Integration of ALOS PALSAR and Landsat Data for Land Cover and Forest Mapping in Northern Tanzania

Land cover and forest mapping supports decision makers in the course of making informed decisions for implementation of sustainable conservation and management plans of the forest resources and environmental monitoring. This research examines the value of integrating of ALOS PALSAR and Landsat data for improved forest and land cover mapping in Northern Tanzania. A separate and joint processing of surface reflectance, backscattering and derivatives (i.e., Normalized Different Vegetation Index (NDVI), Principal Component Analysis (PCA), Radar Forest Deforestation Index (RFDI), quotient bands, polarimetric features and Grey Level Co-Occurrence Matrix (GLCM) textures) were executed using Support Vector Machine (SVM) classifier. The classification accuracy was assessed using a confusion matrix, where Overall classification Accuracy (OA), Kappa Coefficient (KC), Producer’s Accuracy (PA), User’s Accuracy (UA) and F1 score index were computed. A two sample t-statistics was utilized to evaluate the influence of different data categories on the classification accuracy. Landsat surface reflectance and derivatives show an overall classification accuracy (OA = 86%). ALOS PALSAR backscattering could not differentiate the land cover classes efficiently (OA = 59%). However, combination of backscattering, and derivatives could differentiate the land cover classes properly (OA = 71%). The attained results suggest that integration of backscattering and derivative has potential of utilization for mapping of land cover in tropical environment. Integration of backscattering, surface reflectance and their derivative increase the accuracy (OA = 97%). Therefore it can be concluded that integration of ALOS PALSAR and optical data improve the accuracies of land cover and forest mapping and hence suitable for environmental monitoring

Pulo: Mga kasalukuyang kaalaman, kaugalian, kagawian at kalaganapan ng mga sakit na may kaugnayan sa tubig-dagat

Itong case study ng Pulo ay naglalayon maglahad ng kasalukuyang kaalaman, kaugalian, at kagawian ng mga pamamahay sa Pulo na nakaaapekto sa tubig-dagat. Ilalahad din ang kalaganapan ng mga sakit na may kaugnayan sa tubig.Ang pag-aaral na ito ay gumamit ng community case study approach . Ni-limitahan nito ang sampol sa Pulo. Ang mga pamamaraang ginamit ay ang pagsusuri ng dokumento, survey interview, key informant interview at obserbasyon. Ang mga instrumentong ginamit ay ang mga health report, talatanungan at checklist.Sa mga nakuhang kasalukuyang kaalaman, kaugalian at kagawian, mas matimbang ang mga nakasasamang epekto sa tubig-dagat. Hindi naman matiyak ang resultang nakuha sa kalusugan. Ganoon pa man, nakabuo pa rin ng isang ilustrasyon at mga hypothesis sa pag-aaral na ito

Remote Sensing Analysis of Lake Dynamics in Semi-Arid Regions: Implication for Water Resource Management. Lake Manyara, East African Rift, Northern Tanzania

We show here that a remote sensing (RS) approach is a cost-efficient and accurate method to study water resource dynamics in semi-arid areas. We use a MODIS surface reflectance dataset and a Modified Normalized Difference Water Index (MNDWI) to map the variability of Lake Manyara’s water surface area using a histogram segmentation technique. The results indicate that Lake Manyara’s water surface coverage has been decreasing from 520.25 km2 to 30.5 km2 in 2000 and 2011 respectively. We observe that the lake water surface and the lake water balance displayed a similar pattern from 2006 to 2009, probably initiated by heavy rainfall and low temperature in 2006. Lake water surface area appears to have an inverse relationship with MODIS evapotranspiration (ET) and MODIS land surface temperature (LST). We imply that recent fluctuations of Lake Manyara’s surface water area are a direct consequence of global and regional climate fluctuations. We therefore conclude that, by means of RS it is possible to provide timely and up-to-date water resource information to managers and hence enable optimized and operational decisions for sustainable management and conservation. We suggest that the method employed in this research should be applied to monitor water resource dynamics provided that remotely sensed datasets are available

Water Balance Modeling in a Semi-Arid Environment with Limited in situ Data Using Remote Sensing in Lake Manyara, East African Rift, Tanzania

The purpose of this paper is to estimate the water balance in a semi-arid environment with limited in situ data using a remote sensing approach. We focus on the Lake Manyara catchment, located within the East African Rift of northern Tanzania. We use a distributed conceptual hydrological model driven by remote sensing data to study the spatial and temporal variability of water balance parameters within the catchment. Satellite gravimetry GRACE data is used to verify the trends of the inferred lake level changes. The results show that the lake undergoes high spatial and temporal variations, characteristic of a semi-arid climate with high evaporation and low rainfall. We observe that the Lake Manyara water balance and GRACE equivalent water depth show comparable trends; a decrease after 2002 followed by a sharp increase in 2006–2007. Our modeling confirms the importance of the 2006–2007 Indian Ocean Dipole fluctuation in replenishing the groundwater reservoirs of East Africa. We thus demonstrate that water balance modeling can be performed successfully using remote sensing data even in complex climatic settings. Despite the small size of Lake Manyara, GRACE data showed great potential for hydrological research on smaller un-gauged lakes and catchments in similar semi-arid environments worldwide. The water balance information can be used for further analysis of lake variations in relation to soil erosion, climate and land cover/land use change as well as different lake management and conservation scenarios.www.mdpi.com/journal/remotesensin

A concept test for Revicon provita

The Proprietary Business Division (PROBUS) of UNILAB, Inc. plans to launch a vitamin that will target the smoking population of the country. The proponents of this study were given the task of conducting a study which would determine the concept acceptance of the product REVICON PROVITA. In order to achieve this, three (3) Focus Group Discussions (FGDs) were conducted. The participants were divided into Male Smokers, Female Smokers, and Both Female and Male Non-Smokers. The results of the study show the product does have potential in terms of consumer trial. Both Smokers and Non-Smokers are willing to try the product. The participants also gave their insights on what label may be used for the product, what bottle or container, how much they are willing to pay for one capsule of the product. However, knowledge of the product is needed and its effectiveness must be ensured. Therefore, the company must formulate an awareness must be ensured. Therefore, the company must formulate an awareness campaign so that there will not be any misconceptions on what REVICON PROVITA can do. This paper thus suggests a few strategies which the company may use in order to properly market the product

Geospatial based model for malaria risk prediction in Kilombero valley, South-eastern, Tanzania.

BackgroundMalaria continues to pose a major public health challenge in tropical regions. Despite significant efforts to control malaria in Tanzania, there are still residual transmission cases. Unfortunately, little is known about where these residual malaria transmission cases occur and how they spread. In Tanzania for example, the transmission is heterogeneously distributed. In order to effectively control and prevent the spread of malaria, it is essential to understand the spatial distribution and transmission patterns of the disease. This study seeks to predict areas that are at high risk of malaria transmission so that intervention measures can be developed to accelerate malaria elimination efforts.MethodsThis study employs a geospatial based model to predict and map out malaria risk area in Kilombero Valley. Environmental factors related to malaria transmission were considered and assigned valuable weights in the Analytic Hierarchy Process (AHP), an online system using a pairwise comparison technique. The malaria hazard map was generated by a weighted overlay of the altitude, slope, curvature, aspect, rainfall distribution, and distance to streams in Geographic Information Systems (GIS). Finally, the risk map was created by overlaying components of malaria risk including hazards, elements at risk, and vulnerability.ResultsThe study demonstrates that the majority of the study area falls under moderate risk level (61%), followed by the low risk level (31%), while the high malaria risk area covers a small area, which occupies only 8% of the total area.ConclusionThe findings of this study are crucial for developing spatially targeted interventions against malaria transmission in residual transmission settings. Predicted areas prone to malaria risk provide information that will inform decision-makers and policymakers for proper planning, monitoring, and deployment of interventions