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Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa

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dc.contributor.author Van Deventer, Heidi
dc.contributor.author Cho, Moses
dc.contributor.author Mutanga, O
dc.date.accessioned 2021-07-19T06:56:46Z
dc.date.available 2021-07-19T06:56:46Z
dc.date.issued 2015-09
dc.identifier.citation Van Deventer, H., Cho, M. & Mutanga, O. 2015. Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa. http://hdl.handle.net/10204/12058 . en_ZA
dc.identifier.uri http://hdl.handle.net/10204/12058
dc.description.abstract Indigenous forests of South Africa occur in one of the smallest biomes covering less than 0.5% of the total surface area of the country. Regardless of the small and narrow extent of these forests, they offer a range of ecosystem services, such as fuel wood, construction material, food and medicine, especially for the poor. Mapping and monitoring these forests are crucial for their sustainability. Regular monitoring of vegetation composition and condition can be done through localised fieldwork, yet access may be difficult in mountainous terrain, or in swamp and mangrove forests, or where dangerous animals occur. Remote sensing technology offers a feasible alternative. The improved spatial and spectral resolution of space-borne sensors has enabled species mapping at canopy level, as well as assessing pigment and nutrients as indicators of vegetation health and condition. We studied six evergreen tree species found in the subtropical coastal, swamp and mangrove forests of the KwaZulu-Natal Province of South Africa over a period of four seasons: winter, spring, summer and autumn. We present the results and findings of our work, including: i) the ability to monitor pigments and nutrients over four seasons, using leaf-level data; ii) the ability to discriminate between these six species, using seasonal information at leaf level; iii) which bands were found to be important for these species over the four seasons; and iv) whether multispectral sensors, such as RapidEye, can be used to map these six species over four seasons. Our results indicate the importance of remote sensing in monitoring indigenous forests. en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri http://foris.fao.org/wfc2015/api/file/552dfa039e00c2f116f8e78e/contents/35a5b3ac-8314-4424-9252-4f34ce4739b3.pdf en_US
dc.source XIV World Forestry Congress, Durban, South Africa, 7-11 September 2015 en_US
dc.subject Remote sensing en_US
dc.subject Forest monitoring en_US
dc.subject Tree species discrimination en_US
dc.title Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa en_US
dc.type Conference Presentation en_US
dc.description.pages 8 en_US
dc.description.note Paper presented at the XIV World Forestry Congress, Durban, South Africa, 7-11 September 2015 en_US
dc.description.cluster Smart Places
dc.description.impactarea en_US
dc.identifier.apacitation Van Deventer, H., Cho, M., & Mutanga, O. (2015). Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa. http://hdl.handle.net/10204/12058 en_ZA
dc.identifier.chicagocitation Van Deventer, Heidi, Moses Cho, and O Mutanga. "Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa." <i>XIV World Forestry Congress, Durban, South Africa, 7-11 September 2015</i> (2015): http://hdl.handle.net/10204/12058 en_ZA
dc.identifier.vancouvercitation Van Deventer H, Cho M, Mutanga O, Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa; 2015. http://hdl.handle.net/10204/12058 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Van Deventer, Heidi AU - Cho, Moses AU - Mutanga, O AB - Indigenous forests of South Africa occur in one of the smallest biomes covering less than 0.5% of the total surface area of the country. Regardless of the small and narrow extent of these forests, they offer a range of ecosystem services, such as fuel wood, construction material, food and medicine, especially for the poor. Mapping and monitoring these forests are crucial for their sustainability. Regular monitoring of vegetation composition and condition can be done through localised fieldwork, yet access may be difficult in mountainous terrain, or in swamp and mangrove forests, or where dangerous animals occur. Remote sensing technology offers a feasible alternative. The improved spatial and spectral resolution of space-borne sensors has enabled species mapping at canopy level, as well as assessing pigment and nutrients as indicators of vegetation health and condition. We studied six evergreen tree species found in the subtropical coastal, swamp and mangrove forests of the KwaZulu-Natal Province of South Africa over a period of four seasons: winter, spring, summer and autumn. We present the results and findings of our work, including: i) the ability to monitor pigments and nutrients over four seasons, using leaf-level data; ii) the ability to discriminate between these six species, using seasonal information at leaf level; iii) which bands were found to be important for these species over the four seasons; and iv) whether multispectral sensors, such as RapidEye, can be used to map these six species over four seasons. Our results indicate the importance of remote sensing in monitoring indigenous forests. DA - 2015-09 DB - ResearchSpace DP - CSIR J1 - XIV World Forestry Congress, Durban, South Africa, 7-11 September 2015 KW - Remote sensing KW - Forest monitoring KW - Tree species discrimination LK - https://researchspace.csir.co.za PY - 2015 T1 - Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa TI - Using remote sensing for tree species discrimination in the narrow coastal forests of KwaZulu-Natal, South Africa UR - http://hdl.handle.net/10204/12058 ER - en_ZA
dc.identifier.worklist 24673 en_US


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