A spatial map layer of soil type (Australian Soil Classification) for Victoria. The harmonised map consists of 3,300 land units (totaling about 225,000 polygons) derived from around 100 soil and land surveys carried out in Victoria over the past 70 years. The land units have been attributed according to the Australian Soil Classification (Order and Suborder levels of the classification scheme) based on their likely dominant soil type. Particular attention was given to harmonising land units across survey boundaries. A reliability index has been assigned to each land unit based on the quality and relevance of the originating survey, providing a qualitative reliability measure to support interpretation and data use.

Soil site data contained in the Victorian Soil Information System (VSIS), and information on the Victorian Resources Online (VRO) website and original study reports have been combined with landscape knowledge to develop the new maps. Data from approximately 10,000 existing sites recorded, mostly recorded in the VSIS have been used.

The soil type is based on land mapping conducted at different times, at variable scale, and for different purposes. Land units are therefore of variable scale and quality in relation to the soil they are representing. Many units will be comprised of multiple soil types and a range of soil properties, and local variability (e.g. at paddock scale level) can also sometimes be high. The mapping, therefore, is intended to represent the dominant, or most prevalent, broad soil type within the map unit. It is therefore adequate for regional or state-wide overviews but may not often be accurate enough for localised or within-farm assessments. For more detailed soil and land information, users are advised to refer to the original land study for any given map unit (e.g. via Victorian Resources Online website).

This dataset comprises soil property mapping across the whole State of Victoria at 6 prescribed depths. The set depths are 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to …Show full descriptionThis dataset comprises soil property mapping across the whole State of Victoria at 6 prescribed depths. The set depths are 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to 200 cm. The mapped soil properties are pH (1:5 water), EC (dS/m), % clay and soil organic carbon (SOC %). The dataset has been created by the Understanding Soil and Farming Systems project (CMI 102922)and is referred to as Version 1.0 of the Victorian Digital Soil Map (VIC DSM 1.0). Soil point data stored in the Victorian Soil Information System (VSIS) from over 6,000 sites has been standardised to the set depths (using equal area splines or a value weighting derived from the proportional contruibution of each sample to the depth class). This processed data was used to attribute soil land units from a collection of surveys (mapped at 1:100k or better) collated to provide the best map unit coverage across the State. Only data from sites that match the soil type of the dominant soil within the land unit being attributed were used. Sites and land units were assigned an Australian Soil Classification (to the Suborder level) to aid this process. The raw profile data stored in the VSIS (as of March 2013) used to produce these maps were: pH data were either laboratory based (1:5 soil/water suspension) or field pH (Raupach and Tucker 1959). Clay % was laboratory derived particle size data (PSA all methods), or converted field observations of texture class (McKenzie et al. 2000). Organic Carbon measurements methods was either Walkley and Black or Heanes wet oxidation. Electical Conductivity was 1:5 soil/water extract (dS/m). The data is available in polygonal format (i.e. the land units) with soil property median value, standard deviation and assignment qualifier attributes. ESRI grids in ascii format at 100 m cell resolution have been generated from the attributed land unit polygon dataset for each soil property at each depth interval. The assignment qualifiers have been created in order to provide a level of quality evaluation for the soil property assignment to each polygon. Reliability maps generated from these qualifiers have been produced together with each soil property map. The strength of these products is our ability to leverage on the significant investment in soil site and survey mapping data procurement and the capture of tacit knowledge of former soil surveyors. A revised version of these digital soil maps is due to be released at the end of 2014.

Abstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. A spatial dataset of soil and landform classification in Gippsland. The map units are broad packages' of land - divided primarily on the basis of soil type, landform pattern and geology. It contains soil and land information at a scale of 1:100 000 for all land in the region. The dataset has been derived from a combination of …Show full descriptionAbstract This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied. A spatial dataset of soil and landform classification in Gippsland. The map units are broadpackages' of land - divided primarily on the basis of soil type, landform pattern and geology. It contains soil and land information at a scale of 1:100 000 for all land in the region. The dataset has been derived from a combination of past studies and has been collated primarily by Ian Sargeant and Mark Imhof from 1994 to 2013. Data from older surveys have also been included in this consolidated dataset. Mapping in east and northern Gippsland regions is restricted to freehold lands. Webpages on Victorian Resources Online provide a description of each of the map units and indicate source studies used to define the map unit. In June 2013 a dominant soil type was assigned to each unit (by David Rees, Mark Imhof and Ian Sargeant) to facilitate the creation of a digital soil map of Victoria. Australian Soil Classification (Order and SubOrder) have been included in the dataset's attribute table. At the map scale of this dataset soil-landform units are not homogeneous. For each defined soil-landform unit, the number and proportion of landforms and soil types will vary. Representative sites and their associated profile properties are recorded on the Victorian Resources Online website (http://vro.depi.vic.gov.au/dpi/vro/wgregn.nsf/pages/wg_soil_detailed). Importantly it should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only. Purpose Showing soil types and extent within the Gippsland region. Dataset History Data Set Source: Remote Sensed (Radiometrics, DEM), Expert Interviews, Soil site data, Field work, earlier land studies Collection Method: Field work, API, and derived with other datasets Processing Steps: Survey of existing soil and land unit mapping data from earlier studies. New field work and observations to collection soil, land and land use information. Combining old and new data with radiometrics and DEM in GIS. Additional Metadata: The detail available in the current datasets is good for their mapping scale but is not sufficient to provide landscape analysis at finer scales and should not therefore be used to plan land use strategies at more detailed scales (1:25 000 and larger) unless additional soil and land survey is captured to enhance map line work and subdivide the map units. It should be noted that soil attributes (for example texture, sodicity, pH) are expected to vary between acquired soil sites. As the variability of soil attributes within a map unit is difficult to predict, it is important to note that representative soils should be used as a guide only. http://vro.depi.vic.gov.au/dpi/vro/wgregn.nsf/pages/wg_soil_detailed Dataset Citation Victorian Department of Environment and Primary Industries (2014) Land units of the Gippsland region of Victoria. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/5c7f4d52-8e46-4bda-a5c8-70124aaad67b.

This dataset comprises soil property mapping across the whole State of Victoria at 6 prescribed depths. The set depths are 0 to 5 cm, 5 to 15 cm, 15 to 30 cm, 30 to 60 cm, 60 to 100 cm and 100 to 200 cm. The mapped soil properties are pH (1:5 water), EC (dS/m), % clay and soil organic carbon (SOC %). The dataset has been created by the Understanding Soil and Farming Systems project (CMI 102922)and is referred to as Version 1.0 of the Victorian Digital Soil Map (VIC DSM 1.0). Soil point data stored in the Victorian Soil Information System (VSIS) from over 6,000 sites has been standardised to the set depths (using equal area splines or a value weighting derived from the proportional contruibution of each sample to the depth class). This processed data was used to attribute soil land units from a collection of surveys (mapped at 1:100k or better) collated to provide the best map unit coverage across the State. Only data from sites that match the soil type of the dominant soil within the land unit being attributed were used. Sites and land units were assigned an Australian Soil Classification (to the Suborder level) to aid this process. The raw profile data stored in the VSIS (as of March 2013) used to produce these maps were: pH data were either laboratory based (1:5 soil/water suspension) or field pH (Raupach and Tucker 1959). Clay % was laboratory derived particle size data (PSA all methods), or converted field observations of texture class (McKenzie et al. 2000). Organic Carbon measurements methods was either Walkley and Black or Heanes wet oxidation. Electical Conductivity was 1:5 soil/water extract (dS/m). The data is available in polygonal format (i.e. the land units) with soil property median value, standard deviation and assignment qualifier attributes. ESRI grids in ascii format at 100 m cell resolution have been generated from the attributed land unit polygon dataset for each soil property at each depth interval. The assignment qualifiers have been created in order to provide a level of quality evaluation for the soil property assignment to each polygon. Reliability maps generated from these qualifiers have been produced together with each soil property map. The strength of these products is our ability to leverage on the significant investment in soil site and survey mapping data procurement and the capture of tacit knowledge of former soil surveyors. A revised version of these digital soil maps is due to be released at the end of 2014.

This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were? manually digitized from a 1:500,000 map from EMBRAPA originally published in 1983. Oxisols and Ultisols are the predominant soil types in the basin, encompassing 47% and 24% of the total drainage area, respectively. Entisols cover 14%, Alfisols 13% and Eptisols 2% of the basin (Ballester et al., 2003). One data file is provided in ESRI ArcGIS Shapefile format compressed into a single zip file (*.zip).

These polygons represent approximate native soil sub-bases and derived textures based on digitized maps from the Geological Survey of Victoria (c. 1956). Soils are expected to be extensively modified from these types throughout Melbourne due to extensive disturbance, and cut and fill associated with the city's development.

This dataset depicts a national map of available ASS mapping and ASS qualification inferred from surrogate datasets. ASS mapping is classified with a nationally consistent legend that includes risk assessment criteria and correlations between Australian and International Soil Classification Systems.

Existing digital datasets of ASS mapping have been sourced from each coastal state and territory and combined into a single national dataset. Original state classifications have been translated to a common national classification system by the respective creators of the original data and other experts. This component of the Atlas is referred to as the “Coastal” ASS mapping. The remainder of Australia beyond the extent of state ASS mapping has been “backfilled” with a provisional ASS classification inferred from national and state soils, hydrography and landscape coverages. This component is referred to as the “Inland” ASS mapping.

For the state Coastal ASS mapping, the mapping scale of source data ranges from 1:10K aerial photography in SA to 1:250K vegetation mapping in WA and NT, with most East coast mapping being at the 1:100K scale. For the backfilled inferred Inland ASS mapping the base scale is 1:2.5 million (except Tas.) overlaid with 1:250k hydography. As at 06/08, the Tasmanian inland mapping has been re-modelled using superior soil classification map derived from 1:100k landscape unit mapping.

NOTE: This is composite data layer sourced from best available data with polygons depicted at varying scales and classified with varying levels of confidence. Great care must be taken when interpreting this map and particular attention paid to the “map scale” and confidence rating of a given polygon. It is stressed that polygons rated with Confidence = 4 are provisional classifications inferred from surrogate data with no on ground verification. Also some fields contain a “-“, denoting that a qualification was not able to be made, usually because a necessary component of source mapping coverage did not extend to the given polygon. Lineage: Coastal ASS component:

Existing state CASS mapping was received and processed to varying degrees to conform to the NatCASS national ASS classification system. Spatially, all datasets were reprojected from their original projections to geographic GDA94. Classification of state mapping polygons to the NatCASS classification system was as follows. In the case of SA, NSW, Qld and WA it was a matter of directly translating the original state ASS classifications to the NatCASS classifications. These translations were undertaken by the creators of the state data and other experts within the respective states.

Due to the more broad classifications of the original Vic and Tas ASS mapping, polygons for these two states were initially translated to a NatCASS classification group (eg Tidal, Non-Tidal) by the data custodians then subsequently differentiated further through intersecting with other layers. These included the 3 second SRTM DEM and North Coast Mangrove mapping GIS datasets. The former being used to differentiate within the Non-Tidal zones (ie classes Ae-j and Be-j) and the latter used to differentiate the Tidal zones (ie Ab-d, Bb-d).

Mapping of the Tidal-Zone classes was augmented for all states except SA and NSW with 1:100K Coastal Waterways Geomorphic Habitat Mapping (Geoscience Australia). This dataset was used to infer additional areas of subaqueous material in subtidal wetland (class Aa & Ba) and Intertidal Flats (class Ab & Bb).

Inland ASS component:

Provisional Inland ASS classifications are derived from National and (in the case of Tasmania) state soil classification coverages combined with 1:250K series 3 Hydrography and Multiresolution Valley Bottom Floor Index (MrVBF).

A publicly available database and interactive map presenting ambient background soil concentrations and other soil characteristics for Victoria, Australia.

Soil and landscape mapping was collated from Western Australia, South Australia, Victoria, and New South Wales, in combination with latest Digital Soil Mapping products for Australia (Soil and Landscape Grid of Australia) as the basis for a new sandy soils map. A staged map compilation process was undertaken to combine all these available datasets into one uniform map that retains integrity of legacy contextual mapping information.

The key steps undertaken in the mapping of sandy soils include: 1. Define an agricultural region area of interest for this study; 2. Collate available soil-landscape mapping datasets across Australia (including state and national); 3. Assemble and edit existing mapping to form a new sandy soil map for agricultural regions of the study area; 4. Review and revise this mapping in response to feedback from NCST members including state/territory experts.

Maps were revised and updated with input from members of the Digital Soil Assessment Working Group and members of the National Committee on Soil and Terrain. While efforts were made to include these suggestions, it was not possible to refine the map indefinitely, and therefore editing ceased on the 23^rd of February 2021. Due to the variations in scale, mapping techniques, representation, and attribution across Australia, the use of these maps for such purposes as mapping sandy soils across southern Australia proved difficult.

From the new sandy soils map we were able to identify agricultural areas of sandy soils: (Western Australia - 10.611Mha; South Australia - 2.479Mha; New South Wales - 1.867Mha; Victoria - 0.864Mha and Tasmania - 0.215Mha). Nationally there were 16.039Mha of sandy soil identified which is considerably higher than the 11Mha from previous estimates.

This research is funded by the CRC for High Performance Soils and supported by the Cooperative Research Centres program, an Australian Government initiative.

Additional funding and in-kind support are provided by: Murdoch University, PIRSA, Federation University Australia, West Midlands Group and AORA. Contributions from Richard Bell, Amanda Schapel and David Davenport have been critical in shaping the logic and key considerations in mapping sandy soils and benefits of amelioration. James Hall is also thanked for providing insights into sandy soils for South Australia and the formation of the new Arenosol soil order for Australia.

We would also like to acknowledge the contributions of the Digital Soil Assessment Working Group and members of the National Committee on Soil and Terrain that provided valuable feedback on the approach used to map sandy soils.

Administrative and structural details on data files:

• A shapefile (Sandy_soil_map_aglands.shp) is provided for use in a Geographic Information System (GIS). This should be useable in commercial (e.g. ArcGIS) and open source software packages (e.g. QGIS). The shapefile data coordinate system is WGS1984 geographic.
• A RTF file is also provided which includes information on the data fields and content of the shapefile for users. Note that abbreviations for the Australian Soil Classification Order and Suborder fields (as 2021) were used.

Associated publication:

Robinson N, Pope R, Liddicoat C, Holmes K, Griffin E, Kidd D, Jenkins B, Rees D, Searle R. (2021) Sandy Soils: Organic and clay amendments to improve the productivity of sandy soils. Detailed plan for mapping and grouping of sands. Soil CRC Project 3.3.003. Cooperative Research Centre for High Performance Soils.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable soil organic carbon (soc) which measures the mass of carbon in proportion to the mass of the soil. (mass divided by mass.)From Agriculture Victoria: Soil carbon provides a source of nutrients through mineralisation, helps to aggregate soil particles (structure) to provide resilience to physical degradation, increases microbial activity, increases water storage and availability to plants, and protects soil from erosion.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for soil organic carbon are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Soil organic carbon content in the fine earth fraction in g/kgCell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for soc were used to create this layer. You may access soil organic carbon values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

Soil Survey PublicationsON 00 - Preliminary Soil Survey of Southwestern Ontario (1923)ON 02 - Soil Survey Report Elgin County (1929)ON 03 - Soil Survey Report Kent County (1930)ON 05 - Soil Survey Report Welland County (1935)ON 06 - Soil Survey Report Middlesex County (1931)ON 07 - Soil Survey Report Carleton County (1944)ON 08 - Reconnaissance Soil Survey of Parts of Northwestern Ontario (1944)ON 09 - Soil Survey Report Durham County (1946)ON 10 - Soil Survey Report Prince Edward County (1948)ON 11 - Soil Survey Report Essex County (1949)ON 12 - Soil Survey Report Grenville County (1949)ON 13 - Soil Survey Report Huron County (1952)ON 14 - Soil Survey Report Dundas County (1952)ON 15 - Soil Survey Report Perth County (1952)ON 16 - Soil Survey Report Bruce County (1954)ON 17 - Soil Survey Report Grey County (1954)ON 18 - Soil Survey Report Peel County (1953)ON 19 - Soil Survey Report York County (1955)ON 20 - Soil Survey Report Stormont County (1954)ON 21 - Soil Survey Report New Liskeard - Englehart Area (1952)ON 22 - Soil Survey Report Lambton County (1957)ON 23 - Soil Survey Report Ontario County (1956)ON 24 - Soil Survey Report Glengarry County (1957)ON 25 - Soil Survey Report Victoria County (1957)ON 26 - Soil Survey Report Manitoulin Island (1959)ON 27 - Soil Survey Report Hastings County (1962)ON 28 - Soil Survey Report Oxford County (1961)ON 28a - Soil Survey Report Oxford County Upgrade (1996)ON 29 - Soil Survey Report Simcoe County (1962)ON 30 - Soil Associations of Southern Ontario (1964)ON 31 - Soil Survey Report Parry Sound County (1962)ON 32 - Soil Survey Report Wentworth County (1965)ON 33 - Soil Survey Report Prescott Russell County (1962)ON 34 - Soil Survey Report Lincoln County (1963)ON 35 - Soil Survey Report Wellington County (1963)ON 36 - Soil Survey Report Lennox Addington County (1963)ON 37 - Soil Survey Report Renfrew County (1964)ON 38 - Soil Survey Report Dufferin County (1964)ON 39 - Soil Survey Report Frontenac County (1966)ON 40 - Soil Survey Report Lanark County (1967)ON 41 - Soil Survey Report Leeds County (1968)ON 42 - Soil Survey Report Northumberland County (1974)ON 43 - Soil Survey Report Halton County (1971)ON 44 - Soil Survey Report Waterloo County (1971)ON 44a - Soil Survey Report Waterloo County Upgrade (1996)ON 45 - Soil Survey Report Peterborough County (1981)ON 46 - Soils of Timmins-Noranda-Rouyn (1978) - MathesonON 46 - Soils of Timmins-Noranda-Rouyn (1978) - PamourON 46 - Soils of Timmins-Noranda-Rouyn (1978) - TimminsON 46 - Soils of Timmins-Noranda-Rouyn (1978) - Iroquois FallsON 46 - Soils of Timmins-Noranda-Rouyn (1978) - Kirkland LakeON 46 - Soils of Timmins-Noranda-Rouyn (1978) - Porquis JunctionON 46 - Soils of Timmins-Noranda-Rouyn (1978) - Timmins / Noranda / Rouyn AreaON 48 - Soils of Thunder Bay Area (1981) - Jarvis RiverON 48 - Soils of Thunder Bay Area (1981) - LoonON 48 - Soils of Thunder Bay Area (1981) - ParthON 48 - Soils of Thunder Bay Area (1981) - SunshineON 48 - Soils of Thunder Bay Area (1981) - Thunder BayON 48 - Soils of Thunder Bay Area (1981) - Thunder Bay AreaON 48 - Soils of Thunder Bay Area (1981) - Kakabeka FallsON 48 - Soils of Thunder Bay Area (1981) - Onion LakeON 48 - Soils of Thunder Bay Area (1981) - Pigeon RiverON 49 - Soils of Sudbury Area (1983) - CapreolON 49 - Soils of Sudbury Area (1983) - ChelmsfordON 49 - Soils of Sudbury Area (1983) - ConistonON 49 - Soils of Sudbury Area (1983) - Copper CliffON 49 - Soils of Sudbury Area (1983) - EspanolaON 49 - Soils of Sudbury Area (1983) - Lake TemagamiON 49 - Soils of Sudbury Area (1983) - MilnetON 49 - Soils of Sudbury Area (1983) - NoelvilleON 49 - Soils of Sudbury Area (1983) - SudburyON 49 - Soils of Sudbury Area (1983) - VernerON 49 - Soils of Sudbury Area (1983) - Whitefish FallsON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - AlgomaON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Blind River - Sault Ste Marie AreaON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Bruce MinesON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Dean LakeON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Ile ParisienneON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Iron BridgeON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - MadawansonON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Pancake BayON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Sault Ste MarieON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - SearchmountON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - SpanishON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - St. Joseph IslandON 50 - Soils of Blind River - Sault Ste Marie Area (1983) - Whisky LakeON 51 - Soils of Fort Frances - Rainy River Area (1984) - Arbor VitaeON 51 - Soils of Fort Frances - Rainy River Area (1984) - EmoON 51 - Soils of Fort Frances - Rainy River Area (1984) - Fort FrancesON 51 - Soils of Fort Frances - Rainy River Area (1984) - Fort Frances - Rainy River AreaON 51 - Soils of Fort Frances - Rainy River Area (1984) - Northwest BayON 51 - Soils of Fort Frances - Rainy River Area (1984) - Rainy RiverON 52 - Soils of Kenora-Dryden-Pointe Du Bois Area (1987) - Crowduck LakeON 52 - Soils of Kenora-Dryden-Pointe Du Bois Area (1987) - DrydenON 52 - Soils of Kenora-Dryden-Pointe Du Bois Area (1987) - KeewatinON 52 - Soils of Kenora-Dryden-Pointe Du Bois Area (1987) - Vermilion BayON 53 - Soils of Pukaskwa National Park (1985) - PukaskwaON 54 - Soils of North Bay Area (1986) - KioskON 54 - Soils of North Bay Area (1986) - Marten LakeON 54 - Soils of North Bay Area (1986) - MattawaON 54 - Soils of North Bay Area (1986) - North BayON 54 - Soils of North Bay Area (1986) - PowassonON 54 - Soils of North Bay Area (1986) - Sturgeon FallsON 54 - Soils of North Bay Area (1986) - TemiscamingON 55 - Soil Survey Report Brant County (1989)ON 56 - Soil Survey Report Middlesex County (1992)ON 57 - Soil Survey Report Regional Municipality Haldimand Norfolk (1984)ON 58 - Soil Survey Report Regional Municipality Ottawa Carleton (1987)ON 59 - Soils of Gogama Area (1986) - CharltonON 59 - Soils of Gogama Area (1986) - ElkON 59 - Soils of Gogama Area (1986) - GogamaON 60 - Soil Survey Report Regional Municipality Niagara (1989)ON 61 - Soil Survey Report Chapleau Foleyet (1984)ON 63 - Soil Survey Report Elgin County (1992)ON 64 - Soil Survey Report Kent County Upgrade (1994)ON 90 - Soil Survey Report Ville Marie (1990)ON 98 - Location and Extent of the Soils of Southern Ontario (1998)

This NOCA landslide data repository host the driver code and data files needed to run Landlab's LandslideProbability component, which models annual shallow landslide probability in a steep mountainous region in northern Washington, U.S.A. The model application covers North Cascade National Park Complex (NOCA), using 30-m grid resolution over 2,700 km2. The model use the classic infinite slope, limited equilibrium model driven by contemporary climatology from the Variable Infiltration Capacity (VIC) macroscale hydrology model. Readily available topographic, geophysical, and land cover data are provided to calculate the factor-of-safety stability index in a Monte Carlo simulation, which explicitly accounts for parameter uncertainty.

Data used for this analysis are spatial data on landscape characteristics for NOCA. They include soil, geology, vegetation, topography, and landform data that can be used for quantitative landslides hazard assessment. Elevation was acquired from National Elevation Dataset (NED) at 30 m grid scale; other datasets are matched to scale and location. Slope was derived from the elevation file as "tan theta". Specific contributing area represents the 'upstream' area draining to each cell divided by the cell's width (so minimum value is 30 m). Landform data was developed by Jon Riedel of National Park Service. Landslides were extracted from these data identified as "mass wasting" events. Land use and land cover (LULC) data were acquired from USGS National land Cover Data (NLCD) based on 2011 Landsat satellite data and grouped into eight general categories. Cohesion represent total cohesion, which is equivalent to root cohesion in this application; soils are assumed to be primarily cohesionless, lacking “true cohesion” because of their low clay content in this mountain terrain. Root cohesion is based on the LULC referenced to a look-up table within this resource: (https://www.hydroshare.org/resource/a771ba9bbae24ed8b4673c945fc321a3/). Soil depth comes from Soil Survey Geographic Database (SSURGO) maintained by NRCS processed as soil survey depth-to-restricted layer (weighted-average aggregation) within each soil map unit. An alternative modeled soil depth (SD) described in the accompany paper is also provided, but revisions in the driver notebook would be required to reference this file to see adjusted results. Transmissivity was derived from the soil survey saturated hydraulic conductivity (depth averaged) multiplied by depth-to-restricted layer for each soil map unit; another T file based on the model soil depth is also provided. However, the model can be run using hydraulic conductivity using data file provided to calculate T. All soils within this watershed are sandy loam or loamy sand; therefore, soil surface texture was used as an indicator of internal angle of friction (phi). A header file is provided to understand the spatial details of the ASCII files and to facilitate capability with GIS. Spatial reference for raster mapping is NAD_1983, Albers conical equal area projection.

The model run archived in this resource runs with Landlab version 1.1.0 . The component code (landslide_probability9Jun17.py) is provided as an archive to run a notebook that replicates results in Strauch et al., (in review) . As Landlab is developed with newer versions, the notebook and/or provided component code may need updating to run properly. To run the notebook to replicate results, use the resource "Regional Landslide Hazard Using Landlab - NOCA Observatory", HydroShare resource: https://www.hydroshare.org/resource/07a4ed3b9a984a2fa98901dcb6751954/

The map title is Victoria. Tactile map scale. 2 centimetres = 3 kilometres North arrow pointing to the north. Victoria and surrounding area. Juan de Fuca Strait to the south and the Strait of Georgia to the east, are shown with a wavy symbol to indicate water. Main roads, routes 1, 14, 17. A circle with a dot in the middle to indicate a bus station is located in the south of the city. A circle with a cross indicates a Via Rail station located south of the city. A circle with the shape of an airplane indicates an airport located north of the city. A railway line symbol is shown from the rail station and goes west then north. A dashed line indicates a ferry route. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

The map title is Victoria. Tactile map scale. 2.0 centimetres = 100 metres North arrow pointing to the north. Main streets are coded with type and Braille expanded in the PDF file. Secondary streets are not labelled. Victoria downtown details are coded with type and Braille expanded in the PDF file. Victoria Inner Harbour is located at the upper left and shown with a wavy symbol to indicate water. The ferry route is shown as a dashed line. Tactile maps are designed with Braille, large text, and raised features for visually impaired and low vision users. The Tactile Maps of Canada collection includes: (a) Maps for Education: tactile maps showing the general geography of Canada, including the Tactile Atlas of Canada (maps of the provinces and territories showing political boundaries, lakes, rivers and major cities), and the Thematic Tactile Atlas of Canada (maps showing climatic regions, relief, forest types, physiographic regions, rock types, soil types, and vegetation). (b) Maps for Mobility: to help visually impaired persons navigate spaces and routes in major cities by providing information about streets, buildings and other features of a travel route in the downtown area of a city. (c) Maps for Transportation and Tourism: to assist visually impaired persons in planning travel to new destinations in Canada, showing how to get to a city, and streets in the downtown area.

Classified Grid. Digital soil map of South West Victoria pH (Calcium Chloride) 0-5cm Lower Predicted mean

These maps were prepared for the Murray Valley Resources Survey Committee. The 1946 maps were prepared by the Regional Planning Division, Ministry of Post-War Reconstruction, and the 1947 maps were prepared by the Division of Regional Development, Ministry of National Development.

The maps cover the following regional areas of New South Wales, South Australia and Victoria: New South Wales - Upper Murray, Central Murray, Murray-Darling; Victoria - Upper Murray, Upper Goulburn, Goulburn, Loddon, Mallee; South Australia - Pyap, Sturt, and Fleurieu.

The maps show climate, electricity supply, geology and mineral resources, land use, postal services, secondary industries, soil types, transport, water resources, etc. A full listing is available.


(SR Map Nos.52610-23, 52735-41). 21 maps.

Note:
This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.