ABSTRACT:The application of perspective camera systems in photogrammetry and computer vision is state of the art. In recent years nonperspective and especially omnidirectional camera systems were increasingly used in close-range photogrammetry tasks. In general perspective camera model, i. e. pinhole model, cannot be applied when using non-perspective camera systems. However, several camera models for different omnidirectional camera systems are proposed in literature. Using different types of cameras in a heterogeneous camera system may lead to an advantageous combination. The advantages of different camera systems, e. g. field of view and resolution, result in a new enhanced camera system. If these different kinds of cameras can be modeled, using a unified camera model, the total calibration process can be simplified. Sometimes it is not possible to give the specific camera model in advance. In these cases a generic approach is helpful. Furthermore, a simple stereo reconstruction becomes possible using a fisheye and a perspective camera for example. In this paper camera models for perspective, wide-angle and omnidirectional camera systems are evaluated. The crucial initialization of the model's parameters is conducted using a generic method that is independent of the particular camera system. The accuracy of this generic camera calibration approach is evaluated by calibration of a dozen of real camera systems. It will be shown, that a unified method of modeling, parameter approximation and calibration of interior and exterior orientation can be applied to derive 3D object data.

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In the last decades the consumer and industrial market for non-projective cameras has been growing notably. This has led to the development of camera description models other than the pinhole model and their employment in mostly homogeneous camera systems. Heterogeneous camera systems (for instance, combine Fisheye and Catadioptric cameras) can also be easily thought of for real applications. However, it has not been quite clear, how accurate stereo vision with these cameras and models can be. In this paper, different accuracy aspects are addressed by analytical inspection, numerical simulation as well as real image data evaluation. This analysis is generic, for any camera projection model, although only polynomial and rational projection models are used for distortion free, Catadioptric and Fisheye lenses. Note that this is different to polynomial and rational radial distortion models which have been addressed extensively in literature. For single camera analysis it turns out that point features towards the image sensor borders are significantly more accurate than in center regions of the sensor. For heterogeneous two camera systems it turns out, that reconstruction accuracy decreases significantly towards image borders as different projective distortions occur.

The impact of climate change-driven droughts on regenerating forests is poorly understood due to the complexities involved in regeneration processes and the difficulties in measuring the relevant parameters with sufficient spatial and temporal resolution in a timely manner. Drought increases tree mortality in both undisturbed and disturbed forests and may influence forest regeneration dynamics from seed germination to the recruitment, growth, and survival of tree seedlings. Seedlings and small saplings may be more susceptible to changes in water availability than larger individuals due to their shallower roots that may be unable to reach the deeper, moist soil layers, and due to uneven competition with adult trees for soil moisture. The potential range shifts and local extinction of drought-sensitive species can also result in changes in forest species community composition and diversity loss at different scales. There is a need for precise and low-cost monitoring systems that facilitate better capturing of the complexities of such processes for restoration measures. The objective of this paper is to study the use of UAVs (Unmanned Aerial Vehicles) for monitoring responses of regenerating forests under increasing climate change-driven droughts. UAVs have several advantages over traditional field-based monitoring techniques and flexibility in selecting the required spatiotemporal resolution over other remote sensing methods, making them a promising tool for monitoring forest recovery. Although further research is required to ensure the accuracy and effectiveness of UAV-facilitated measures for monitoring forest regeneration, UAVs possess great potential in forest management in the event of increasing occurrences of climate-change driven droughts.