Das Projekt "Initiative Grün in der Stadt - Studie zum Projekt 'Bundeswettbewerb Grün in der Stadtentwicklung'" wird/wurde gefördert durch: Bundesinstitut für Bau-, Stadt- und Raumforschung (BBSR). Es wird/wurde ausgeführt durch: Deutsche Gartenbau-Gesellschaft 1822 e.V..Grün- und Weißbuch Stadtgrün des Bundes stellen die Bedeutung urbaner Grün- und Freiflächen für die Lebensqualität der Stadtbewohnerinnen und -bewohner und für die Attraktivität einer Kommune als Wohn- und Wirtschaftsstandort komplex dar. In Fortentwicklung der Stadtgrün-Strategie des Bundes wurde eine Studie zum Projekt 'Bundeswettbewerb Grün in der Stadtentwicklung' beauftragt. Ziel ist es, einen Wettbewerb zu konzipieren, der gelungene Beispiele, innovative Konzepte, integrierte Planungsansätze und vernetzende Ideen zur Sicherung und Qualifizierung von öffentlichen Grün- und Freiflächen öffentlichkeitswirksam hervorhebt. Ausgangslage: Mit der zunehmenden Urbanisierung gelangt die Infrastruktur vieler Städte an ihre Kapazitätsgrenze. In kleineren Städten gibt es umgekehrt Abwanderungstendenzen. Die größeren Städte müssen darum ressourceneffizienter werden und die kleineren Städte insgesamt attraktiver. Ein bewusster Umgang mit der Stadt als grünem, vielseitig nutzbarem Lebensraum mit Synergie-Effekten für Menschen, Flora, Fauna und Umwelt wird immer dringlicher. Das Stadtgrün mit seinen vielschichtigen Dimensionen erfüllt schon jetzt vielfältige Aufgaben: Krankenhausgärten öffnen sich als Naherholungsraum für die Anrainer, Green-Gym-Angebote in den Grünanlagen dienen gleichermaßen der Gesundheit und der Parkpflege und die Dächer unserer Städte bieten Raum für Spielplätze, Urban Farms oder artenreiche Wiesen. Die Tendenz geht allgemein dahin, bei der Entwicklung innovativer Ideen im Zusammenhang mit Stadtgrün viele Akteure einzubinden und lokale Bündnisse zu bilden. Die städtische Gesellschaft, grüne Start-ups, Verbände, Interessengruppen und Kommunen bilden ein breites Bündnis für eine lebenswerte, vielfältige und grüne Stadt. Vielerorts widmen sich die verschiedenen Gruppierungen bereits auf unterschiedliche Weise den Themen Gesundheit, Klimawandel, Smart City, bezahlbarer Wohnraum, Barrierefreiheit, kulturelle Vielfalt sowie Integration im Kontext des Stadtgrüns. Das Grünbuch Stadtgrün des Bundes legt diese Themen und Trends der Stadtentwicklung detailliert dar. Darauf aufbauend wurde das Weißbuch 'Stadtgrün' erarbeitet. Es enthält konkrete Maßnahmen und Handlungsempfehlungen des Bundes, wie der die Kommunen dabei unterstützen kann, Grün- und Freiräume zu sichern und zu qualifizieren. Eine Maßnahme ist ein zu entwickelnder Wettbewerb, der die gesellschaftlichen Aufgaben des Stadtgrüns für die Stadtbewohnerinnen und -bewohner verdeutlicht, nachahmenswerte Beispiele herausstellt und Impulse für die zukünftige Stadtentwicklung gibt.
Das Projekt "Bauen im laendlichen Raum" wird/wurde ausgeführt durch: Technische Universität Darmstadt, Fachgebiet Entwerfen und Gebäudekunde.Ueberall in Europa sind die historischen Doerfer und laendlichen Siedlungen, die - eingebunden in ihre Umgebung - seit Jahrhunderten die Landschaften gepraegt und unverwechselbar gemacht haben, in ihrer Urspruenglichkeit von vielfaeltigen Einfluessen bedroht. Es sind dies im wesentlichen folgende: 1. Fortschreitende Rationalisierungsmassnahmen der Landwirtschaft, 2. Schaffung neuer Arbeitsplaetze im laendlichen Raum durch Ansiedlung von Gewerbe und Industrie, 3. Erschliessung des laendlichen Raumes fuer den Tourismus, 4. anhaltende Landflucht in abgelegenen Gebieten wegen mangelnder Arbeitsmoeglichkeiten und unvollstaendiger Infrastruktur, 5. Verstaedterung des laendlichen Raumes in Gebieten, die in der Naehe von Ballungsraeumen liegen. Die Arbeit versucht, die typischen Merkmale, die die Qualitaet des Lebens und Bauens auf dem Lande gepraegt haben, zu analysieren und in einpraegsamer Form darzustellen. Aufgrund dieser Analysen sollen praktische Vorschlaege erarbeitet werden, in welcher Form laendliche Bausubstanz erhalten, wiederhergestellt, revitalisiert und sinnvoll ergaenzt werden kann.
Das Projekt "Statt Landschaft Stadtlandschaft: Kölns Tierleben" wird/wurde gefördert durch: Stadt Köln, Grünflächenamt. Es wird/wurde ausgeführt durch: Universität Köln, Institut für Zoologie, Biozentrum Köln, Arbeitsgruppe Allgemeine Ökologie.In Köln wird seit 1989 ein breites Spektrum von zur Zeit 49 Wirbellosengruppen (Insekten, Spinnen und Mollusken) sowie der gebietsfremden, eingeschleppten Tierarten oder Neozoen unter Beteiligung von 51 Wissenschaftlern untersucht. Betrachtet man Biodiversitätin seiner einfachsten Form, dem Artenreichtum, dann ist Köln mit mehr als 5500 registrierten Tierarten die zur Zeit bestuntersuchte und artenreichste Großstadt. Die Bewertung der untersuchten Stadtbiotope stützt sich dabei nicht allein auf die zahlreich nachgewiesenen 'Rote-Liste'-Arten, die für die Wissenschaft neu entdeckten Tierarten oder den Umfang des Artenspektrums. In aktuellen Untersuchungen (Huckenbeck und Wipking) erweisen sich Laufkäfer (Carabidae) als geeignete Instrumente, wenn wichtige Lebenszyklus-Komponenten bei innerstädtischen Populationen mit solchen aus naturnahen Habitaten am Stadtrand verglichen werden sollen, um Biotopinseln in der Innenstadt als 'Quellstrukturen' für die Überlebensfähigkeit von Tierarten zu beurteilen und zum Ziel von (Natur-)Schutzbem ühungen in den flächenhaft immer stärker expandierenden Stadtlandschaften zu machen.
The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.
The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.
Das Projekt "Aufwertung lokaler Märkte durch Nutzung biogener Reststoffe" wird/wurde ausgeführt durch: Hochschule für Forstwirtschaft Rottenburg, Institut für angewandte Forschung.
The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.
The World Settlement Footprint (WSF) 2019 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2019 multitemporal Sentinel-1 (S1) and Sentinel-2 (S2) imagery. Based on the hypothesis that settlements generally show a more stable behavior with respect to most land-cover classes, temporal statistics are calculated for both S1- and S2-based indices. In particular, a comprehensive analysis has been performed by exploiting a number of reference building outlines to identify the most suitable set of temporal features (ultimately including 6 from S1 and 25 from S2). Training points for the settlement and non-settlement class are then generated by thresholding specific features, which varies depending on the 30 climate types of the well-established Köppen Geiger scheme. Next, binary classification based on Random Forest is applied and, finally, a dedicated post-processing is performed where ancillary datasets are employed to further reduce omission and commission errors. Here, the whole classification process has been entirely carried out within the Google Earth Engine platform. To assess the high accuracy and reliability of the WSF2019, two independent crowd-sourcing-based validation exercises have been carried out with the support of Google and Mapswipe, respectively, where overall 1M reference labels have been collected based photointerpretation of very high-resolution optical imagery. Starting backwards from the year 2015 - for which the WSF2015 is used as a reference - settlement and non-settlement training samples for the given target year t are iteratively extracted by applying morphological filtering to the settlement mask derived for the year t+1, as well as excluding potentially mislabeled samples by adaptively thresholding the temporal mean NDBI, MNDWI and NDVI. Finally, binary Random Forest classification in performed. To quantitatively assess the high accuracy and reliability of the dataset, an extensive campaign based on crowdsourcing photointerpretation of very high-resolution airborne and satellite historical imagery has been performed with the support of Google. In particular, for the years 1990, 1995, 2000, 2005, 2010 and 2015, ~200K reference cells of 30x30m size distributed over 100 sites around the world have been labelled, hence summing up to overall ~1.2M validation samples. It is worth noting that past Landsat-5/7 availability considerably varies across the world and over time. Independently from the implemented approach, this might then result in a lower quality of the final product where few/no scenes have been collected. Accordingly, to provide the users with a suitable and intuitive measure that accounts for the goodness of the Landsat imagery, we conceived the Input Data Consistency (IDC) score, which ranges from 6 to 1 with: 6) very good; 5) good; 4) fair; 3) moderate; 2) low; 1) very low. The IDC score is available on a yearly basis between 1985 and 2015 and supports a proper interpretation of the WSF evolution product. The WSF evolution and IDC score datasets are organized in 5138 GeoTIFF files (EPSG4326 projection) each one referring to a portion of 2x2 degree size (~222x222km) on the ground. WSF evolution values range between 1985 and 2015 corresponding to the estimated year of settlement detection, whereas 0 is no data. A comprehensive publication with all technical details and accuracy figures is currently being finalized. For the time being, please refer to Marconcini et al,. 2021.
The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.
The World Settlement Footprint (WSF) 2019 is a 10m resolution binary mask outlining the extent of human settlements globally derived by means of 2019 multitemporal Sentinel-1 (S1) and Sentinel-2 (S2) imagery. Based on the hypothesis that settlements generally show a more stable behavior with respect to most land-cover classes, temporal statistics are calculated for both S1- and S2-based indices. In particular, a comprehensive analysis has been performed by exploiting a number of reference building outlines to identify the most suitable set of temporal features (ultimately including 6 from S1 and 25 from S2). Training points for the settlement and non-settlement class are then generated by thresholding specific features, which varies depending on the 30 climate types of the well-established Köppen Geiger scheme. Next, binary classification based on Random Forest is applied and, finally, a dedicated post-processing is performed where ancillary datasets are employed to further reduce omission and commission errors. Here, the whole classification process has been entirely carried out within the Google Earth Engine platform. To assess the high accuracy and reliability of the WSF2019, two independent crowd-sourcing-based validation exercises have been carried out with the support of Google and Mapswipe, respectively, where overall 1M reference labels have been collected based photointerpretation of very high-resolution optical imagery.
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