In this research

Maps are a natural and popular choice for scientists and natural resource managers to share ecological and other scientific data with others. This field lesson teaches students about river management plans and hydrosocial relationships using a field mapping method for collecting social, cultural, and relational information. Using mapping prompts, an instructor-supplied base map of the watershed, clear transparency film, and permanent markers, students are asked to team up in groups of 4-6 to collect observational data that captures different stakeholders’ knowledge, values, interests, and relationships to a river at multiple, discrete sites. Collected data can be compared in the field to identify immediately how different river uses and cultural values are spatially distributed throughout a watershed, or digitized later for additional analysis in the classroom. Although this field lesson was designed to support deliberative conversation and learning about watershed and river policies, this lesson could be used to complement other on-river lessons that collect physical and other environmental data.

The map describes the main geomorphological features according to surface cover type on Irizar - Crater Lake Area, Deception Island, Antarctica. The map was developed to support the analysis of the backscattering signal in SAR imagery and the interpretation of Din SAR products. Geomorphological units were mapped in the field during several summer seasons since 2011 based on a topographical map with a scale of 1:25,000. A QuickBird scene was used to improve the delineation of the geomorphological units. Detailed information about the geomorphological units can be found in the product guide.

The map shows the geomorphological units of Hurd Peninsula on Livingston Island. Mapping was done with high resolution field mapping supported by the analysis of a QuickBird scene. Mapping focused on present-day geomorphological processes and on the characteristics of the surface materials. The map was produced with the objective to contribute to analysis of surface deformation products derived from remote sensing imagery and permafrost modelling within the project ESA Data User Element - GlobPermafrost (DUE-GlobPermafrost).

More information about the geomorphological mapping and units can be found in the product guide.

Magnetic Field Mapping Satellite Market Outlook

According to our latest research, the global magnetic field mapping satellite market size reached USD 1.38 billion in 2024, reflecting robust expansion driven by advancements in satellite technology and rising demand for precision geomagnetic data. The sector is experiencing a strong compound annual growth rate (CAGR) of 8.7% and is projected to reach USD 2.82 billion by 2033. This remarkable growth is primarily attributed to the increasing adoption of magnetic field mapping satellites for applications in earth observation, scientific research, and defense, as well as the proliferation of small satellite constellations and ongoing investments in space infrastructure.

One of the key growth factors propelling the magnetic field mapping satellite market is the surge in demand for high-resolution geomagnetic data across various sectors. Industries such as oil and gas, mining, and infrastructure development are increasingly relying on precise magnetic field information to support exploration and construction activities. Additionally, the growing threat of space weather events, such as geomagnetic storms, has prompted governments and commercial entities to invest in advanced satellite systems capable of providing real-time magnetic field monitoring. These satellites play a crucial role in safeguarding critical infrastructure, including power grids and communication networks, by offering early warnings and actionable insights.

Another significant driver is the rapid technological advancement in satellite miniaturization and sensor capabilities. The emergence of small satellites, equipped with sophisticated magnetometers and onboard data processing units, has democratized access to space-based magnetic field mapping. These compact satellites offer cost-effective solutions for both governmental and commercial users, enabling frequent and comprehensive coverage of the Earth's magnetic environment. Furthermore, the integration of artificial intelligence and machine learning algorithms in data analysis enhances the accuracy and utility of magnetic field data, further expanding the market's application scope.

The increasing collaboration between space agencies, research institutions, and private companies is also fueling market growth. Joint missions and data-sharing agreements facilitate the pooling of resources and expertise, accelerating the development and deployment of advanced magnetic field mapping satellites. International initiatives, such as the European Space Agency's Swarm mission and NASA's Magnetospheric Multiscale mission, have set new benchmarks in magnetic field research, inspiring further investments and innovation in the sector. As a result, the market is witnessing a steady influx of new entrants and startups, contributing to a dynamic and competitive landscape.

From a regional perspective, North America and Europe currently dominate the magnetic field mapping satellite market, owing to their well-established space programs and robust research ecosystems. However, the Asia Pacific region is rapidly emerging as a key growth engine, driven by increasing investments in space technology by countries such as China, India, and Japan. These nations are launching ambitious satellite missions aimed at enhancing their geomagnetic monitoring capabilities and supporting a wide range of scientific and commercial applications. As regional players continue to expand their satellite fleets and capabilities, the global market is expected to witness a more balanced and diversified growth trajectory in the coming years.

Satellite Type Analysis

The magnetic field mapping satellite market is segmented by satellite type into small satellites, medium satellites, and large satellites. Each category plays a distinct role in the market's evolution, catering to varying mission requirements and budget constraints. Small satellites, typically weighing less than 500 kilograms, have gained significant traction in recent years due to their

Responses time series of voxels in each visual field map region of interest.

Regolith information derived from field mapping. Includes information on regolith materials, landforms, bedrock lithology, geomorphological processes and environmental hazards for particular field sites.

The Field Mapping Precision Farming report features an extensive regional analysis, identifying market penetration levels across major geographic areas. It highlights regional growth trends and opportunities, allowing businesses to tailor their market entry strategies and maximize growth in specific regions.

Raw data and simulation files to generate the figures in "Near-field mapping of the edge mode of a topological valley slab waveguide at λ = 1.55 μm" by Alexander M. Dubrovkin et al.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. After the field mapping crew finished the initial map unit polygon census, data was entered into a geodatabase. This data was quality checked and the final version was passed to WSAL. Polygons in the initial segmentation that were modified by crews as noted on the hardcopy maps supplied by the field crew were edited directly in the geodatabase. Any new map unit polygons created had a letter added to their original polygon-id field. A crosswalk table was created that linked the initial field key types to the USNVC series of hierarchical classifications and the field comments for each type. These classification attributes were then joined to the initial and final map units in the geodatabase.

🚑 Clinical Field Mappings for Healthcare Systems

This synthetic dataset provides a wide variety of alternative names for clinical database fields, mapping them to standardized targets for healthcare data normalization.

Using LLMs, we generated and validated thousands of plausible variations, including misspellings, abbreviations, country-specific nuances, and common real-world typos.

This dataset is perfect for training models that need to standardize, clean, or map heterogeneous healthcare data schemas into unified, normalized formats.

✅ Applications include: - Data cleaning and ETL pipelines for clinical databases - Fine-tuning LLMs for schema matching - Clinical data interoperability projects - Zero-shot field matching research

The dataset is machine-generated and validated with LLM feedback loops to ensure high-quality mappings.

This guide will teach you everything you need to know to successfully migrate your field workflows to Field Maps.

This data set contains land use types for 246 fields in Gera district in Southwestern Ethiopia. I collected this data in 2011 as part of a PhD project. Twenty-one smallholding farmers selected for the study used 213 of these fields while the remaining (33 fields) were fields adjacent to some of the fields used by the sample farmers. In addition to recording the land use in 2011 for all fields, through interview with the land users the land use types in 1991 and 1974 were identified for 151 and 117 fields, respectively. Major events occurred in 1974 (the socialist military government overthrew the last feudal monarch) and 1991 (the socialist military government was itself overthrown) in Ethiopia have helped trigger the interviewed farmers’ memory of past events. Farmers were able to identify the land use types during the three reference years (2011, 1991 and 1974) for 115 fields. Of the 213 fields used by the 21 farmers, I recorded the coordinates of the boundaries of 208 fields with a hand-held GPS. Similarly, I recorded the coordinates of the boundaries of the 33 fields adjacent to some of the studied fields. Using the coordinates and field notes, I have built two shape files in ESRI ArcMap in 2018 showing these fields (208 and 33). Data set also includes some biophysical features, e.g. location of the fields in relation to forest edges, of the fields. Moreover, the data set provides also the family size as well as the gender, age and educational status of the head of the household of the 21 studied farmers. I have reported detail descriptions of the purpose of this study and methods used to select village and household, and the results of the study in my PhD thesis (http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-128537).

Dataset contains land use types for 246 areas in the Gera district in southwestern Ethiopia. Data consists of GIS files with additional data in excel format.

Lunar Prospector magnetometer (MAG) Level 4 Data (CODMAC Level 5). Large-Scale Vector Field Maps at a Common Altitude of 37 km. The spatial resolution of the grid (0.25 x 0.25 degrees) is much less than the mean S/C altitude.

description: This dataset consists of digital geologic data for the Dry Valley Hydrographic area, Nevada and California. It was compiled from individual 1:250,000-scale geologic data for Washoe County, Nevada, 1:62,500-scale geologic data for the Chilcoot and Doyle 15' quadrangles in California and the results of field mapping within the study area in 2004. A revised geologic map was needed in the study area because the available published maps have large discrepancies between the reported geologic units along the state line. The 2004 field mapping was confined to an area approximately 2000 feet east and west of the California/Nevada state line and about 1.5 miles north and south of Dry Valley Creek. No attempt was made to resolve discrepancies between the published maps in the area outside of the designated mapping area. The discrepancies between geologic units in the previously published maps directly affect flow calculations used in the water budget for Dry Valley. The geologic unit involved in the greatest discrepancy is a non-welded rhyolitic tuff. Contacts between this unit and Quaternary basin-fill sediments were refined based on field mapping and sampling; and aerial photography. During mapping, low hills along the southern side of the valley floor 0.5 to 1.3 miles east of the state line mapped as Quaternary alluvium by previous efforts were recognized as non-welded rhyolitic tuff. In the locations described above, the non-welded tuff is distinguished by a lag deposit of yellow and red rhyolitic gravel at land surface. In the sub-surface, reached by digging, the tuff is weathered to a dense clay. Outcrops of the tuff with faint bedding planes were located in washes. Sample points, outcrops, and contacts between the tuff and unconsolidated sediments were located in the field using a handheld Garmin GPS unit (model GPS76).; abstract: This dataset consists of digital geologic data for the Dry Valley Hydrographic area, Nevada and California. It was compiled from individual 1:250,000-scale geologic data for Washoe County, Nevada, 1:62,500-scale geologic data for the Chilcoot and Doyle 15' quadrangles in California and the results of field mapping within the study area in 2004. A revised geologic map was needed in the study area because the available published maps have large discrepancies between the reported geologic units along the state line. The 2004 field mapping was confined to an area approximately 2000 feet east and west of the California/Nevada state line and about 1.5 miles north and south of Dry Valley Creek. No attempt was made to resolve discrepancies between the published maps in the area outside of the designated mapping area. The discrepancies between geologic units in the previously published maps directly affect flow calculations used in the water budget for Dry Valley. The geologic unit involved in the greatest discrepancy is a non-welded rhyolitic tuff. Contacts between this unit and Quaternary basin-fill sediments were refined based on field mapping and sampling; and aerial photography. During mapping, low hills along the southern side of the valley floor 0.5 to 1.3 miles east of the state line mapped as Quaternary alluvium by previous efforts were recognized as non-welded rhyolitic tuff. In the locations described above, the non-welded tuff is distinguished by a lag deposit of yellow and red rhyolitic gravel at land surface. In the sub-surface, reached by digging, the tuff is weathered to a dense clay. Outcrops of the tuff with faint bedding planes were located in washes. Sample points, outcrops, and contacts between the tuff and unconsolidated sediments were located in the field using a handheld Garmin GPS unit (model GPS76).

Fit parameters of all neural response models to responses of voxels in each visual field map region of interest.

Map display service according to WMS standard. The field block map is a digital field map, with agricultural land collected in field blocks. A field block is a geographically coherent unit of agricultural land. The boundaries of the field blocks typically follow permanent boundaries in the landscape. The map is used for the administration of cases related to the geographical location of arable land, primarily by EU area-based aid schemes. The field block map contains about 450,000 blocks, which cover approximately 2.8 million hectares of agricultural land. Each block shall be identified by a field block number and shall contain attributes for geographical area, type and eligible area.

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Legacy product - no abstract available

The Field Mapping Precision Farming market is rapidly evolving, driven by advancements in data analytics, satellite imagery, and GPS technology, which are transforming agricultural practices worldwide. This innovative approach allows farmers to optimize their land use, improve crop yield, and make informed decisions