SADC LC Metadata

SADC Landcover Dataset

Metadata also available as

Metadata:

Identification_Information
Data_Quality_Information
Spatial_Data_Organization_Information
Spatial_Reference_Information
Entity_and_Attribute_Information
Distribution_Information
Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: Environmentek, CSIR
Publication_Date: 2002-06-30
Publication_Time: Unknown
Title: SADC Landcover Dataset
Geospatial_Data_Presentation_Form: vector digital data
Online_Linkage:

Description:

Abstract:: A significant proportion of southern Africa has already been mapped in terms of national land cover (vegetation status and current land-use) at 1:250 000 scale from satellite imagery. This data is available in digital, spatial formats. The information is of key strategic importance at both national (e.g. food security) and international (e.g. global climate modelling) scales for environmental management. In general, this national level data has been produced independently of any other regional mapping initiative, by local organizations, often assisted by international aid agencies. To-date, none of these individual inventories have been integrated into an easily accessible, single dataset that would provide, detailed, cross-border coverage of a large part of SADC. Many of the country-level datasets are regarded as national "assets", and are covered by various copyright and commercial data distribution agreements. For this reason, the SADC-level land cover dataset has been compiled in such a manner so as not to conflict with, or infringe on, any national-level copyrights, commercialisation models, or distribution restrictions. The methodology that has been employed to compile the regional database involved both spatial and classification resampling.
Purpose:: The objective of the project was to create a comprehensive, strategic regional inventory of land cover data available for the SADC region. The project is a regional initiative which includes inputs from land cover data custodians of many SADC countries.
Supplemental_Information:: The SADC land cover database can be used to provide base-line information for regional research and environmental management applications. The land cover database will be a resource for the region as a whole to be used as a marketing tool to the more detailed original information. It will provide significant regional and international exposure for the individual remote sensing and GIS mapping facilities within each participating SADC country, as will as illustrate the technical capabilities within the SADC region.

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2002-06-30

Currentness_Reference: ground condition

Status:

Progress: Complete
Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: 16.360001
East_Bounding_Coordinate: 42.000000
North_Bounding_Coordinate: -1.000767
South_Bounding_Coordinate: -34.830002

Keywords:

Theme:

Theme_Keyword_Thesaurus: Regional
Theme_Keyword: land cover
Theme_Keyword: land
Theme_Keyword: cover
Theme_Keyword: digital datasets

Place:

Place_Keyword: SADC
Place_Keyword: Southern African Development Community
Place_Keyword: South Africa
Place_Keyword: Tanzania
Place_Keyword: Zimbabwe
Place_Keyword: Zambia
Place_Keyword: Botswana
Place_Keyword: Namibia
Place_Keyword: Mozambique
Place_Keyword: Malawi
Place_Keyword: Swaziland
Place_Keyword: Lesotho
Place_Keyword: SADC-FANR

Access_Constraints:

The regional land cover database is a free data resource available in CD format from participating SADC countries or downloadable from the internet (FTP).

Use_Constraints:

Whilst all possible care and attention has been taken in the production of the SADC land cover database, neither the CSIR or any of their respective sub-organisations, or any of the participating SADC countries, accept any liability what-so-ever for any perceved inaccuracies or misrepresentations of the information presented within the digital data or accompanying report. Any boundaries either implied or inferred within the digital dataset do not have any legal status what-so-ever.

Point_of_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Jillian Muller
Contact_Organization: CSIR, Environmentek

Contact_Position: GIS Specialist

Contact_Address:

Address_Type: mailing address
Address: P.O. Box 395
City: Pretoria
State_or_Province: Gauteng
Postal_Code: 0001
Country: South Africa

Contact_Voice_Telephone: 012 841 3992

Contact_Facsimile_Telephone: 012 841 2628

Contact_Electronic_Mail_Address: jmuller@csir.co.za

Hours_of_Service: 08H00-16H30

Data_Set_Credit:

A significant proportion of southern Africa has already been mapped using satellite imagery; therefore the project was conducted in close collaboration with SADC-based national mapping agencies. The project has been funded by the South African Department of Arts, Culture, Science and Technology (DACST) under their Regional S&T programme. Support for the project has been received from the Food, Agriculture and Natural Resources (FANR) Development Unit in Harare, Zimbabwe.

Native_Data_Set_Environment:

Microsoft Windows 2000 Version 5.0 (Build 2195) Service Pack 1; ESRI ArcCatalog 8.1.1.649

Cross_Reference:

Citation_Information:

Originator: Environmentek, CSIR
Publication_Date: 2002-06-30
Publication_Time: Unknown
Title: SADC Regional Land Cover Database
Geospatial_Data_Presentation_Form: map
Online_Linkage:

Data_Quality_Information:

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator: Mapping company: Satellibild (Sweden)
Publication_Date: 1993
Publication_Time: Unknown
Title: Malawi Landcover
Geospatial_Data_Presentation_Form: vector digital data
Other_Citation_Details:: Captured from Landsat TM images. Date of source images: 1990-1991. Mapping method: Manual mapping from paper copy images.

Source_Scale_Denominator: 1:250 000

Type_of_Source_Media: LANDSAT 7 images

Source_Citation_Abbreviation: Malawi

Source_Information:

Source_Citation:

Citation_Information:

Originator: Mapping company: IGN/CENECARTA.
Publication_Date: end 1999
Publication_Time: Unknown
Title: Mozambique landcover
Geospatial_Data_Presentation_Form: vector digital data
Other_Citation_Details:: Captured from Landsat TM images. Date of source images: 1996/1997/1998/1999. Mapping method: Manual interpretation from paper copy images.

Source_Scale_Denominator: 1:250 000

Type_of_Source_Media: LANDSAT 7 images

Source_Citation_Abbreviation: Mozambique

Source_Information:

Source_Citation:

Citation_Information:

Originator: Mapping company: CSIR/ARC.
Publication_Date: March 1999
Publication_Time: Unknown
Title: South Africa landcover
Geospatial_Data_Presentation_Form: vector digital data
Other_Citation_Details:: Captured from Landsat TM images. Date of source images: 1994/1995. Mapping method: Manual interpretation from paper copy images.

Source_Scale_Denominator: 1 : 250 000

Type_of_Source_Media: LANDSAT 7 images

Source_Citation_Abbreviation: South Africa, Lesotho, and Swaziland

Source_Information:

Source_Citation:

Citation_Information:

Originator: Mapping company: Hunting Techical Services (UK).
Publication_Date: mid 1997
Publication_Time: Unknown
Title: Tanzania landcover
Geospatial_Data_Presentation_Form: vector digital data
Other_Citation_Details:: Captured from Landsat TM images. Date of source images: 1994/1995. Mapping method: Manual interpretation from paper copy images.

Source_Scale_Denominator: 1 : 250 000

Type_of_Source_Media: LANDSAT 7 images

Source_Citation_Abbreviation: Tanzania

Source_Information:

Source_Citation:

Citation_Information:

Originator:: Mapping company: Forestry Commission and German Development Co-operation.
Publication_Date: 1997
Publication_Time: Unknown
Title: Zimbabwe landcover
Geospatial_Data_Presentation_Form: vector digital data
Other_Citation_Details:: Captured from Landsat TM images. Date of source images: 1992. Mapping method: Manual interpretation from paper copy images.

Source_Scale_Denominator: 1 : 250 000

Type_of_Source_Media: LANDSAT 7 images

Source_Citation_Abbreviation: Zimbabwe

Process_Step:

Process_Description:: Existing land cover datasets (as compiled by the SADC-based national mapping agencies) have been sourced from the national data custodians. For most countries, data was captured at approximately 1 : 250 000 scale. To facilitate copyright and commercialisation issues, individual datasets have been downgraded both spatially and classification wise. Spatial degradation occured through rasterisation of data to a 1 x 1 km horizontal resolution. A standardized classification system was developed which collated detailed land use classes into more generalised categories.

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Vector

Point_and_Vector_Object_Information:

SDTS_Terms_Description:

SDTS_Point_and_Vector_Object_Type: G-polygon
Point_and_Vector_Object_Count: 96360

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Geographic:

Latitude_Resolution: 0.000000
Longitude_Resolution: 0.000000
Geographic_Coordinate_Units: Decimal degrees

Geodetic_Model:

Horizontal_Datum_Name: wgs84
Ellipsoid_Name: wgs84
Semi-major_Axis: 6378206.400000
Denominator_of_Flattening_Ratio: 294.978698

Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: sadc_lc
Entity_Type_Definition: Description of land cover type.

Attribute:

Attribute_Label: FID

Attribute_Definition: Internal feature number.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:: Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: Shape

Attribute_Definition: Feature geometry.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain: Coordinates defining the features.

Attribute:

Attribute_Label: AREA

Attribute:

Attribute_Label: PERIMETER

Attribute:

Attribute_Label: SADC_LC_

Attribute:

Attribute_Label: SADC_LC_ID
Attribute_Domain_Values:

Attribute:

Attribute_Label: SADC_CLASS

Attribute_Definition: Types of land cover.

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: Forest
Enumerated_Domain_Value_Definition:: All wooded areas with greater than 70% (>70% SA & Mozambique; >80% Tanzania, Zimbabwe & Malawi) tree canopy cover, where the dominant canopy is greater than +/- 5 metres in height (minimum height) (>5m SA; >8m Mozambique; >15m Zimbabwe). Essentially indigenous tree species, growing under natural or semi-natural conditions (although it may include some localised areas of self-seeded exotic species). Excludes planted forests (and woodlots).

Enumerated_Domain:

Enumerated_Domain_Value: Woodland
Enumerated_Domain_Value_Definition:: All wooded areas with +/- 20 - 70% (10 - 70% SA & Mozambique; 20 - 80% Tanzania & Zimbabwe) tree canopy cover. A closed-to-open canopy community, typically consisting of a single tree canopy layer greater than +/- 5 metres in height (minimum) and a herb (grass) layer (>5m SA; 5-15m Zimbabwe). Essentially indigenous tree species, growing under natural conditions (thought it may include some localised areas of self-seeding exotic species). Excludes planted forests (and woodlots.)

Enumerated_Domain:

Enumerated_Domain_Value: Bushland
Enumerated_Domain_Value_Definition:: Shrub dominated communities typically composed of tall, woody, self-supporting, single and/or multi-stemmed plants (branching at or near the ground), with, in most cases no clearly definable structure. Total canopy cover >20% (>10% SA; >40% Mozambique; >20% Zimbabwe; >20% Tanzania), with canopy height < +/- 5metres (maximum) (2 - 5m SA; 3 - 7m Mozambique; 1 - 5m Zimbabwe). Essentially indigenous species, growing under natural conditions (although it may include some localised areas of self-seeded exotic species, especially along riparian zones).

Enumerated_Domain:

Enumerated_Domain_Value: Low shrubland
Enumerated_Domain_Value_Definition:: Shrub dominated communities dominated by low, woody, self-supporting, multi-stemmed plants branching at or near the ground, less than +/- 2m in height (maximum). Total tree cover < 1%. Essentially indigenous species, growing under natural or semi-natural conditions. (This class is only present in the SA and Mozambique datasets.).

Enumerated_Domain:

Enumerated_Domain_Value: Grassland
Enumerated_Domain_Value_Definition:: All areas of grassland with less than +/- 10% (10% SA, Mozambique & Zimbabwe; 10% Tanzania with scattered cropland in some areas) tree and/or shrub canopy cover, and greater than +/- 2% total vegetation cover. Dominated by grass-like, non-woody, rooted herbaceous plants.

Enumerated_Domain:

Enumerated_Domain_Value: Bare ground
Enumerated_Domain_Value_Definition:: Mainly natural areas of exposed sand, soil or rock with no, or very little vegetation cover (i.e. less than +/- 2% cover) during any time of the year, (excluding agricultural fields with no crop cover, opencast mines and quarries). Category also includes major erosion features (i.e. sheet and gully scars). Salt crusts in Tanzania are mapped as bare ground.

Enumerated_Domain:

Enumerated_Domain_Value: Plantation
Enumerated_Domain_Value_Definition:: All areas of systematically planted, human-managed tree resources, composed of primarily exotic species (including hybrids). Category includes both young and mature plantations that have been established for commercial timber production, seedling trials, and woodlots/ windbreaks. Exclude all non-timber based plantations such as tea and sisal, as well as orchards used in the production of citrus or nut crops.

Enumerated_Domain:

Enumerated_Domain_Value: Cultivation
Enumerated_Domain_Value_Definition:: Areas of land that are ploughed and/or prepared for raising crops (excluding timber production). The category includes areas currently under crop, fallow land, and land being prepared for planting. Either no remaining natural vegetation cover, or severely impacted in most cases.

Enumerated_Domain:

Enumerated_Domain_Value: Built-on
Enumerated_Domain_Value_Definition:: An area where there is a permanent concentration of people, buildings, and other man-made structures and activities, from village to city scale, including residential, commercial, and industrial (including opencast mines and quarries) land-uses. Small rural communities are often included within the surrounding land-cover category (i.e. subsistence/semi-commercial agriculture) if mapping scales do not permit identification of such settlements as individual features.

Enumerated_Domain:

Enumerated_Domain_Value: Open water
Enumerated_Domain_Value_Definition:: Areas of (generally permanent) open water. The category includes natural and man -made water bodies, which are either static or flowing, and fresh, brackish and salt water conditions. This category includes features such as rivers, dams (i.e. reservoirs), permanent pans, lakes, lagoons and coastal waters.

Enumerated_Domain:

Enumerated_Domain_Value: Wetland
Enumerated_Domain_Value_Definition:: Natural or artificial areas where the water level is at (or very near the land surface) on a permanent or temporary basis, typically covered in either herbaceous or woody vegetation cover. The category includes both fresh, brackish and salt water conditions. Examples include saltmarsh, pans (with non-permanent water cover), hydromorphic grasslands, reed-marsh and papyrus-swamp.

Enumerated_Domain:

Enumerated_Domain_Value: Ice-cap/Snow
Enumerated_Domain_Value_Definition:: Mainly natural areas covered with snow with no, or very little vegetation cover (i.e. less than +/- 2% cover) during any time of the year. This class is present in the Tanzania dataset, Mount Kilimanjaro.

Enumerated_Domain:

Enumerated_Domain_Value: Not classified
Enumerated_Domain_Value_Definition: Undefined class present in Malawi dataset.

Distribution_Information:

Distribution_Liability:

Whilst all possible care and attenton has been taken in the production of the SADC Land-Cover Database, neither the CSIR or any of their respective sub-organisations, or any of the participating SADC countries, accept any liability what-so-ever for any perceved inaccuracies or misrepresentations of the information presented within the digital data or accompanying report. Any boundaries either implied or inferred within the digital dataset do not have any legal status what-so-ever.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information: