This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. services; ecological connectivity; ecological status; and proximity/potential accessibility to the public. The results of this analysis were combined using Multi-Criteria Evaluation (MCE) techniques, thus offering different alternatives for defining and designing GI. The GI maps obtained show better results in less restrictive situations, which could be considered to articulate the existing protected areas. Not only is our proposal a promising tool for defining this kind of infrastructure, but its implementation only requires a limited amount of base spatial datasets.

As 3D cadastres offer advantages in several areas by providing information with greater accuracy and a high level of detail, a diagnosis of the cadastral situation is required prior to the implementation of a 3D cadastral model. Therefore, this study focuses on diagnosing the urban cadastral situation in Ecuador based on an analysis of eight cantonal decentralized autonomous governments that were selected primarily for the availability of their cadastral information. The twelve characteristics included in the analysis supported the definition of a cadastral development scale based on the fulfillment of each characteristic. The official cadastral databases, meetings, and interviews with personnel related to the cadastres were used in the analysis to gain in-depth knowledge of the situation in each canton. The findings demonstrated that most cantons had similar characteristics and are at an intermediate level of cadastral development. Therefore, there is the need for cantons to have standardized cadastral information in accordance with national and international regulations. Thus, in this research, we developed an initial Ecuadorian land administration domain model country profile to initiate the transition towards 3D cadastre.

Satellite monitoring of forests plays a relevant role in the agendas of tropical countries, mainly in the framework of international negotiations to implement a mechanism that ensures a reduction in global CO2 emissions from deforestation. An efficient way to approach this monitoring is to avoid duplication of efforts, generating products in a regional context that are subsequently adopted at the national level. In this effort, you should take advantage of the different data sources available by integrating geospatial tools and satellite image classification algorithms. In this research, a methodological framework was developed to generate cost-efficient national maps of forest cover and its dynamics for the countries of Central America, and its scalability and replicability was explored in the Democratic Republic of the Congo (DRC) and the State of Pará in Brazil. The maps were generated from Landsat images from the years 2000, 2012, and 2017. New geoprocessing elements have been incorporated into the digital classification procedures for satellite images, such as the automated extraction of training samples from secondary sources, the use of official national reference maps that respond to nationally adopted forest definitions, and automation of post-classification adjustments incorporating expert criteria. The applied regional approach offers advantages in terms of reducing costs and time, as well as improving the consistency and coherence of reports at different territorial levels (regional and national), reducing duplication of efforts and optimizing technical and financial resources. In Central America, the percentage of forest area decreased from 44% in 2000 to 38% in 2017. Average deforestation in the 2000–2012 period was 197,443 ha/year and that of 2012–2017 was 332,243 ha/year. Average deforestation for the complete period 2000–2017 was 264,843 ha/year. The tropical forests in both the State of Pará, Brazil, and the DRC have decreased over time.

El Catastro constituye una fuente de información de gran relevancia en los estudios de ámbito urbano e intraurbano. Ofrece información espacial detallada y precisa, de gran utilidad para apoyar la toma de decisiones en los procesos de planificación y ordenación territoriales. No obstante, en muchas ocasiones su uso se ve limitado por la exigencia de tener conocimiento, más o menos avanzado, de su estructura, contenido, relaciones entre los bancos de datos, etc. y, sobre todo, por ciertas dificultades técnicas en su obtención, tratamiento y adaptación que suponen importantes inversiones de tiempo y recursos. En este trabajo se propone una metodología específica para una explotación más ágil y eficiente del contenido del Catastro. Basada en consultas a la componente alfanumérica de los datos catastrales, utilizando PostgreSQL-PostGIS, para alimentar la tabla de atributos asociada a la cartografía vectorial de parcelas catastrales, se ha aplicado, a modo de ejemplo, al análisis de los usos del suelo en la ciudad de Alcalá de Henares (Comunidad de Madrid). Los resultados a nivel de parcela permiten identificar la distribución de usos del suelo en la ciudad, la especialización de áreas en unos usos determinados, los principales ejes comerciales, etc. A pesar de las limitaciones, se trata de una propuesta suficientemente concreta, pero a la vez abierta, y aplicable en cualquier área de estudio, lo que podría facilitar y potenciar la utilización de este tipo de información en diversos ámbitos del análisis urbano, en los que se precise de un elevado nivel de detalle de la información espacial.

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