Pedro Ribeiro de Andrade

An extensible toolbox for modeling nature-society interactions

Modeling interactions between social and natural systems is a hard task. It involves collecting data, building up a conceptual approach, implementing, calibrating, simulating, validating, and possibly repeating these steps again and again. There are different conceptual approaches proposed in the literature to tackle this problem. However, for complex problems it is better to combine different approaches, giving rise to a need for flexible and extensible frameworks for modeling nature-society interactions. In this paper we present TerraME, an open source toolbox that supports multi-paradigm and multi-scale modeling of coupled human-environmental systems. It enables models that combine agent-based, cellular automata, system dynamics, and discrete event simulation paradigms. TerraME has a GIS interface for managing real-world geospatial data and uses Lua, an expressive scripting language. TerraME is a toolbox for modeling and simulation of nature-society interactions.Novel abstractions and services support multiscale spatiotemporal modeling.It allows the combined use of several paradigms for model implementation.It provides an extensible high-level modeling language.GIS integration supports real-world case studies.

Fields as a Generic Data Type for Big Spatial Data

This paper defines the Field data type for big spatial data. Most big spatial data sets provide information about properties of reality in continuous way, which leads to their representation as fields. We develop a generic data type for fields that can represent different types of spatiotemporal data, such as trajectories, time series, remote sensing and, climate data. To assess its power of generality, we show how to represent existing algebras for spatial data with the Fields data type. The paper also argues that array databases are the best support for processing big spatial data and shows how to use the Fields data type with array databases.

Entities and Relations for Agent-Based Modelling of Complex Spatial Systems

This work presents a contribution towards generalising the representation of geospatial entities and their relations for simulating complex spatial systems using the agent based approach. We analyse the literature, and argue that each of the four types of relation is necessary. These relations can be grouped in two classes, placements and neighbourhoods, with likenesses and differences between them. Given that, we define requirements for representing geospatial entities and their relations, and study seven agent-based modelling toolkits (NetLogo, OBEUS, Repast, Swarm, Cormas, GRSP, and TerraME), analysing their capabilities to address the proposed requirements. Finally, we present our current work and future directions on developing TerraME.

From Input-Output Matrixes to Agent-Based Models: A Case Study on Carbon Credits in a Local Economy

Analytical macroeconomic scenarios are currently the most common approach to assist in the development and evaluation of economic policies. Reproducing and evaluating the results found by analytic models is one major hurdle to be overcome by social simulation on its early development in any specific knowledge area. This work describes an initial step toward moving from algebraic input-output economic models to agent-based models, in order to get more flexibility, adding decision capabilities to the agents and exploring more complex scenarios. We study economic scenarios of carbon credits for reducing deforestation in a region of Par´a state, in the Brazilian Amazonia. The objective is to investigate the underlying assumptions of the analytic model through an agent-based approach, deriving new challenges to be tackled by future agent-based models.

Modeling the environmental susceptibility of landfill sites in California

The proper management of solid waste (SW) is a global environmental challenge. A major issue is the proper disposal of SW while balancing a wide range of criteria and working with different spatial data. In this study, we used geographic information system as a tool to perform multi-criteria decision analysis with an analytical hierarchy process to develop an environmental impact susceptibility model (EISM) for landfills. The model was applied to the state of California, USA and results are presented herein. In particular, the EISM considers factors such as geology, pedology, geomorphology, water resources, and climate as represented by 13 associated environmental indicators. The results of the EISM indicate that more than 75% of California’s territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 25% of the state’s land, 61 landfills are located in the high and very high categories. These results are alarming because during the period from 2000 to 2015, these 61 landfills received approximately 308 million tons of SW, which corresponds to more than 57% of all SW disposed in California. The model results can be used toward mitigating the environmental impacts of these facilities.

Comunidades ribeirinhas como forma socioespacial de expressão urbana na Amazônia: uma tipologia para a região do Baixo Tapajós (Pará-Brasil)

The phenomenon of urban growth in the Amazon can be seen throughout the territory today and is structured into many different sociospatial forms. One such form consists of local communities, which, as they develop incipient urban networks, show specific characteristics that define their importance in the structuring of the territory throughout the region. In this paper we propose the use of qualiquantitative techniques for defining a typology for riverine communities along the Lower Tapajos River, in the State of Para in northern Brazil. Descriptive variables were obtained through field-applied questionnaires in 62 communities between the towns of Santarem and Itaituba. The variables were then submitted to multi-variate statistics. On the basis of the analysis of the main components of 30 variables and hierarchical grouping, five groups of communities were identified and described, and the results were considered consistent with the field-based observations. Variables related mainly to the use of the land and to infrastructure conditioned this classification. Communities located in conservation units, regardless of exactly where they were located along the banks of the Tapajos river, were in a situation different from that of the other communities, since the maintenance of all of them depended on programs of the Para State Government. The methodology presented can also be applied to other areas in the Amazon, provided that the specific characteristics of each area are taken into consideration. The typology proposed identifies the differences and presence of the communities in the regional space along the Lower Tapajos, and can be used for drawing up public policies addressed to local populations.

Modelling Land Use Change in Brazil:2000-2050 (Dataset)

The input and output land cover dataset across all modelled time periods (2000-2050) and scenarios resulting from the work of the REDD-PAC project in Brazil. Please consult the data section of the REDD-PAC website (http://redd-pac.org/new_page.php?contents=data1.csv) to access a data visualization tool and to obtain the dataset in WFS format. This dataset can be accessed and displayed using GIS software such as QGIS. Please consult the metadata file for further instructions

Using Models to inform Policies that meet multiple Objectives. Assessing the Contribution of Brazil's Forest Code to Biodiversity Conservation

Land-use change models can help to develop a holistic understanding of the range of potential impacts of different land-use related policy options, and so can strengthen development and implementation of policies to meet a range of objectives, including biodiversity conservation, climate change mitigation, sustainable development and food security. Brazil’s Native Vegetation Protection Act, commonly known as the Forest Code (FC), is one example of a policy that can be used to achieve several objectives. Using land-use modelling to inform ongoing decisions on how the provisions of the FC are put into practice can help to increase its effectiveness in meeting multiple objectives and commitments. Model projections show that the full implementation of the provisions of the FC will both reduce emissions of greenhouse gases and contribute to conserving biodiversity in Brazil. They further highlight the importance for biodiversity conservation of implementing the Environmental Reserve Tradable Certificate (CRA in Portuguese) mechanism quickly and effectively. Model results also show the need to put in place additional measures to protect areas, such as the Caatinga forests and grassy savanna in the Cerrado, which may suffer increased land-use pressures as a result of the FC.

A webmapping platform for publishing, sharing, and managing EO-derived data for forest protection

Ecometrica, together with partners in the UK, Mexico and Brazil, have collaborated on a UK Space Agency international partnership space programme (IPSP) project to advance EO applications in forests. A key objective was to improve EO derived information management for forest protection. Ecometrica’s cloud-based mapping platform was used to establish regional EO Labs within the partner organizations: ECOSUR (Mexico), INPE and FUNCATE (Brazil) and the University of Edinburgh (UK). The regional networks of EO Labs have provided a unified view of forestry-related data that is easy to access. In Mexico and Brazil the EO Labs enabled collaboration between research organisations and NGOs to develop applications for monitoring forest change in specified study areas and has enabled the compilation of previously unavailable regional EO and other spatial datasets into products that can be used by researchers, NGOs and state governments. Data on forest loss was linked to dynamic earth system models developed by the University of Edinburgh and INPE, utilising the EO Labs to provide an intuitive and powerful environment in which non-expert end- users can investigate the results from the huge datasets produced by multi-run model simulations. This paper demonstrates and discusses examples of mapping applications created on Ecometrica EO Labs by ECOSUR, INPE and the University of Edinburgh as part of this project, illustrating how cloud technology can enhance the field of forest protection.

Experiências com um Curso de Modelagem Socioambiental

In a social-environmental modeling course, students need to learn complementary skills that include the conceptualisation of a model, different modeling paradigms, computer programming, and the process of rigorously converting ideas and data into a computational program using a given toolkit. Such topics need to be taught in parallel in order to keep a heterogeneous audience motivated. Based on the experience with multidisciplinary audiences, this paper describes a socio-environmental modeling course that explores three modeling paradigms: System dynamics, Cellular automata, and Agent-based modeling. We also present a small tutorial with some examples developed for the course.