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The objective of this Ph.D. thesis is the development and validation of a VTOL-based (Vertical Take Off and Landing) micro-drone for the measurement of gas concentrations, to locate gas emission sources, and to build gas distribution maps. Gas distribution mapping and localization of a static gas source are complex tasks due to the turbulent nature of gas transport under natural conditions [1] and becomes even more challenging when airborne. This is especially so, when using a VTOL-based micro-drone that induces disturbances through its rotors, which heavily affects gas distribution. Besides the adaptation of a micro-drone for gas concentration measurements, a novel method for the determination of the wind vector in real-time is presented. The on-board sensors for the flight control of the micro-drone provide a basis for the wind vector calculation. Furthermore, robot operating software for controlling the micro-drone autonomously is developed and used to validate the algorithms developed within this Ph.D. thesis in simulations and real-world experiments. Three biologically inspired algorithms for locating gas sources are adapted and developed for use with the micro-drone: the surge-cast algorithm (a variant of the silkworm moth algorithm) [2], the zigzag / dung beetle algorithm [3], and a newly developed algorithm called “pseudo gradient algorithm”. The latter extracts from two spatially separated measuring positions the information necessary (concentration gradient and mean wind direction) to follow a gas plume to its emission source. The performance of the algorithms is evaluated in simulations and real-world experiments. The distance overhead and the gas source localization success rate are used as main performance criteria for comparing the algorithms. Next, a new method for gas source localization (GSL) based on a particle filter (PF) is presented. Each particle represents a weighted hypothesis of the gas source position. As a first step, the PF-based GSL algorithm uses gas and wind measurements to reason about the trajectory of a gas patch since it was released by the gas source until it reaches the measurement position of the micro-drone. Because of the chaotic nature of wind, an uncertainty about the wind direction has to be considered in the reconstruction process, which extends this trajectory to a patch path envelope (PPE). In general, the PPE describes the envelope of an area which the gas patch has passed with high probability. Then, the weights of the particles are updated based on the PPE. Given a uniform wind field over the search space and a single gas source, the reconstruction of multiple trajectories at different measurement locations using sufficient gas and wind measurements can lead to an accurate estimate of the gas source location, whose distance to the true source location is used as the main performance criterion. Simulations and real-world experiments are used to validate the proposed method. The aspect of environmental monitoring with a micro-drone is also discussed. Two different sampling approaches are suggested in order to address this problem. One method is the use of a predefined sweeping trajectory to explore the target area with the micro-drone in real-world gas distribution mapping experiments. As an alternative sampling approach an adaptive strategy is presented, which suggests next sampling points based on an artificial potential field to direct the micro-drone towards areas of high predictive mean and high predictive variance, while maximizing the coverage area. The purpose of the sensor planning component is to reduce the time that is necessary to converge to the final gas distribution model or to reliably identify important parameters of the distribution such as areas of high concentration. It is demonstrated that gas distribution models can provide an accurate estimate of the location of stationary gas sources. These strategies have been successfully tested in a variety of real-world experiments in different scenarios of gas release using different gas sensors to verify the reproducibility of the experiments. The adaptive strategy was also successfully validated in simulations using predefined sweeping trajectories as reference criteria. The results of this Ph.D. thesis reflect the applicability of gas-sensitive microdrones in a variety of scenarios of gas release. Effective counteractive measures can be set in motion after accidents involving gas emissions with the aid of spatially resolved gas concentration and wind data collected with micro-drones. Monitoring of geochemically active regions, landfills, CO2 storage facilities, and the localization of gas leaks are further areas of application.