Heavy rainfall, combined with expanding (unplanned) urban settlements in flood prone areas, expose Dar es Salaam (Tanzania) to the risks of flooding. The urbanisation is so rapid in many areas that it is not beneficial to carry out expensive surveys which are quickly out of date. The work carried out by community-mapping project Dar Ramani Huria (Swahili for "Open map") aims to make a detailed map of Dar es Salaam, to enable the hydrologic models to approach the real situation more closely. However, the surveying methods used until recently are not sufficiently accurate. However, an alternative emerges in the form of community members using a low-cost, dual-frequency global navigation satellite system (GNSS) receiver during surveys. However, before this receiver can be implemented a detailed research has to be done. In this thesis the horizontal and vertical performance of the U-blox ZED-F9P receiver in Delft (the Netherlands) and Dar es Salaam is studied. The research is divided into two parts: performance and case study. For the performance study a series of post-processed kinematic (PPK) experiments were conducted in Delft and Dar es Salaam. The experiments have been designed in order to provide a variety of location, antenna-performance, baseline length, software package and movability. In addition, two re-initialisation experiments were conducted to measure how fast the interrupted GNSS signal is regained by the receiver. The case study focused on the desirability and feasibility, mainly focussing on accuracy, of implementation in the project of Dar Ramani Huria. Structured and unstructured interviews with employees of the Humanitarian OpenStreetMap Team (HOT) Tanzania were held to find out the requirements of implementation. The positioning performance of the receiver varies between the different experiments. The conclusions regarding the positioning performance are based on the scatter plots in the horizontal plane and the positioning over time for the three separate directional components; East, North and Up. The values for the horizontal performance (RMS East, RMS North) and for the vertical performance (RMS Up) of the fix solutions insofar as they fall inside the 95% confidence ellipse are decisive. Only the relevant experiments, namely those who can map a larger area with a single reference station are taken into consideration. The horizontal positioning performance ranges from 1.13 till 16.83 However the latter, high value is from the 9 baseline Dar es Salaam experiment with a very low percentage of fixed solutions. If we disregard the experiments with low percentage of fixed solutions then the horizontal positioning performance ranges van 1.13 till 9.42. The vertical positioning performance shows less accuracy ranging from 3.56 till 14.75. If we compare this performance with the requirements for Dar Ramani Huria’s project, even the strictest of 2cm, the performance is more than adequate according to the "few cm accuracy" requirement. The experiment with the high-end antenna shows with values 2.44mm (RMS East) and 3.42mm (RMS North) the best horizontal and with the value 3.75$mm(RMS Up) the best vertical performance. Another factor influencing the performance is the location, in particular the aspect of atmospheric delay that varies between Dar es Salaam and Delft. This research thesis concludes that the implementation of the receiver in Dar Ramani Huria's project is well possible and that the performance of the receiver is adequate. This conclusion is confirmed by what is actually occurring in the field: HOT Tanzania and Dar Ramani Huria already started using the GNSS receiver and carrying out surveys with this receiver.

This report contains the findings of a multidisciplinary project in Mozambique which ran from mid-November 2018 to mid-January 2019. This study is part of the IWACA-TECH project, which is an abbreviation for “Improved Water efficiency Control based on remote sensing TECHnologies. The goal is to increase water efficiency and crop yield without increasing the consumptive use of water, using remote sensing and Model Predictive Control (MPC). The structural water scarcity in the region points out the relevance of the IWACATECH project and with that this study. The research, carried out by students of Delft University of Technology, is of importance for both the company Tongaat Hulett and all inhabitants who are direct or indirect dependent on the water of the Incomati river. The study area on the plantation in Xinavane copes not only with inefficient irrigation water use but also suffers a sugarcane yield decline in recent years ??. Therefore, the overall aim of this report is to improve water efficiency and crop yield within Tongaat Hulett. To achieve this from a multidisciplinary perspective several research questions have been formulated. Although they all contribute to the overall aim, they do so from different angles and in varying degrees. Therefore, to increase the readability of the report, the research questions have been divided into three sections: (1) Irrigation Practices, (2) Field Assessment on Yield Variability and (3) Decision Support System. Fieldwork was conducted over a five week period in order to gather data. Groundwater levels were measured, water quality of irrigation, ground- and precipitation water samples was analysed and soil moisture content was measured. This led to further research of soil types and quality. Soil profiles along the edges of both fields were made revealing a shallow aquifer in the bad-performing field. Irrigation water quality seems to form no hazard, but ground water quality analyses revealed significantly high electrical conductivity levels and a high sodium adsorption ratio in areas without growth. These findings, combined with an analysis of the digital elevation map and socio-technical data revealed that evaporation of irrigation water seems to be a large contributor to the impaired crop growth. When excess water cannot run off, puddles are formed. When these puddles evaporate, salts can be taken up by the soil once the thickened irrigation water infiltrates. This process is strengthened by the clay soil layer and the shallow aquifer, which prevent water from infiltrating deeper into the ground. Results concerning remote sensing prove the relationship between soil moisture content and precipitation for meteo-station XNA-20. Combining spatial and temporal variability of soil moisture content with remote sensing can play an essential role in managing irrigation practices. For the decision support system, and in specific the controller part of the system, measurements have been done. It can be concluded that storage area and delay times can be considered insignificant, and that canals do not have to be modelled. This makes the controller significantly easier and thus more time and effort can be spend on other aspects of the controller.

Trees are an important aspect of the world around us, and play a sufficient role in our daily lives. They contribute to human health and well-being in various ways. Tree inventory and monitoring are of great interest for biomass estimations and changes in the purifying effect on the air. It is a very time consuming and cost inefficient way to check every tree in and around a city or town, therefore there is further research required in the use of AHN data. Together with the “tree information data set” formthemunicipality ofDelft, the location and the corresponding point cloud of tree different species of trees are selected. For the species of interest, Aesculus Hippocastanum, Acer Saccharinum and Platanus x Hispanica, different characteristics are determined. In this research six different characteristics are estimated; Height, Trunk Height, Normalized Trunk Height, Canopy Projected Area, Normalized Canopy Projected Area, Ratio of Diameters, Normalized Ratio of Diameter, Centre of Gravity and at least the Normalized Centre of Gravity. These characteristics are used as features for the Random Forest Classification, Consequently the Confusion Matrix is used as performance measurement. The results of a test of 30 pointclouds, per species of interest, show that the Random Forest Classification is able to classify individual trees. However, these three different species cannot by sufficiently classified using clustering.