This map was created to be used in the CBF website map gallery as updated satellite imagery content for the Chesapeake Bay watershed.This map includes the Chesapeake Bay watershed boundary, state boundaries that intersect the watershed boundary, and NLCD 2019 Land Cover data as well as a imagery background. This will be shared as a web application on the CBF website within the map gallery subpage.

NZ Parcel Boundaries Wireframe provides a map of land, road and other parcel boundaries, and is especially useful for displaying property boundaries.
This map service is for visualisation purposes only and is not intended for download. You can download the full parcels data from the NZ Parcels dataset.
This map service provides a dark outline and transparent fill, making it perfect for overlaying on our basemaps or any map service you choose.
Data for this map service is sourced from the NZ Parcels dataset which is updated weekly with authoritative data direct from LINZ’s Survey and Title system. Refer to the NZ Parcel layer for detailed metadata.
To simplify the visualisation of this data, the map service filters the data from the NZ Parcels layer to display parcels with a status of 'current' only.
This map service has been designed to be integrated into GIS, web and mobile applications via LINZ’s WMTS and XYZ tile services. View the Services tab to access these services.
See the LINZ website for service specifications and help using WMTS and XYZ tile services and more information about this service.

Land Cover Map 2021 (LCM2021) is a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2021. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2021. Land cover maps describe the physical material on the surface of the country. For example grassland, woodland, rivers & lakes or man-made structures such as roads and buildingsThis is a 10 m Classified Pixel dataset, classified to create a single mosaic of national cover. Provenance and quality:UKCEH’s automated land cover classification algorithms generated the 10m classified pixels. Training data were automatically selected from stable land covers over the interval of 2017 to 2019. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.Land cover was validated by organising the pixel classification into a land parcel framework (the LCM2021 Classified Land Parcels product). The classified land parcels were compared to known land cover producing confusion matrix to determine overall and per class accuracy.View full metadata information and download the data at catalogue.ceh.ac.uk

This dataset consists of the vector version of the Land Cover Map 2015 (LCM2015) for Great Britain. The vector data set is the core LCM data set from which the full range of other LCM2015 products is derived. It provides a number of attributes including land cover at the target class level (given as an integer value and also as text), the number of pixels within the polygon classified as each land cover type and a probability value provided by the classification algorithm (for full details see the LCM2015 Dataset Documentation). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019.

Approximate boundaries for all land parcels in New Brunswick. The boundaries are structured as Polygons. The Property Identifier number or PID is included for each parcel.

This is the 25m rasterised land parcels dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Great Britain. It describes Great Britain's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived by rasterising the corresponding LCM2019 land parcels dataset into 25m pixels. It is provided as a 3-band, 8-bit integer raster. The first band is the UKCEH Land Cover Class identifier. Bands 2 and 3 are indicators of classification confidence. For a fuller description please refer to the product documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/f15289da-6424-4a5e-bd92-48c4d9c830cc

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2018(LCM2018) representing Great Britain. It describes Great Britain's land cover in 2018 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2018 20m classified pixels dataset. All further LCM2018 datasets for Great Britain are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value, and a range of per-parcel pixel statistics to help to assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2018 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2018. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2018. LCM2018 was simultaneously released with LCM2017 and LCM2019. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

This data set includes: (1) fine-scale snow and land cover maps from two mountainous study sites in the Western U.S., produced using machine-learning models trained to extract land cover data from WorldView-2 and WorldView-3 stereo panchromatic and multispectral images; (2) binary snow maps derived from the land cover maps; and (3) 30 m and 465 m fractional snow-covered area (fSCA) maps, produced via downsampling of the binary snow maps. The land cover classification maps feature between three and six classes common to mountainous regions and integral for accurate stereo snow depth mapping: illuminated snow, shaded snow, vegetation, exposed surfaces, surface water, and clouds. Also included are Landsat and MODSCAG fSCA map products. The source imagery for these data are the Maxar WorldView-2 and Maxar WorldView-3 Level-1B 8-band multispectral images, orthorectified and converted to top-of-atmosphere reflectance. These Level-1B images are available under the NGA NextView/EnhancedView license.

This is the 20m classified pixels dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Great Britain. It describes Great Britain's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset is the Random Forest classification result from classifying a 20m pixel raster containing multi-season spectral information combined with context layers, which help to resolve spectral confusion. It is provided as a two-band, 8-bit integer raster. Band 1 is the UKCEH Land Cover Class identifier, band 2 is an indicator of classification confidence. For a fuller description please refer to the product documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are one in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

The U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) collaborated on the creation of the global land datasets using Landsat data from 1972 through 2008. NASA and the USGS have again partnered to develop the Global Land Survey 2010 (GLS2010), a new global land data set with core acquisition dates of 2008-2011. This dataset consists of both Landsat TM and ETM+ images that meet quality and cloud cover standards established by the earlier GLS collections. Data acquired in 2011 were used to fill areas of low image quality or excessive cloud cover.

This dataset consists of the 1km raster, percentage target class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km percentage product provides the percentage cover for each of 21 land cover classes for 1km x 1km pixels. This product contains one band per target habitat class (producing a 21 band image). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019. Full details about this dataset can be found at https://doi.org/10.5285/505d1e0c-ab60-4a60-b448-68c5bbae403e

This dataset consists of the vector version of the Land Cover Map 1990 (LCM1990) for Great Britain. The vector data set is the core LCM data set from which the full range of other LCM1990 products are derived. It provides a number of attributes including land cover at the target class level (given as an integer value and also as text), the number of pixels within the polygon classified as each land cover type and a probability value provided by the classification algorithm (for full details see the LCM1990 Dataset Documentation). The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. LCM1990 is a land cover map of the UK which was produced at the UK Centre for Ecology & Hydrology by classifying satellite images (mainly from 1989 and 1990) into 21 Broad Habitat-based classes. It is the first in a series of land cover maps for the UK, which also includes maps for 2000, 2007, 2015, 2017, 2018 and 2019. LCM1990 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the UKCEH web site and the LCM1990 Dataset documentation) to select the product most suited to their needs. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

High resolution orthorectified images combine the image characteristics of an aerial photograph with the geometric qualities of a map. An orthoimage is a uniform-scale image where corrections have been made for feature displacement such as building tilt and for scale variations caused by terrain relief, sensor geometry, and camera tilt. A mathematical equation based on ground control points, sensor calibration information, and a digital elevation model is applied to each pixel to rectify the image to obtain the geometric qualities of a map.

A digital orthoimage may be created from several photographs mosaicked to form the final image. The source imagery may be black-and-white, natural color, or color infrared with a pixel resolution of 1-meter or finer. With orthoimagery, the resolution refers to the distance on the ground represented by each pixel.

This dataset represents a high resolution urban land cover classification map across the southern California Air Basin (SoCAB) with a spatial resolution of 60 cm in urban regions and 10 m in non-urban regions. This map was developed to support NASA JPL-based urban biospheric CO2 modeling in Los Angeles, CA. Land cover classification was derived from a novel fusion of Sentinel-2 (10-60 m x 10-60 m) and 2016 NAIP (60 cm x 60 cm) imagery and provides identification of impervious surface, non-photosynthetic vegetation, shrub, tree, grass, pools and lakes.

Land Cover Classes in .tif file: 0: Impervious surface 1: Tree (mixed evergreen/deciduous) 2: Grass (assumed irrigated) 3: Shrub 4: Non-photosynthetic vegetation 5: Water (masked using MNDWI/NDWI)

Google Earth Engine interactive app displaying this map: https://wcoleman.users.earthengine.app/view/socab-irrigated-classification

A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Support from the Earth Science Division OCO-2 program is acknowledged. Copyright 2020. All rights reserved.

AR50 is a nationwide dataset that shows the main types of land resources adapted to use on scales from 1:20 000 to 1:100 000. The data set consists of the following properties that can be used to produce map layers with predefined presentation rules (sld files): area type (ARTYPE), agriculture (ARJORD USE), tree species (ARTRESLAG), forest bondage (ARSKOGBON) and snauland (ARSKOGBON). AR50 is produced by generalising FKB-AR5 below the tree line and interpreting satellite imagery across the tree line. For classification of tree species, N50 forests have also been used without registered tree species where there is no AR5. Figures that are less than 15 acres do not appear on the map, but are merged with adjacent areas. AR50 is thus not suitable for spatial analyses or production of land-use statistics. The AR50 has been updated approximately every three years with the latest annual version of FKB-AR5. The production is fully automated and based on a complex rule-based production route for compiling the data sets. The latest version of the AR50 was published in May 2022 with data from AR5 and N50 from 31.12.2021, as well as new AR-FJELL2. The satellite images are from the period 2020 and 2022 (Sentinel 2 satellite). The production track was then rewritten with a new code. The code is adjusted to changes in the input data sets. The generalised figures will therefore differ slightly from previous versions. In addition, there is topological straightening including smoothing of the figures. Data is downloaded as county or municipal files. The first version of the AR50 year 2010 dataset was produced by AR5 and N50 as of 31.12.2010, and AR-FJELL with satellite imagery (IMAGE2000) from the period 1994 and 2006. It has since made annual version 2013 (AR5 and N50 as per 31.12.2013) and annual version 2016 (AR5 and N50 as of 31.12.2016). AR-FJELL has not been updated since 2010. The latest update of the first version of the AR50 has data from 31.12.2016.

This dataset provides global maps describing the land surface into 22 classes, which have been defined using the United Nations Food and Agriculture Organization’s (UN FAO) Land Cover Classification System (LCCS). In addition to the land cover (LC) maps, four quality flags are produced to document the reliability of the classification and change detection. In order to ensure continuity, these land cover maps are consistent with the series of global annual LC maps from the 1990s to 2015 produced by the European Space Agency (ESA) Climate Change Initiative (CCI), which are also available on the ESA CCI LC viewer. To produce this dataset, the entire Medium Resolution Imaging Spectrometer (MERIS) Full and Reduced Resolution archive from 2003 to 2012 was first classified into a unique 10-year baseline LC map. This is then back- and up-dated using change detected from (i) Advanced Very-High-Resolution Radiometer (AVHRR) time series from 1992 to 1999, (ii) SPOT-Vegetation (SPOT-VGT) time series from 1998 to 2012 and (iii) PROBA-Vegetation (PROBA-V), Sentinel-3 OLCI (S3 OLCI) and Sentinel-3 SLSTR (S3 SLSTR) time series from 2013. Beyond the climate-modelling communities, this dataset’s long-term consistency, yearly updates, and high thematic detail on a global scale have made it attractive for a multitude of applications such as land accounting, forest monitoring and desertification, in addition to scientific research.

This collection of geo-referenced photos vary with regards to spatial accuracy and resolution. Use the hotlinks below to learn the details of each collection or review MassGIS's new story map explaining all the vintages of aerial photos. Tip: Reviewing that story map might be an easier way to digest the information rather than reviewing the more formal/standard metadata accessible via the hotlinks below.Within the web map certain layers will only be visible at particular zoom extents. If a layer is unavailable to turn on/off, then zoom in or out as needed until the layer becomes active.All photos, except year 1938, are captured during leaf-off (typically late winter/early spring). With the exception of the 1938 & 1990s collection, all photos are in true color. The 1938 & 1990s are in black and white. With regards to Dukes County (which includes the Islands of Martha's Vineyard and the Elizabeth Islands) these are the applicable years of acquisition for those State-wide collections that span multiple years: "1990s collection" -- Only year 1999 for Dukes County"2001-2003 collection" -- Only year 2003 for Dukes County"2008-2009 collection" - Only year 2009 for Dukes County"2011-2012 collection" - Only year 2011 for Dukes County"2013-2014 collection" - Only year 2014 for Dukes CountyPhoto Details (Metadata)1938 Black & White Aerials (georeferenced & hosted by Harvard Forest)1990s Black & White Aerials2001-2003 Color Aerials2005 Color Aerials2008-2009 Color Aerials2011-2012 Color Aerials2013-2014 Color Aerials2015 Satellite Images - Extra Details2019 Color Aerials2021 Color Aerials2023 Color AerialsParcel Lines -- These data are NOT survey grade and are intended for general reference only. The parcel data comply with the MassGIS Level 3 parcel data standard. Each town in Dukes County hires a GIS Consultant to prepare their digital parcel lines and to link the properties to the respective records from the town's assessing database. The linkage is static and not updated in real-time - it is only 'as current' as the day the data was exported from the assessing database. The Martha's Vineyard Commission does not edit nor maintain any assessing data or parcel lines/property bounds. Each town within Dukes County updates their digital parcel data when they see fit (most, typically, update annually). Click on a specific town in this map to see when their parcel data was updated and by whom. Similarly, clicking on a parcel in this "MA Aerial Photos Since 1990s web map" will show you the applicable Fiscal Year the assessing info was exported.

The Open-API service can be used to build background maps and national points of interest (POI) information based on the latest spatial information held by the National Geographic Information Institute, and to link and utilize them in other information systems. The Open-API service is provided in two forms: background maps (including general maps, multilingual, image maps, satellite maps, color quantum maps, large letters, blank maps, educational blank maps, night maps, and hybrid maps) and search APIs (POI, place names, reference points, and geocoders). When developing and operating a website, you can implement spatial information and location search functions using DHTML and Javascript without building separate map information. The Open-API service is provided in the form of WMTS (Web Map Tile Service), and the National Geographic Information Platform Open API service is a service for members. Please proceed after logging in (signing up). (Application process) Register authenticated users and institutions → Apply for authentication key issuance → Issuance of authentication key → Service implementation → API user history management

This web map service (WMS) shows a 1km resolution raster version of the Land Cover Map 2007 for Great Britain. Each 1km pixel represents the dominant target class across the 1km area. The target classes broadly represent Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

The land cover maps published here were produced for four regions of the northern part of Chin state in Myanmar: Hakha, Falam, Tedim and Thantlang. This work was carried out as part of the ALIVE FNS project to monitor land use (forests, cultivated land, built-up areas, etc.). We used the Moringa processing chain, which is based on satellite imagery (Sentinel 2 free of charge time series and SPOT6-7 very high spatial resolution) and a supervised classification algorithm (Random Forest) trained on a reference database made of polygons associated with a land cover class. Generally, this database comes from ground GPS surveys, but it can be replaced by photo-interpretation of very high spatial resolution images if field collection is unavailable or impossible, as it is the case here in the State of Chin. The database was therefore obtained by photo-interpretation of Spot6/7 images acquired as part of the Dinamis programme. The nomenclature includes 4 crop classes (irrigated crops - mainly rice, shifting cultivation, new shifting cultivation, old shifting cultivation) and 6 non-crop classes (open spaces with little or no vegetation, herbaceous vegetation, shrubland, wooded vegetation, water, built-up areas). The maps are available, for the years 2020 and 2021, at a spatial resolution of 1.5 m over the parts covered by SPOT6/7 imagery (approximately half of the study area) and at a spatial resolution of 10m using only Sentinel-2 imagery over the whole area comprising the 4 regions: Hakha, Falam, Tedim, Thantlang. The overall and class accuracies (f-score) of the maps are available in a text file included in the archive containing the maps. Les cartes d'occupation du sol diffusées ici ont été produites sur quatre régions situées au Nord de l’état du Chin au Mynanmar : Hakha, Falam, Tedim, Thantlang. Ces travaux ont été réalisés dans le cadre du projet ALIVE FNS pour observer l'occupation des sols (forêts, terres cultivées, surfaces bâties, etc.). Nous avons utilisé la chaine Moringa qui s'appuie sur l'imagerie satellite (Sentinel 2 et SPOT6-7) et un algorithme de classification supervisée entraîné à partir d'une base de données de référence représentative de l'occupation des sols. Généralement, cette base de données est constituée à partir de relevés GPS sur le terrain, mais elle peut être remplacée par une photo-interprétation sur des images à très haute résolution spatiale si la collecte sur le terrain n'est pas disponible ou impossible, comme c'est le cas ici dans l'État de Chin. La base de données a donc été obtenue par photo-interprétation d’images Spot56/7 acquises dans le cadre du dispositif Dinamis. La nomenclature comprend 4 classes de cultures (cultures irriguées - principalement le riz, cultures itinérantes, nouvelles cultures itinérantes, anciennes cultures itinérantes) et 6 classes de non-cultures (espaces ouverts avec peu ou pas de végétation, végétation herbacée, zones arbustives, végétation boisée, eau, surfaces bâties). Les cartes sont disponibles, pour les années 2020 et 2021, à une résolution spatiale de 1,5m sur les parties couvertes par l'imagerie SPOT6/7 (non gratuites) et à une résolution spatiale de 10m utilisant uniquement des images Sentinel-2 (gratuites) sur une zone plus grande comprenant l’ensembles dans 4 régions : Hakha, Falam, Tedim, Thantlang. Les précisions globales et par classes des cartes sont disponible dans un fichier texte inclus dans l’archive contenant les cartes.