Answer Set Programming Modulo `Space-Time'

We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components. Supported are capabilities for mixed qualitative-quantitative reasoning, consistency checking, and inferring compositions of space-time relations; these capabilities combine and synergise for applications in a range of AI application areas where the processing and interpretation of spatio-temporal data is crucial. The framework and resulting system is the only general KR-based method for declaratively reasoning about the dynamics of `space-time' regions as first-class objects. We present an empirical evaluation (with scalability and robustness results), and include diverse application examples involving interpretation and control tasks

Transfer function-noise modeling and spatial interpolation to evaluate the risk of extreme (shallow) water-table levels in the Brazilian Cerrados

Water regimes in the Brazilian Cerrados are sensitive to climatological disturbances and human intervention. The risk that critical water-table levels are exceeded over long periods of time can be estimated by applying stochastic methods in modeling the dynamic relationship between water levels and driving forces such as precipitation and evapotranspiration. In this study, a transfer function-noise model, the so called PIRFICT-model, is applied to estimate the dynamic relationship between water-table depth and precipitation surplus/deficit in a watershed with a groundwater monitoring scheme in the Brazilian Cerrados. Critical limits were defined for a period in the Cerrados agricultural calendar, the end of the rainy season, when extremely shallow levels

Agroecological aspects of evaluating agricultural research and development:

In this paper we describe how biophysical data can be used, in conjunction with agroecological concepts and multimarket economic models, to systematically evaluate the effects of agricultural R&D in ways that inform research priority setting and resource allocation decisions. Agroecological zones can be devised to help estimate the varying, site-specific responses to new agricultural technologies and to evaluate the potential for research to spill over from one agroecological zone to another. The application of agroecological zonation procedures in an international agricultural research context is given special attention.Agricultural research., Technological innovations., Agricultural economics and policies.,

Dasymetric distribution of votes in a dense city

[EN] A large proportion of electoral analyses using geography are performed on a small area basis, such as polling units. Unfortunately, polling units are frequently redrawn, provoking breaks in their data series. Previous electoral results play a key role in many analyses. They are used by political party workers and journalists to present quick assessments of outcomes, by political scientists and electoral geographers to perform detailed scrutinizes and by pollsters and forecasters to anticipate electoral results. In this paper, we study to what extent more complex geographical approaches (based on a proper location of electors on the territory using dasymetric techniques) are of value in comparison to simple methods (like areal weighting) for the problem of reallocating votes in a large, dense city. Barcelona is such a city and, having recently redrawn the boundaries of its census sections, it is an ideal candidate for further scrutiny. Although previous studies show the approaches based on dasymetric techniques outperforming simpler solutions for interpolating census figures, our results show that improvements in the process of reallocating votes are marginal. This brings into question the extra effort that entails introducing ancillary sources of information in a dense urban area for this kind of data. Additional research is required to know whether and when these results are extendable. (C) 2017 Elsevier Ltd. All rights reserved.This work was supported by the Spanish Ministry of Economics and Competitiveness under Grant CSO2013-43054-R.Pavia, JM.; Cantarino-Martí, I. (2017). Dasymetric distribution of votes in a dense city. Applied Geography. 86:22-31. https://doi.org/10.1016/j.apgeog.2017.06.021S22318

Spatiotemporal Data Augmentation of MODIS-LANDSAT Water Bodies Using Generative Adversarial Networks

The monitoring of the shape and area of a water body is an essential component for many Earth science and Hydrological applications. For this purpose, these applications require remote sensing data which provides accurate analysis of the water bodies. In this thesis the same is being attempted, first, a model is created that can map the information from one kind of satellite that captures the data from a distance of 500m to another data that is captured by a different satellite at a distance of 30m. To achieve this, we first collected the data from both of the satellites and translated the data from one satellite to another using our proposed Hydro-GAN model. This translation gives us the accurate shape, boundary, and area of the water body. We evaluated the method by using several different similarity metrics for the area and the shape of the water body. The second part of this thesis involves augmenting the data that we obtained from the Hydro-GAN model with the original data and using this enriched data to predict the area of a water body in the future. We used the case study of Great Salt lake for this purpose. The results indicated that our proposed model was creating accurate area and shape of the water bodies. When we used our proposed model to generate data at a resolution of 30m it gave us better areal and shape accuracy. If we get more data at this resolution, we can use that data to better predict coastal lines, boundaries, as well as erosion monitoring

Guidance for benthic habitat mapping: an aerial photographic approach

This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor