Capacity building in the use of geospatial tools for natural resource management in Tajikistan: Final Report

The Swiss Swiss Consultant Trust Fund (CTF) support covered the period from July to December 2007 and comprised four main tasks: (1) Analysis of historic land degradation trends in the four watersheds of Zerafshan, Surkhob, Toirsu, and Vanj; (2) Translation of standard CDE GIS training materials into Russian and Tajik to enable local government staff and other specialists to use geospatial data and tools; (3) Demonstration of geospatial tools that show land degradation trends associated with land use and vegetative cover data in the project areas, (4) Preliminary training of government staff in using appropriate data, including existing information, global datasets, inexpensive satellite imagery and other datasets and webbased visualization tools like spatial data viewers, etc. The project allowed building of local awareness of, and skills in, up-to-date, inexpensive, easy-to-use GIS technologies, data sources, and applications relevant to natural resource management and especially to sustainable land management. In addition to supporting the implementation of the World Bank technical assistance activity to build capacity in the use of geospatial tools for natural resource management, the Swiss CTF support also aimed at complementing the Bank supervision work on the ongoing Community Agriculture and Watershed Management Project (CAWMP).

Capacity building in the use of geospatial tools for natural resource management in Tajikistan: Inception report BNWPP project

The Centre for Development and Environment (CDE) has been contracted by the World Bank Group to conduct a program on capacity development in use of geospatial tools for natural resource management in Tajikistan. The program aimed to help improving natural resource management by fostering the use of geospatial tools among governmental and non-governmental institutions in Tajikistan. For this purpose a database including a Geographic Information System (GIS) has been prepared, which combines spatial data on various sectors for case study analysis related to the Community Agriculture and Watershed Management Project (CAWMP). The inception report is based on the findings resulting from the Swiss Consultant Trust Fund (CTF) financed project, specifically on the experiences from the awareness creation and training workshop conducted in Dushanbe in November 2007 and the analysis of historical land degradation trends carried out for the four CAWMP watersheds. Furthermore, also recommendations from the inception mission of CDE to Tajikistan (5-20 August 2007) and the inception report for the Swiss CTF support were considered. The inception report for the BNWPP project (The Bank-Netherlands Water Partnership Program) discusses the following project relevant issues: (1) Preliminary list of additional data layers, types of data analysis, and audiences to be covered by BNWPP grant (2) Assessing skills and equipment already available within Tajikistan, and implications for training program and specific equipment procurement plans (3) Updated detailed schedule and plans for all activities to be financed by BNWPP grant, and (4) Proposed list of contents for the final report and web-based presentations.

Capacity Building in the Use of Geospatial Tools for Natural Resource Management in Tajikistan: Inception report

The sustainable management of natural resources is a key issue for sustainable development of a poor, mountainous country such as Tajikistan. In order to strengthen its agricultural and infrastructural development efforts and alleviate poverty in rural areas, spatial information and analysis are of crucial importance to improve priority setting and decision making efficiency. However, poor access to geospatial data and tools, and limited capacity in their use has greatly constrained the ability of governmental institutions to effectively assess, plan, and monitor natural resources management. The Centre for Development and Environment (CDE) has thus been mandated by the World Bank Group to provide adequate technical support to the Community Agriculture and Watershed Management Project (CAWMP). This support consists of a spatial database on soil degradation trends in 4 watersheds, capacity development in and awareness creation about geographic information technology and a spatial data exchange hub for natural resources management in Tajikistan. CDE’s support has started in July 2007 and will last until December 2007 with a possible extension in 2008.

Coastal Survey Maps: From Historical Documents to Digital Databases

This paper describes the spatial data handling procedures used to create a vector database of the Connecticut shoreline from Coastal Survey Maps. The appendix contains detailed information on how the procedures were implemented using Geographic Transformer Software 5 and ArcGIS 8.3. The project was a joint project of the Connecticut Department of Environmental Protection and the University of Connecticut Center for Geographic Information and Analysis.

Análisis de componentes principales con datos georreferenciados : una aplicación en agricultura de precisión

La utilización de nuevas tecnologías asociadas a la agricultura de precisión permite capturar información de múltiples variables en gran cantidad de sitios georreferenciados dentro de lotes en producción. Las covariaciones espaciales de las propiedades del suelo y el rendimiento del cultivo pueden evaluarse a través del análisis de componentes principales clásico (PCA). No obstante, como otros métodos multivariados descriptivos, el PCA no ha sido desarrollado explícitamente para datos espaciales. Nuevas versiones de análisis multivariado permiten contemplar la autocorrelación espacial entre datos de sitios vecinos. En este trabajo se aplican y comparan los resultados de dos técnicas multivariadas, el PCA y MULTISPATI-PCA. Este último incorpora la información espacial a través del cálculo del índice de Moran entre los datos de un sitio y el dato promedio de sus vecinos. Los resultados mostraron que utilizando MULTISPATI-PCA se detectaron correlaciones entre variables que no fueron detectadas con el PCA. Los mapas de variabilidad espacial construidos a partir de la primera componente de ambas técnicas fueron similares; no así los de la segunda componente debido a cambios en la estructura de co-variación identificada, al corregir la variabilidad por la autocorrelación espacial de los datos. El método MULTISPATI-PCA constituye una herramienta importante para el mapeo de la variabilidad espacial y la identificación de zonas homogéneas dentro de lotes.

Probability inundation map for a scenario combining storm surge and sea-level rise

Coastal managers require reliable spatial data on the extent and timing of potential coastal inundation, particularly in a changing climate. Most sea level rise (SLR) vulnerability assessments are undertaken using the easily implemented bathtub approach, where areas adjacent to the sea and below a given elevation are mapped using a deterministic line dividing potentially inundated from dry areas. This method only requires elevation data usually in the form of a digital elevation model (DEM). However, inherent errors in the DEM and spatial analysis of the bathtub model propagate into the inundation mapping. The aim of this study was to assess the impacts of spatially variable and spatially correlated elevation errors in high-spatial resolution DEMs for mapping coastal inundation. Elevation errors were best modelled using regression-kriging. This geostatistical model takes the spatial correlation in elevation errors into account, which has a significant impact on analyses that include spatial interactions, such as inundation modelling. The spatial variability of elevation errors was partially explained by land cover and terrain variables. Elevation errors were simulated using sequential Gaussian simulation, a Monte Carlo probabilistic approach. 1,000 error simulations were added to the original DEM and reclassified using a hydrologically correct bathtub method. The probability of inundation to a scenario combining a 1 in 100 year storm event over a 1 m SLR was calculated by counting the proportion of times from the 1,000 simulations that a location was inundated. This probabilistic approach can be used in a risk-aversive decision making process by planning for scenarios with different probabilities of occurrence. For example, results showed that when considering a 1% probability exceedance, the inundated area was approximately 11% larger than mapped using the deterministic bathtub approach. The probabilistic approach provides visually intuitive maps that convey uncertainties inherent to spatial data and analysis.

Integrated topographic database for King George Island, South Shetland Islands, with links to shapefiles

SCAR KGIS (SCAR King George Island GIS Project) was an integrated topographic database for King George Island, South Shetland Islands, including the SCAR Feature Catalogue to semantically integrate the data sets. The project, operated by the University of Freiburg, was available at http://portal.uni-freiburg.de/AntSDI as "The Antarctic Spatial Data Infrastructure (AntSDI)". Operation ended in 2007. The remaining data files were archived in shape format (zipped) in projections as recommended by SCAR. The source data was provided by a variety of institutions which were not referenced in the original product.

Infrastructure and Workflow for the Formal Evaluation of Semantic Search Technologies

This paper describes an infrastructure for the automated evaluation of semantic technologies and, in particular, semantic search technologies. For this purpose, we present an evaluation framework which follows a service-oriented approach for evaluating semantic technologies and uses the Business Process Execution Language (BPEL) to define evaluation workflows that can be executed by process engines. This framework supports a variety of evaluations, from different semantic areas, including search, and is extendible to new evaluations. We show how BPEL addresses this diversity as well as how it is used to solve specific challenges such as heterogeneity, error handling and reuse

Modelos de análisis econométrico espacial aplicados al desarrollo económico

Los modelos de desarrollo regional, rural y urbano arrancaron en la década de los 90 en Estados Unidos, modelando los factores relacionados con la economía que suministran información y conocimiento acerca de cómo los parámetros geográficos y otros externos influencian la economía regional. El desarrollo regional y en particular el rural han seguido diferentes caminos en Europa y España, adoptando como modelo los programas estructurales de la UE ligados a la PAC. El Programa para el Desarrollo Rural Sostenible, recientemente lanzado por el Gobierno de España (2010) no profundiza en los modelos económicos de esta economía y sus causas. Este estudio pretende encontrar pautas de comportamiento de las variables de la economía regional-rural, y como el efecto de distribución geográfica de la población condiciona la actividad económica. Para este propósito, y utilizando datos espaciales y económicos de las regiones, se implementaran modelos espaciales que permitan evaluar el comportamiento económico, y verificar hipótesis de trabajo sobre la geografía y la economía del territorio. Se utilizarán modelos de análisis espacial como el análisis exploratorio espacial y los modelos econométricos de ecuaciones simultáneas, y dentro de estas los modelos ampliamente utilizados en estudios regionales de Carlino-Mills- Boarnet. ABSTRACT The regional development models for rural and urban areas started in USA in the ´90s, modeling the economy and the factors involved to understand and collect the knowledge of how the external parameters influenced the regional economy. Regional development and in particular rural development has followed different paths in Europe and Spain, adopting structural programs defined in the EU Agriculture Common Policy. The program for Sustainable Rural Development recently implemented in Spain (2010) is short sighted considering the effects of the regional economy. This study endeavors to underline models of behavior for the rural and regional economy variables, and how the regional distribution of population conditions the economic activities. For that purpose using current spatial regional economic data, this study will implement spatial economic models to evaluate the behavior of the regional economy, including the evaluation of working hypothesis about geography and economy in the territory. The approach will use data analysis models, like exploratory spatial data analysis, and spatial econometric models, and in particular for its wide acceptance in regional analysis, the Carlino-Mills-Boarnet equations model.

OOPS! (OntOlogy Pitfall Scanner!): a web-based tool for ontology evaluation

Presentación en Workshop EUON 2014

Patrones y procesos espaciales en poblaciones y comunidades vegetales: nuevas herramientas e hipótesis

Generalmente los patrones espaciales de puntos en ecología, se definen en el espacio bi-dimensional, donde cada punto representado por el par ordenado (x,y), resume la ubicación espacial de una planta. La importancia de los patrones espaciales de plantas radica en que proceden como respuesta ante importantes procesos ecológicos asociados a la estructura de una población o comunidad. Tales procesos incluyen fenómenos como la dispersión de semillas, la competencia por recursos, la facilitación, respuesta de las plantas ante algún tipo de estrés, entre otros. En esta tesis se evalúan los factores y potenciales procesos subyacentes, que explican los patrones de distribución espacial de la biodiversidad vegetal en diferentes ecosistemas como bosque mediterráneo, bosque tropical y matorral seco tropical; haciendo uso de nuevas metodologías para comprobar hipótesis relacionadas a los procesos espaciales. En este trabajo se utilizaron dos niveles ecológicos para analizar los procesos espaciales, el nivel de población y el nivel de comunidad, con el fin de evaluar la importancia relativa de las interacciones intraespecíficas e interespecíficas. Me centré en el uso de funciones estadísticas que resumen los patrones de puntos para explorar y hacer inferencias a partir de datos espaciales, empezando con la construcción de un nuevo modelo nulo para inferir variantes del síndrome de dispersión de una planta parásita en España central. Se analizó la dependencia de los patrones espaciales tanto de los hospedantes afectados como de los no-afectados y se observó fuerte dependencia a pequeña y mediana distancia. Se utilizaron dos funciones (kernel) para simular la dispersión de la especie parásita y se identificó consistencia de estos modelos con otros síndromes de dispersión adicionalmente a la autodispersión. Un segundo tema consistió en desarrollar un método ANOVA de dos vías? para patrones de puntos replicados donde el interés se concentró en evaluar la interacción de dos factores. Este método se aplicó a un caso de estudio que consitió en analizar la influencia de la topografía y la altitud sobre el patrón espacial de un arbusto dominante en matorral seco al sur del Ecuador, cuyos datos provienen de patrones de puntos replicados basados en diseño. Partiendo de una metodología desarrollada para procesos uni-factoriales, se construyó el método para procesos bi-factoriales y así poder evaluar el efecto de interacción. Se observó que la topografía por sí sola así como la interacción con la altitud presentaron efecto significativo sobre la formación del patrón espacial. Un tercer tema fue identificar la relación entre el patrón espacial y el síndrome de dispersión de la comunidad vegetal en el bosque tropical de la Isla de Barro Colorado (BCI), Panamá. Muchos estudios se han desarrollado en este bosque tropical y algunos han analizado la relación síndrome-patrón espacial, sin embargo lo novedoso de nuestro estudio es que se evaluaron un conjunto amplio de modelos (114 modelos) basados en procesos que incorporan la limitación de la dispersión y la heterogeneidad ambiental, y evalúan el efecto único y el efecto conjunto, para posteriormente seleccionar el modelo de mejor ajuste para cada especie. Más de la mitad de las especies presentaron patrón espacial consistente con el efecto conjutno de la limitación de la dispersión y heterogeneidad ambiental y el porcentaje restante de especies reveló en forma equitativa el efecto único de la heterogeneidad ambiental y efecto único de limitación de la dispersión. Finalmente, con la misma información del bosque tropical de BCI, y para entender las relaciones que subyacen para mantener el equilibrio de la biodiversidad, se desarrolló un índice de dispersión funcional local a nivel de individuo, que permita relacionar el patrón espacial con cuatro rasgos funcionales clave de las especies. Pese a que muchos estudios realizados involucran esta comunidad con la teoría neutral, se encontró que el ensamble de la comunidad de BCI está afectado por limitaciones de similaridad y de hábitat a diferentes escalas. ABSTRACT Overall the spatial point patterns in ecology are defined in two-dimensional space, where each point denoted by the (x,y) ordered pair, summarizes the spatial location of a plant. The spatial point patterns are essential because they arise in response to important ecological processes, associated with the structure of a population or community. Such processes include phenomena as seed dispersal, competition for resources, facilitation, and plant response to some type of stress, among others. In this thesis, some factors and potential underlying processes were evaluated in order to explain the spatial distribution patterns of plant biodiversity. It was done in different ecosystems such as Mediterranean forest, tropical forest and dry scrubland. For this purpose new methodologies were used to test hypothesis related to spatial processes. Two ecological levels were used to analyze the spatial processes, at population and community levels, in order to assess the relative importance of intraspecific and interspecific interactions. I focused on the use of spatial statistical functions to summarize point patterns to explore and make inferences from spatial data, starting with the construction of a new null model to infer variations about the dispersal syndrome of a parasitic plant in central Spain. Spatial dependence between point patterns in a multivariate point process of affected and unaffected hosts were analyzed and strong dependence was observed at small and medium distance. Two kernel functions were used to simulate the dispersion of parasitic plant and consistency of these models with other syndromes was identified, in addition to ballistic dispersion. A second issue was to analyze altitude and topography effects on the spatial population structure of a dominant shrub in the dry ecosystem in southern Ecuador, whose data come from replicated point patterns design-based. Based on a methodology developed for uni-factorial process, a method for bi-factorial processes was built to assess the interaction effect. The topography alone and interacting with altitude showed significant effect on the spatial pattern of shrub. A third issue was to identify the relationship between the spatial pattern and dispersal syndromes of plant community in the tropical forest of Barro Colorado Island (BCI), Panamá. Several studies have been developed in this tropical forest and some focused on the spatial pattern-syndrome relationship; however the novelty of our study is that a large set of models (114 models) including dispersal limitation and environmental heterogeneity were evaluated, used to identify the only and joint effect to subsequently select the best fit model for each species. Slightly more than fifty percent of the species showed spatial pattern consistent with only the dispersal limitation, and the remaining percentage of species revealed the only effect of environmental heterogeneity and habitat-dispersal limitation joined effect, equitably. Finally, with the same information from the tropical forest of BCI, and to understand the relationships underlying for balance of biodiversity, an index of the local functional dispersion was developed at the individual level, to relate the spatial pattern with four key functional traits of species. Although many studies involve this community with neutral theory, the assembly of the community is affected by similarity and habitat limitations at different scales.

Bathymetric Terrain Model of the Puerto Rico Trench and the Northeastern Caribbean Region for Marine Geological Investigations

Multibeam bathymetric data collected in the Puerto Rico Trench and northeastern Caribbean region are compiled into a seamless bathymetric terrain model for broad-scale geological investigations of the trench system. These data, collected during eight separate surveys between 2002 and 2013 and covering almost 180,000 square kilometers, are published here in large-format map sheet and digital spatial data. This report describes the common multibeam data collection and processing methods used to produce the bathymetric terrain model and corresponding data-source polygon. Details documenting the complete provenance of the data are provided in the metadata in the Data Catalog section.

A software tool for accurate assessment of costs and CO2 emissions in wood transport using OpenStreetMap©

Costs and environmental impacts are key elements in forest logistics and they must be integrated in forest decision-making. The evaluation of transportation fuel costs and carbon emissions depend on spatial and non-spatial data but in many cases the former type of data are dicult to obtain. On the other hand, the availability of software tools to evaluate transportation fuel consumption as well as costs and emissions of carbon dioxide is limited. We developed a software tool that combines two empirically validated models of truck transportation using Digital Elevation Model (DEM) data and an open spatial data tool, specically OpenStreetMap©. The tool generates tabular data and spatial outputs (maps) with information regarding fuel consumption, cost and CO2 emissions for four types of trucks. It also generates maps of the distribution of transport performance indicators (relation between beeline and real road distances). These outputs can be easily included in forest decision-making support systems. Finally, in this work we applied the tool in a particular case of forest logistics in north-eastern Portugal