOI: 10.17026/dans-25w-q9zm
title: Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data

description: Crop lodging - the bending of crop stems from their upright position or the failure of root-soil anchorage systems - is a major yield-reducing factor in wheat and causes deterioration of grain quality. The severity of lodging can be measured by a lodging score (LS)- an index calculated from the crop angle of inclination (CAI) and crop lodged area (LA). LS is difficult and time consuming to measure manually meaning that information on lodging occurrence and severity is limited and sparse. Remote sensing-based estimates of LS can provide more timely, synoptic and reliable information on crop lodging across vast areas. This information could improve estimates of crop yield losses, inform insurance loss adjusters and influence management decisions for subsequent seasons.This research - conducted in the 600 ha wheat sown area in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy - evaluated the performance of RADARSAT-2 and Sentinel-1 data to discriminate and classify lodging severity based on field measured LS. We measured temporal crop status characteristics related to lodging (e.g. lodged area, CAI, crop height) and collected relevant meteorological data (wind speed and rainfall) throughout May-June 2018. These field measurements were used to distinguish healthy (He) wheat from lodged wheat with different degrees of lodging severity (moderate, severe and very severe). We acquired multi-incidence angle (FQ8-27° and FQ21-41°) RADARSAT-2 and Sentinel-1 (40°) images and derived multiple metrics from them to discriminate and classify lodging severity. As a part of our data exploration, we performed a correlation analysis between the image-based metrics and LS. Next, a multi-temporal discriminant analysis approach, including a partial least squares (PLS-DA) method, was developed to classify lodging severities. We used the area under the curve-receiver operating characteristics (AUC-ROC) and confusion matrices to evaluate the accuracy of the PLS-DA classification models.Results show that (1) volume scattering components were highly correlated with LS at low incidence angles while double and surface scattering was more prevalent at high incidence angles; (2) lodging severity was best classified using low incidence angle R-FQ8 data (overall accuracy 72%) and (3) the Sentinel-1 data-based classification model was able to correctly identify 60% of the lodging severity cases in the study site. The results from this first study on classifying lodging severity using satellite-based SAR platforms suggests that SAR-based metrics can capture a substantial proportion of the observed variation in lodging severity, which is important in the context of operational crop lodging assessment in particular, and sustainable agriculture in general.
DOI: 10.17026/dans-2zz-a4td
title: Rock sample data from the footwall of the Kangaroo Caves Cu-Zn deposit, Pilbara, Western Australia

description: The 11 rock samples in this dataset have been collected for the characterization of hydrothermal alteration zonation in the footwall of the Kangaroo Caves volcanogenic massive sulfide deposit in the East Pilbara Granite Greenstone Terrane in Western Australia. The rock samples were collected along a transect that crosscut several alteration zones, one chlorite-quartz and two quartz-sericite alteration zones. Samples were acquired during a field visit in 2003.
DOI: 10.17026/dans-zpz-fg5t
title: Scientific Relevance and Future of Digital Immortality and Virtual Humans

description: We are on the threshold of a significant change in the way we view digital life, which will have a major effect on the physical world. Computers have increasingly emulated deceased human beings through growing awareness in the fields of artificial intelligence, big data, and machine learning, and have symbolically managed to overcome death with the help of technology. One thing is clear, though: now that there are proper and legitimate discussions happening about human immortality, we can be certain that the future is upon us. This article attempts to explain and challenge the ways in which digital immortality, in particular, has manifested itself. This paper summarizes the technological solutions, research findings and technical challenges of major researchers by reviewing the key technologies and general technical schemes in the field of digital human beings. The prospects of digital human beings are being investigated.
DOI: 10.17026/dans-xc5-jx74
title: Search Engine Optimisation (SEO) Strategy as Determinants to Enhance the Online Brand Positioning

description: The main purpose of this study is to identify the persistency of using SEO strategy inclusive the niche point of differentiation, valuable content, targeted keyword and scalable link building, as the determinants that enhance the success of online brand positioning.
DOI: 10.6084/m9.figshare.22658662.v1
title: Supplementary Material for: Mazabraud syndrome associated with McCune-Albright syndrome: a case report and literature review

description: The Mazabraud syndrome is a rare form of bone fibrous dysplasia associated with intramuscular myxomas. The McCune-Albright syndrome is characterized by the association of dysplasia fibrous bone to one or more extra-osseous manifestations, including café-au-lait skin spots and endocrine disturbances. Here, we report on a new case of a 52-year-old man with sacroiliac polyostic bone fibrous dysplasia associated with intramuscular myxomas of the left buttock and thigh and café-au-lait skin spot. Biopsy analysis of one muscular lesions on the left thigh analysis revealed a spindle cell tumor with myxoid stroma with GNAS gene mutation, confirming the diagnosis of intramuscular myxoma. Given the absence of radiological sign of malignancy at the bone level and a few pains relieved by simple analgesics, no specific treatment was applied. In March 2022, after 18 months of follow-up, the MRI and the PET-CT scan showed a stable disease. To our knowledge this case is the fourth one reporting association of Mazabraud syndrome and McCune-Albright syndrome in a man. The association of intramuscular tumors and bone tumors in the same anatomical region and without any continuity, especially in lower limbs, must evoke the diagnosis of Mazabraud syndrome.
DOI: 10.17026/dans-24k-fxw4
title: Its4Land Automating Image-Based Cadastral Boundary Mapping

description: This Ph.D. research introduces an approach that simplifies image-based cadastral mapping. We develop an automated cadastral boundary delineation approach that is applicable to remote sensing data of high-resolution. The approach is designed for areas, in which boundaries are demarcated by physical objects and are thus visible. Areas for early development are European rural areas in France and Germany. Areas of later investigation are East African developing countries including Kenya, Rwanda, and Ethiopia. The data contain remote sensing data, as well as scripts and info on the method development.
DOI: 10.17026/dans-zak-epb8
title: TOP10NL, digitaal topografisch bestand - versie 2010

description: TOP10NL is een digitaal topografisch bestand, bruikbaar op een schaalniveau tussen 1:5.000 en 1:25.000.DANS en het Kadaster werken samen met betrekking tot het duurzaam archiveren en beschikbaar stellen van topografische en kadastrale kaarten. Iedereen mag deze data gebruiken.Het betreft de volgende topografische bestanden: TOP50Vector, TOP250Raster, TOP50Raster, TOP25Raster, de Kadastrale Kaart, TOP10NL, TOP50Vector, TOP50NL, en TOP10Vector.Zie ook het overzicht van de Kadasterbestanden die via DANS beschikbaar zijn.De meest actuele versies van de Kadasterbestanden kunnen direct gedownload worden via de website van Publieke Dienstverlening op de Kaart – PDOK.In het informatieblad vindt u meer informatie over toegang tot de TOP-kaart.
DOI: 10.17026/dans-xmp-fw6h
title: Development of an Automatic system for Mapping Air quality risks in Space and Time (DAMAST)

description: The DAMAST project uses data from the ILM air quality monitoring network in Eindhoven which is part of the AiREAS civil initiative. This dataset contains the data from 2013-2017 on a number of air pollutants (PM10, PM2.5, PM1, UFP, NO2, O3) and additional variables measured (temperature, relative humidity, GPS location). It also contains the code used for data quality analysis, outlier detection, calibration, spatio-temporal modelling and mapping, and health impact assessment.
DOI: 10.17026/dans-xu9-c5rp
title: The SPLENDID chewing detection challenge (Version 2)

description: This dataset contains approximately 60 hours of recordings from a prototype chewing detection system. The sensor signals include photoplethysmography (PPG) and processed audio from the ear-worn chewing sensor, and signals from a belt-mounted 3D accelerometer. The recording sessions include 14 participants and were conducted in the context of the EU funded SPLENDID project, at Wageningen University, The Netherlands, during the summer of 2015. The purpose of the dataset is to help develop effective algorithms for chewing detection based PPG, audio and accelerometer signals.-x-x-x-x-x-x-If you use this dataset, please cite the following papers:[1] V. Papapanagiotou, C. Diou, L. Zhou, J. van den Boer, M. Mars and A. Delopoulos, “The SPLENDID chewing detection challenge,” 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jeju Island, South Korea, 2017, pp. 817-820.doi: 10.1109/EMBC.2017.8036949URL: http://ieeexplore.ieee.org/document/8036949/[2] V. Papapanagiotou, C. Diou, L. Zhou, J. van den Boer, M. Mars and A. Delopoulos, “A Novel Chewing Detection System Based on PPG, Audio, and Accelerometry,” in IEEE Journal of Biomedical and Health Informatics, vol. 21, no. 3, pp. 607-618, May 2017.doi: 10.1109/JBHI.2016.2625271URL: http://ieeexplore.ieee.org/document/7736096/****ATTENTION: This dataset replaces an old version of the SPLENDID dataset. To go to the old version look at the reference list.****
DOI: 10.17026/dans-xr2-m6d8
title: Ten years profile soil moisture and temperature measurements in Twente (version 2022)

description: The Twente region in the east of the Netherlands hold a network that monitors since 2009 profile soil moisture and temperature at twenty locations mostly in the rural environment. In addition, intensive measurement campaigns have been performed in 2009, 2015, 2016, and 2017 at number of measurement locations as a part of MSc and PhD research. The development of the network infrastructure has been supported through various EU and NWO-funded projects, and forthcoming data has been successfully used for the validation of satellite derived surface soil moisture products.The early development of the network has been described in Dente et al. (2011), but over the years the design of the network has altered considerably with the most recent updates documented in Van der Velde et al. (2021).In 2019, the Twente network has been operational for more than a decade and with this deposit we would like to make this data freely and well documented available for use by the science and professional communities. An accompanying data paper is under development and will be submitted to Earth System Science Data journal, which provide additional background information.
DOI: 10.17026/dans-zvb-py6u
title: Energy and nutrient recovery for municipal wastewater treatment: How to design a feasible plant layout?

description: Activated sludge systems are commonly used for robust and efficient treatment of municipal wastewater. However, these systems cannot achieve their maximum potential to recover valuable resources from wastewater. This study demonstrates a procedure to design a feasible novel configuration for maximizing energy and nutrient recovery. A simulation model was developed based on literature data and recent experimental research using steady-state energy and mass balances with conversions. The analysis showed that in the Netherlands, proposed configuration consists of four technologies: bioflocculation, cold partial nitritation/Anammox, P recovery, and anaerobic digestion. Results indicate the possibility to increase net energy yield up to 0.24 kWh/m3 of wastewater, while reducing carbon emissions by 35%. Moreover, sensitivity analysis points out the dominant influence of wastewater organic matter on energy production and consumption. This study provides a good starting point for the design of promising layouts that will improve sustainability of municipal wastewater management in the future.
DOI: 10.17026/dans-22e-7n2b
title: Data of the paper "The Wastewater Contamination Index: A methodology to assess the risk of wastewater contamination from satellite-derived water quality indicators"

description: This dataset is part of the article with DOI: https://doi.org/10.3389/fenvs.2023.1130655. In the article, the authors employed satellite-derived Water Quality Indicators and spatiotemporal analysis to assess the risk of wastewater contamination in Conceição Lagoon, a coastal lagoon in Southern Brazil. The WQIs used are satellite-derived absorption coefficients of chlorophyll-a (chla) and coloured dissolved organic matter (CDOM), and the backscattering coefficient of suspended particulate matter (SPM).The dataset comprises: 1) time series (2019-2021) of WQIs generated from the processing of Sentinel-2 Level 2A scenes with the 2SeaColor model, 2) time series (2019-2021) of the WQIs standardized anomalies (WQIs_Anomalies), and 3) time series (2019-2021) of the final Wastewater Contamination Index (WCI). The files are raster stacks in ENVI format (flat-binary raster file with an accompanying ASCII header file - *.HDR), which can be opened with most GIS software. The header file contains metadata of the rasters, including the coordinate system, pixel size, and band names (which in this case correspond to the image date in the format YYYYmmdd).More details on the methods can be found in the associated article.
DOI: 10.17026/dans-xee-n9rq
title: Detection of plastic litter using an ARIS sonar

description: Dataset used for the note titled "Detection of plastic litter using an ARIS sonar."Summary:This report describes a first test in April 2021 to use an ARIS sonar to detect macro- and mesoplastic in the water column of the river Waal (a free flowing distributary of the river Rhine in the Netherlands). Tests were performed in standing water, flowing water along the shore of the river and fast flowing water in the main channel simultaneous with stow net fishing. The costs associated with the ARIS sonar were financed by Rijkswaterstaat Oost Nederland. The preliminary data acquisition and analysis were performed by the Radboud University.The dataset includes raw ARIS sonar data (.aris format) collected on two separate dates:1.Dataset collected on 16-04-2021; file names are date_time_name of the plastic litter assessed.2.Dataset collected on 19-04-2021; file names end date_time_name of the plastic litter assessed (If not included then it was a test with several items).Opens with: ARISFish software
DOI: 10.17026/dans-zsb-rn8e
title: Position Estimation of Mobile Mapping Imaging Sensors Using Aerial Images

description: This project aims to improve the position estimation of mobile mapping platforms. Mobile Mapping (MM) is a technique to obtain geo-information on a large scale using sensors mounted on a car or another vehicle. Under normal conditions, accurate positioning is provided by the integration of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS). However, especially in urban areas, where building structures impede a direct line-of-sight to navigation satellites or lead to multipath effects, MM derived products, such as laser point clouds or images, lack the expected reliability and contain an unknown positioning error. This issue has been addressed by many researchers, whose aim to mitigate these effects mainly concentrates on utilising tertiary data, such as digital maps, ortho images or airborne LiDAR. These data serve as a reliable source of orientation and are being used subsidiarily or as the basis for adjustment. However, these approaches show limitations regarding the achieved accuracy, the correction of error in height, the availability of tertiary data and their feasibility in difficult areas. This project is addressing the aforementioned problem by employing high resolution aerial nadir and oblique imagery as reference data. By exploiting the MM platform?s approximate orientation parameters, very accurate matching techniques can be realised to extract the MM platform?s positioning error. In the form of constraints, they serve as a corrective for an orientation update, which is conducted by an estimation or adjustment technique.
DOI: 10.17026/dans-2zf-h8zr
title: Snow covered with dust after Chamoli rockslide: inference based on high-resolution satellite data

description: Data used for analysis in the paper "Snow covered with dust after Chamoli rockslide: inference based on high-resolution satellite data" published in Remote Sensing Letters
DOI: 10.17026/dans-xrz-y92s
title: Development and Validation of a Dense 18-Year Time Series of Surface Water Fraction Estimates from MODIS for the Mediterranean Region

description: In this paper, we developed a time series of surface water fraction maps at 500 m spatial resolution and 8-day temporal resolution over 18 years (2000-2017) for the Mediterranean region.
DOI: 10.17026/dans-x8z-ymqe
title: A modified model for estimating tree height from PolInSAR with compensation for temporal decorrelation

description: This chapter is based on the published paper: Ghasemi, N., Tolpekin, V. and Stein, A., (2018). A modified model for estimating tree height from PolInSAR with compensation for temporal decorrelation. International Journal of Applied Earth Observation and Geoinformation, 73, pp.313–322.https://www.sciencedirect.com/science/article/pii/S0303243418302563?via%3DihubThe dataset has been acquired by European Space Agency in the context of BioSAR2010 campaign conducted on Southwest Sweden by airborne SAR sensor and extensive field research.The RMoG (Random-Motion-over-Ground) model is commonly used to ob- tain tree height values from PolInSAR images. The RMoG model borrows its structure function from conventional RVoG (Random-Volume-over-Ground) model which is limited for modelling structural variety in canopy layer. This chapter extends the RMoG model to improve tree height estimation accur- acy by using a Fourier-Legendre polynomial as the structure function. The new model is denoted by the RMoGL model. The proposed modification makes height estimation less prone to errors by enabling more flexibility in representing the vertical structure of the vegetation layer. We applied the RMoGL model on airborne P- and L-band PolInSAR images from the Remingstorp test site in southern Sweden. We compared it with the RMoG and the conventional RVoG models using Lidar height map and field data for validation. For P-band, the relative error was equal to 37.5% for the RVoG model, to 23.7% for the RMoG model, and to 18.5% for the RMoGL model. For L-band it was equal to 30.54% for the RVoG model, to 20.02% for the RMoG model, and to 21.63% for the RMoGL. We concluded that the RMoGL model estimates tree height more accurately in P-band, while in L-band the RMoG model was equally good. The RMoGL model is of a great value for future SAR sensors that are more focused than before on tree height and biomass estimation.