The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
SYNTHESYS+(link is external) creates an integrated European infrastructure for natural history collections. Within SYNTHESYS+, subproject NA3.1, led (for GGBN) by ZFMK, performs a landscape analysis of biodiversity and environmental biobanks and their standards and practices, investigates commonalities and differences, and identifies missing standards. Environmental and biodiversity biobanks often follow very similar goals, and many parallels exist among their respective practices. However, the dialogue between the various biobank or repository types is limited. We aim at opening up interfaces by collecting and sharing information on workflows and standard operating procedures.
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
Ziele des Projekts sind es, die Ausformung und den Wandel der historischen Kulturlandschaft in verschiedenen Räumen vergleichend zu rekonstruieren, zu interpretieren und dabei noch erkennbaren Einflüsse menschlicher Landnutzungen zu dokumentieren und soziokulturelle Einflüsse auf Entwicklung der Kulturlandschaft zu erfassen. Ziele des Projekts sind es, im ersten Schritt die Ausformung und den Wandel der historischen Kulturlandschaft in verschiedenen Räumen des Schwarzwaldes sowie im Mittelgebirgsraum Japans vergleichend zu rekonstruieren, zu interpretieren und dabei (noch) erkennbare Einflüsse menschlicher Landnutzungen im Gelände als kulturelles Erbe zu dokumentieren. Durch dieses Projekt soll ein Beitrag zur Erhaltung der Kulturlandschaft und ihrer Elemente geleistet werden. Im zweiten Schritt wird eine Untersuchung der soziokulturellen Bedürfnisse der Bevölkerung und der interessierten Stakeholder in der Kulturlandschaft durchgeführt. Diese beiden Schritte sollen zusammengeführt werden, so dass ausgehend von der gewachsenen Kulturlandschaft Szenarien für die zukünftige Entwicklung der Kulturlandschaft in den Untersuchungsgebieten entwickelt werden können. Als Untersuchungsgebiete der Arbeit werden drei Orte ausgewählt; zwei im Schwarzwald und einer in Japan, zum einen im Schwarzwald das Terrain der Gemeinde Fröhnd im Wiesental (Südschwarzwald) und das Gebiet des Stadtteils Yach im Elztal (mittlerer Schwarzwald), zum anderen das Gebiet der Gemarkung Isarigami der Gemeinde Kami-cho in der Hyogo-Präfektur (Japan). Methodisch sollen diese Zielsetzungen durch eine historisch orientierte Landschaftsanalyse auf der Basis von Geländeaufnahmen mit Unterstützung von historischen Karten und schriftlichen Quellen und durch eine Untersuchung sozio-kultureller Aspekte mit Hilfe von Methoden der empirischen Sozialforschung erreicht werden. Für die Datenverarbeitung der Landschafts-, Literatur- sowie der sozio-kulturellen Analyse wird auf geographische Informationsinstrumente (GIS) zurückgegriffen. Darüber hinaus werden im Rahmen der Dokumentation graphische Darstellungen historisch bedeutsamer Kulturlandschaftselemente (z.B. Weidbuchen, Steinmauer, Terrassen usw.) angefertigt.
Das Typische und die Eigenart einer Landschaft setzen sich aus zwei großen Komponenten zusammen: Auf der einen Seite aus den durch die Landschaftsgenese entstandenen natürlichen Standortfaktoren und zum anderen aus anthropogenen Einflüssen - wie beispielsweise Nutzung, Kultivierung, Pflege. Die Jahrhunderte lange Einwirkung des Menschen auf die Landschaft ist gleichsam ein Spiegelbild gesellschaftlicher, demographischer, politisch-ökonomischer und kultureller Entwicklungen. Das auf einen großen Zeitrahmen festgelegte Forschungsvorhaben soll, neben dem monographisch ausgerichteten Aspekt historischer Landschaftsanalysen, zu folgenden übergeordneten Fragestellungen Ergebnisse liefern: - Determinanten der landschaftlichen Entwicklung, Faktoren bei der Herausbildung regionaler Eigenarten von Kulturlandschaften, - Inventarisierung von Kulturlandschaften, Herausarbeitung historischer Erscheinungen einzelner Kulturlandschaftsepochen, - Erarbeitung regionaler Kulturlandschaftstypen Baden-Württembergs. Bisherige Schwerpunkte im Projekt: Wasserbaugeschichte, Wiesenwässerung, Kulturtechnik, historische Waldwirtschaft, historische Feldwirtschaft. Bisherige räumliche Schwerpunkte: Oberschwaben, Schwäbische Alb, Hotzenwald, Mittlerer Schwarzwald, Südlicher Schwarzwald, Kaiserstuhl. Weiterhin werden Möglichkeiten der Vermittlung von Kenntnissen über Kulturlandschaften erarbeitet. Kooperationspartner hierfür sind die Freilichtmuseen Baden-Württemberg, im Zusammenhang mit historischen Lehrpfaden, bestehen Kooperationen mit der Forstverwaltung und der Denkmalpflege.
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
AUFGABEN und gesetzliche GRUNDLAGEN Das Aufgabenspektrum der Landschaftsrahmenplanung leitet sich aus dem Bundesnaturschutzgesetz ab. Demnach gilt es, die Erfordernisse zur nachhaltigen Sicherung der Leistungsfähigkeit des Naturhaushalts, der Nutzungsfähigkeit der Naturgüter, der Pflanzen- und Tierwelt sowie der Vielfalt, Eigenart und Schönheit von Natur und Landschaft aufzuzeigen - und dies entsprechend der Planungshierarchie auf regionaler Ebene. In Sachsen übernehmen die Regionalpläne zugleich die Funktion der Landschaftsrahmenpläne nach § 4 Abs. 2 SächsLPlG und § 5 Abs. 2 SächsNatSchG. Der Regionalplan ist damit ein Instrument, mit dem gezielt auch landschaftsrahmenplanerische Erfordernisse Verbindlichkeit erlangen. Vor einer Integration landschaftsrahmenplanerischer Erfordernisse müssen zunächst fundierte und in sich schlüssige, unabgewogene Grundlagen der Landschaftsrahmenplanung erarbeitet werden. INHALTE Betrachtungsgegenstand der Landschaftsrahmenplanung sind Natur und Landschaft im unbesiedelten wie im besiedelten Bereich. Um die Komplexität der Landschaft planerisch behandeln zu können, wird untergliedert in * Boden * Klima/Luft * Grund- und Oberflächenwasser * Arten und Biotope * Landschaftserleben/Erholung * Entwicklung der Kulturlandschaft. Auf Grundlage einer Analyse und Bewertung des vorhandenen und zu erwartenden Zustands von Natur und Landschaft erfolgt die Erarbeitung der Ziele und der für ihre Verwirklichung erforderlichen Maßnahmen des Naturschutzes und der Landschaftspflege für den Planungsraum. Darüber hinaus sind Leitbilder für Naturräume und Landschaftseinheiten zu entwickeln. Die Grundlagen und Inhalte der Landschaftsrahmenplanung sind für das Gebiet jeder Planungsregion als Fachbeitrag zusammenhängend darzustellen. Der "Fachbeitrag Naturschutz und Landschaftspflege zum Landschaftsrahmenplan Planungsregion Westsachsen" liegt nunmehr vor. Er kann als CD durch alle Interessierten bei der Regionalen Planungsstelle bezogen werden.
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