Home /Search
Search datasets
We have found 13 datasets for the keyword " lha". You can continue exploring the search results in the list below.
Datasets: 106,057
Contributors: 42
Results
13 Datasets, Page 1 of 2
Local Health Area Boundaries
Local Health Area (LHA) boundaries; 2022 boundary configuration. The LHAs are a mutually exclusive and exhaustive classification of the land area in BC. LHAs are contiguous (land area is geographically adjacent) and fit within an existing geographical hierarchy structure, e.g., cannot violate higher-level geography boundaries such as the Health Service Delivery Areas (HSDA) and Health Authorities (HA).
Health Authority Boundaries
Health Authority (HA) boundaries; 2022 boundary configuration. The HAs are a mutually exclusive and exhaustive classification of the land area in BC. HAs are contiguous (land area is geographically adjacent) and fit within an existing geographical hierarchy, e.g., cannot violate lower-level geography boundaries such as the Health Service Delivery Areas (HSDA) and Local Health Area (LHA).
230 m agricultural mask from the Crop Condition Assessment Program (CCAP) - 2015
The following dataset correspond to the 230 m agricultural mask from Statistics Canada’s Crop Condition Assessment Program (CCAP). The mask have been generated from the classes 110 to 199 of the 2015 Agriculture and Agri-Food Canada’s landcover classification. The selection was then generalized to a spatial resolution of 230 m. The 2015 mask was used from the 2015 to the 2018 growing seasons inclusively.
Level curves
Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Ministry of Transportation (MOT) Highway Profile
A Highway Profile defines the number of through travel lanes, including passing and truck lanes, and whether the road is divided or not. It is a Linear feature
1 km agricultural mask from the Crop Condition Assessment Program (CCAP) - 2015
The following dataset correspond to the 1 km agricultural mask from Statistics Canada’s Crop Condition Assessment Program (CCAP). The mask have been generated from the classes 110 to 199 of the 2015 Agriculture and Agri-Food Canada’s landcover classification. The selection was then generalized to a spatial resolution of 1 km. The 2015 mask was used from the 2015 to the 2018 growing seasons inclusively.
FADM - Tree Farm License Agreement Boundary (TFL)
This view reflects what is in the Tree Farm License Agreement. Once an agreement is signed additions and deletions and changes occur that are not reflected in this layer. If you would like to see the current boundary please use the FADM - Tree Farm License Current View (TFL). Further information on Tree Farm Licenses please visit this website: https://www2.gov.bc.ca/gov/content?id=A93E6DFD8C164AD19CD17880450289A3 The spatial representation for a Tree Farm License, which is an agreement entered into under Part 3, Division 5 of the Forest Act which grants the rights to harvest timber. A tree farm licence has a term of 25 years and requires a management plan providing for the establishment, management, and harvesting of timber in a described area (Crown and private land) on a sustained or perpetual yield basis
Digital Soil Mapping
## Purpose The Ministry of Agriculture, Food and Agribusiness (OMAFA) is responsible for Ontario’s provincial soil maps and maintains and update them as necessary. Digital Soil Mapping (DSM) is a modern methodology using spatially explicit soils and environmental data to predict soil variation throughout a landscape at a high, consistent resolution. Digital soil maps are being rolled out throughout Ontario’s agricultural land base to update provincial soil maps. ## Reach Provincial soil maps are used in many decision-making processes including: * land use planning * land evaluation * farming practices * best management practices * ecological monitoring * land resource mapping Potential users of this data include: * farmers * certified crop advisors * conservation authorities * academic researchers * land use planners ## Potential impacts Digital soil maps provide more accurate and precise soils data and enables improved management of soil resources across multiple stakeholders. This allows for better decision making to maximize land use efficiency, improve economic efficiency of soil resources and promote soil health and soil conservation. ## Technical description Digital soil mapping combines geo-referenced soil observations with geo-referenced environmental layers to mathematically model soil variation as a function of environment variation. These models are based on well established, but often complex relationships, between soil properties and topography, biology, geology and hydrology.
Leading Group for the Cariboo Region
####Leading Group for the Cariboo Region (pinegroup or firgroup). #### 1. IDF - Fir Group: includes all forest polygons in NDT 4 (IDF and BG biogeoclimatic zones) that meet any of the following criteria: *a) Douglas-fir ( Fd or Fdi) leading or ponderosa pine leading; *b) Lodgepole pine leading, and Douglas-fir ( Fd or Fdi) or ponderosa pine greater than 15% in any inventory layer; *c) Trembling aspen leading, and Douglas-fir ( Fd or Fdi) or Ponderosa pine greater than 15% in any inventory layer, and spruce, red-cedar, cottonwood and birch less than 6% in any inventory layer; *d) No species information in inventory data (usually NSR stands), and inventory type group for pre-harvest stand or the current stand = 1, 2, 3, 4, 5, 6, 7, 8, 29, or 32 These inventory type groups correspond to the following species compositions F, FC, FCy, FH, FS, FPl, Fpy, FL, FDEcid, PlF and Py. If inventory type group=0 and pre-harvest inventory type is not available, classify the polygon as Pine Group. 2. IDF-Pl Group: includes all forest polygons in NDT 4 (IDF and BG biogeoclimatic zones) that do not meet the above definition for IDF-Fir Group.
Canadian Index of Multiple Deprivation
The Canadian Index of Multiple Deprivation (CIMD) is an area-based index which used 2016 Census of Population microdata to measure four key dimensions of deprivation at the dissemination area (DA)-level: residential instability, economic dependency, situational vulnerability and ethno-cultural composition.Using factor analysis, DA-level factor scores were calculated for each dimension. Within a dimension, ordered scores were assigned a quintile value, 1 through 5, where 1 represents the least deprived and 5 represents the most deprived.The CIMD allows for an understanding of inequalities in various measures of health and social well-being. While it is a geographically-based index of deprivation and marginalization, it can also be used as a proxy for an individual. The CIMD has the potential to be widely used by researchers on a variety of topics related to socio-economic research. Other uses for the index may include: policy planning and evaluation, or resource allocation.
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and topics that matter to you.
Please send us your feedback