Browsing by Author "Makandi, H. A"

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    Evaluation Of Remotely –Sensed Reflected and Emitted Energy for Monitoring Woodland Carbon in Liwale and Kilwa in Tanzania
    (University of Dar es salaam, 2019) Makandi, H. A
    Evaluation Of Remotely –Sensed Reflected and Emitted Energy for Monitoring Woodland Carbon in Liwale and Kilwa in Tanzania. Harun Atupele Makandi Phd (Natural Resource Assessment and Management University of Dar Es Salaam, Institute of Resource Assessments, 2019 A functional, cost-effective, and comprehensive system for respective measurement, resporting and verification (MRV) of forest carbon is important for sustainable forest management. Optical remote sensing datasets are critical for the development of such a system because they are free, and have a wall –to- wall and repetitive coverage. However, their accuracy in estimating woodland above-ground biomass and carbon (AGB and C) using mainstream methods is limited. One such method is using the magnitude of woodland greenness quantified using the normalized difference vegetation index (NDVI) draw from the imagery. NDVI saturates with increasing AGB and C, thereby limiting the range of estimations and accuracy. Also, the greenness fluctuates seasonally in tropical woodlands and evaluates the variable canopy moisture than the otherwise stable AGB and C. Cloud contamination on the datasets is another limitation. There is a need enhance the accuracy of the estimations to leverage the strengths of optical satellite data.The objective of this study was to develop of Forest Biomass Index (FoBI) to model the magnitude of the latent and sensible thermal fluxes prevalent in woodland conditions. The satellite-delivered surface temperature (Ts) and NDVI were combine in the modeling using the index. The magnitude of the fluxes correlates better with woodland AGC and is less prone to seasonal fluctuations than does that of the commonly used woodland greenness. The resulting FoBI maps were regressed with plot-based AGC measurement to estimate the AGC in Liwale and Kilwa districts in 2014 and 2018 and its change between the two years. The regression of the FoBI maps of 2014 with plot-based AGC returned R2 of 0.52 and 0.58 respectively. This compared favourably to R2 of 0.44 from pairing the annual NDVI map of 2014 wuith plot estimate. Also, the range of estimation of FoBI map was from 0 to 266 t ha-1 C, over twice that of NDVI. FoBI’s extended range indicates the elimination of the saturation problem at least for estimations of AGC IN miombo woodlands. Cloid cover was also eliminated by compositing multiple Ts and NDVI layers using the maximum value compositing (MVC) method. Using the regressed FoBI maps of 2014 and 2018, the mean carbon stock density I the study area was estimated to be 44 t ha-1 at 95% confidence level in both years. The total AGC was about 220 Mt in 2014 and 213 in 2018. Change analysis shows a decline of 6.6 Mt (ca.3%) of total AGC between the two years, indicating general stability of the AGC pools in Liwale and Kilwa. The developed FoBI enhances the accuracy of comprehensive and repetitive estimations of woodland AGC using free and widely available optical satellite datasets by eliminating the main cited problems with using them. Using FoBI , the monitoring reporting, and verification of woodland carbon stocking meeting international standards of reporting can be done.