Production Rates of Mechanized Tree Felling Operations at Sao-Hill Forest Plantation, Tanzania

With the advancement of technology in forest operations, utilization of advanced machines in timber harvesting has been increasing in the last decades. However, in order to understand their contribution in harvesting operations, it is important to quantify their production rates. The findings will assist the development of timber harvesting plans. Therefore, this study was conducted at Sao-Hill Forest Plantation in Tanzania to determine time consumption and production rates of whole tree harvesting system using feller buncher. Regression models for predicting time consumption and production rates were also developed. The results showed that average productive felling time was 0.7 minutes per tree and production rates was 32.6 m3/h respectively. The production rates varied among tree size classes. For trees with diameter at breast height (dbh) of 10-19.9 the average production rates was 19.07 m3/h while for dbh class of 30-39.9 the production rate was 75.48 m3/h. Time consumption and production rates models were having Adjusted-R2 of 50% and 56 % respectively. Their relative root mean square errors (RMSEr), computed based on the predictions from 10 - fold across validation results, were 28.69% and 45.37%, respectively. Applicability of the models should be limited within the ranges from which they have been developed

Energy expenditure and physiological strain of pitsawing activity in Agroforestry

Heart rate is one of the accurate means to evaluate the physiological or functional demands of work on the worker. Hence the study was undertaken to know the workload of manual timber sawing activity. The results revealed that, the cardiac cost of work while sawing was 68.9 beats/min and during recovery was 25.09 beats/min. The average working heart rate during sawing was observed to be 135 (±17.83) beats/min and the average energy expenditure was 12.85 kj/min. The task was classified as heavy work. The energy spent by the topman to pull the saw upwards was 13.36 kj/min which was significantly higher than energy spent by the pitman (10.88 kj/min) when pulling the saw down wards. To minimize fatigue a rest allowance of 28.88 minutes for every 30 minutes of work is recommended. Reduction of workload load can be achieved by improving the hand tools and work environment. Keywords: Heart Rate, Cardiac Cost of Work, Rest Allowanc

The Influence of Performance Incentives in Performance Contracting on Service Delivery at the Ministry of Tourism, Kenya

Performance contracting is aimed at enhancing job satisfaction for the employees with the hope that their satisfaction would lead to improved job performance. Performance contracts originated from the perceptions that the performance of the public sector had consistently been falling below the expectations of the public. Performance incentives are also critical in the link between performance contracting and service delivery. This paper sought to establish the influence of performance incentives in service delivery in the tourism ministry. The study, based on contract theory employed descriptive survey design. The study population constituted 164 employees working in the ministry of tourism. Close ended questionnaires were used to collect data which was then analyzed and presented in form of tables and charts. The study found that performance incentive system does not enhance performance in the ministry of tourism. The study findings may be of interest and may enable the government know whether the reform initiative has positively impacted on the service delivery process and has been accepted or embraced by all the employees. The public service reform secretariat and performance contract steering committee may find the findings useful in deployment of employees in other service state corporations and government agencies yet to adopt the performance contracting. Keywords: Performance Incentives, Influence, Contract Theory, Performance Contractin

Modelling Above Ground Biomass Using Sentinel 2 and Planet Scope Data in Dense Tropical Montane Forests of Tanzania

Forest biomass estimation using field -based inventories at a large scale is challenging and generally entails large uncertainty in tropical regions. In this study, we investigated the performance of Sentinel 2 and Planet Scope data for above ground biomass (AGB) modelling, in the tropical rainforest of Tanzania. A total of 296 field inventory plots were measured across the west Usambara mountain forests. The results showed that, Sentinel 2-based model fitted using GLMs had better performance (cvRMSEr = 67.00 % and pseudo-R2= 20%) as compared to Planet Scope-based models (cvRMSEr = 72.1 % and pseudo-R2= 5.2%). Overall GLMs resulted into models with less prediction errors in contrast to random forest when using Sentinel 2 data. However, for the Planet Scope, there was marginal improvement when using random forest (cvRMSEr = 72.0%). Models that incorporated texture variables produced better prediction accuracy as compared to those with band values and indices only. The study has shown that, Sentinel 2 and Planet Scope remotely sensed data can be used to develop cost-effective method for AGB estimation in tropical rainforests of Tanzania

Infective mitral valve myxoma with coronary artery embolization: Surgical intervention followed by prolonged survival

Mauyaetal.CarbonBalanceandManagement (2015) 10:10 DOI 10.1186/s13021-015-0021-x © 2015 Mauya et al.; licensee Springer. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.Background: Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent re- search in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. Results: The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based esti- mates relative to model-assisted variance ranged from 1.7 to 7.7. Conclusions: This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory

OPEN FORIS AND GOOGLE EARTH ENGINE LINKING EXPERT PARTICIPATION WITH NATURAL RESOURCE MAPPING AND REMOTE SENSING TRAINING IN TANZANIA

There is an increasing amount of open Earth observation (EO) data available, offering solutions to map, assess and monitor natural resources and to obtain answers to global and local societal challenges. With the help of free and open source software (FOSS) and open access cloud computing resources, the remote sensing community can take the full advantage of these vast geospatial data repositories. To empower developing societies, support should be given to higher education institutions (HEIs) to train professionals in using the open data, software and tools. In this paper, we describe a participatory mapping methodology, which utilizes open source software Open Foris and QGIS, various open Earth observation data catalogues, and computing capacity of the free Google Earth Engine cloud platform. Using this methodology, we arranged a collaborative data collection event, Mapathon, in Tanzania, followed by a training of the related FOSS tools for HEIs’ teaching staff. We collected feedback from the Mapathon participants about their learning experiences and from teachers about the usability of the methodology in remote sensing training in Tanzania. Based on our experiences and the received feedback, using a participatory mapping campaign as a training method can offer effective learning about environmental remote sensing through a real-world example, as well as networking and knowledge sharing possibilities for the participating group

FOSS4G 2018

The GEO-ICT is an institutional cooperation project aiming at improving the quality and societal relevance of geospatial and ICT research and education at the Universities of Dar es Salaam (UDSM), Ardhi University (ARU), State University of Zanzibar (SUZA) and Sokoine University of Agriculture (SUA). Jointly with the University of Turku (UTU) Finland, the institutions focus on strengthening geospatial and ICT skills of the staff, establishing new curricula, upgrading supportive infrastructures and creating synergetic cooperation modalities with different stakeholders in the society. In this paper we share how our practical experiences of the cooperation, including what is the background for the establishment of institutional cooperation between these universities, how is the project operating in practice, what type of activities and cooperation modalities we do together and how do we think institutional cooperation contributes to the advancement of geospatial expertise in Tanzania and what is the role of open source solutions in this development.</p

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVI-4/W2-2021: FOSS4G 2021 – Academic Track, 27 September–2 October 2021, Buenos Aires, Argentina

This paper is based on the experiences from Resilience Academy project in Dar es Salaam, Tanzania, where students’ are engaged to a mass-internships for a period of 8-12 weeks. Student internship model of the Resilience Academy is designed to work with the local organisations to conduct geospatial data collection campaigns based on the use of various open-source data and tools combined with community mapping and digital online working. Simultaneously, students’ exposure to practical training during the internship provides them with relevant applied geospatial skills, which increase their future employment opportunities and participation in informed decision-making.</p