n Southern African Forestry Journal - Modeling woody vegetation resources using Landsat TM imagery in northern Namibia : scientific paper
|Article Title||Modeling woody vegetation resources using Landsat TM imagery in northern Namibia : scientific paper|
|© Publisher:||South African Institute of Forestry (SAIF)|
|Journal||Southern African Forestry Journal|
|Author||Alex Verlinden and Risto Laamanen|
|Publication Date||Jul 2006|
|Pages||27 - 39|
|Keyword(s)||Forestry, Kalahari woodland, Remote sensing, Tree biomass, Tree cover and Tree volume|
In 1995 a forest inventory covering northern Namibia was initiated, based on stratified systematic field sampling of plots with a radius of up to 30 m. In these plots detailed tree parameters were measured. Due to security problems the most important wooded parts of the area could not be covered. This study investigated whether Landsat TM imagery could be used to estimate woody vegetation parameters. As the existing field sampling method did not result in significant relationships between pixel values of different bands and tree cover, two sampling methods of different design were tested. Both resulted in statistically significant relationships between tree cover and pixel values of mainly band 4 reflectance of Landsat TM. Regression equations to estimate cover and volumes were obtained. The increased size of the sample plots in both methods was the main reason for improved correlations. The relation between tree cover and Landsat TM band 4 was influenced by fire scars and patches of heavy grazing. Estimated tree cover and volumes obtained by remote sensing were compared with volume estimates obtained by field inventories. All fell within 95 % confidence limits of the field estimates. The results suggest that Landsat TM imagery is suitable for estimating tree cover, volumes and biomass on a regional scale for dry semideciduous Kalahari woodland vegetation. More research is needed to better understand the impacts of fire and heavy grazing on cover estimates and future inventories should use larger sample plots.
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