Spatial high-resolution socio-energetic data for municipal energy system analyses

Abstract In the context of the energy transition, municipalities are increasingly attempting to exploit renewable energies. Socio-energetic data are required as input for municipal energy system analyses. This Data Descriptor provides a compilation of 40 indicators for all 11,131 German municipalities. In addition to census data such as population density, mobility data such as the number of vehicles and data on the potential of renewables such as wind energy are included. Most of the data set also contains public data, the allocation of which to municipalities was an extensive task. The data set can support in addressing a wide range of energy-related research challenges. A municipality typology has already been developed with the data, and the resulting municipality grouping is also included in the data set.

Download Full-text

Using kites for 3-D mapping of gullies at decimetre-resolution over several square kilometres: a case study on the Kamech catchment, Tunisia

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-1567-2018 ◽

2018 ◽

Vol 18 (6) ◽

pp. 1567-1582 ◽

Cited By ~ 9

Author(s):

Denis Feurer ◽

Olivier Planchon ◽

Mohamed Amine El Maaoui ◽

Abir Ben Slimane ◽

Mohamed Rached Boussema ◽

...

Keyword(s):

High Resolution ◽

Aerial Photography ◽

Airborne Lidar ◽

Data Set ◽

Topographic Data ◽

Independent Field ◽

Wide Range ◽

Laser Systems ◽

High Level

Abstract. Monitoring agricultural areas threatened by soil erosion often requires decimetre topographic information over areas of several square kilometres. Airborne lidar and remotely piloted aircraft system (RPAS) imagery have the ability to provide repeated decimetre-resolution and -accuracy digital elevation models (DEMs) covering these extents, which is unrealistic with ground surveys. However, various factors hamper the dissemination of these technologies in a wide range of situations, including local regulations for RPAS and the cost for airborne laser systems and medium-format RPAS imagery. The goal of this study is to investigate the ability of low-tech kite aerial photography to obtain DEMs with decimetre resolution and accuracy that permit 3-D descriptions of active gullying in cultivated areas of several square kilometres. To this end, we developed and assessed a two-step workflow. First, we used both heuristic experimental approaches in field and numerical simulations to determine the conditions that make a photogrammetric flight possible and effective over several square kilometres with a kite and a consumer-grade camera. Second, we mapped and characterised the entire gully system of a test catchment in 3-D. We showed numerically and experimentally that using a thin and light line for the kite is key for a complete 3-D coverage over several square kilometres. We thus obtained a decimetre-resolution DEM covering 3.18 km2 with a mean error and standard deviation of the error of +7 and 22 cm respectively, hence achieving decimetre accuracy. With this data set, we showed that high-resolution topographic data permit both the detection and characterisation of an entire gully system with a high level of detail and an overall accuracy of 74 % compared to an independent field survey. Kite aerial photography with simple but appropriate equipment is hence an alternative tool that has been proven to be valuable for surveying gullies with sub-metric details in a square-kilometre-scale catchment. This case study suggests that access to high-resolution topographic data on these scales can be given to the community, which may help facilitate a better understanding of gullying processes within a broader spectrum of conditions.

Download Full-text

A public data set of spatio-temporal match events in soccer competitions

Scientific Data ◽

10.1038/s41597-019-0247-7 ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 12

Author(s):

Luca Pappalardo ◽

Paolo Cintia ◽

Alessio Rossi ◽

Emanuele Massucco ◽

Paolo Ferragina ◽

...

Keyword(s):

Data Science ◽

Social Systems ◽

Team Sports ◽

Data Set ◽

Evaluation Of Performance ◽

Public Data ◽

Wide Range ◽

Spatio Temporal ◽

Measurement And Evaluation ◽

Temporal Events

Abstract Soccer analytics is attracting increasing interest in academia and industry, thanks to the availability of sensing technologies that provide high-fidelity data streams for every match. Unfortunately, these detailed data are owned by specialized companies and hence are rarely publicly available for scientific research. To fill this gap, this paper describes the largest open collection of soccer-logs ever released, containing all the spatio-temporal events (passes, shots, fouls, etc.) that occured during each match for an entire season of seven prominent soccer competitions. Each match event contains information about its position, time, outcome, player and characteristics. The nature of team sports like soccer, halfway between the abstraction of a game and the reality of complex social systems, combined with the unique size and composition of this dataset, provide an ideal ground for tackling a wide range of data science problems, including the measurement and evaluation of performance, both at individual and at collective level, and the determinants of success and failure.

Download Full-text

Spatial Disaggregation of Historical Census Data Leveraging Multiple Sources of Ancillary Information

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8080327 ◽

2019 ◽

Vol 8 (8) ◽

pp. 327 ◽

Cited By ~ 5

Author(s):

Monteiro ◽

Martins ◽

Murrieta-Flores ◽

Moura Pires

Keyword(s):

Machine Learning ◽

Neural Networks ◽

High Resolution ◽

Census Data ◽

Population Changes ◽

Multiple Sources ◽

Machine Learning Methods ◽

Wide Range ◽

Spatial Disaggregation ◽

Modern Machine

High-resolution population grids built from historical census data can ease the analyses ofgeographical population changes, at the same time also facilitating the combination of populationdata with other GIS layers to perform analyses on a wide range of topics. This article reports onexperiments with a hybrid spatial disaggregation technique that combines the ideas of dasymetricmapping and pycnophylactic interpolation, using modern machine learning methods to combinedifferent types of ancillary variables, in order to disaggregate historical census data into a 200 mresolution grid. We specifically report on experiments related to the disaggregation of historicalpopulation counts from three different national censuses which took place around 1900, respectively inGreat Britain, Belgium, and the Netherlands. The obtained results indicate that the proposed methodis indeed highly accurate, outperforming simpler disaggregation schemes based on mass-preservingareal weighting or pycnophylactic interpolation. The best results were obtained using modernregression methods (i.e., gradient tree boosting or convolutional neural networks, depending on thecase study), which previously have only seldom been used for spatial disaggregation.

Download Full-text

Inversion of Chromophoric Dissolved Organic Matter From EO-1 Hyperion Imagery for Turbid Estuarine and Coastal Waters

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2012.2224117 ◽

2013 ◽

Vol 51 (6) ◽

pp. 3286-3298 ◽

Cited By ~ 34

Author(s):

Weining Zhu ◽

Qian Yu

Keyword(s):

Organic Matter ◽

High Resolution ◽

Dissolved Organic Matter ◽

Coastal Waters ◽

Ocean Color ◽

Chromophoric Dissolved Organic Matter ◽

Significant Implication ◽

Coastal Regions ◽

Data Set ◽

Wide Range

The significant implication of chromophoric dissolved organic matter (CDOM) for water quality and biogeochemical cycle leads to an increasing need of CDOM monitoring in coastal regions. Current ocean-color algorithms are mostly limited to open-sea water and have high uncertainty when directly applied to turbid coastal waters. This paper presents a semianalytical algorithm, quasi-analytical CDOM algorithm (QAA-CDOM), to invert CDOM absorption from Earth Observing-1 (EO-1) Hyperion satellite images. This algorithm was developed from a widely used ocean-color algorithm QAA and our earlier extension of QAA. The main goal is to improve the algorithm performance for a wide range of water conditions, particularly turbid waters in estuarine and coastal regions. The algorithm development, calibration, and validation were based on our intensive high-resolution underwater measurements, International Ocean Color Coordinating Group synthetic data, and global National Aeronautics and Space Administration Bio-Optical Marine Algorithm Data Set data. The result shows that retrieved CDOM absorption achieved accuracy (root mean square error (RMSE) = 0.115 m-1andR2= 0.73) in the Atchafalaya River plume area. QAA-CDOM is also evaluated for scenarios in three additional study sites, namely, the Mississippi River, Amazon River, and Moreton Bay, whereag(440) was in the wide range of 0.01-15 m-1. It resulted in expected CDOM distribution patterns along the river salinity gradient. This study improves the high-resolution observation of CDOM dynamics in river-dominated coastal margins and other coastal environments for the study of land-ocean interactive processes.

Download Full-text

Reducing climate risks with fast and complete energy transitions: applying the precautionary principle to the Paris agreement

10.31219/osf.io/5wf64 ◽

2021 ◽

Author(s):

Harald Desing ◽

Rolf Widmer

Keyword(s):

Precautionary Principle ◽

Energy Transition ◽

Energy System ◽

The Precautionary Principle ◽

Climate Risks ◽

System A ◽

Prior Consent ◽

Wide Range ◽

Transition Pathways ◽

Climate Action

Averting the climate catastrophe requires the transformation of the energy system. A wide range of energy transition pathways are being explored in literature, which limit peak heating during this century as likely as not to 2°C or 1.5°C. Growing understanding of the Earth system suggests that peak heating beyond 1.5°C may be an existential threat to the biosphere and therefore also humanity. Transitions that exceed this vital threshold with a high probability expose future generations to substantial risks without their prior consent. Here we advocate the precautionary principle and explore with a minimal energy transition model the energy requirements to minimize climate risks. Fast and complete transitions are energetically possible when temporarily increasing fossil emissions above current levels for the sole purpose of accelerating the growth of renewable energy capacity. This reduces the probability to exceed 1.5°C peak heating at best to 20%, highlighting the urgency for climate action.

Download Full-text

On the exploration of alternative spatial representation for land models; a vector-based setup for the Variable Infiltration Capacity model

10.5194/egusphere-egu2020-6524 ◽

2020 ◽

Author(s):

Shervan Gharari ◽

Martyn Clark

Keyword(s):

High Resolution ◽

Spatial Heterogeneity ◽

Spatial Data ◽

Land Surface ◽

Spatial Representation ◽

Variable Infiltration Capacity ◽

Infiltration Capacity ◽

Data Set ◽

Wide Range ◽

Model Setup

Land models are increasingly used as the backbone of the terrestrial hydrology as they cover a wide range of processes (from rainfall/runoff processes to carbon cycle). The recent improvements in high-resolution spatial data set including detailed digital elevation models, DEMs, and land cover and soil type maps are encouraging the modelers to set up the land surface models at the highest resolution possible. However, this high-resolution setup does not often coincide with rigorous model diagnostics and also the &#8220;optimal&#8221; spatial representation based on the context of modeling (e.g. streamflow). A model can be seen as a tool to interpolate or extrapolate our knowledge in time and space and therefore it remains an important aspect of land surface modeling to which level the spatial heterogeneity can be represented in a model so that the states and fluxes &#8220;improve&#8221; given the context of modeling. The representation of spatial data in our models has important implications including (1) removing the unnecessarily computational burden from model setups which in turn results in better assessment of uncertainty and sensitivity analysis of the parameters on a less computational expensive model. (2) Proper corresponding between the communications of spatial variability while avoiding overconfidence in the nature of model response on illogically smallest units.In this study, in contrast to the often used grid-based model setup, we use the concept of vector-based group response units (GRUs) for setting up the Variable Infiltration Capacity, the VIC model, and vector-based MizuRoute routing scheme. We explore the added information by stepwise inclusion of more detailed spatial data and higher resolution forcing data while the vector-based routing setup remains identical for each of the configurations. Using this flexible workflow we explore three major questions:<ul><li>1- How the performance of model changes in the calibration mode for various configuration of spatial heterogeneity representation and forcing resolution given the context of modeling, for example, streamflow simulations or snow water equivalent spatial pattern?</li> <li>2- How well a simplified version of a more complex model in spatial representation can reproduce its own simulation? The answer to this question will provide us with iso-performing model setups, configurations of forcing distribution and spatial heterogeneity representation, and the possible loss in the performance metric given the context of modeling under the simplification decisions.</li> <li>3- How the model performs across various configurations of spatial data and forcing resolutions with a given set of so-called physically parameters that are often considered to be identical for GRUs with the same physical characteristics, soil, vegetation type, elevation zone, slope and aspect, varies?</li> </ul>Our findings indicate that the optimal spatial representation in the context of modeling, streamflow, for example, may very well be much less computationally demanding than the model setup that contains all the details with the highest resolution of the data. In a complementary attempt, it is shown that the often good performing parameter sets are able to reproduce good performing simulation in comparison to the model setup with the highest model resolution.

Download Full-text

Progressive landslide activity analysis and monitoring from Multi-temporal high-resolution geoinfomatic data sets

10.5194/egusphere-egu2020-9090 ◽

2020 ◽

Author(s):

Kuo-Jen Chang ◽

Chih-Ming Tseng ◽

Ho-Hsuan Chang ◽

Mei-Jen Huang

Keyword(s):

High Resolution ◽

Unmanned Aircraft ◽

Airborne Lidar ◽

Landslide Monitoring ◽

Data Sets ◽

Data Set ◽

Wide Range ◽

Hazardous Area ◽

Multi Temporal ◽

Rtk Gps

Due to the high seismicity and high annual precipitation, numerous landslides have occurred and caused severe impact in Taiwan. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precise geoinformation. The Small unmanned aircraft system (sUAS) has been widely used in landslide monitoring and geomorphic change detection. To access potential hazards we combine sUAS, field survey, terrestrial laser scanner (ground LiDAR) and UAS LiDAR for data acquisition. Based on the methods we construct multi-temporal high-resolution DTMs so as to access the activity and to monitoring the creeping landslides in Paolai village, southern Taiwan. The data set are qualified from 21 ground control points (GCPs) and 11 check points (CPs) based on real-time kinematic-global positioning system (RTK-GPS) and VBS RTK-GPS (e-GNSS). Since 2015, more than 10 geospatial datasets have been produced for an area between 5-80 Km2 with 8-12 cm spatial resolution. These datasets were then compared with the airborne LiDAR data to access the quality and interpretability of the data sets. Since 2017, we integrate UAS LiDAR to monitoring landslide area, and re-evaluate the data accuracy. Since 2018 we have integrate UAS LiDAR, terrestrial LiDAR, and photogrammetric point cloud for landslide study, to ensure no shadow effect of the dataset. The geomorphologic changes and landslide activities were quantified in Paolai area. The results of this study provide not only geoinfomatic datasets of the hazardous area, but also for essential geomorphologic information for other study, and for hazard mitigation and planning, as well.

Download Full-text

ENSO Signals Contribute to Variations in Breeding Bird Densities in Grand Teton Nationl Park

The UW National Parks Service Research Station Annual Reports ◽

10.13001/uwnpsrc.2009.3739 ◽

2009 ◽

Vol 32 ◽

pp. 21-25

Author(s):

Martin Cody

Keyword(s):

Census Data ◽

Bird Species ◽

Breeding Bird ◽

Data Set ◽

Wide Range ◽

Fixed Area ◽

Migrant Birds ◽

The Subject ◽

Breeding Seasons ◽

Preceding Winter

We have monitored breeding bird densities over a variety of sites and habitats in GTNP since the early 1990s, utilizing fixed-area census sites of around 5 ha in size. The sites are located throughout the park in all habitat types and over a wide range of elevations, and number 30 in all. At some of these monitoring sites we have accumulated data in successive breeding seasons for almost two decades; the power of these census data in interpreting variation in bird species composition and breeding densities, species to species, site to site, and especially year to year, clearly increases with the span of the data set. Some of the measured variation in breeding densities is presumably attributable to conditions encountered by resident birds during the preceding winter, on-site in GTNP. Some may be attributable to conditions evaluated by migrant birds returning to GTNP after wintering elsewhere, also an on-site contribution. However, a further potential source of variation is off-site, and may be ascribed to conditions endured by the migrants on their wintering grounds. It is the source and extent of such variation in the winter habitats of GTNP migrants that is the subject of the ensuing discussion.

Download Full-text

Narrowband-to-Broadband Conversions for Top-of-Atmosphere Reflectance from the Advanced Very High Resolution Radiometer (AVHRR)

Remote Sensing ◽

10.3390/rs12020305 ◽

2020 ◽

Vol 12 (2) ◽

pp. 305 ◽

Cited By ~ 3

Author(s):

Tom Akkermans ◽

Nicolas Clerbaux

Keyword(s):

High Resolution ◽

Global Climate ◽

Regional Scale ◽

Radiant Energy ◽

Large Data ◽

Energy System ◽

Climate Data ◽

Data Set ◽

Regional Analyses ◽

Very High

The current lack of a long, 30+ year, global climate data record of reflected shortwave top-of-atmosphere (TOA) radiation could be tackled by relying on existing narrowband records from the Advanced Very High Resolution Radiometer (AVHRR) instruments, and transform these measurements into broadband quantities like provided by the Clouds and the Earth’s Radiant Energy System (CERES). This paper presents the methodology of an AVHRR-to-CERES narrowband-to-broadband conversion for shortwave TOA reflectance, including the ready-to-use results in the form of scene-type dependent regression coefficients, allowing a calculation of CERES-like shortwave broadband reflectance from AVHRR channels 1 and 2. The coefficients are obtained using empirical relations in a large data set of collocated, coangular and simultaneous AVHRR-CERES observations, requiring specific orbital conditions for the AVHRR- and CERES-carrying satellites, from which our data analysis uses all available data for an unprecedented observation matching between both instruments. The multivariate linear regressions were found to be robust and well-fitting, as demonstrated by the regression statistics on the calibration subset (80% of data): adjusted R 2 higher than 0.9 and relative RMS residual mostly below 3%, which is a significant improvement compared to previous regressions. Regression models are validated by applying them on a validation subset (20% of data), indicating a good performance overall, roughly similar to the calibration subset, and a negligible mean bias. A second validation approach uses an expanded data set with global coverage, allowing regional analyses. In the error analysis, instantaneous accuracy is quantified at regional scale between 1.8 Wm − 2 and 2.3 Wm − 2 (resp. clear-sky and overcast conditions) at 1 standard deviation (RMS bias). On daily and monthly time scales, these errors correspond to 0.7 and 0.9 Wm − 2 , which is compliant with the GCOS requirement of 1 Wm − 2 .

Download Full-text

Decision support for renewables deployment through spatially explicit energy system alternatives

10.5194/egusphere-egu21-16205 ◽

2021 ◽

Author(s):

Bryn Pickering ◽

Francesco Lombardi ◽

Stefan Pfenninger

Keyword(s):

Energy Systems ◽

Energy Transition ◽

Weather Conditions ◽

Energy System ◽

Spatially Explicit ◽

Energy System Model ◽

Modelling Framework ◽

Wide Range ◽

Adverse Weather ◽

Generation Capacity

A decarbonised European energy system will require a number of potentially contested decisions on where best to locate renewable generation capacity. Typically, modellers determine the &#8220;best&#8221; system based on the least cost to society, focussing on a cost-minimising energy system model result to inform planning and policy. This approach neglects potentially more desirable alternative results which might, for example, avoid problematic concentrations of onshore wind power deployment, increase national supply security, or lower the risk of system failure in adverse weather conditions.In response, we have developed a method to generate spatially explicit, practically optimal results (SPORES) in the context of energy system optimisation. SPORES can be used to explore energy systems which may offer more socially, politically, or environmentally acceptable alternatives. Furthermore, we have developed metrics to aid identification of interesting alternatives, like those which maximise the spatial distribution of wind generation capacity or minimise exposure to multi-year demand and weather uncertainty.In this presentation, we will detail the application of the SPORES method in two cases of energy system decarbonisation: &#160;the Italian power system and the European energy system. We will present technology deployment strategies which are prevalent across SPORES, such as solar photovoltaics coupled with battery storage, as well as those which offer flexibility of choice in location and extent of deployment. To help with the urgent task of planning socially and politically acceptable energy system decarbonisation strategies, our implementation of SPORES in the open-source energy systems modelling framework Calliope makes it accessible to a wide range of potential users; we will also discuss how other research groups can further build on this to accelerate the energy transition.

Download Full-text