Reconstructing Holocene European land cover using data-model integration

2012 ◽  
Vol 279-280 ◽  
pp. 314 ◽  
Author(s):  
Achille Mauri
Keyword(s):  
Land Cover ◽  
Data Model ◽  
Model Integration ◽  
Using Data

scholarly journals Distance-Based Estimation Methods for Models for Discrete and Mixed-Scale Data

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 107
Author(s):  
Elisavet M. Sofikitou ◽  
Ray Liu ◽  
Huipei Wang ◽  
Marianthi Markatou
Keyword(s):  
Data Model ◽  
Null Hypothesis ◽  
Model Misspecification ◽  
Asymptotic Properties ◽  
Estimation Methods ◽  
Measurement Scale ◽  
Interval Scale ◽  
Pearson Residuals ◽  
Using Data ◽  
Scale Data

Pearson residuals aid the task of identifying model misspecification because they compare the estimated, using data, model with the model assumed under the null hypothesis. We present different formulations of the Pearson residual system that account for the measurement scale of the data and study their properties. We further concentrate on the case of mixed-scale data, that is, data measured in both categorical and interval scale. We study the asymptotic properties and the robustness of minimum disparity estimators obtained in the case of mixed-scale data and exemplify the performance of the methods via simulation.

scholarly journals A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

2016 ◽  
Vol 100 (1) ◽  
pp. 27-38 ◽  
Author(s):  
Grazia Caradonna ◽  
Antonio Novelli ◽  
Eufemia Tarantino ◽  
Raffaela Cefalo ◽  
Umberto Fratino
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Geospatial Data ◽  
Usage Patterns ◽  
Mediterranean Regions ◽  
Multi Temporal ◽  
Using Data ◽  
Set Up

Abstract Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

An Integrated View of Complex Landscapes: A Big Data-Model Integration Approach to Transdisciplinary Science

BioScience ◽  
2018 ◽  
Vol 68 (9) ◽  
pp. 653-669 ◽  
Author(s):  
Debra P C Peters ◽  
N Dylan Burruss ◽  
Luis L Rodriguez ◽  
D Scott McVey ◽  
Emile H Elias ◽  
...  
Keyword(s):  
Big Data ◽  
Data Model ◽  
Model Integration ◽  
Integration Approach ◽  
Transdisciplinary Science ◽  
Complex Landscapes

scholarly journals Research-ready data for multi-cohort analyses: The Dementias Platform UK (DPUK) C-Surv data model

2021 ◽  
Author(s):  
Sarah Bauermeister ◽  
Joshua R Bauermeister ◽  
R Bridgman ◽  
C Felici ◽  
M Newbury ◽  
...  
Keyword(s):  
Data Model ◽  
Data Access ◽  
Data Discovery ◽  
Standard Data ◽  
Technology Standard ◽  
Access Request ◽  
Nested Structure ◽  
Using Data ◽  
Model C ◽  
Cohort Analyses

Abstract Research-ready data (that curated to a defined standard) increases scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following user consultation, a standard data model (C-Surv), optimised for data discovery, was developed using data from 12 Dementias Platform UK (DPUK) population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. It was concluded that developing and applying a standard data model (C-Surv) for research cohort data is feasible and useful.

Autonomous journaling response using data model LUTS

2009 ◽  
Author(s):  
Holger Jaenisch ◽  
James Handley ◽  
Nathaniel Albritton ◽  
David Whitener ◽  
Randel Burnett ◽  
...  
Keyword(s):  
Data Model ◽  
Using Data

scholarly journals Beyond Modeling: A Roadmap to Community Cyberinfrastructure for Ecological Data-Model Integration

2020 ◽  
Author(s):  
Istem Fer ◽  
Anthony K. Gardella ◽  
Alexey N. Shiklomanov ◽  
Shawn P. Serbin ◽  
Martin G. De Kauwe ◽  
...  
Keyword(s):  
Global Change ◽  
21St Century ◽  
Data Model ◽  
Model Integration ◽  
Science And Society ◽  
Model Data ◽  
Ecological Data ◽  
New Era ◽  
Natural Systems ◽  
New Knowledge

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks in our ability to process information have reduced our capacity to fully exploit the growing volume and variety of data. Here, we take a critical look at the information infrastructure that connects modeling and measurement efforts, and propose a roadmap that accelerates production of new knowledge. We propose that community cyberinfrastructure tools can help mend the divisions between empirical research and modeling, and accelerate the pace of discovery. A new era of data-model integration requires investment in accessible, scalable, transparent tools that integrate the expertise of the whole community, not just a clique of ‘modelers’. This roadmap focuses on five key opportunities for community tools: the underlying backbone to community cyberinfrastructure; data ingest; calibration of models to data; model-data benchmarking; and data assimilation and ecological forecasting. This community-driven approach is key to meeting the pressing needs of science and society in the 21st century.

scholarly journals Inattention and Switching Costs as Sources of Inertia in Medicare Part D

2021 ◽  
Vol 111 (9) ◽  
pp. 2737-2781
Author(s):  
Florian Heiss ◽  
Daniel McFadden ◽  
Joachim Winter ◽  
Amelie Wuppermann ◽  
Bo Zhou
Keyword(s):  
Data Model ◽  
Switching Costs ◽  
Medicare Part D ◽  
Medicare Part ◽  
Part D ◽  
Plan Choice ◽  
Using Data ◽  
Two Stages ◽  
Ability And Willingness ◽  
Over Time

Consumers’ health plan choices are highly persistent even though optimal plans change over time. This paper separates two sources of inertia, inattention to plan choice and switching costs. We develop a panel data model with separate attention and choice stages, linked by heterogeneity in acuity, i.e., the ability and willingness to make diligent choices. Using data from Medicare Part D, we find that inattention is an important source of inertia but switching costs also play a role, particularly for low-acuity individuals. Separating the two stages and allowing for heterogeneity is crucial for counterfactual simulations of interventions that reduce inertia. (JEL D12, G22, H51, I13, I18, L65)

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