dc.contributor.author |
van der Zel, DW
|
|
dc.date.accessioned |
2008-08-13T12:32:51Z |
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dc.date.available |
2008-08-13T12:32:51Z |
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dc.date.issued |
1988 |
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dc.identifier.citation |
van der Zel, DW. 1988. Forest map of southern Africa with the aid of LANDSAT imagery. National Scientific Programmes Unit: CSIR, SANSP Report 154, pp 83 |
en |
dc.identifier.isbn |
0 7988 4500 7 |
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dc.identifier.uri |
http://hdl.handle.net/10204/2377
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dc.description.abstract |
Even after 300 years of indigenous forest protection as well as 100 years of plantation forestry, no forestry map of South Africa was available. The development and availability of LANDSAT images in the early 1970s opened up possibilities to use satellite data. A project was initiated in 1981 to compile a forestry map of southern Africa (Republic of South-Africa, Swaziland, Lesotho, Ciskei, Venda, Transkei and Bophuthatswana). A portfolio of 31 maps on a scale of 1:250 000 has now been produced. Three examples of these form part of this report. A combination of LANDSAT and field data was used to bring about this set of maps. A number of teething problems were experienced, e.g. mountain shadow; distinction between pine and wattle; no tree canopy before about 10 years of plantation growth. In this report the procedure is discussed in detail. Problems are stated and solutions offered. Both sophisticated computer classification and qualitative approaches were used. The experience related in this report will be of considerable benefit to many other researchers and planners contemplating the inclusion of satellite data in their particular application fields |
en |
dc.language.iso |
en |
en |
dc.publisher |
National Scientific Programmes Unit: CSIR |
en |
dc.relation.ispartofseries |
CSIR |
en |
dc.subject |
SANSP |
en |
dc.subject |
Forests |
en |
dc.subject |
Maps |
en |
dc.subject |
LANDSAT |
en |
dc.title |
Forest map of southern Africa with the aid of LANDSAT imagery |
en |
dc.type |
Report |
en |
dc.identifier.apacitation |
van der Zel, D. (1988). <i>Forest map of southern Africa with the aid of LANDSAT imagery</i> (CSIR). National Scientific Programmes Unit: CSIR. Retrieved from http://hdl.handle.net/10204/2377 |
en_ZA |
dc.identifier.chicagocitation |
van der Zel, DW <i>Forest map of southern Africa with the aid of LANDSAT imagery.</i> CSIR. National Scientific Programmes Unit: CSIR, 1988. http://hdl.handle.net/10204/2377 |
en_ZA |
dc.identifier.vancouvercitation |
van der Zel D. Forest map of southern Africa with the aid of LANDSAT imagery. 1988 [cited yyyy month dd]. Available from: http://hdl.handle.net/10204/2377 |
en_ZA |
dc.identifier.ris |
TY - Report
AU - van der Zel, DW
AB - Even after 300 years of indigenous forest protection as well as 100 years of plantation forestry, no forestry map of South Africa was available. The development and availability of LANDSAT images in the early 1970s opened up possibilities to use satellite data. A project was initiated in 1981 to compile a forestry map of southern Africa (Republic of South-Africa, Swaziland, Lesotho, Ciskei, Venda, Transkei and Bophuthatswana). A portfolio of 31 maps on a scale of 1:250 000 has now been produced. Three examples of these form part of this report. A combination of LANDSAT and field data was used to bring about this set of maps. A number of teething problems were experienced, e.g. mountain shadow; distinction between pine and wattle; no tree canopy before about 10 years of plantation growth. In this report the procedure is discussed in detail. Problems are stated and solutions offered. Both sophisticated computer classification and qualitative approaches were used. The experience related in this report will be of considerable benefit to many other researchers and planners contemplating the inclusion of satellite data in their particular application fields
DA - 1988
DB - ResearchSpace
DP - CSIR
KW - SANSP
KW - Forests
KW - Maps
KW - LANDSAT
LK - https://researchspace.csir.co.za
PY - 1988
SM - 0 7988 4500 7
T1 - Forest map of southern Africa with the aid of LANDSAT imagery
TI - Forest map of southern Africa with the aid of LANDSAT imagery
UR - http://hdl.handle.net/10204/2377
ER -
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en_ZA |