Dieser Dienst enthält Daten der Planungsregionen Oberes Elbtal/Osterzgebirge, Region Chemnitz und Oberlausitz-Niederschlesien und deckt im Endausbau den gesamten Freistaat Sachsen ab. Entsprechend des Landesentwicklungsplanes 2013 als fachübergreifendes Gesamtkonzept zur räumlichen Entwicklung, Ordnung und Sicherung des Freistaates Sachsen stellen die Regionalpläne einen verbindlichen Rahmen für die räumliche Entwicklung, Ordnung und Sicherung des Raumes dar. Im Dienst sind regionalplanerische Festlegungen des Komplexes Raumstruktur enthalten. Die rechtsverbindlichen Karten Raumstruktur werden in der Regel in Maßstäben zwischen 1:300.000 und 1:450.000 erstellt. Eine Darstellung der Inhalte der Regionalpläne erfolgt in diesem Dienst nur im Maßstab kleiner 1:10.000.
Inhaltsverzeichnis des Kartenteils der ersten Gesamtfortschreibung des Regionalpla-nes für die Anhörung entsprechend Sächsisches Landesplanungsgesetz (SächsLPlG): Karte 1 Raumnutzung (1:100 000) Karte 2 Siedlungswesen (1:280 000) Karte 3 Raumstruktur (1:280 000) Karte 4 Tourismus (1:280 000) Karte 5 Landschaftsbereiche mit besonderen Nutzungsanforderungen (1:200 000) Karte 6 Sanierungsbedürftige Bereiche der Landschaft (1:200 000) Karte 7 Tierhaltungsstandorte (1:280 000) Karte 8 Bergbauumgang (1:280 000)
Beikarte des Rechtskräftigen Regionales Raumordnungsprogramm des Landkreises Rotenburg (Wümme) in zeichnerischer Darstellung zur Information über die Ermittlung der Vorranggebiete für Windenergienutzung
"Landschaftsrahmenplanung für die Sächsische Schweiz" Natürliche und kulturgeschichtliche Grundlagen in der Sächsischen Schweiz, Heimatschutz, Natur und Landschaftsschutz, Verwaltungsgliederung, Landschaftsanalyse, Biotopkartierung, Flächenutzung, Landschaftsbelastung und Landschaftschäden, Landschaftsdiagnose und Synthese, Raumgliederung, Landschaftsprognose, Leitbilder für die Raumeinheiten, Zielkonzeption
Soil structure determines a large part of the spatial heterogeneity in water storage and fluxes from the plot to the hillslope scale. In recent decades important progress in hydrological research has been achieved by including soil structure in hydrological models. One of the main problems herein remains the difficulty of measuring soil structure and quantifying its influence on hydrological processes. As soil structure is very often of biogenic origin (macropores), the main objective of this project is to use the influence of bioactivity and resulting soil structures to describe and support modelling of hydrological processes at different scales. Therefore, local scale bioactivity will be linked to local infiltration patterns under varying catchment conditions. At hillslope scale, the spatial distribution of bioactivity patterns will be linked to connectivity of subsurface structures to explain subsurface stormflow generation. Then we will apply species distribution modelling of key organisms in order to extrapolate the gained knowledge to the catchment scale. As on one hand, bioactivity influences the hydrological processes, but on the other hand the species distribution also depends on soil moisture contents, including the feedbacks between bioactivity and soil hydrology is pivotal for getting reliable predictions of catchment scale hydrological behavior under land use change and climate change.
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
The project is part of the COST action FP0603 Forest models for research and decision support in sustainable forest management (http://www.cost.esf.org/index.php?id=143&action number=FP0603) which aims at extending the scope of forest models from growth only to population dynamics and ecophysiology. Rationale: For sustainable forest management over large areas and for simulating different forest functions especially under changing conditions, different aspects of the system forest' must be modelled jointly: ecophysiological/biogeochemical processes, population dynamics, spatial interactions, and horizontal/vertical species stand structure. We develop a forest model with a stand-size grain suitable to be applied on large areas for assessment of, e.g., climate change or management effects on forest functions. This is achieved by merging and if necessary up- and down-scaling model functions of ecophysiological and population dynamical processes contained in existing models (single tree physiology, local scale ecophysiological, empirical forest growth, spatio-temporal forest landscape, and dynamic global vegetation models). Drought is predicted to occur more frequently with climate change, thus the main focus is on drought and the mechanisms how it affects the trees. Research questions: What are the mechanisms by which drought affects trees? Which is the best (sufficiently accurate and efficient) way to model and simulate these mechanisms? How can population dynamics and ecophysiology be combined in a landscape scale model concerning - allocation of water and carbohydrates to trees and organs? - spatial heterogeneity of soil water and trees? Methods: The project builds on the climate-driven forest landscape model TreeMig (Lischke et al., 2006). Process descriptions from various existing models are compiled, evaluated and included into TreeMig. This involves a thorough scaling of process formulations. Drought effects, involving soil water balance, stomata regulation, photosynthesis, CO2 fertilization effects, allocation of carbohydrates, dynamics of reserve pools and the relationship between these and regeneration, growth and mortality are studied in literature and other models and included into MEPHYSTO.
Regionaler Entwicklungsplan für die Planungsregion Anhalt-Bitterfeld-Wittenberg mit den Planinhalten „Raumstruktur, Standortpotenziale, technische Infrastruktur und Freiraumstruktur“ Die oberste Landesentwicklungsbehörde hat am 21.12.2018 die Genehmigung unter einer Maßgabe erteilt. Am 29.03.2019 trat die Regionalversammlung mit Beschluss Nr. 03/2019 der Maßgabe bei. Mit Bekanntmachung der Genehmigung trat der Regionale Entwicklungsplan am 27.04.2019 in Kraft.
# Faszination Nächtlicher Vogelzug A web component for visualizing migratory bird detections on an interactive map. Built with React, MapLibre GL, and the BirdWeather GraphQL API. Designed for embedding into CMS platforms like Contao. ## Tech Stack - **React 19** + **TypeScript** (Vite) - **MapLibre GL** -- WebGL map rendering (Stadia Maps dark theme) - **Supercluster** -- per-species spatial clustering - **Apollo Client 4** -- GraphQL data fetching with caching - **GraphQL Code Generation** -- type-safe queries from BirdWeather schema - **SunCalc** -- astronomical day/night calculations - **Tailwind CSS 4** + **Ant Design 6** -- UI - **Vitest** -- testing ## Features - **Interactive map** with color-coded detection clusters per species - **Timeline animation** with autoplay, step controls, and throttled slider - **Night-only mode** that compresses inactive daytime hours using SunCalc sunrise/sunset calculations - **Day/night overlay** showing the terminator (day/night boundary) as a real-time GeoJSON polygon - **Species search** with autocomplete and availability checking per map viewport - **Supplementary layers** (light pollution, noise mapping via WMS) - **Web component** (`<zug-birdnet>`) for CMS embedding without routing ## Project Structure ``` src/ main.tsx Web component registration App.tsx Root component, species selection state api/ fragments.ts GraphQL fragments (DetectionItem, SpeciesItem) queries.ts GraphQL queries (detections, species, search) useDetections.ts Detection fetch hook with prefetching components/ DatesProvider.tsx Time state context (date range, animation, night mode) MapProvider.tsx MapLibre GL instance context SpeciesDropdown.tsx Species selection with search autocomplete Timeline.tsx Date picker, animation slider, playback controls LayersDropdown.tsx Toggle info layers (light pollution, noise) InfoPopup.tsx Map info marker popups map/ Map.tsx MapLibre GL initialization and rendering clusterUtils.ts Per-species Supercluster index creation colorUtils.ts MapLibre paint expression builder mapStyles.ts Map layer definitions usePersistentColors.ts Stable color assignment per species infopoints.ts Static info marker data lib/ apollo-client.ts Apollo Client with cache type policies buildAvailableSpeciesQuery.ts Dynamic aliased query generation getDayPolygon.ts Day/night terminator polygon calculation getTranslatedSpeciesName.ts i18n species name lookup isNotNull.ts, hasNonNullProp.ts Type guard utilities throttle.ts Throttle utility gql/ Auto-generated GraphQL types (do not edit) ``` ## Architecture Three React context providers compose the application: ``` ApolloProvider GraphQL caching and data fetching DatesProvider Date range, animation state, night-only time segments MapProvider MapLibre GL map instance App Species selection, filtered detections, color mapping ``` **Data flow:** Apollo fetches detections for the current bounding box and date range. Detections are filtered client-side by the visualisation time window (controlled by the timeline slider). Each species gets its own Supercluster index for independent color-coded clustering. Cluster features are rendered via MapLibre GL layers with dynamic `match` paint expressions. **GraphQL:** Queries and fragments are defined in `src/api/` and typed via `@graphql-codegen/client-preset`. Run `npm run codegen` after schema changes to regenerate `src/gql/`. ## Development ```sh npm install npm run dev ``` The dev server uses a self-signed SSL certificate via `@vitejs/plugin-basic-ssl`. Accept the browser warning on first visit. Other commands: ```sh npm run build # Production build npm run test # Run tests npm run lint # ESLint npm run codegen # Regenerate GraphQL types ``` ## Build & Integration Run `npm run build` to produce the `dist/` folder. The build outputs stable filenames (no hashes) and splits vendor dependencies into separate chunks for caching: ``` dist/ index.html assets/ index.css App styles (Tailwind + Ant Design) index.js Application code, React, Supercluster, dayjs, SunCalc maplibre.js MapLibre GL antd.js Ant Design + icons apollo.js Apollo Client + graphql ``` Only `index.js` changes on application updates. Vendor chunks are cache-stable between deploys. To embed the web component, include the built CSS and JS, then use the custom element: ```html <link rel="stylesheet" href="/assets/index.css"> <script type="module" src="/assets/index.js"></script> <zug-birdnet></zug-birdnet> ``` No routing. The component is self-contained and can be placed anywhere on the page. Third-party CMS integration (e.g., Contao) only needs to include the built assets and the custom element tag. ## Configuration App-level settings are in `src/config.ts`: | Option | Default | Description | |---|---|---| | `SHOW_DEMO_INFOPOINTS` | `false` | Show static info markers on the map (demo/development only) |
Der Datensatz beinhaltet Daten des LBGR über die Hydrogeologische Raumgliederung Brandenburgs und wird über je einen Darstellungs- und Downloaddienst bereitgestellt. Die Karte gibt einen Überblick zu den hydrogeologischen Raumgliederungen Brandenburgs. Die Gliederungseinheiten tragen den angewandten Charakter von Nutzungsräumen. Sie werden anhand von Wassereinzugsgebieten und Charakteristiken dazugehöriger Grundwasserdynamik beschrieben. Für das Territorium einer hydrogeologischen Einheit werden vergleichbare Grundwasserverhältnisse vorausgesetzt.
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