A study was conducted to estimate the forest cover change, quantify and map tree above-ground carbon stock using Remote sensing and GIS techniques together with forest inventory. Landsat images of 1980, 1995 and 2010 acquired during dry season were used in the estimation of cover changes. Supervised image classification using Maximum Likelihood Classifier was performed in ERDAS Imagine software to analyze the images and further analysis was performed in Arc GIS 9.3 software. Stratified sampling procedure was used to select concentric inventory plots in Pugu Forest Reserve (PFR) and Kazimzumbwi Forest Reserve (KFR). Plots were laid according to NAFORMA, and the tree parameters in each sampling plot were collected. A Microsoft Excel spreadsheet was used to compute the above-ground biomass for each plot using an empirical equation relating wood basic density and tree height. The above-ground carbon was calculated using a conversion factor of 0.49. Geostatistical method in ArcGIS was used to analyze and map carbon. Results revealed that for the periods 1980-1995 and 1995-2010, Closed Forest in PFR decreased by 4.5% and 25.3% respectively, while for KFR, Closed Forest decreased by 11.9% and 31.3% respectively. The mean carbon density for PFR and KFR were respectively 5.72 tC/ha and 0.98 tC/ha while carbon stocks were 14 730.41 tC and 7 206.46 tC respectively. The revealed low carbon densities were attributable to decline in area under Closed Forest in the two Forest Reserves. The study recommends concerted efforts to enhance proper management of the forests so that the two forest reserves may contribute to REDD initiatives.

Rapid urbanization is threatening sustainable development of urban areas in Tanzania. Among the risks of rapid urbanization are Urban Heat Island (UHI) effect and climate change. While this has been noted, it is not known to what extent these risks are being realized in fast growing urban areas like Morogoro and other areas of similar geographic and climatic conditions. Therefore a study was conducted to assess the influence of urbanization on UHI and climate in Morogoro Municipality using remote sensing and climate data. Landsat imageries acquired in 1990, 2000 and 2015 were used to assess the change of impervious surface for the year 1990 to 2015 using a Classification and Regression Tree (CART). Radiant surface temperature and normalized difference vegetation index (NDVI) were derived from thermal band and reflectance bands respectively. Mann-Kendall test was used to analyze climate data for trends. Results revealed an increase of impervious surface (built up areas) from 9 km 2 in 1990 to 48 km 2 in 2000 and 82 km 2 in 2015; which is associated with UHI. UHI was not apparent in 1990, but was apparent in 2000 and 2015 with the temperature rise of 1.08˚C and 1.22˚C respectively. A linear relationship between radiant surface temperature (T B ) and percent Impervious Surface (ISA); and between T B and NDVI it revealed that NDVI is better indicator of variations in T B dynamics than percent ISA. Mann-Kendall test indicated a significant increasing trend in mean annual maximum temperature. The results imply that increasing ISA coupled with vegetation degradation has contributed to temperature rise and change. Consequently, Morogoro Municipality residents are likely to suffer heat stress due to rapid urbanization. It is recommended that education on the use of reflective surfaces should be given to the residents; and an effective master plan that protects vegetation should be in place.