The Port and Port Statistical Area web service allows users to visualize and access two USACE enterprise-wide feature classes: the Port Feature Class and the Port Statistical Area Feature Class, both of which include polygon geometries used to generate statistics for commerce data and vessel movements. The GIS service includes attributes such as port name, boundary description, and associated legislative documentation.

USACE works with port authorities from across the United States to develop the statistical port boundaries through an iterative and collaborative process. Port boundary information is prepared by USACE to increase transparency on public waterborne commerce statistic reporting, as well as to modernize how the data type is stored, analyzed, and reported.

A Port Area is defined by the limits set by overarching legislative enactments of state, county, or city governments, or the corporate limits of a municipality. A port typically refers to a geographical area that includes operational activities related to maritime transport as well as acquisition, operation, and management of port infrastructure and property, such as might be associated with ownership, concession, construction approval, or policy decision-making authority.

A Port Statistical Area (PSA) is a region with formally justified shared economic interests and collective reliance on infrastructure related to waterborne movements of commodities that is formally recognized by legislative enactments of state, county, or city governments. PSAs generally contain groups of county legislation for the sole purpose of statistical reporting. Through GIS mapping, legislative boundaries, and stakeholder collaboration, PSAs often serve as the primary unit for aggregating and reporting commerce statistics for broader geographical areas.

Per Engineering Regulation 1130-2-520, the U.S. Army Corps of Engineers' Navigation Data Center is responsible to collect, compile, publish, and disseminate waterborne commerce statistics. This task has subsequently been charged to the Waterborne Commerce Statistics Center to perform. Performance of this work is in accordance with the Rivers and Harbors Appropriation Act of 1922. Included in this work is the definition of a port area. A port area is defined in Engineering Pamphlet 1130-2-520 as: (1) Port limits defined by legislative enactments of state, county, or city governments. (2) The corporate limits of a municipality. The USACE enterprise-wide port and port statistical area feature classes per EP 1130-2-520 are organized in SDSFIE 4.0.2 format.

This data set contains reduced-resolution QuickBird imagery and geospatial data for the entire Barrow QuickBird image area 156.15° W - 157.07° W, 71.15° N - 71.41° N) and the Barrow B4 Quadrangle (156.29° W - 156.89° W, 71.25° N - 71.40° N), for use in Geographic Information Systems (GIS) and remote sensing software. The original QuickBird data sets were acquired by DigitialGlobe from 1 to 2 August 2002, and consist of orthorectified satellite imagery. Federal Geographic Data Committee (FGDC)-compliant metadata for all value-added data sets are provided in text, HTML, and XML formats.

Accessory layers include: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); an index map for the 62 QuickBird tiles (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow QuickBird image area and the Barrow B4 quadrangle area (ESRI Shapefile format).

The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest.

Data are available either via FTP or on CD-ROM.

The U.S. Army Corps of Engineers Geospatial Open Data provides shared and trusted USACE geospatial data, services and applications for use by our partner agencies and the public.

We provide the entire dataset of the paper "Dataset of seismic ambient vibrations from the Quaternary Norcia basin (central Italy)" submitted to "Data in Brief" journal, including geophysical and geospatial data.

The dataset was used and analysed in the article:

Di Giulio, G., Ercoli, M., Vassallo, M., Porreca, M. (2020). Investigation of the Norcia basin (Central Italy) through ambient vibration measurements and geological surveys, Engineering Geology, 267, 105501, https://doi.org/10.1016/j.enggeo.2020.105501

The geophysical dataset was collected in the Norcia basin in Central Italy, area struck by a long earthquake sequence during the 2016-2017, including five main-shocks with Mw>5.0.

The Mw 6.5 mainshock occurred on 30 October 2016 close to the town of Norcia. Different degrees of damages were observed during this seismic crisis, with a variable seismic shaking controlled, among many factors, by important 1D and 2D variation of Quaternary fluvio-lacustrine sediments infilling the basin.

Following this seismic sequence, we registered seismic vibration measurements, mainly single-seismic station noise data. We aimed to determine the distribution of resonant frequency (f0) of the basin and, though a join analysis with the available geological information, to infer the subsurface basin architecture.

A total of 60 sites were measured to cover the entire extension in the basin. We deployed seismometers along three transects of a total length of 21 km, mostly along the main structural directions of the basin (i.e. NNW-SSE and NE-SW).

Two 2D arrays of seismic stations with a elicoidal-shaped geometry, and a set of MASW active data were also acquired in the northern sector of the basin, in order to better constrain the seismic velocity of the sedimentary infilling.

In comparison to the data used in the paper Di Giulio et al. (2020), seven additional records have been here recovered across the basin (i.e. N54-N60).

We also provide geospatial ancillary data, both as a complete open-source Geographical Information Systems (GIS) project and as a set of single GeoPackage (.gpkg) and Keyhole Markup Language (.kml) files.

The dataset can be used for different purposes: specific researches on the Norcia basin, comparative studies on similar areas around the world, development of new data modeling/analysis software.

IIt includes data that were used in the manuscript(A Geospatial and Binomial Logistic Regression Model to Prioritize Sampling for Per- and Polyfluorinated Alkyl Substances (PFAS) in Public Water Systems.) It includes layers that were created in online ArcGIS pro in manuscript and result of regression model that was done in the manuscript.

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.

This feature class is the BLM Natl GTLF Public Motorized Roads subset of the feature dataset containing the BLM Ground Transportation Linear Features. A linear feature for ground transportation includes roads, primitive roads, primitive routes, trails, temporary routes, and linear disturbances. The Ground Transportation Linear Feature (GTLF) data standard provides a national geospatial data standard of the ground transportation linear features in BLM’s Enterprise GIS (E-GIS). A national BLM GTLF data standard is essential for collecting the landscape-scale data necessary to identify management opportunities and challenges that may not be evident when managing smaller land areas. GTLF data not only serve the crucial function of improving BLM transportation planning, but is also invaluable to numerous other BLM programs affected by transportation (e.g. water and air quality, wildlife habitat fragmentation, engineering, realty, cultural resources). This dataset is a subset of the official national dataset, containing features and attributes intended for public release and has been optimized for online map service performance. The Schema Workbook represents the official national dataset from which this dataset was derived.

Data contains historical polygons of in-channel islands within the Sacramento San Joaquin Delta. Data consists of merged datasets from 1929, 1940, 1949, 1952, 1995, 2002, and 2017. The 2017 polygons are digitized from the 2017 Delta LiDAR imagery by the Division of Engineering, Geomatics Branch, Geospatial Data Support Section. The older pre-2017 polygons were all digitized by staff in the Delta Levees Program. Data can be queried for a single year or date range using the 'Year' field. Historical data was compiled and merged from datasets provided by the Delta Levees program. Data coverage differs between years. Absences or gaps in historical data may occur. Older acquisitions generally have a smaller footprint than recent imagery acquisitions. The 2017 in-channel islands cover the Legal Delta, and also include Chipps Island.

Levee stations, usually in feet but in some cases miles, snapped to 2017 Delta levee centerlines (derived from the 2017 Delta LiDAR). Base source for station locations are surveyed field markers on the levees or distance-derived CAD files, in either case as supplied by local maintaining agency's engineers. DWR collected station location data and snapped the stations into the levee centerline file from 2012. After updated levee centerlines were created, the existing points were snapped to the new lines. So there is some small difference between the supplied station locations, previous station locations and these station locations. In some cases, multiple series of stations exist for a district, generally associated with distinct waterways. Also, district levees may be demarked in feet or in miles. The label fields are simply cartographic support, the label data are identical in all cases, but are provided to support fast labeling at more infrequent intervals as needed. Stationing is not as simple as it may seem. In some cases, multiple sets of stationing exist for a district's levees (see Sherman Island for example). What this dataset intends to represent is the current stationing used by District engineers for that District on levee maintenance and improvement projects. As changes are made to the stationing, and the new stationing data become available to the Levee Program, they will be added to this database. Some islands also have separate groups of stations for various parts of the district. This version is current as of 03/24/2020. Source of the original levee stationing is DWR Delta Levees Program, compiled from data provided by internal files, from CSU Chico State, MBK Engineers, KSN Engineers, Siegfried Engineers, Malani & Associates, Green Mountain Engineers, and DCC Engineers. Processing work done by CA DWR, Division of Engineering, Geodetic Branch, Geospatial Data Support Section, specifically by Arina Ushakova (Research Data Analyst I), and initial QC by Joel Dudas (Senior Engineer, Water Resources).

This dataset provides attributed geospatial and tabular information for identifying and querying flight lines of interest for the Airborne Visible InfraRed Imaging Spectrometer-Classic (AVIRIS-C) and Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) Facility Instrument collections. It includes attributed shapefile and GeoJSON files containing polygon representation of individual flights lines for all years and separate KMZ files for each year. These files allow users to visualize and query flight line locations using Geographic Information System (GIS) software. Tables of AVIRIS-C and AVIRIS-NG flight lines with attributed information include dates, bounding coordinates, site names, investigators involved, flight attributes, associated campaigns, and corresponding file names for associated L1B (radiance) and L2 (reflectance) files in the AVIRIS-C and AVIRIS-NG Facility Instrument Collections. Tabular information is also provided in comma-separated values (CSV) format.

Analysis of ‘Delta In-Channel Islands’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/5cd67f4f-ca7d-44b0-881c-741b0d70381a on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Data contains historical polygons of in-channel islands within the Sacramento San Joaquin Delta. Data consists of merged datasets from 1929, 1940, 1949, 1952, 1995, 2002, and 2017. The 2017 polygons are digitized from the 2017 Delta LiDAR imagery by the Division of Engineering, Geomatics Branch, Geospatial Data Support Section. The older pre-2017 polygons were all digitized by staff in the Delta Levees Program. Data can be queried for a single year or date range using the 'Year' field. Historical data was compiled and merged from datasets provided by the Delta Levees program. Data coverage differs between years. Absences or gaps in historical data may occur. Older acquisitions generally have a smaller footprint than recent imagery acquisitions. The 2017 in-channel islands cover the Legal Delta, and also include Chipps Island. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.1, dated September 11, 2019. DWR makes no warranties or guarantees — either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to the official GIS steward as available and appropriate at gis@water.ca.gov.

--- Original source retains full ownership of the source dataset ---

This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes.No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary.The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices.Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust.These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation.The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.These data have been made publicly available from an authoritative source other than this Atlas and data should be obtained directly from that source for any re-use. See the original metadata from the authoritative source for more information about these data and use limitations. The authoritative source of these data can be found at the following location: https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-790442341The BIA Indian Lands dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. This data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support. Please feel free to contact us at 1-877-293-9494 geospatial@bia.gov

Unfortunately, the provided README for the ckanext-dwgviewer extension lacks specific details about its functionality and features. Based on the name, it is likely that this extension enables CKAN to preview and handle DWG (drawing) files, a common file format for CAD (Computer-Aided Design) drawings. This would enhance CKAN's ability to manage and share geospatial and engineering data. Key Features (Inferred): DWG File Preview: The extension probably renders a preview of DWG files directly within the CKAN interface. DWG Metadata Extraction: Metadata, such as author, creation date, or layers, could be extracted from DWG files upon upload and stored as part of the dataset metadata. Format Support: Supports DWG files, and potentially related CAD formats. Integration with existing viewers Integration with open-source libraries or viewers enabling DWG file viewing Use Cases (Inferred): Engineering and Construction: Agencies involved in civil engineering, infrastructure projects, or construction can share design and as-built drawings through CKAN. Geospatial Data Management: Organizations dealing with maps, GIS data, or urban planning can publish and share DWG-based spatial information. Data Publishing for CAD: Institutions managing CAD datasets can support visualization and metadata browsing through a CKAN deployment. Technical Integration (Based on Standard CKAN Extension Practices): The ckanext-dwgviewer plugin is installed like a normal CKAN extension; by adding the plugin it is assumed the extension will integrate by automatically interpreting available resources with the appropriate file type, or by providing upload fields to load the file type and relevant metadata. This requires installation by following the given instructions, including installation of dependencies, activating the plugin and adding to the CKAN configuration file settings. Benefits & Impact (Inferred): Using the ckanext-dwgviewer can make CKAN more useful for organizations that manage geospatial, engineering, or CAD data. Users can discover, preview, and download DWG files directly from the CKAN interface, improving data accessibility and collaboration.

Polygons of active and historic large lot development in unincorporated Pierce County. Please read metadata (https://matterhorn.piercecountywa.gov/GISmetadata/pdbplandev_large_lots.html) for additional information. Any use or data download constitutes acceptance of the Terms of Use (https://matterhorn.piercecountywa.gov/Disclaimer/PierceCountyGISDataTermsofUse.pdf).

FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines). These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13)

Data contains historical polygons of in-channel islands within the Sacramento San Joaquin Delta. Data consists of merged datasets from 1929, 1940, 1949, 1952, 1995, 2002, and 2017. The 2017 polygons are digitized from the 2017 Delta LiDAR imagery by the Division of Engineering, Geomatics Branch, Geospatial Data Support Section. The older pre-2017 polygons were all digitized by staff in the Delta Levees Program. Data can be queried for a single year or date range using the 'Year' field. Historical data was compiled and merged from datasets provided by the Delta Levees program. Data coverage differs between years. Absences or gaps in historical data may occur. Older acquisitions generally have a smaller footprint than recent imagery acquisitions. The 2017 in-channel islands cover the Legal Delta, and also include Chipps Island. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.1, dated September 11, 2019. DWR makes no warranties or guarantees — either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to the official GIS steward as available and appropriate at gis@water.ca.gov.

FEMA Framework Basemap datasets comprise six of the seven FGDC themes of geospatial data that are used by most GIS applications (Note: the seventh framework theme, orthographic imagery, is packaged in a separate NFIP Metadata Profile): cadastral, geodetic control, governmental unit, transportation, general structures, hydrography (water areas & lines. These data include an encoding of the geographic extent of the features and a minimal number of attributes needed to identify and describe the features. (Source: Circular A16, p. 13)

Planning, Engineering & Permitting - GIS Mapping files

This is the authors’ version of the work. It is based on a poster presented at the Wageningen Conference on Applied Soil Science, http://www.wageningensoilmeeting.wur.nl/UK/ Cite as: Bosco, C., de Rigo, D., Dewitte, O., Montanarella, L., 2011. Towards the reproducibility in soil erosion modeling: a new Pan-European soil erosion map. Wageningen Conference on Applied Soil Science “Soil Science in a Changing World”, 18 - 22 September 2011, Wageningen, The Netherlands. Author’s version DOI:10.6084/m9.figshare.936872 arXiv:1402.3847

Towards the reproducibility in soil erosion modeling:a new Pan-European soil erosion map

Claudio Bosco ¹, Daniele de Rigo ¹ ² , Olivier Dewitte ¹, Luca Montanarella ¹ ¹ European Commission, Joint Research Centre, Institute for Environment and Sustainability,Via E. Fermi 2749, I-21027 Ispra (VA), Italy² Politecnico di Milano, Dipartimento di Elettronica e Informazione,Via Ponzio 34/5, I-20133 Milano, Italy

Soil erosion by water is a widespread phenomenon throughout Europe and has the potentiality, with his on-site and off-site effects, to affect water quality, food security and floods. Despite the implementation of numerous and different models for estimating soil erosion by water in Europe, there is still a lack of harmonization of assessment methodologies. Often, different approaches result in soil erosion rates significantly different. Even when the same model is applied to the same region the results may differ. This can be due to the way the model is implemented (i.e. with the selection of different algorithms when available) and/or to the use of datasets having different resolution or accuracy. Scientific computation is emerging as one of the central topic of the scientific method, for overcoming these problems there is thus the necessity to develop reproducible computational method where codes and data are available. The present study illustrates this approach. Using only public available datasets, we applied the Revised Universal Soil loss Equation (RUSLE) to locate the most sensitive areas to soil erosion by water in Europe. A significant effort was made for selecting the better simplified equations to be used when a strict application of the RUSLE model is not possible. In particular for the computation of the Rainfall Erosivity factor (R) the reproducible research paradigm was applied. The calculation of the R factor was implemented using public datasets and the GNU R language. An easily reproducible validation procedure based on measured precipitation time series was applied using MATLAB language. Designing the computational modelling architecture with the aim to ease as much as possible the future reuse of the model in analysing climate change scenarios is also a challenging goal of the research.

References [1] Rusco, E., Montanarella, L., Bosco, C., 2008. Soil erosion: a main threats to the soils in Europe. In: Tóth, G., Montanarella, L., Rusco, E. (Eds.), Threats to Soil Quality in Europe. No. EUR 23438 EN in EUR - Scientific and Technical Research series. Office for Official Publications of the European Communities, pp. 37-45 [2] Casagrandi, R. and Guariso, G., 2009. Impact of ICT in Environmental Sciences: A citation analysis 1990-2007. Environmental Modelling & Software 24 (7), 865-871. DOI:10.1016/j.envsoft.2008.11.013 [3] Stallman, R. M., 2005. Free community science and the free development of science. PLoS Med 2 (2), e47+. DOI:10.1371/journal.pmed.0020047 [4] Waldrop, M. M., 2008. Science 2.0. Scientific American 298 (5), 68-73. DOI:10.1038/scientificamerican0508-68 [5] Heineke, H. J., Eckelmann, W., Thomasson, A. J., Jones, R. J. A., Montanarella, L., and Buckley, B., 1998. Land Information Systems: Developments for planning the sustainable use of land resources. 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Abstr. 13, 3351 [13] Bollinne, A., Laurant, A., and Boon, W., 1979. L’érosivité des précipitations a Florennes. Révision de la carte des isohyétes et de la carte d’erosivite de la Belgique. Bulletin de la Société géographique de Liége 15, 77-99 [14] Ferro, V., Porto, P and Yu, B., 1999. A comparative study of rainfall erosivity estimation for southern Italy and southeastern Australia. Hydrolog. Sci. J. 44 (1), 3-24. DOI:10.1080/02626669909492199 [15] de Santos Loureiro, N. S. and de Azevedo Coutinho, M., 2001. A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal. J. Hydrol. 250, 12-18. DOI:10.1016/S0022-1694(01)00387-0 [16] Rogler, H., and Schwertmann, U., 1981. Erosivität der Niederschläge und Isoerodentkarte von Bayern (Rainfall erosivity and isoerodent map of Bavaria). Zeitschrift fur Kulturtechnik und Flurbereinigung 22, 99-112 [17] Nearing, M. A., 1997. 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