Lia Duarte

A dynamic map application for the assessment of groundwater vulnerability to pollution

AbstractGroundwater pollution is a major environmental concern at global scale. It usually restricts the use of water resources for domestic, agricultural or industrial purposes, with significant impact on human well-being. Aquifer remediation may be very difficult or even impossible due to technical and/or economic constraints. To help prevent groundwater pollution, several cartographic methods have already been developed. Geographical information systems (GIS) provide useful tools for understanding the spatial distribution of groundwater vulnerability to pollution. This paper presents a new tool to produce groundwater vulnerability to pollution maps under a GIS open source environment. This application was developed within the QGIS software. The tool determines the spatial distribution of the DRASTIC index and incorporates all the procedures required under a single plugin. One of the main advantages of this application is the easiness to use and the possibility of viewing different results modifying indexes, weight values and table descriptions or importing the input data attribute file description. The user can also generate the maps according to his perception regarding each aquifer system. This application is free and presents a valuable contribution to assess and map groundwater vulnerability to pollution through a GIS open source.

Open-source GIS application for UAV photogrammetry based on MicMac

ABSTRACT Remote-sensing applications using the remotely piloted aerial system (RPAS) are becoming more frequent. RPAS is used in different contexts and in several areas, such as environmental studies, cultural heritage, civil engineering, forestry, and cartography. To process the images resulting from the RPAS, different types of image-based 3D modelling software (proprietary or open source) are used. MicMac is an open-source software which allows generating georeferenced information which can be manipulated or visualized under a geographical information system (GIS) environment. So, the integration between the MicMac procedures within a GIS software could be very useful. The main objective of this work was to create an open-source GIS application based on MicMac photogrammetric tools to obtain the orthophotographs, point clouds, and digital surface models. To test the application developed, two distinct areas were considered: one in a more natural environment (Aguda beach near Porto city, Portugal) and another in an urban environment in the city of Coimbra, Portugal. High-resolution data sets were obtained with a ground sampling distance (GSD) of approximately 4.5 cm. Shaded relief image and dense point cloud were generated. This open-source application can be automated and can create all the files required to run the functionalities from MicMac to obtain the georeferenced information, within a GIS software, bringing photogrammetric data generation to a wider user community. Moreover, integrating this application with the GIS software has several advantages like generating more georeferenced information, such as vegetation indices, or even creating the land use land cover map. Creation of shapefiles with the projection centre of the camera, the area covered by each photograph, and taking account of the number of images that appear in each location are also useful in performing certain tasks.

Radio Astronomy Demonstrator: Assessment of the Appropriate Sites through a GIS Open Source Application

In the framework of Portuguese radio astronomical capacitation towards participation in the Square Kilometer Array (SKA) project, a site was selected for radio astronomical testing purposes and the development of a radio astronomical infrastructure. The site is within Herdade da Contenda (HC), a large national forest perimeter, located in Alentejo (Portugal). In order to minimize the impacts in the ecosystem and landscape, an application based on the Geographic Information System (GIS) open source environment was created, the HC Environmental Integrated Management System. This application combines several functionalities and menus with different characterization methods allowing the creation of multiple maps regarding the HC characteristics, such as Digital Elevation Model (DEM), Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), groundwater vulnerability, erosion risk, flood risk and forest fire risk. Other geographical information can be added if necessary (human heritage visualization and fauna and flora). A decision making support tool was also developed. It incorporates an algorithm running through a series of assigned weights and eliminatory factors to find the locations best suited for the infrastructure with minimal impact to the local ecosystem. In order to test the application and the decision making tool, several maps were used as input in order to decide which sites are more adequate. The application developed can be adopted for other protected or natural areas.

QPhenoMetrics: An open source software application to assess vegetation phenology metrics

Abstract Phenology is one of the most reliable indicators of vegetation dynamics. Assessing and monitoring the dynamics of phenology is relevant to support several decisions in order to improve the efficiency of several farming practices. An open source application – QPhenoMetrics - implemented in QGIS software that estimates vegetation phenology metrics is presented, using Earth Observation Systems (EOS) based time-series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) as proxies for phenology. QPhenoMetrics is characterized by freely-usable and updatable code, acceptance of satellite images or text formats, time-series analysis toolbox allowing the selection of region of interest with statistical quality assessment for Vegetation Indices (VI), and estimation of ensemble metrics. The application is structured in three components: (i) input data; (ii) pre-processing of the VI time-series and several fitting methods and (iii) computation of the phenological metrics. QPhenoMetrics produces a plot with the VI time-series and corresponding phenology metrics, and a spreadsheet is created with a list of NDVI or EVI values estimated using the selected fitting method. To evaluate the application, two main Portuguese crops, vineyards and maize, and MOD13 data from MODIS sensor during 2011–2012 were considered. QPhenoMetrics was validated with vineyard phenology observations (2007–2011). A comparative analysis with software products TimeSat and Spirits was also performed. It was concluded that QPhenoMetrics can be very useful for common users to extract phenology information for 16 daily MODIS data in HDF format, text files with NDVI/EVI data and ASCII files, through a simple and intuitive graphic interface. Furthermore, the user can evaluate the quality assessment of VI of the images used. QPhenoMetrics is an effective open source tool that in addition to being free, is readily modifiable by user according to the study requirements.

Deriving phenological metrics from NDVI through an open source tool developed in QGIS

Vegetation indices have been commonly used over the past 30 years for studying vegetation characteristics using images collected by remote sensing satellites. One of the most commonly used is the Normalized Difference Vegetation Index (NDVI). The various stages that green vegetation undergoes during a complete growing season can be summarized through time-series analysis of NDVI data. The analysis of such time-series allow for extracting key phenological variables or metrics of a particular season. These characteristics may not necessarily correspond directly to conventional, ground-based phenological events, but do provide indications of ecosystem dynamics. A complete list of the phenological metrics that can be extracted from smoothed, time-series NDVI data is available in the USGS online resources (http://phenology.cr.usgs.gov/methods_deriving.php).This work aims to develop an open source application to automatically extract these phenological metrics from a set of satellite input data. The main advantage of QGIS for this specific application relies on the easiness and quickness in developing new plug-ins, using Python language, based on the experience of the research group in other related works. QGIS has its own application programming interface (API) with functionalities and programs to develop new features. The toolbar developed for this application was implemented using the plug-in NDVIToolbar.py. The user introduces the raster files as input and obtains a plot and a report with the metrics. The report includes the following eight metrics: SOST (Start Of Season – Time) corresponding to the day of the year identified as having a consistent upward trend in the NDVI time series; SOSN (Start Of Season – NDVI) corresponding to the NDVI value associated with SOST; EOST (End of Season – Time) which corresponds to the day of year identified at the end of a consistent downward trend in the NDVI time series; EOSN (End of Season – NDVI) corresponding to the NDVI value associated with EOST; MAXN (Maximum NDVI) which corresponds to the maximum NDVI value; MAXT (Time of Maximum) which is the day associated with MAXN; DUR (Duration) defined as the number of days between SOST and EOST; and AMP (Amplitude) which is the difference between MAXN and SOSN. This application provides all these metrics in a single step. Initially, the data points are interpolated using a moving average graphic with five and three points. The eight metrics previously described are then obtained from the spline using numpy functions. In the present work, the developed toolbar was applied to MODerate resolution Imaging Spectroradiometer (MODIS) data covering a particular region of Portugal, which can be generally applied to other satellite data and study area. The code is open and can be modified according to the user requirements. Other advantage in publishing the plug-ins and the application code is the possibility of other users to improve this application.

Correlation between the habitats productivity and species richness (amphibians and reptiles) in Portugal, through remote sensed data

Several biogeographic theories propose that the species richness depends on the structure and ecosystems diversity. The habitat productivity, a surrogate for these variables, can be evaluated through satellite imagery, namely using vegetation indexes (e.g. NDVI). We analyzed the correlation between species richness (from the Portuguese Atlas of Amphibians and Reptiles) and NDVI (from Landsat, MODIS, and Vegetation images). The species richness database contains more than 80000 records, collected from bibliographic sources (at 1 or 10 km of spatial resolution) and fieldwork sampling stations (recorded with GPS devices). Several study areas were chosen for Landsat images (three subsets), and all Portugal for MODIS and Vegetation images. The Landsat subareas had different climatic and habitat characteristics, located in the north, center and south of Portugal. Different species richness datasets were used depending on the image spatial resolution: data with metric resolution were used for Landsat, and with 1 km resolution, for MODIS and Vegetation images. The NDVI indexes and all the images were calculated/processed in an open source software (Quantum GIS). Several plug-ins were applied in order to automatize several procedures. We did not find any correlation between the species richness of amphibians and reptiles (not even after separating both groups by species of Atlantic and Mediterranean affinity) and the NDVI calculated with Landsat, MODIS and Vegetation images. Our results may fail to find a relationship because as the species richness is not correlated with only one variable (NDVI), and thus other environmental variables must be considered.

Remote Sensing in Human Health: A 10-Year Bibliometric Analysis

A mixed methods bibliometric analysis was performed to ascertain the characteristic of scientific literature published in a 10-year period (2007–2016) regarding the application of remote sensing data in human health. A search was performed on the Scopus database, followed by manual revision using synthesis studies’ techniques, requiring the authors to sort through more than 8000 medical concepts to create the query, and to manually select relevant papers from over 2000 documents. From the initial 2752 papers identified, 520 articles were selected for analysis, showing that the United States ranked first, with a total of 250 (48.1% of the total) documents, followed by France and the United Kingdom, with 67 (12.9% of the total) and 54 (10.4% of the total) documents, respectively. When considering authorship, the top three authors were Vounatsou P (22 articles), Utzinger J (19 articles), and Vignolles C (13 articles). Regarding disease-specific keywords, malaria, dengue, and schistosomiasis were the most frequent keywords, occurring 142, 34, and 24 times, respectively. For some infectious diseases and other highly pathogenic or emerging infectious diseases, remote sensing has become a very powerful instrument. Also, several studies relate different environmental factors retrieved by remote sensing data with other diseases, such as asthma exacerbations. Health-related remote sensing publications are increasing and this paper highlights the importance of these related technologies toward better information and, ideally, better provision of healthcare. On the other hand, this paper provides an overall picture of the state of the research regarding the application of remote sensing data in human health and identifies the most active stakeholders e.g., authors and institutions in the field, informing possible new collaboration research groups.

An integrated and open source GIS environmental management system for a protected area in the south of Portugal

Herdade da Contenda (HC), located in Moura municipality, Beja district (Alentejo province) in the south of Portugal (southwestern Iberia Peninsula), is a national hunting area with 5270ha. The development of an integrated system that aims to make the management of the natural and cultural heritage resources will be very useful for an effective management of this area. This integrated system should include the physical characterization of the territory, natural conservation, land use and land management themes, as well the cultural heritage resources. This paper presents a new tool for an integrated environmental management system of the HC, which aims to produce maps under a GIS open source environment (QGIS). The application is composed by a single button which opens a window. The window is composed by twelve menus (File, DRASTIC, Forest Fire Risk, Revised Universal Soil Loss Equation (RUSLE), Bioclimatic Index, Cultural Heritage, Fauna and Flora, Ortofoto, Normalizes Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), Land Use Land Cover Cover (LULC) and Help. Several inputs are requires to generate these maps, e.g. DEM, geologic information, soil map, hydraulic conductivity information, LULC map, vulnerability and economic information, NDVI. Six buttons were added to the toolbar which allows to manipulate the information in the map canvas: Zoom in, Zoom out, Pan, Print/Layout and Clear. This integrated and open source GIS environment management system was developed for the HC area, but could be easily adapted to other natural or protected area. Despite the lack of data, the methodology presented fulfills the objectives.

Assessing Groundwater Vulnerability to Pollution through the DRASTIC Method

Groundwater pollution is a constant concern. Geographical Information Systems (GIS) provide useful tools to manipulate the variables that can be used prevent/minimize these issues. This article presents the development of a tool to produce maps under a GIS open source environment. The application was developed through Quantum GIS (QGIS) software. The tool is developed based on DRASTIC method and incorporates some procedures under a plugin. The Drastic method comprises several steps and several maps: Depth to groundwater (D), Net Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of Vadose Zone (I) and Hydraulic Conductivity (C). These maps are produced according to indexes defined by Aller et al (1987), [2]. One of the main advantage of this application is the easiness to use. The user can generate the maps according to his perception regarding field conditions. The application is free for the institution or user and presents a great contribution to predict the intrinsic vulnerability pollution through GIS open source.

Remote sensing and GIS combination to evaluate the ecosystems' conditions in "Serras do Porto"

Forests are dynamic, complex and multidimensional ecosystems and play an irreplaceable role in social, economic, environmental, ecological and cultural context. Eucalyptus is the most common exotic species in Portugal forests. This species is fundamental in the industries related to the pulp paper production and the concern about their effects in ecosystems is growing. Geographical Information Systems (GIS) combined with Remote Sensing (RS) data can help to understand this complex ecosystem. Moreover, GIS and RS are commonly used in forest management. GIS allows the manipulation, analysis, and generation of considerable amounts of environmental information. This information can be used in the evaluation of ecosystems’ conditions and for decision making. The study case of this project was the municipal lands included in “Serras do Porto” and Valongo’s Nature 2000 network (Porto district, Portugal). The study zone considered in this work is a landscape of extreme relevance to Porto Metropolitan Area. For decades this area was extensively explored with eucalyptus plantations in order to produce cellulose for paper industry. Due to the characteristics of the area and its extension (40 hectares) the use of GIS became the most accurate and reliable alternative to characterize it. The combination of GIS tools and RS data allows the characterization of terrain relief, namely the analysis of altimetry, hypsometry, hydrography, the creation of environmental indexes such as Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Normalized Difference Water Index (NDWI), and the Digital Elevation Model (DEM). RS technology offer the potential to explore the effects of land-use changes and disturbances on forest dynamics at large spatial scales. A Sentinel-2A image was used to produce NDVI, EVI, and NDWI environmental indexes and to generate the Land Use Land Cover (LULC) map, through Semi-Automatic Classification Plugin from QGIS software using Minimum Distance algorithm. The LULC was classified with two classes because the study area only presents two types of species: eucalyptus and bare soil. The LULC map obtained was validated through field points collected in the study area with a GPS receptor. An overall accuracy of 92.98% and a kappa statistic of 0.842 was obtained. Also, some of the geographic information obtained in the field was then integrated in QGIS software. Moreover, a phenological study was performed using NDVI values obtained from Sentinel-2A images, to understand the eucalyptus behavior in a certain period of time.. Because of that RS data provided useful information about the landscape dynamics allowing the assess to forest cover change and land use helping to create decision making plans and forest conservation measures.