Browsing by Author "Katani, J."

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Combining airborne laser scanning and Landsat data for statistical modeling of soil carbon and tree biomass in Tanzanian Miombo woodlands
(Springer Open, 2017-04-17) Egberth, M.; Nyberg, G.; Næsset, E.; Gobakken, T.; Mauya, E; Malimbwi, R.; Katani, J.; Chamuya, N.; Bulenga, G.; Olsson, H.
Background: Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations. Results: Cross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon. Conclusion: The results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.
Forest cover changes, stocking and removals under different decentralized forest management regimes in Tanzania
(Forest Research Ins, 2013) Mongo, C.; Kashaigili, J. J.; Malimbwi, R. E.; Kajembe, G. C.; Katani, J.; Eid, T.
By the end of the last century many countries including Tanzania moved from centralised towards decentralised forest management but little empirical evidence exists on how such changes have influenced forest conditions. The objective of this study was to provide insights on how decentralised approaches might influence forest resource conditions. Forest cover analyses from satellite images (1993, 2000 and 2009) and systematic sample plot inventories (2009) in two state forest reserves under joint forest management (JFM) and two village forest reserves under community-based forest management (CBFM) in Babati District, Tanzania were carried out. Based on the results, it was not possible to claim that the decentralised management had been successful in improving forest conditions. Proportions of closed woodland decreased significantly over time (from over 80 to 50-60% under JFM and from around 70 to almost 0% under CBFM. In all forests, numbers of régénérants were high, but proportions of larger trees were low and levels of removals (legal and illegal) were relatively high. In general the situation under JFM was better than under CBFM. Results of this study can be used by policymakers to assess the influence of decentralised forest management in Tanzania.