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Assessing edge effect on the spatial distribution of selected forest biochemical properties derived using the Worldview data in Dukuduku forests, South Africa
Author(s) -
Mutanga Onisimo,
Dube Timothy,
Omer Galal
Publication year - 2019
Publication title -
african journal of ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.499
H-Index - 54
eISSN - 1365-2028
pISSN - 0141-6707
DOI - 10.1111/aje.12604
Subject(s) - spatial distribution , random forest , environmental science , species distribution , distribution (mathematics) , nitrogen , forestry , physical geography , ecology , geography , remote sensing , mathematics , biology , chemistry , habitat , computer science , mathematical analysis , organic chemistry , machine learning
This work explores the potential of the high‐resolution WorldView‐2 sensor in quantifying edge effects on the spatial distribution of selected forest biochemical properties in fragmented Dukuduku forest in KwaZulu‐Natal, South Africa. Specifically, we sought to map fragmented patches within forested areas in Dukuduku area, using very high spatial resolution WorldView‐2 remotely sensed data and to statistically determine the effect of these fragmented patches on the spatial distribution of selected forest biochemical properties. Edge effects on carbon, LAI and foliar nitrogen were quantified based on the models derived by Omer et al. ( IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2015, 8, 4825). Edge effect statistical results on the spatial distribution of carbon, LAI and nitrogen showed significant ( α = 0.05) variations with change in distance from fragmented patches (>150 m 2 ). Forest foliar carbon concentrations significantly ( p ‐value = 0.016) increased from 44.8% to 45.3% with increasing distance (25–375 m) from fragmented patches. A similar trend was observed for LAI. Nevertheless, for nitrogen the results show that its concentration significantly ( p = 0.016) decreased with increase in distance from the fragmented patches. Overall, the findings of this work underscore the invaluable potential and strength of WorldView‐2 data set in assessing edge effect on the spatial distribution of selected forest biochemical properties.