The integration of rooftop greenhouses (RTGs) in urban buildings is a practice that is becoming increasingly important in the world for their contribution to food security and sustainable development. However, the supply of tools and procedures to facilitate their implementation at the city scale is limited and laborious. This work aims to develop a specific and automated methodology for identifying the feasibility of implementation of rooftop greenhouses in non-residential urban areas, using airborne sensors. The use of Light Detection and Ranging (LIDAR) and Long Wave Infrared (LWIR) data and the Leica ALS50-II and TASI-600 sensors allow for the identification of some building roof parameters (area, slope, materials, and solar radiation) to determine the potential for constructing a RTG. This development represents an improvement in time and accuracy with respect to previous methodology, where all the relevant information must be acquired manually. The methodology has been applied and validated in a case study corresponding to a non-residential urban area in the industrial municipality of Rubí, Barcelona (Spain). Based on this practical application, an area of 36,312m out of a total area of 1,243,540m of roofs with ideal characteristics for the construction of RTGs was identified. This area can produce approximately 600tons of tomatoes per year, which represents the average yearly consumption for about 50% of Rubí total population. The use of this methodology also facilitates the decision making process in urban agriculture, allowing a quick identification of optimal surfaces for the future implementation of urban agriculture in housing. It also opens new avenues for the use of airborne technology in environmental topics in cities.
Since the advent of the first large format digital aerial cameras, high expectations have been placed on their performance. The dream of obtaining aerial images virtually free of geometric errors and with greater radiometric quality is getting close. Nevertheless, systematic image residuals, unexpected height errors in aerial triangulation and the need for additional self‐calibration parameters have been reported since 2005. In this paper a preliminary analysis of the theoretical accuracies in aerial triangulation using the Zeiss/Intergraph (Z/I) Digital Mapping Camera (DMC) and an analogue camera is conducted, motivated by those recent reports. This analysis considers a mathematical model where the image has conical geometry and is free of systematic errors. The influence on the propagated block accuracy of the base‐to‐height ratio, image pointing precision (both manual and automatic), GPS observations for projection centres and of pass/tie point density is studied. Moreover, the expected accuracy in the aerial triangulation of analogue images using current procedures (having regard to the a priori accuracy for image pointing, ground control measurement and GPS and pass/tie point density) is computed. The goal of this theoretical study is to find the requirements for aerial triangulation with DMC data which would yield the same or an even higher level of accuracy than that obtained with analogue data under the same conditions. The paper continues with a check on the conclusions of this theoretical analysis, using real data‐sets and aerial triangulation set‐up, which fit with the theoretical analysis. The results prove that the expected theoretical accuracy in aerial triangulation is only obtained if an appropriate self‐calibration parameter set is considered in the bundle block adjustment and/or if good GPS observations are available. These requirements result from the unfavourable propagation from unmodelled systematic error in the DMC image blocks. Some authors have detected systematic residuals in the order of one‐tenth of a pixel rms in DMC image space. For this reason, investigations are being carried out on systematic error characterisation, distribution in image space and stability over time and flying height, and systematic error modelling, using self‐calibration parameter sets and applying correction grids. Finally, conclusions are drawn from the investigations.
Airborne hyperspectral cameras provide the basic information to estimate the energy wasted skywards by outdoor lighting systems, as well as to locate and identify their sources. However, a complete characterization of the urban light pollution levels also requires evaluating these effects from the city dwellers standpoint, e.g. the energy waste associated to the excessive illuminance on walls and pavements, light trespass, or the luminance distributions causing potential glare, to mention but a few. On the other hand, the spectral irradiance at the entrance of the human eye is the primary input to evaluate the possible health effects associated with the exposure to artificial This is an author-created, accepted version of the paper "Ground-based hyperspectral analysis of the urban nightscape" by R. We also present the preliminary results from a field campaign carried out in the downtown of Barcelona.
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