Get key insights from Market Research Intellect's Digital Map Software Market Report, valued at USD 5.2 billion in 2024, and forecast to grow to USD 10.2 billion by 2033, with a CAGR of 8.5% (2026-2033).

La Cartografía de Andalucía para Móviles consiste en una compilación de mapas y ortofotos de 34 ámbitos comarcales y espacios naturales protegidos de Andalucía, en un formato que permite su explotación por OruxMaps, el visor de mapas offline para Android más extendido en España entre senderistas y actividades en el medio rural.

Uncover Market Research Intellect's latest Heatmap And Session Recording Software Market Report, valued at USD 1.2 billion in 2024, expected to rise to USD 3.5 billion by 2033 at a CAGR of 15.6% from 2026 to 2033.

The Unpublished Digital Geologic-GIS Map of Parts of Great Sand Dunes National Park and Preserve (Sangre de Cristo Mountains and part of the Dunes), Colorado is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (gsam_geology.gdb), a 10.1 ArcMap (.mxd) map document (gsam_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (grsa_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (grsa_geology_gis_readme.pdf). Please read the grsa_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). The data is also available as a 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. Google Earth software is available for free at: http://www.google.com/earth/index.html. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gsam_geology_metadata.txt or gsam_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 13N, however, for the KML/KMZ format the data is projected upon export to WGS84 Geographic, the native coordinate system used by Google Earth. The data is within the area of interest of Great Sand Dunes National Park and Preserve.

Neste estudo, foram buscadas as principais formas de delimitação microrregional da porção norte do litoral do estado do Rio Grande do Sul. As áreas encontradas foram as seguintes: AMLINORTE: Associação dos Municípios do Litoral Norte; AULINORTE: Aglomeração Urbana do Litoral Norte; CBHT: Comitê da Bacia Hidrográfica do Rio Tramandaí; CODETER Litoral RS: Colegiado de Desenvolvimento Territorial Litoral RS; COREDE Litoral: Conselho Regional de Desenvolvimento Litoral; CRE11: Coordenadoria Regional de Educação Osório; CRS18: Coordenadoria Regional de Saúde Osório; IBGE_MI: Microrregião de Osório; e RF4: Região Funcional de Planejamento 4. Com base nos limites dos municípios do Rio Grande do Sul, obtidos na Malha Municipal de 2020 do IBGE e das diversas fontes de regionalização, foi gerada uma camada no software QGIS 3.16, na qual foram inseridos atributos relativos a cada região em cada município, sendo designado 1 ou 0, se o município faz parte ou não da região em questão, respectivamente. Em seguida, por meio dos atributos preenchidos, foi possível gerar outra camada, com o contorno referente a cada região. As camadas de municípios e contornos foram exportadas para os formatos GeoPackage, KML e Shapefile. Todos arquivos geoespaciais estão referenciados ao sistema geodésico SIRGAS2000, na projeção UTM 22S. A partir das camadas vetoriais, no software ArcGIS Pro 2.3, foram elaborados mapas para cada uma das regiões. Os mapas foram salvos como figuras no formato PNG e estão otimizadas para o tamanho 16 cm por 20 cm. Além das figuras e vetores, estão disponíveis arquivos do tipo tabela, nos quais constam a relação de municípios, as delimitações em que estão inseridos e informações acerca da origem destas microrregiões.

These maps are georeferenced versions of the maps produced by The University Museum, University of Pennsylvania, project at Tikal, Guatemala and published as Tikal Report 11. These georeferenced maps are intended for use with GIS (Geographic Information System) software. The maps should be useful for archaeologists, tourists and managers of Tikal National Park. This map set consists of eleven georeferenced maps. The set includes two versions of the overview map of the central sixteen square kilometers of Tikal—the "Ruins of Tikal" map. One version includes the map border. The other version is without the border. The nine remaining maps cover the inner nine square kilometers in detail, without borders. The maps were georeferenced as part of a University of Cincinnati project in Tikal, under permit of the Guatemalan government. The UC Project georeferenced the maps using land survey methods. We created transformation equations based on a point of beginning, a reference direction and a map scale. Directions and distances on the ground were transformed into UTM projected directions and distances. The point of beginning was the Petty Company benchmark shown on the "Camp Quad" map. In 2010 we determined the location with a GPS receiver. We accessed both the horizontal and vertical accuracy of the georeferenced maps. Based on 96 test points spread throughout the area of the maps, we found the median horizontal accuracy of the maps, compared to GPS, to be 5.6 meters. Based on 103 test points spread throughout the area of the maps, we found the median vertical accuracy of the maps, compared to a NASA radar altimetry mission, to be 2.1 meters. The borders of the maps were removed so the set of maps will “seamlessly” fit together in GIS. See Tikal Report No.11 for versions of the maps with borders (one version of the georeferenced "Ruins of Tikal" map includes the border). The georeferencing files are optimized for use in ArcGIS version 9.2 and beyond. The PDF file of TR11 from which these maps were extracted was made with the generous assistance of the University Museum Library and the Tikal Archives. Details of the georeferencing and accuracy check are in a report to the Dirección Patrimonio Cultural y Natural de Guatemala: Christopher Carr, Eric Weaver, Nicholas Dunning, and Vernon Scarborough (2011) EVALUACIÓN DE LA EXACTITUD DE LOS MAPAS DE TIKAL DE LA UNIVERSIDAD DE PENNSYLVANIA, POR GPS Y ESTACIÓN TOTAL (Accuracy assessment of the Penn Project maps of Tikal, by GPS and Total Station). In Lentz, D., C. Ramos, N. Dunning, V. Scarborough and L. Grazioso. PROYECTO DE SILVICULTURA Y MANEJO DE AGUAS DE LOS ANTIGUOS MAYAS DE TIKAL. Additional details of the strategies the Penn Project used to produce these high quality maps, the georeferencing methodology, and the accuracy check process are forthcoming in a book chapter. The book is on the UC project at Tikal, to be published by Cambridge University Press. The chapter is Carr, Weaver, Dunning and Scarborough. Bringing the University of Pennsylvania maps of Tikal into the era of electronic GIS. In Lentz, Dunning, Scarborough (eds). Tikal and Maya Ecology: Water, Landscapes and Resilience. Permission to publish these maps must be secured from: The University of Pennsylvania Museum of Archaeology and Anthropology, 3260 South Street, Philadelphia, PA 19104, Tel: (215) 898-4050, Fax: (215) 573-9369, Email: publications@pennmuseum.org. .................................................................................................................. Estos mapas son versiones georeferenciados de los mapas producidos por el Museo Universitario de la Universidad de Pennsylvania, Proyecto Tikal, Guatemala y publicado como Informe de Tikal No. 11. La intensión de estos mapas georeferenciados es para ser utilizados con el Sistema de Información Geográfica (SIG). Los mapas deben ser útiles para los arqueólogos, los turistas y los administradores del Parque Nacional Tikal. Este conjunto de mapas consta de once mapas georreferenciados. El juego incluye dos versiones del mapa general de los 16 km2 centrales del mapa de las "Ruins of Tikal". Una versión del mapa incluye sus encuadrados. La otra versión esta sin los encuadrados. Los nueve mapas restantes cubren los mapas interiores de 9 km2 en detalle, sin encuadrados. Los mapas fueron georeferenciados como parte de un proyecto de la Universidad de Cincinnati en Tikal, con permiso del Ministerio de Cultura y Deportes del Gobierno de Guatemala. El Proyecto de la Universidad de Cincinnati georeferenció los mapas utilizando métodos de reconocimiento de campo. Creamos ecuaciones de transformación basado en un punto de inicio, una dirección de referencia y un mapa a escala. Direcciones y distancias en el campo se transformaron en direcciones proyectadas UTM y distancias. El punto de inicio fue el punto de refere... Visit https://dataone.org/datasets/doi%3A10.6067%3AXCV8ST7QQN_meta%24v%3D1377891297095 for complete metadata about this dataset.

Visualização do Borel em 3DEste aplicativo oferece a visualização do Borel em três dimensões executada com o software City Engine, através das bases cartográficas na escala de 1:500 do ano 2009.Nessa aplicação é possível observar, sobre uma ortofoto modelada de acordo com o terreno da comunidade, as suas edificações classificadas segundo o uso (Residencial, Público, Comercial, Misto e Religioso), além das árvores e postes localizados no interior do Borel. Ao clicar em cima de cada edificação o usuário visualiza informações básicas sobre a mesma, incluindo o nome de diversos estabelecimentos, como o "INSTITUTO CIDADANIA UNIDOS DA TIJUCA", o "BAR DO BICÃO", o "CENTRO CULTURAL RODA VIVA" e a "ASSOCIAÇÃO DE MORADORES DO BOREL".Além disso, é possível buscar por elementos no mapa e até alterar a posição do sol de acordo com a hora do dia e mês. Por fim, nessa mesma janela o usuário poderá exportar uma imagem em alta resolução da tela sendo visualizada no momento.

The Digital Geologic-GIS Map of Canyon de Chelly National Monument and Vicinity, Arizona and New Mexico is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (cach_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (cach_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (cach_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (cach_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (cach_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (cach_geology_metadata_faq.pdf). Please read the cach_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (cach_geology_metadata.txt or cach_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:250,000 and United States National Map Accuracy Standards features are within (horizontally) 127 meters or 416.7 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

We have developed a utility to both stitch cube maps into other types of texture maps (equirectangular, dual paraboloid, and octahedral), and stitch those other types back into cube maps. The utility allows for flexibility in the image size of the conversion - the user can specify the desired image width, and the height is computed (cube, paraboloid, and octahedral mappings are square, and spherical maps are generated to have 16:9 aspect ratio). Moreover, the utility is sampling-agnostic, so the user can select whether to use uniform or jittered sampling over the pixels, as well as the number of samples to use per pixel. The rest of this paper discusses the mathematical framework for projecting from cube maps to equirectangular, dual paraboloid, and octahedral environment maps, as well as the mathematical framework for the inverse projections. We also describe two sampling techniques: uniform sampling and correlated multi-jittered sampling. We perform an evaluation of the sampling techniques and a comparative analysis of the different projections using objective image quality assessment metrics.

The recent enhanced sophistication of non-invasive mapping of the human motor cortex using MRI-guided Transcranial Magnetic Stimulation (TMS) techniques, has not been matched by refinement of methods for generating maps from motor evoked potential (MEP) data, or in quantifying map features. This is despite continued interest in understanding cortical reorganization for natural adaptive processes such as skill learning, or in the case of motor recovery, such as after lesion affecting the corticospinal system. With the observation that TMS-MEP map calculation and quantification methods vary, and that no readily available commercial or free software exists, we sought to establish and make freely available a comprehensive software package that advances existing methods, and could be helpful to scientists and clinician-researchers. Therefore, we developed NeuroMeasure, an open source interactive software application for the analysis of TMS motor cortex mapping data collected from Nexstim® and BrainSight®, two commonly used neuronavigation platforms. NeuroMeasure features four key innovations designed to improve motor mapping analysis: de-dimensionalization of the mapping data, fitting a predictive model, reporting measurements to characterize the motor map, and comparing those measurements between datasets. This software provides a powerful and easy to use workflow for characterizing and comparing motor maps generated with neuronavigated TMS. The software can be downloaded on our github page: https://github.com/EdwardsLabNeuroSci/NeuroMeasureAimThis paper aims to describe a software platform for quantifying and comparing maps of the human primary motor cortex, using neuronavigated transcranial magnetic stimulation, for the purpose of studying brain plasticity in health and disease.

Para obter as imagens em alta resolução basta acessar através do software de sua preferência nosso serviço de Web Map Service (WMS) utilizando-se do link: http://geoserver.dados.al.gov.br:8080/geoserver/Alagoas/ows?

La elaboración de mapas estratégicos de ruido se enmarca en los siguientes textos, que especifican, entre otras cosas, los métodos de cálculo, los indicadores que deben utilizarse y los resultados esperados: — Los artículos L.572-1 a L.572-11 del Código de Medio Ambiente, relativos a la elaboración de mapas de ruido y planes para la prevención del ruido ambiental y la modificación del código urbanístico; — Artículos R.572-1 a R.572-11 sobre la elaboración de mapas de ruido y planes de prevención del ruido ambiental y la modificación del código de planificación urbana; — sus decretos de aplicación de 3 y 4 de abril de 2006 sobre la elaboración de mapas de ruido y planes de prevención del ruido ambiental.

Los mapas estratégicos de ruido están destinados a representar un nivel de incomodidad acústica en un momento de referencia. Están desarrollados por software de modelado acústico que tiene en cuenta la fuente de ruido generado por el tráfico de automóviles, así como muchos elementos del contexto como la topografía, la velocidad autorizada o los edificios circundantes.

Se logran mediante dos indicadores armonizados: Lden (Noche de Noche de Nivel) y Ln (Noche de Nivel). Lden representa el ruido promedio durante todo el día de 24 horas y Ln el ruido promedio durante el período nocturno 10 p.m. — 6 en punto.

Los documentos gráficos producidos permiten representar:

— áreas expuestas al ruido utilizando curvas de isófono.

Se generan dos tipos de tarjetas: uno muestra curvas de isófono en pasos de 5 dB(A) (mapas de tipo A), los otros muestran áreas donde se exceden los valores límite (mapas de tipo C).

Infraestructuras afectadas en el Loiret:

— Carreteras departamentales: D8, D14, D93, D94, D97, D520, D920, D921, D928, D948, D952, D960, D2007, D2020, D2060, D2107, D2152, D2271, D2701

Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward). Valores de tendência calculados da posição horizontal do litoral em relação ao litoral de base para o ano de 2017. Os números e mapas são processados anualmente no livro de mapas costeiros emitido pela RWS WVL. Com base neste livro, o cronograma de suplementação para o ano dois anos após a medição é determinado. Mostra-se a tendência de desvio da posição do litoral a controlar (TKL) em relação ao litoral de base. Na tabela subjacente, todos os parâmetros de teste calculados pelo software Morphan. A coloração indica a direção da tendência (seaward/landward) e mostra a localização do tkl (seaward/landward).

These maps are georeferenced versions of the maps produced by The University Museum, University of Pennsylvania, project at Tikal, Guatemala and published as Tikal Report 11. These georeferenced maps are intended for use with GIS (Geographic Information System) software. The maps should be useful for archaeologists, tourists and managers of Tikal National Park.

This map set consists of eleven georeferenced maps. The set includes two versions of the overview map of the central sixteen square kilometers of Tikal—the "Ruins of Tikal" map. One version includes the map border. The other version is without the border. The nine remaining maps cover the inner nine square kilometers in detail, without borders.

The maps were georeferenced as part of a University of Cincinnati project in Tikal, under permit of the Guatemalan government. The UC Project georeferenced the maps using land survey methods. We created transformation equations based on a point of beginning, a reference direction and a map scale. Directions and distances on the ground were transformed into UTM projected directions and distances. The point of beginning was the Petty Company benchmark shown on the "Camp Quad" map. In 2010 we determined the location with a GPS receiver. We accessed both the horizontal and vertical accuracy of the georeferenced maps. Based on 96 test points spread throughout the area of the maps, we found the median horizontal accuracy of the maps, compared to GPS, to be 5.6 meters. Based on 103 test points spread throughout the area of the maps, we found the median vertical accuracy of the maps, compared to a NASA radar altimetry mission, to be 2.1 meters.

The borders of the maps were removed so the set of maps will “seamlessly” fit together in GIS. See Tikal Report No.11 for versions of the maps with borders (one version of the georeferenced "Ruins of Tikal" map includes the border). The georeferencing files are optimized for use in ArcGIS version 9.2 and beyond. The PDF file of TR11 from which these maps were extracted was made with the generous assistance of the University Museum Library and the Tikal Archives. Details of the georeferencing and accuracy check are in a report to the Dirección Patrimonio Cultural y Natural de Guatemala: Christopher Carr, Eric Weaver, Nicholas Dunning, and Vernon Scarborough (2011) EVALUACIÓN DE LA EXACTITUD DE LOS MAPAS DE TIKAL DE LA UNIVERSIDAD DE PENNSYLVANIA, POR GPS Y ESTACIÓN TOTAL (Accuracy assessment of the Penn Project maps of Tikal, by GPS and Total Station). In Lentz, D., C. Ramos, N. Dunning, V. Scarborough and L. Grazioso. PROYECTO DE SILVICULTURA Y MANEJO DE AGUAS DE LOS ANTIGUOS MAYAS DE TIKAL.

Additional details of the strategies the Penn Project used to produce these high quality maps, the georeferencing methodology, and the accuracy check process are forthcoming in a book chapter. The book is on the UC project at Tikal, to be published by Cambridge University Press. The chapter is Carr, Weaver, Dunning and Scarborough. Bringing the University of Pennsylvania maps of Tikal into the era of electronic GIS. In Lentz, Dunning, Scarborough (eds). Tikal and Maya Ecology: Water, Landscapes and Resilience.

Permission to publish these maps must be secured from: The University of Pennsylvania Museum of Archaeology and Anthropology, 3260 South Street, Philadelphia, PA 19104, Tel: (215) 898-4050, Fax: (215) 573-9369, Email: publications@pennmuseum.org. .................................................................................................................. Estos mapas son versiones georeferenciados de los mapas producidos por el Museo Universitario de la Universidad de Pennsylvania, Proyecto Tikal, Guatemala y publicado como Informe de Tikal No. 11. La intensión de estos mapas georeferenciados es para ser utilizados con el Sistema de Información Geográfica (SIG). Los mapas deben ser útiles para los arqueólogos, los turistas y los administradores del Parque Nacional Tikal.

Este conjunto de mapas consta de once mapas georreferenciados. El juego incluye dos versiones del mapa general de los 16 km2 centrales del mapa de las "Ruins of Tikal". Una versión del mapa incluye sus encuadrados. La otra versión esta sin los encuadrados. Los nueve mapas restantes cubren los mapas interiores de 9 km2 en detalle, sin encuadrados.

Los mapas fueron georeferenciados como parte de un proyecto de la Universidad de Cincinnati en Tikal, con permiso del Ministerio de Cultura y Deportes del Gobierno de Guatemala. El Proyecto de la Universidad de Cincinnati georeferenció los mapas utilizando métodos de reconocimiento de campo. Creamos ecuaciones de transformación basado en un punto de inicio, una dirección de referencia y un mapa a escala. Direcciones y distancias en el campo se transformaron en direcciones proyectadas UTM y distancias. El punto de inicio fue el punto ... Visit https://dataone.org/datasets/doi%3A10.6067%3AXCV8542PFP_meta%24v%3D1378224005745 for complete metadata about this dataset.

A elaboração de mapas estratégicos de ruído é enquadrada pelos seguintes textos, que especificam, nomeadamente, os métodos de cálculo, os indicadores a utilizar e os resultados esperados: — Artigos L.572-1 a L.572-11 do Código do Ambiente, relativos à elaboração de mapas de ruído e de planos de prevenção do ruído ambiente e à alteração do código do planeamento urbano;

— Artigos R.572-1 a R.572-11 relativos à elaboração de mapas de ruído e de planos de prevenção do ruído ambiente e à alteração do código de planeamento urbano; — os seus decretos de execução de 3 e 4 de abril de 2006 relativos à elaboração de mapas de ruído e de planos de prevenção do ruído ambiente.

Os mapas estratégicos de ruído destinam-se a representar um nível de desconforto sonoro num momento de referência. Eles são desenvolvidos por software de modelagem acústica que leva em conta a fonte de ruído gerado pelo tráfego de automóveis, bem como muitos elementos do contexto, como topografia, velocidade autorizada ou edifícios circundantes.

São alcançados através de dois indicadores harmonizados: Lden (Level Day Evening Night) e Ln (Nível Noite). Lden representa o ruído médio durante todo o dia de 24 horas e Ln o ruído médio durante o período noturno 10 p.m. — 6 horas.

Os documentos gráficos produzidos permitem assim representar:

— áreas expostas ao ruído usando curvas isofone.

São gerados dois tipos de cartões: um mostra curvas isofone em passos de 5 dB(A) (mapas do tipo A), os outros mostram áreas onde os valores-limite são excedidos (mapas do tipo C).

Infraestruturas em causa no Loiret:

— Autoestradas: A6, A10, A19, A71 e A77

Valores de tendencia calculados para la posición horizontal del litoral en relación con el litoral de base para el año 2021. Las figuras y los mapas se procesan anualmente en el libro de mapas costeros publicado por RWS WVL. Sobre la base de este libro, se determina el calendario de suplementación para el año 2 años después de la medición. Se representa la tendencia en la desviación de la posición de la línea de costa a probar (TKL) en relación con la línea de costa de base. En la tabla subyacente todos los parámetros de prueba calculados por el software de prueba MorphAn. La coloración indica la dirección de la tendencia (marina/tierra) e indica la ubicación del tkl (marina/tierra).

GnoIDE garantiza la disponibilidad de recursos tecnológicos específicos para que las administraciones que no los poseen, puedan compartir información geográfica y centren sus esfuerzos en el mantenimiento de los conjuntos de datos de los que son competentes y que la legislación señala como obligatoria su publicación.

Es el Instituto de Estadística y Cartografía de Andalucía (IECA) quien pone a disposición su infraestructura tecnológica de servidores, software de servidor de aplicaciones, bases de datos o programas específicos para publicar mapas (GeoServer) o metadatos (Geonetwork), de acuerdo a estándares internacionales que garantizan su interoperabilidad.

Los usuarios externos al IECA solo necesitan conectarse a una aplicación web desde donde cargar sus capas de información espacial, configurar una leyenda y publicar mapas como servicios interoperables. Una vez compartidos los servicios de mapas, pueden visualizarse directamente en la aplicación, o en infinidad de visores web o clientes de escritorio como QGIS, GVSIG o ArcGis, ya que todos tienen la capacidad de consumir los servicios estandarizados generados por GnoIDE.

These maps and GIS file provide visualizations of the landslide that occurred in Brgy. Masara, Maco, Davao de Oro, Philippines on 06 February 2024.

The PlanetScope Super Dove satellite image was acquired four (4) days after the landslide event (10 February 2024). Using the satellite image, the extents of the landslide were manually delineated using GIS software. We estimated that the larger landslide has a surface area of approximately 85,960 sq. m., while the smaller one measures approximately 759 sq. m. Unfortunately, some portions of the image near the landslide area are contaminated by cloud shadows, making it challenging to visualize and accurately map the extent of the landslide.

Also included is a high-resolution satellite image depicting Brgy. Masara before the occurrence of the landslide. The image was acquired sometime in November 2019. The manually delineated extent of the landslide area (from the PlanetScope image) is overlaid to easily visualize the impact of the landslide on the nearby community.

Credits:

* GIS analysis and map preparation: Jojene R. Santillan
* Imagery © 2024 Planet Labs Inc., Maxar

Access to the PlanetScope image was made possible by the Planet Education and Research Program.

****
Disclaimers:

The maps and GIS files ("Products") shall be used for non-commercial, reference purposes only. They shall not be used as replacements to authoritative maps and information provided/issued by mandated government agencies.

Accuracy and Limitations: The accuracies of the Products are dependent on the source datasets, and limitations of the software and algorithms used and implemented procedures. The Products are provided “as is” without any warranty of any kind, expressed or implied. CCGeo does not warrant that the Products will be complete, and meet the needs or expectations of the user, or that the operations or use of the maps and GIS files will be error-free.

Limitation of Liability: CCGeo and Caraga State University will not be held liable for any incidental, consequential, special, exemplary, or indirect damages (including lost profits and lost data) arising from or relating to the use of the maps and GIS files.

The dataset contains a map of the main classes of agricultural land use (dominant crop types and other land use types) in Germany for the year 2023. It complements a series of maps that are produced annually at the Thünen Institute beginning with the year 2017 on the basis of satellite data. The maps cover the entire open landscape, i.e., the agriculturally used area (UAA) and e.g., uncultivated areas. The map was derived from time series of Sentinel-1, Sentinel-2, Landsat 8 and additional environmental data. Map production is based on the methods described in Blickensdörfer et al. (2022).

All optical satellite data were managed, pre-processed and structured in an analysis-ready data (ARD) cube using the open-source software FORCE - Framework for Operational Radiometric Correction for Environmental monitoring (Frantz, D., 2019), in which SAR and environmental data were integrated.

The map extent covers all areas in Germany that are defined as agricultural land, grassland, small woody features, heathland, peatland or unvegetated areas according to ATKIS Basis-DLM (Geobasisdaten: © GeoBasis-DE / BKG, 2020).

Version v201:
Post-processing of the maps included a sieve filter as well as a ruleset for the reduction of non-plausible areas using the Basis-DLM and the digital terrain model of Germany (Geobasisdaten: © GeoBasis-DE / BKG, 2015).

The maps are available as cloud optimized GeoTiffs, which makes downloading the full dataset optional. All data can directly be accessed in QGIS, R, Python or any supported software of your choice using the URL that will be provided on request. By doing so the entire map area or only the regions of interest can be accessed. QGIS legend files for data visualization can be downloaded separately.

Class-specific accuracies for each year are proveded in the respective tables. We provide this dataset "as is" without any warranty regarding the accuracy or completeness and exclude all liability.

_

Mailing list

If you do not want to miss the latest updates, please enroll to our mailing list.

_

References:

Blickensdörfer, L., Schwieder, M., Pflugmacher, D., Nendel, C., Erasmi, S., & Hostert, P. (2022). Mapping of crop types and crop sequences with combined time series of Sentinel-1, Sentinel-2 and Landsat 8 data for Germany. Remote Sensing of Environment, 269, 112831.

BKG, Bundesamt für Kartographie und Geodäsie (2015). Digitales Geländemodell Gitterweite 10 m. DGM10. https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/dgm10.pdf (last accessed: 28. April 2022).

BKG, Bundesamt für Kartographie und Geodäsie (2020). Digitales Basis-Landschaftsmodell.
https://sg.geodatenzentrum.de/web_public/gdz/dokumentation/deu/basis-dlm.pdf (last accessed: 28. April 2022).

Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, 1124.

Statistisches Bundesamt, Deutschland (2024). Ökosystematlas Deutschland
https://oekosystematlas-ugr.destatis.de/ (last accessed: 08.02.2024).

_
National-scale crop type maps for Germany from combined time series of Sentinel-1, Sentinel-2 and Landsat data (2017 to 2021) © 2024 by Schwieder, Marcel; Tetteh, Gideon Okpoti; Blickensdörfer, Lukas; Gocht, Alexander; Erasmi, Stefan; licensed under CC BY 4.0.

Funding was provided by the German Federal Ministry of Food and Agriculture as part of the joint project “Monitoring der biologischen Vielfalt in Agrarlandschaften” (MonViA, Monitoring of biodiversity in agricultural landscapes).