Abstract
Water is a vital resource for sustaining human life, well-being, and the Earth’s biodiversity and ecosystems. However, its availability and usability are decreasing due to strong anthropogenic pressure and intense climatic stress, leading to a variety of environmental issues, including desertification. Consequently, areas exposed to these factors, such as those in Southern Italy, are highly vulnerable to desertification. To address soil deterioration, it is crucial to identify and implement appropriate land management strategies aimed at promoting sustainability and improving ecosystem services. Remote sensing techniques provide a low-cost and non-destructive tool for extracting baseline information on water bodies, land use/cover classes, and Earth morphology features. When combined with meteorological data, these techniques can help identify the most effective, efficient, and sustainable water management strategies to tackle desertification. This is made possible by the vast amount of publicly available medium-resolution satellite data, such as Landsat and Sentinel missions, as well as open-source cloud infrastructures for managing big geographic data, like Google Earth Engine (GEE). The primary goal of this study is to provide a reference framework for a comprehensive workflow that moves from available data, through their proper elaboration with models, to knowledge management aimed at informing public policies. The case study presented provides a snapshot of the current state of natural water resource availability in the Apulian environment by identifying and evaluating the key hydrological balance components provided by the BIGBANG model. The input data for the model were images from Landsat missions and climate data handled in GEE. The results from the BIGBANG model were then used to define a scenario analysis to determine the best water resource planning and management policies.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Flint, R.W.: The sustainable development of water resources. Water Resour. Update 127, 48–59 (2004)
Custodio, E.: Concepts on groundwater resources. In: Calvache, M.L., Duque, C., Pulido-Velazquez, D. (eds.) Groundwater and Global Change in the Western Mediterranean Area, pp. 85–92. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-69356-9_10
Karimidastenaei, Z., AvellĂ¡n, T., Sadegh, M., Kløve, B., Haghighi, A.T.: Unconventional water resources: global opportunities and challenges. Sci. Total Environ. 827, 154429 (2022)
Kummu, M., Ward, P.J., De Moel, H., Varis, O.: Is physical water scarcity a new phenomenon? Global assessment of water shortage over the last two millennia. Environ. Res. Lett. 5(3), 034006 (2010)
Macedonio, F., Drioli, E., Gusev, A.A., Bardow, A., Semiat, R., Kurihara, M.J.C.E.: Efficient technologies for worldwide clean water supply. Chem. Eng. Process. 51, 2–17 (2012)
Capolupo, A., Saponaro, M., Fratino, U., Tarantino, E.: Detection of spatio-temporal changes of vegetation in coastal areas subjected to soil erosion issue. Aquat. Ecosyst. Health Manage. 23(4), 491–499 (2020)
Solomon, B.D.: Intergovernmental panel on climate change (IPCC). In: Haddad, B.M., Solomon, B.D. (eds.) Dictionary of Ecological Economics: Terms for the New Millennium, pp. 302–302. Edward Elgar Publishing (2023)
Bouderbala, A.: Effects of climate variability on groundwater resources in coastal aquifers (case of Mitidja plain in the North Algeria). In: Calvache, M.L., Duque, C., Pulido-Velazquez, D. (eds.) Groundwater and Global Change in the Western Mediterranean Area, pp. 43–51. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-69356-9_6
Capolupo, A., Boccia, L.: Innovative method for linking anthropisation process to vulnerability. World Rev. Sci. Technol. Sustain. Dev. 17(1), 4–22 (2021)
Capolupo, A., Nasta, P., Palladino, M., Cervelli, E., Boccia, L., Romano, N.: Assessing the ability of hybrid poplar for in-situ phytoextraction of cadmium by using UAV-photogrammetry and 3D flow simulator. Int. J. Remote Sens. 39(15–16), 5175–5194 (2018)
Palladino, M., Nasta, P., Capolupo, A., Romano, N.: Monitoring and modelling the role of phytoremediation to mitigate non-point source cadmium pollution and ground-water contamination at field scale. Ital. J. Agron. 13(s1), 59–68 (2018)
Su, Z., et al.: First results of the earth observation Water Cycle Multi-mission Observation Strategy (WACMOS). Int. J. Appl. Earth Obs. Geoinf. 26, 270–285 (2014)
Sun, Y., Liu, N., Shang, J., Zhang, J.: Sustainable utilisation of water resources in China: a system dynamics model. J. Clean. Prod. 142, 613–625 (2017)
Kummerow, C., et al.: The evolution of the Goddard Profiling Algorithm (GPROF) for rainfall estimation from passive microwave sensors. J. Appl. Meteorol. 40(11), 1801–1820 (2001)
Kidd, C., Levizzani, V.: Status of satellite precipitation retrievals. Hydrol. Earth Syst. Sci. 15(4), 1109–1116 (2011)
Aires, F., Prigent, C.: Toward a new generation of satellite surface products? J. Geophys. Res.: Atmos. 111(D22) (2006)
De Jeu, R.A., Wagner, W., Holmes, T.R.H., Dolman, A.J., Van De Giesen, N.C., Friesen, J.: Global soil moisture patterns observed by space borne microwave radiometers and scatterometers. Surv. Geophys. 29, 399–420 (2008)
Pekel, J.F., Cottam, A., Gorelick, N., Belward, A.S.: High-resolution mapping of global surface water and its long-term changes. Nature 540(7633), 418–422 (2016)
Trombetta, A., Iacobellis, V., Tarantino, E., Gentile, F.: Calibration of the AquaCrop model for winter wheat using MODIS LAI images. Agric. Water Manag. 164, 304–316 (2016)
Peschechera, G., Tarantino, E., Fratino, U.: Crop water requirements estimation at irrigation district scale from remote sensing: a comparison between MODIS ET product and the analytical approach. In: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), vol. 10773, pp. 413–421). SPIE (2018)
Tellman, B., et al.: Satellite imaging reveals increased proportion of population exposed to floods. Nature 596(7870), 80–86 (2021)
Capolupo, A., Barletta, C., Tarantino, E.: Copernicus services and data to support a sustainable and adaptive water resource management (No. EGU23-2449). Copernicus Meetings (2023)
Capolupo, A., Monterisi, C., Caporusso, G., Tarantino, E.: Extracting land cover data using GEE: A review of the classification indices. In: Gervasi, O., et al. (eds.) ICCSA 2020. LNCS, vol. 12252, pp. 782–796. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-58811-3_56
Capolupo, A., Monterisi, C., Saponaro, M., Tarantino, E.: Multi-temporal analysis of land cover changes using Landsat data through Google Earth Engine platform. In: Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), vol. 11524, pp. 447–458. SPIE (2020)
Mutanga, O., Kumar, L.: Google earth engine applications. Remote Sens. 11(5), 591 (2019)
Gorelick, N.: Google earth engine. In: EGU General Assembly Conference Abstracts, vol. 15, p. 11997. American Geophysical Union, Vienna, Austria (2013)
Braca, G., Bussettini, M., Lastoria, B., Mariani, S., Piva, F.: Il bilancio idrologico GIS based a scala nazionale su griglia regolare—BIGBANG: Metodologia e stime. Rapporto sulla disponibilità naturale della risorsa idrica. Rapp. ISPRA 339, 1–181 (2021)
Braca, G., Ducci, D.: Development of a gis based procedure (BIGBANG 1.0) for evaluating groundwater balances at national scale and comparison with groundwater resources evaluation at local scale. In: Calvache, M.L., Duque, C., Pulido-Velazquez, D. (eds.) Groundwater and Global Change in the Western Mediterranean Area. EES, pp. 53–61. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-69356-9_7
Capolupo, A., Monterisi, C., Barletta, C., Tarantino, E.: Google Earth Engine for land surface albedo estimation: comparison among different algorithms. In: Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, vol. 11856, pp. 51–63. SPIE (2021)
Barletta, C., Capolupo, A., Tarantino, E.: Exploring the potentialities of landsat 8 and sentinel-2 satellite data for estimating the land surface albedo in urban areas using GEE platform. 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. 435–449. Springer International Publishing, Cham (2022). https://doi.org/10.1007/978-3-031-10545-6_30
Braca, G., Bussettini, M., Lastoria, B., Mariani, S., Piva, F.: Elaborazioni modello BIGBANG versione 4.0 (2021)
Thornthwaite, C.W., Mather, J.R.: The water balance. Laboratory of Climatology, Publ. No. 8 (1955)
Sangiorgio, V., Capolupo, A., Tarantino, E., Fiorito, F., Santamouris, M.: Evaluation of absolute maximum urban heat island intensity based on a simplified remote sensing approach. Environ. Eng. Sci. 39(3), 296–307 (2022)
Ghosh, S., Kumar, D., Kumari, R.: Cloud-based large-scale data retrieval, mapping, and analysis for land monitoring applications with google earth engine (GEE). Environ. Challenges 9, 100605 (2022)
Braca, G., Bussettini, M., Lastoria, B., Mariani, S., Piva, F.: Il Bilancio Idrologico Gis Based a scala Nazionale su Griglia regolare – BIGBANG: metodologia e stime. Rapporto sulla disponibilità naturale della risorsa idrica. Istituto Superiore per la Protezione e la Ricerca Ambientale, Rapporti 339/21, Roma (2021)
Hargreaves, G.L., Hargreaves, G.H., Riley, J.P.: Agricultural benefits for Senegal River basin. J. Irrig. Drain. Eng. 111(2), 113–124 (1985)
Pindozzi, S., Faugno, S., Okello, C., Boccia, L.: Measurement and prediction of buffalo manure evaporation in the farmyard to improve farm management. Biosys. Eng. 115(2), 117–124 (2013)
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
Capolupo, A., Barletta, C., Esposito, D., Tarantino, E. (2024). Earth Observation Data for Sustainable Management of Water Resources to Inform Spatial Planning Strategies. 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_3
Download citation
DOI: https://doi.org/10.1007/978-3-031-54118-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-54117-9
Online ISBN: 978-3-031-54118-6
eBook Packages: EngineeringEngineering (R0)