Abstract
The use of clean and renewable energies, such as solar power, is essential for improving local economies, reducing reliance on scarce fossil fuels, and mitigating climate change. However, although solar power harvested using PhotoVoltaic (PV) cells has grown significantly in recent years, the actual amount of energy produced is unknown and challenging to define because of the lack of geographic data on the number of PV panels installed on rooftops. Due to the low spatial resolution of open-source satellite images, free surveying PV small-scale installations is currently not feasible. YouthMappers, an academic network dedicated to the creation and use of open map** for development and humanitarian purposes, offers a possible solution. Indeed, it is an effective method to gather free detailed information on a large scale thanks to the support of high-resolution satellite images such as MapBox, Bing, or DigitalBox in an open-source environment, like Java OpenStreetMap (JOSM). As a result, in this study, an ad hoc tool written in JOSM was created to map PV panels on rooftops manually. This preset collects all of the information needed to describe PV panel features, such as type, size, and orientation, and calculate the amount of energy produced. Furthermore, its interface is simple and easy to use for both Information Technology (IT) and non-IT users. All data collected is stored in a geodatabase accessible to local governments, communities, industries, and scientists, allowing for a global overview of installed PV panel systems, the potential amount of energy produced, and the tracking of their evolution over time.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kabir, E., Kumar, P., Kumar, S., Adelodun, A., Kim, K.: Solar energy: potential and future prospects. Renew. Sustain. Energy Rev. 82, 894–900 (2018)
Rabaia, M., Abdelkareem, M., Sayed, E., Elsaid, K., Chae, K.-J., Wilberforce, T., Olabi, A.G.: Environmental impacts of solar energy systems: a review. Sci. Total Env. 754, 141989 (2021)
Monforti, F., Huld, T., Bódis, K., Vitali, L., D’Isidoro, M., Lacal-Arántegui, R.: Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach. Renew. Energy 63, 576–586 (2014)
Gašparović, I., Gašparović, M.: Determining optimal solar power plant locations based on remote sensing and GIS methods: a case study from Croatia. Remote Sens. 11(12), 1481 (2019)
Pindozzi, S., Faugno, S., Cervelli, E., Capolupo, A., Sannino, M., Boccia, L.: Consequence of land use changes into energy crops in Campania region. J. Agric. Eng. 44(2s) (2013)
Peters, I., Liu, H., Reindl, T., Buonassisi, T.: Global prediction of photovoltaic field performance differences using open-source satellite data. Joule 2(2), 307–322 (2017)
Tarantino, E., Figorito, B.: Steerable filtering in interactive tracing of archaeological linear features using digital true colour aerial images. Int. J. Digital Earth 7(11), 870–880 (2014)
Ladisa C, Capolupo A, Ripa M, Tarantino E (2022) Combining OBIA approach and Machine Learning algorithm to extract photovoltaic panels from Sentinel 2 images automatically. Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV (Vol. 12262, pp. 67–76). SPIE
Ladisa, C., Capolupo, A., Ripa, M., Tarantino, E.: Evaluation of ecognition developer and orfeo toolbox performances for segmenting agrophotovoltaic systems from sentinel-2 images. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds.) Computational Science and Its Applications – ICCSA 2022 Workshops: Malaga, Spain, July 4–7, 2022, Proceedings, Part III, pp. 466–482. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-10545-6_32
Viana, C., Girão, I., Rocha, J.: Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region. Remote Sens. 11(9), 1104 (2019)
Stowell, D., Kelly, J., Tanner, D., et al.: A harmonised, high-coverage, open dataset of solar photovoltaic installations in the UK. Sci. Data 7, 394 (2020)
Figorito, B., Tarantino, E.: Semi-automatic detection of linear archaeological traces fromorthorectified aerial images. Int. J. Appl. Earth Obs. Geoinf. 26(1), 458–463 (2014)
Gaspari, F.: Innovation in teaching: the Polimappers collaborative and humanitarian map** course at Politecnico di Milano. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives, International Society for Photogrammetry and Remote Sensing (2021)
Hite, R., SolÃs, P., Wargo, L., Larsen, T.: Exploring affective dimensions of authentic geographic education using a qualitative document analysis of students’ youthmappers blogs. Educ. Sci. 8(4), 173 (2018)
SolÃs, P., Zeballos, M. (eds.): Open Map** towards Sustainable Development Goals: Voices of YouthMappers on Community Engaged Scholarship. Springer International Publishing, Cham (2023)
GarcÃa-Nieto, A., Quintas-Soriano, C., GarcÃa-Llorente, M., Palomo, I., Montes, C., MartÃn-López, B.: Collaborative map** of ecosystem services: the role of stakeholders’ profiles. Ecosyst. Serv. 13, 141–152 (2015)
SolÃs, P., Anderson, J., Rajagopalan, S.: Open geospatial tools for humanitarian data creation, analysis, and learning through the global lens of YouthMappers. J. Geogr. Syst. 23(4), 599–625 (2021)
Schott, M., Grinberger, A., Lautenbach, S., Zipf, A.: The impact of community happenings in openstreetmap—establishing a framework for online community member activity analyses. ISPRS Int. J. Geo-Inform. 10(3), 164 (2021)
Vargas-Munoz, J., Srivastava, S., Tuia, D., Falcao, A.: OpenStreetMap: challenges and opportunities in machine learning and remote sensing. IEEE Geosci. Remote Sens. Mag. 9(1), 184–199 (2021)
Ahamed, A., Vakilzadian, H.: Impact of direction parameter in performance of modified AODV in VANET. J. Sens. Actuator Netw. 9(3), 40 (2020)
Scioscia, F., Binetti, M., Ruta, M., Ieva, S., Di Sciascio, E.: A framework and a tool for semantic annotation of POIs in OpenStreetMap. Procedia Soc. Behav. Sci. 111, 1092–1101 (2014)
Ramm, F., Topf, J.: OpenStreetMap: Die freie Weltkarte nutzen und mitgestalten. Lehmanns Media (2010)
Wang, Z., Niu, L.: A data model for using openstreetmap to integrate indoor and outdoor route planning. Sensors (Switzerland) 18(7) (2018)
Girres, J., Touya, G.: Quality assessment of the french OpenStreetMap dataset. Trans. GIS 14(4), 435–459 (2010). https://doi.org/10.1111/j.1467-9671.2010.01203.x
LearnOSM Homepage https://learnosm.org/en/josm/start-josm/. Last accessed 18 May 2023
WikiOpenStreetMap Homepage. https://wiki.openstreetmap.org/wiki/IT:Pagina%20Principale?uselang=it. Last accessed 18 May 2023
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ladisa, C., Capolupo, A., Tarantino, E. (2024). A Customized JAVA OpenStreetMap Preset to Extract Solar Panel Installations for Humanitarian Purposes. In: Marucci, A., Zullo, F., Fiorini, L., Saganeiti, L. (eds) Innovation in Urban and Regional Planning. INPUT 2023. Lecture Notes in Civil Engineering, vol 467. Springer, Cham. https://doi.org/10.1007/978-3-031-54118-6_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-54118-6_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-54117-9
Online ISBN: 978-3-031-54118-6
eBook Packages: EngineeringEngineering (R0)