SummaryA study by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of Interior Southeast Climate Adaptation Science Center, evaluated the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land cover change for the period 1952-2099. An application of the Precipitation Runoff Modeling System (PRMS) was used to develop the hydrologic simulations. The model simulations were used to compute the potential changes in hydrologic response across the southeastern U.S. using historical observations of climate and streamflow, and 13 downscaled general circulation models with four representative concentration pathways representing a range of potential future changes in climate. The PRMS simulated hydrologic response within the entire geographic study area – the model domain. The model domain was subset into small local watersheds delineating areas expected to have a similar hydrologic response due to changes in the model inputs. These local watersheds are called “hydrologic response units” or HRUs. The PRMS computes flow generated locally on each HRU for each time step. These flow components then are directed to stream segments (SEGs) for flow aggregation. These segments connect the network of HRUs to simulate accumulated streamflow from the upstream watershed. Each HRU and SEG has a unique ID. For each HRU and SEG, 52 summary streamflow metrics (Index of Hydrologic Alteration or IHA metrics) were calculated based on the daily flow outputs. A description of each IHA metric may be found here (streamflow_description_table.xlsx). The summary information presented here shows geospatial results from three main components: 1) The future percent difference from historical conditions for each HRU and SEG and for each of 50 IHA metrics (two metrics excluded due to a predominance of missing values). The results are based on the difference between future conditions in 2045-2075 and historical conditions from 1952-2005. Values are expressed as the percent difference based on a median of 45 future scenarios. https://www.sciencebase.gov/catalog/item/597b37bbe4b0a38ca27563d4 Data source - HRU: “Summary of percent change in statistics by GCM/RCP scenario by HRU”stats_difference_hru_gcm_v2_csvData source - SEG: “Summary of percent change in statistics by GCM/RCP scenario by SEG”stats_difference_seg_gcm_v2_csv PurposeThe streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. The data presented here are intended to provide more easily accessible landscape scale summary information in support of the USGS flow modeling project.

CDFW BIOS GIS Dataset, Contact: Melanie Gogol-Prokurat, Description: Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for California's wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California.

Attachment regarding a request by NNP Briar Chapel for a revision to the Conditional Use Permit to (1) revise the civic site at the intersection of Andrews Store Rd and Parker Herndon Rd (possible Chatham County elementary school site) on master plan to allow for full development of the site (rather than just 2 acres as shown), (2) create the possibility of having up to 2,650 residential units (currently approved for 2,500), (3) revise the master plan map to reduce the perimeter buffer (a) from 100’ to 50’ along the frontage with Chapel in the Pines church (at the church’s request); (b) from 100’ to 50’ along the short boundary with Duke Energy RoW at SD-N; and (c) from 100’ to 75’ along Phase 15-S boundary to eliminate the need to build a retaining wall within the perimeter buffer, and (4) revise the color key table on the master plan map to reflect adjustments to residential densities in particular locations.

Vector datasets of CWHR range maps are one component of California Wildlife Habitat Relationships (CWHR), a comprehensive information system and predictive model for Californias wildlife. The CWHR System was developed to support habitat conservation and management, land use planning, impact assessment, education, and research involving terrestrial vertebrates in California. CWHR contains information on life history, management status, geographic distribution, and habitat relationships for wildlife species known to occur regularly in California. Range maps represent the maximum, current geographic extent of each species within California. They were originally delineated at a scale of 1:5,000,000 by species-level experts and have gradually been revised at a scale of 1:1,000,000. For more information about CWHR, visit the CWHR webpage (https://www.wildlife.ca.gov/Data/CWHR). The webpage provides links to download CWHR data and user documents such as a look up table of available range maps including species code, species name, and range map revision history; a full set of CWHR GIS data; .pdf files of each range map or species life history accounts; and a User Guide.

Dans dans le cadre de l’étude sur la sécheresse à Gand (2021), plusieurs cartes ont été établi. Cette collection donne un aperçu du matériel disponible pour la création des "cartes d'analyse et de données SIG". L'analyse SIG et les cartes de données montrent les analyses sous-jacentes qui ont été effectuées, telles que le degré moyen de durcissement par parcelle et l'urgence d'irrigation pour les parcelles agricoles, ainsi que la répartition géographique des données collectées, y compris la capacité d'infiltration et les mesures du niveau des eaux souterraines. Les légendes pour la visualisation des sources dans ArcMap et dans QGIS, ainsi que les fichiers Tiff, peuvent être trouvées sous "Exporter".

Description Les couches "ensoleillement" représentent des simulations de l'ensoleillement théorique basant sur le modèle numérique de la surface. Ces simulations prennent en compte les situations topographiques (alentours, pentes, expositions) et la variation temporaire pendant l'année de l'ensoleillement théorique pour une position géographique spécifique. Cette analyse crée deux type de résultats sous forme d'une grille avec une résolution d'1 m : Une visualisation de la durée de l'ensoleillement en heures par jour Une accumulation de l’énergie solaire potentielle en Watt/m2 par jour Actuellement, cette analyse a été calculée pour trois jours, notamment le 15/02 (hiver), 15/05 (printemps) et 15/08 (été) sur le modèle numérique de la surface de 2017 mis à disposition par l’Administration National Aérienne (ANA). (Lien vers dataset du MNS) L'analyse de l'ensoleillement a été réalisé avec l'outil "Rayonnement solaire zonal" du logiciel ESRI ArcMap. Une documentation détaillée est disponible ici. Une documentation détaillée du calcul d’insolation utilisé est disponible ici. Les paramètres utilisés pour l'analyse Raster en entrée : Modèle numérique de surface mis à disposition par l'Administration de la navigantion aérienne (ANA) se basant sur des données LiDAR de 2017. Latitude: 49.46 ° Configuration du temps: Time Within a day (pour 3 dates: 15/02 hiver, 15/05 printemps et 15/08 été) Intervalle de temps : 0.5 Des intervalles de 30 minutes sont utilisés et les données sont accumulées par jours. Pente et exposition : Les rasters de pente et d'exposition sont calculés à partir du modèle numérique de surface en entrée. Nombre de directions azimutales : 32 directions. Ce nombre est approprié pour une topographie complexe. Proportion du flux du rayonnement normal global : La valeur utilisée est 0,3 pour des conditions de ciel dégagé. Fraction du rayonnement traversant l'atmosphère : 0,5 pour des conditions de ciel dégagé. Grille de la durée de l'ensoleillement directe : Raster en sortie correspondant à la durée du rayonnement solaire direct en heures par jour. Structure et format des données Les données sont disponibles dans le format GeoTIF avec une résolution 1 m (système de coordonnées LUREF – EPSG : 2169). Pour chaque date, il y a un fichier duration avec la durée de l’ensoleillement en heures par jour et un fichier radiation avec l’énergie solaire potentielle en Watt/m2 par jour.

Funded by a grant from the Sloan Foundation, and with support from Massachusetts Open Cloud, the Center for Geographic Analysis(CGA) at Harvard developed a “big geodata”, remotely hosted, real-time-updated dataset which is a prototype for a new data type hosted outside Dataverse which supports streaming updates, and is accessed via an API. The CGA developed 1) the software and hardware platform to support interactive exploration of a billion spatio-temporal objects, nicknamed the "BOP" (billion object platform) 2) an API to provide query access to the archive from Dataverse 3) client-side tools for querying/visualizing the contents of the archive and extracting data subsets. This project is currently no longer active. For more information please see: http://gis.harvard.edu/services/project-consultation/project-resume/billion-object-platform-bop. “Geotweets” are tweets containing a GPS coordinate from the originating device. Currently 1-2% of tweets are geotweets, about 8 million per day. The CGA has been harvesting geotweets since 2012.

Scottsdale is upgrading the ERP system that manages this data. Open Data will not be updated during this time. We expect to resume presenting the data in the next 60 days. We are sorry for any inconvenience this may cause and appreciate your patience while we upgrade financial systems.Please click here and download to view the Data Dictionary, a description of the fields in this table. Details about solicitations for construction projects-to purchase products and services, to determine availability of vendor products and/or services and to sell surplus property items. 1 year of rolling data.

In het kader van de droogtestudie voor Gent (2021) werden verschillende kaarten opgemaakt.Dit verzameling geeft een overzicht van het beschikbaar materiaal voor de aanmaak van de "GIS-analyse en data kaarten".De GIS-analyse en data kaarten tonen achterliggende analyses die uitgevoerd werden, zoals de gemiddelde verhardingsgraad per perceel en de irrigatienood voor landbouwpercelen, alsook de geografische verspreiding van de data die verzameld werden, onder andere infiltratiecapaciteits- en grondwaterpeilmetingen.Legendes voor de visualisatie van de bronnen in ArcMap en in QGIS, samen met de Tiff bestanden, zijn onder "Exporteren" te vinden.

The purpose and need of the project is derived from the need to move specific aspects of the ecosystem within the project area further towards desired conditions, goals, and objectives in the Payette National Forest Land and Resource Management Plan (forest plan).

Railroad Saddle Forest Restoration Project on the Payette National Forest, New Meadows Ranger District, Idaho.The Forest has developed the proposed action to address the purpose and need of the project. The proposed action includes vegetation management and associated roads related activities.Vegetation management includes commercial timber harvest, non-commercial thinning (NCT), and prescribed fire. NCT and prescribed fire are proposed across the project area, outside of the inner half of riparian conservation areas (RCAs). The silviculture - NIDGS map shows the location of commercial harvest units (plus NCT NIDGS units).Road related activities include temporary road construction, log hauling on roads, the obliteration of undetermined roads, and the conversation of closed roads to two wheeled motorized use

In late 1996, the Dept of Conservation (DOC) surveyed state and federal agencies about the county boundary coverage they used. As a result, DOC adopted the 1:24,000 (24K) scale U.S. Bureau of Reclamation (USBR) dataset (USGS source) for their Farmland Mapping and Monitoring Program (FMMP) but with several modifications. Detailed documentation of these changes is provided by FMMP and included in the lineage section of the metadata. A dataset named cnty24k97_1 was made available (approximately 2004) through the California Department of Forestry and Fire Protection - Fire and Resource Assessment Program (CDF - FRAP) and the California Spatial Information Library (CaSIL).In late 2006, the Department of Fish and Game (DFG) reviewed cnty24k97_1. Comparisons were made to a high-quality 100K dataset (co100a/county100k from the former Teale Data Center GIS Solutions Group) and legal boundary descriptions from ( http://www.leginfo.ca.gov ). The cnty24k97_1 dataset was missing Anacapa and Santa Barbara islands. DFG added the missing islands using previously-digitized coastline data (coastn27 of State Lands Commission origin), corrected a few county boundaries, built region topology, added additional attributes, and renamed the dataset to county24k.In 2007, the California Mapping Coordinating Committee (CMCC) requested that the California Department of Forestry and Fire Protection (CAL FIRE) resume stewardship of the statewide county boundaries data. CAL FIRE adopted the changes made by DFG and collected additional suggestions for the county data from DFG, DOC, and local government agencies. CAL FIRE incorporated these suggestions into the latest revision, which has been renamed cnty24k09_1. Detailed documentation of changes is included in the Process Step section of the metadata.

The FGGD CV of LGP map is a global raster datalayer with a resolution of 5 arc-minutes. Each pixel contains an average coefficient of variation of LGP for the pixel area over the period 1901-1996. The data are from FAO and IIASA, 2000, Global agro-ecological zones, as reported in FAO and IIASA, 2007, Mapping biophysical factors that influence agricultural production and rural vulnerability, by H. von Velthuizen et al.

Service d'affichage (WMS) du plan FNP_Bienenbüttel (regroupement) Il s'agit d'un service utilitaire d'assemblage d'éléments de plan avec une couche par classe XPlanung. La dernière modification est le 31.08.2021. Les contours des plans de modification sont résumés dans la couche Champs d'application.

Service de téléchargement (WFS) du plan FNP_Bremervörde (résumé). Plan d’affectation des sols de la ville de Bremervörde Plan d’affectation des sols de la ville de Bremervörde, y compris modifications et rectifications jusqu’à l’entrée en force de la loi 14.03.2020 Il s’agit d’un service d’utilité publique consistant à regrouper des éléments de plans avec une couche par classe XPlanung. La dernière modification est le 14.03.2020. Les contours des plans de modification sont résumés dans la couche Champs d'application.

This is the AGOL Description. Publication Date: 2024-10-07

Para abrir y visualizar el proyecto, deben utilizar QGIS 3.38 y abrir el archivo "PampeanLakes.qgz". Geographic Information Systems (GIS) consists of data, software and hardware to generate, store, manage, analyse, and visualise georeferenced information. The use of GIS has increased in recent decades for three reasons: 1) public, free and high-quality georeferenced information is increasingly available, 2) free and powerful GIS software has been developed, and 3) georeferenced information has been incorporated into our daily life. Nowadays, GIS is an indispensable part of many fields and studies thanks to its ability to integrate and analyse large volumes of data with little effort and computational requirements. The development of GIS has led to a democratisation of the information created and visualised through them, a process we aim to contribute to. This GIS was developed for the book 'Pampean Lakes' using information from 13 of its chapters. The GIS includes lakes, wetlands, valley boundaries, paleochannels, streams, dunes, flooded areas, fault systems, salinas, orography, vegetation and aeolian units, archaeological sites, and weather stations. Additionally, we present a series of uses examples. Los sistemas de información geográfica (SIG) consisten en datos, software y hardware para generar, almacenar, gestionar, analizar y visualizar información georreferenciada. El uso de los SIG ha aumentado en las últimas décadas debido a tres motivos: 1) la disponibilidad de información georreferenciada pública, gratuita y de alta calidad es cada vez mayor, 2) el desarrollo de software SIG libre y poderoso, y 3) la incorporación de la información georreferenciada en nuestra vida cotidiana. Hoy en día, los SIG son una parte indispensable de muchos campos y estudios gracias a su capacidad para integrar y analizar grandes volúmenes de datos con poco esfuerzo y requisitos computacionales. El desarrollo de los SIG ha llevado a una democratización de la información creada y visualizada a través de ellos, un proceso al que queremos contribuir. Este SIG fue elaborado para el libro "Pampean Lakes" utilizando información de 13 de sus capítulos. El SIG incluye lagos, humedales, límites de valles, paleocanales, arroyos, dunas, áreas inundadas, sistemas de fallas, salinas, orografía, vegetación y unidades eólicas, sitios arqueológicos y estaciones meteorológicas. Además, presentamos una serie de ejemplos de usos.

Dive into Market Research Intellect's GIS Tank-Type Surge Arrester Market Report, valued at USD 450 million in 2024, and forecast to reach USD 710 million by 2033, growing at a CAGR of 6.5% from 2026 to 2033.

SummaryA study by the U.S. Geological Survey (USGS), in cooperation with the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) and the Department of Interior Southeast Climate Adaptation Science Center, evaluated the hydrologic response of a daily time step hydrologic model to historical observations and projections of potential climate and land cover change for the period 1952-2099. An application of the Precipitation Runoff Modeling System (PRMS) was used to develop the hydrologic simulations. The model simulations were used to compute the potential changes in hydrologic response across the southeastern U.S. using historical observations of climate and streamflow, and 13 downscaled general circulation models with four representative concentration pathways representing a range of potential future changes in climate. The PRMS simulated hydrologic response within the entire geographic study area – the model domain. The model domain was subset into small local watersheds delineating areas expected to have a similar hydrologic response due to changes in the model inputs. These local watersheds are called “hydrologic response units” or HRUs. The PRMS computes flow generated locally on each HRU for each time step. These flow components then are directed to stream segments (SEGs) for flow aggregation. These segments connect the network of HRUs to simulate accumulated streamflow from the upstream watershed. Each HRU and SEG has a unique ID. For each HRU and SEG, 52 summary streamflow metrics (Index of Hydrologic Alteration or IHA metrics) were calculated based on the daily flow outputs. A description of each IHA metric may be found here (streamflow_description_table.xlsx). The summary information presented here shows geospatial results from three main components: 1) The future percent difference from historical conditions for each HRU and SEG and for each of 50 IHA metrics (two metrics excluded due to a predominance of missing values). The results are based on the difference between future conditions in 2045-2075 and historical conditions from 1952-2005. Values are expressed as the percent difference based on a median of 45 future scenarios. https://www.sciencebase.gov/catalog/item/597b37bbe4b0a38ca27563d4 Data source - HRU: “Summary of percent change in statistics by GCM/RCP scenario by HRU”stats_difference_hru_gcm_v2_csvData source - SEG: “Summary of percent change in statistics by GCM/RCP scenario by SEG”stats_difference_seg_gcm_v2_csv PurposeThe streamflow statistics were selected to describe streamflow conditions that may be most useful in defining the suitability for each river or stream to support sustaining populations of priority aquatic species across the GCPO LCC. The data presented here are intended to provide more easily accessible landscape scale summary information in support of the USGS flow modeling project.

Check out Market Research Intellect's Ultrahigh Voltage Gis Market Report, valued at USD 12.5 billion in 2024, with a projected growth to USD 22.8 billion by 2033 at a CAGR of 8.3% (2026-2033).

Laatste update: 12 februari 2025Let op! De laatste versie van ArcGIS Insights wordt in het derde kwartaal van 2025 gereleased! Meer informatie vind je hier: Deprecation Notice for ArcGIS InsightsDit artikel bespreekt hoe een ArcGIS Insights analyse gemaakt kan worden en gedeeld kan worden met de organisatie.