In diesem Beitrag wird das am Leibniz-Institut für ökologische Raumentwicklung eV. (IÖR) entwickelte Informations- und Entscheidungsunterstützungssystem „Weißeritz-Info“ vorgestellt, das der Aufbereitung und Bereitstellung von Informationen zum Hochwasserrisikomanagement für das Einzugsgebiet der Weißeritz dient. Zielgruppen sind sowohl Bürger und Landnutzer als auch Entscheidungsträger in Kommunen, Behörden und Verbänden. Erstellt wurde das WebGIS-basierte System für die Initiative „Weißeritz-Regio“, einem Verbund von 26 Institutionen, die seit Ende 2003 auf informeller Basis zusammenarbeiten, um die Hochwasservorsorge im Flussgebiet zu verbessern.

Il controllo in agricoltura delle malattie causate da patogeni fungini può essere effettuato attraverso l’uso di modelli di previsione che si basano comunemente sul monitoraggio in tempo reale di una serie di variabili di input. Queste informazioni generalmente combinano dati metereologici locali con modelli matematici costruiti allo scopo di predire il rischio di malattie. Il processo decisionale si attiva quando un avvertimento sul potenziale rischio viene riconosciuto da parte dei modelli. Diversi modelli epidemiologici sono stati sviluppati e validati nel mondo. Negli Stati Uniti d’America, ad esempio, l’università della California ha sviluppato un supporto decisionale on-line per gestire la coltura secondo i principi della lotta integrata (Integrated Pest Management - IPM). Ciascun agricoltore può consultare il proprio database informativo e prendere decisioni sui trattamenti da effettuare basandosi su dati sito-specifici. Le difficoltà sorgono quando non sono disponibili dati meteorologici da stazioni poste nelle vicinanze del sito in studio o per le zone montane caratterizzate da una forte variabilità altimetrica. Inoltre i dati meteorologici disponibili possono presentarsi in formato non adeguato rispetto alle esigenze del modello previsionale. Con l’intento di avere una visione regionale e una maggiore accuratezza nella gestione del controllo delle malattie, l’obiettivo della tesi è stato l’utilizzo contemporaneo di modelli epidemiologici (Lobesia botrana e Erysiphe necator, agente causale dell’oidio della vite) con modelli fenologici (cultivar di vite Chardonnay) utilizzando parametri meteorologici come la temperatura per creare mappe a livello regionale, a frequenza giornaliera e con una risoluzione spaziale di 200 metri. L’utilizzo contemporaneo di entrambi i modelli aiuta ad essere più precisi nel consigliare interventi colturali nel periodo di sensibilità dell’ospite nei confronti del patogeno o della malattia in modo da poterne stimare il reale rischio di diffusione o insorgenza. Dopo aver calibrato e validato i modelli in Trentino-Alto Adige (Nord Italia) con dati metereologici locali, basandoci sul modello del cambiamento climatico HadAM3 dell’Hadley Centre (Pope et al., 2000),l’andamento climatico previsto è stato proiettato e statisticamente portato. in scala, utilizzando lo scenario A2 e B2. L’algoritmo statistico utilizzato per ridurre la scala giornaliera di risoluzione è chiamato “transfer function” (Eccel et al., 2009). Per completare l’analisi, è stato inoltre utilizzato lo scenario ridimensionato di ENSEMBLES attraverso l’uso di set di dati provenienti da 49 stazioni meteorologiche della FEM e dal pacchetto “RMAWGEN” (Cordano et al., 2012) creato con il software statistico R. (Gentleman et al., 1997). Per mappare i modelli è stata sviluppata una semplice piattaforma modulare WEB-GIS chiamata ENVIRO. I moduli sono “Open Source” e seguono gli standard internazionali dell’“Open Geospatial Consortium” (OGC) e sono stati implementati come segue: i) enviDB è il database per i dati spazio-temporali, ii) enviGRID permette agli utenti di navigare attraverso i dati e i modelli nello spazio e nel tempo, iii) enviMapper è l’interfaccia web per prendere le decisioni, consiste in uno stato dell’arte per mappare la vulnerabilità del cambiamento climatico a diverse scale di aggregazione nello spazio e nel tempo, iv) enviModel è l’interfaccia web per i ricercatori a cui viene fornita una piattaforma per processare e condividere modelli di rischio ambientali utilizzando il “web processing Technologies” (WPS) seguendo gli standard OGC. Con l’obiettivo di diventare ancora più accurati nelle previsioni dei volumi per i trattamenti contro insetti e malattie, in accordo con la direttiva 2009/128/EC, il seguente lavoro dimostra che il sensore LIDAR può essere utilizzato per caratterizzare la geometria della pianta della vite e stimare l’area fogliare (LAI) ad ogni stadio di crescita. Inoltre permette di calcolare il volume da applicare (Tree Row Volume -TRV) visualizzato nelle mappe 3D in GRASS. (Neteler et al., 2008, Neteler et al., 2012). / Control of agricultural pests and diseases is often based on forecasting models commonly based on real time monitoring of inputs variables. This information generally combines meteorological local databases and mathematical models designed to forecast pest and disease risk. The decision process starts when an alert or a potential risk event from the outputs of the models is issued. Epidemiological models based on local datasets have been created and validated worldwide, for example in USA, the University of California developed the online Integrated Pest Management (IPM) program where each farmer can consult with his own database and make the pest management decision based on site-specific conditions. Difficulties arise when no data from a close weather station are available, in mountain areas where weather conditions highly depend on the altimetry, or if data are not in a standard format to feed the model. In a view of having a regional vision and an increased accuracy in the pest control management, the goal of this thesis was to run contemporaneously epidemiological (the pest Lobesia botrana and the pathogen causing Powdery mildew Erysiphe necator) and phenological models (grapevine cv. chardonnay) using environmental variables as temperature and to create maps at regional level, with 200 meters of resolution and daily scale or frequency. Running both models together helps to be more precise in the sensibility period of the host versus the pest or the disease and to understand the real final risk. After calibrating and validating the models in the Trentino-Alto Adige Region (Italy) with local weather data, the forecasted climate was projected and statistically downscaled, based on the output of the Hadley Centre climate model - HadAM3 (Pope et al., 2000) under scenarios A2 and B2. The statistical downscaling algorithm was “transfer function method” (Eccel et al., 2009) at daily resolution. In order to complete the analysis, the downscaled scenario from ENSEMBLES was also used with the datasets of 49 weather stations from FEM and the “RMAWGEN” packages (Cordano et al., 2012) created for this project in R statistical open source software (Gentleman et al., 1997). In order to map the models, a friendly modular WEB-GIS platform called ENVIRO was developed. Modules are Open Source, follow international Open Geospatial Consortium (OGC) standards and were implemented as follows: i) enviDB is the database for spatial temporal data, ii) enviGRID allows users to navigate through data and model in space and time, iii) enviMapper is the web interface for decision makers, a state of the art client to map vulnerability to climate change at different aggregation scales in time and space; finally, iv) enviModel is the web interface for researchers that provides a platform to process and share environmental risk models using web geo-processing technologies (WPS) following OGC standards. With the aim of being even more accurate in pests and diseases spraying volumes and according with the Directive 2009/128/EC, the current work shows that the LIDAR sensor can be used to characterize the geometry of the grapevine and the Leaf Area Index (LAI) at each growth stage and calculate the Tree Row Volume (TRV) visualized in 3D maps in GRASS (Neteler et al., 2008, Neteler et al., 2012).

Mit dem Zieljahr 2030 wird ein neuer Regionaler Flächennutzungsplan (RegFNP) für den Ballungsraum FrankfurtRheinMain erstellt. Durch diesen werden für 75 Kommunen im Verbandsgebiet des Regionalverbands FrankfurtRheinMain die Siedlungsentwicklung und Verkehrsinfrastruktur gesteuert sowie der Freiraum gesichert. Für die Neuaufstellung des RegFNP hat der Regionalverband das gesamträumliche Plankonzept „Vorzugsräume Wohnen“ erarbeitet. Dieses zeigt Suchräume für Wohnbauflächenpotenziale an Schienenhaltepunkten und dient damit sowohl der Bewertung von bestehenden Wohnbauflächenpotenzialen sowie als Entscheidungsgrundlage für das Ausweisen neuer Wohnbauflächen. Für die Erfassung der Entwicklungsvorstellungen der Verbandskommunen wurde eine WebGIS-basierte Plattform zur Onlinebeteiligung entwickelt (RegFNP-Viewer). Hier können die Verbandskommunen neue Entwicklungsvorstellungen eintragen und bisher bestehende RegFNP-Darstellungen prüfen. Der Einsatz des RegFNP-Viewers hat zu einer deutlichen Verfahrensbeschleunigung und effizienteren Kommunikation und Abstimmung mit den Verbandskommunen beigetragen. Durch die digitale Erfassung der Entwicklungsvorstellungen war es möglich, die Entwicklungsvorstellungen im Vorfeld von Gesprächen mit allen 75 Verbandskommunen zu sichten und erste Einschätzungen vorzunehmen. Diese wurden genauso wie die aktuelle Planungssituation diskutiert und bilden im nächsten Schritt die Grundlage für einen ersten Planentwurf.

A presente pesquisa propôs o desenvolvimento e a aplicação de um web-GIS interativo alimentado por usuários visando ao mapeamento do risco de inundações por meio da coleta de dados de ameaça, exposição e vulnerabilidade percebidos pela população. Foi também estimado o risco de inundação a partir de uma expressão de indicadores propostos por Mendiondo (2008). As duas metodologias foram aplicadas em sub-bacias urbanas da cidade de São Carlos. Foram realizadas entrevistas com a população da cidade para coletar dados de percepção de risco, enquanto se desenvolvia o web-GIS, para o qual, uma vez terminado, foram transferidos os referidos dados online. O portal se mostrou uma ferramenta de uso simples e confiável. As estimativas de risco calculadas por meio da expressão citada levaram a concluir que as sub-bacias com maior risco de inundação são as dos córregos Tijuco Preto e Medeiros. Entretanto, o risco estimado a partir da análise de percepção evidenciou as sub-bacias Gregório e Santa Maria Madalena como as de maior risco de inundação. As duas ferramentas apresentaram-se valiosas e econômicas para estimativa de risco de inundação em ambiente urbano, podendo constituir ótimos sistemas de apoio à decisão. O webGIS, em particular, é potencialmente útil para informar aos moradores sobre quais são as áreas de risco de inundação na cidade. / This dissertation presents the development and application of an interactive web-GIS in which internet users map flood risk collaboratively by filling up a geotagged form with questions on flood hazard, exposure and vulnerability. Flood risk was also assessed through the use of a set of environmental risk indicators proposed by Mendiondo (2008). The two methodologies were applied to six urban watersheds of the city of São Carlos (State of São Paulo, Brazil). Interviews including questions asked on the web-GIS were carried out in city streets while the portal was being developed. Thus perceived risk data gathered from the interviews was later transferred online onto the web-GIS. The web-GIS proved to be an easy to use and intuitive tool. According to the results of risk calculation obtained with the indicators expression the watersheds with higher flood risk were the Tijuco Preto and Medeiros, which were also the ones with smallest area and higher population density. The results of perceived risk, which was assessed through the analysis of the interviews data, gave evidence that Gregorio and Santa Maria Madalena where the watersheds at higher risk. These watersheds are the two which experience a higher rate of occurrence on a year basis. The two approaches for assessing risk proved to be consistent and relatively inexpensive for the estimate of flood risk in urban areas, with the potential of representing valid decision support systems. The webGIS is a particularly interesting solution as a medium of information to inhabitants on the level of risk to which they are exposed.

A presente pesquisa propôs o desenvolvimento e a aplicação de um web-GIS interativo alimentado por usuários visando ao mapeamento do risco de inundações por meio da coleta de dados de ameaça, exposição e vulnerabilidade percebidos pela população. Foi também estimado o risco de inundação a partir de uma expressão de indicadores propostos por Mendiondo (2008). As duas metodologias foram aplicadas em sub-bacias urbanas da cidade de São Carlos. Foram realizadas entrevistas com a população da cidade para coletar dados de percepção de risco, enquanto se desenvolvia o web-GIS, para o qual, uma vez terminado, foram transferidos os referidos dados online. O portal se mostrou uma ferramenta de uso simples e confiável. As estimativas de risco calculadas por meio da expressão citada levaram a concluir que as sub-bacias com maior risco de inundação são as dos córregos Tijuco Preto e Medeiros. Entretanto, o risco estimado a partir da análise de percepção evidenciou as sub-bacias Gregório e Santa Maria Madalena como as de maior risco de inundação. As duas ferramentas apresentaram-se valiosas e econômicas para estimativa de risco de inundação em ambiente urbano, podendo constituir ótimos sistemas de apoio à decisão. O webGIS, em particular, é potencialmente útil para informar aos moradores sobre quais são as áreas de risco de inundação na cidade. / This dissertation presents the development and application of an interactive web-GIS in which internet users map flood risk collaboratively by filling up a geotagged form with questions on flood hazard, exposure and vulnerability. Flood risk was also assessed through the use of a set of environmental risk indicators proposed by Mendiondo (2008). The two methodologies were applied to six urban watersheds of the city of São Carlos (State of São Paulo, Brazil). Interviews including questions asked on the web-GIS were carried out in city streets while the portal was being developed. Thus perceived risk data gathered from the interviews was later transferred online onto the web-GIS. The web-GIS proved to be an easy to use and intuitive tool. According to the results of risk calculation obtained with the indicators expression the watersheds with higher flood risk were the Tijuco Preto and Medeiros, which were also the ones with smallest area and higher population density. The results of perceived risk, which was assessed through the analysis of the interviews data, gave evidence that Gregorio and Santa Maria Madalena where the watersheds at higher risk. These watersheds are the two which experience a higher rate of occurrence on a year basis. The two approaches for assessing risk proved to be consistent and relatively inexpensive for the estimate of flood risk in urban areas, with the potential of representing valid decision support systems. The webGIS is a particularly interesting solution as a medium of information to inhabitants on the level of risk to which they are exposed.

In diesem Beitrag wird das am Leibniz-Institut für ökologische Raumentwicklung eV. (IÖR) entwickelte Informations- und Entscheidungsunterstützungssystem „Weißeritz-Info“ vorgestellt, das der Aufbereitung und Bereitstellung von Informationen zum Hochwasserrisikomanagement für das Einzugsgebiet der Weißeritz dient. Zielgruppen sind sowohl Bürger und Landnutzer als auch Entscheidungsträger in Kommunen, Behörden und Verbänden. Erstellt wurde das WebGIS-basierte System für die Initiative „Weißeritz-Regio“, einem Verbund von 26 Institutionen, die seit Ende 2003 auf informeller Basis zusammenarbeiten, um die Hochwasservorsorge im Flussgebiet zu verbessern.

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De nos jours, la préservation de l’environnement constitue un enjeu prioritaire. La compréhension des phénomènes environnementaux passe par l’étude et la combinaison d’un nombre croissant de données hétérogènes. De nombreuses initiatives internationales (INSPIRE, GEOSS) visent à encourager le partage et l’échange de ces données. Dans ce sujet de recherche, nous traitons de l’intérêt de mettre à disposition des modèles scientifiques sur le web. Nous montrons l’intérêt d’utiliser des applications s’appuyant sur des données géoréférencées et présentons des méthodes et des moyens répondant aux exigences d’interopérabilité. Nous illustrons notre approche par l’implémentation de modèles d’estimation des besoins en eau agricoles et domestiques fonctionnant à diverses échelles spatiales et temporelles. Un prototype basé sur une architecture entièrement orientée services web a été développé. L’outil s’appuie sur les standards Web Feature Service (WFS), Sensor Observation Service (SOS) et Web Processing Service (WPS) de l’OGC. Enfin, la prise en compte des imperfections des données est également abordée avec l’intégration de méthodes d’analyse de sensibilité et de propagation de l’incertitude. / Nowadays, preservation of the environment is a main priority. Understanding of environmental phenomena requires the study and the combination of an increasing number of heterogeneous data. Several international initiatives (INSPIRE, GEOSS) aims to encourage the sharing and exchange of those data.In this thesis, the interest of making scientific models available on the web is discussed. The value of using applications based on geospatial data is demonstrated. Several methods and means that satisfy the requirements of interoperability are also purposed.Our approach is illustrated by the implementation of models for estimating agricultural and domestic water requirements. Those models can be used at different spatial scales and temporal granularities. A prototype based on a complete web service oriented architecture was developed. The tool is based on the OGC standards Web Feature Service (WFS), Sensor Observation Service (SOS) and Web Processing Service (WPS).Finally, taking into account the imperfections of the data is also discussed with the integration of methods for sensitivity analysis and uncertainty propagation.