Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe: exploring the effect of the red-edge band in forest carbon stocks estimation

T.W. Gara; A. Murwira; H. Ndaimani

doi:10.1080/10106049.2015.1041563

Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe: exploring the effect of the red-edge band in forest carbon stocks estimation

T.W. Gara^*, A. Murwira, H. Ndaimani

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

21 Citations (Scopus)

19 Downloads (Pure)

Original language	English
Pages (from-to)	176-192
Journal	Geocarto international
Volume	31
Issue number	2
DOIs	https://doi.org/10.1080/10106049.2015.1041563
Publication status	Published - 2016

Keywords

n/a OA procedure
ITC-ISI-JOURNAL-ARTICLE

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1080/10106049.2015.1041563

Cite this

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title = "Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe: exploring the effect of the red-edge band in forest carbon stocks estimation",

keywords = "n/a OA procedure, ITC-ISI-JOURNAL-ARTICLE",

author = "T.W. Gara and A. Murwira and H. Ndaimani",

year = "2016",

doi = "10.1080/10106049.2015.1041563",

language = "English",

volume = "31",

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journal = "Geocarto international",

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publisher = "Taylor & Francis",

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T2 - exploring the effect of the red-edge band in forest carbon stocks estimation

AU - Gara, T.W.

AU - Murwira, A.

AU - Ndaimani, H.

PY - 2016

Y1 - 2016

KW - n/a OA procedure

KW - ITC-ISI-JOURNAL-ARTICLE

U2 - 10.1080/10106049.2015.1041563

DO - 10.1080/10106049.2015.1041563

M3 - Article

SN - 1010-6049

VL - 31

SP - 176

EP - 192

JO - Geocarto international

JF - Geocarto international

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