Abstract
The processes of land transformation related to soil erosion and land degradation are complex phenomena that require an approach as detailed and multidisciplinary as possible. In some Mediterranean inland areas, these issues seem to be very connected to the dynamics of transformation and abandonment of agricultural areas. In order to carry out this preliminary investigation for the assessment of dynamics and relationships between processes and land cover, an approach based on GIS and remote sensing has been applied. The study started with implementation of the Revised Universal Soil Loss Equation (RUSLE) model to calculate soil erosion on a monthly and annual basis. The resulting data were then processed through a Getis-Ord local autocorrelation index in order to produce a persistent erosion map. All datasets created were correlated with the cover classes that need more attention, i.e., arable land and post-cultivation vegetation area. All the techniques and methodologies, have been applied in a rural area of the Basilicata Region (South Italy) using exclusively a Free and Open Source Software (FoSS) GIS approach as it guarantees the possibility to perform a series of complex analyses in a simple and effective way so that they can be implemented in environmental monitoring actions and plans.
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References
Bajocco, S., Smiraglia, D., Scaglione, M., Raparelli, E., Salvati, L.: Exploring the role of land degradation on agricultural land use change dynamics. Sci. Total Environ. 636, 1373–1381 (2018). https://doi.org/10.1016/j.scitotenv.2018.04.412
Basso, F., Pisante, M., Basso, B.: Soil erosion and land degradation, In: Geeson, N.A., Brandt, C.J., Thornes, J.B., (eds.) Mediterranean Desertification, a Mosaic of Processes and Responses. John Wiley & Sons, Ltd (2002)
Basso, B., et al.: Evaluating responses to land degradation mitigation measures in Southern Italy. Int J Environ Res. 6(2), 367–380 (2012)
Bivand, R.S., Wong, D.W.S.: Comparing implementations of global and local indicators of spatial association. TEST 27(3), 716–748 (2018). https://doi.org/10.1007/s11749-018-0599-x
Borrelli, P., Robinson, D.A., Fleischer, L.R., et al.: An assessment of the global impact of 21st century land use change on soil erosion. Nat. Commun. 8, 2013 (2017). https://doi.org/10.1038/s41467-017-02142-7
Capolongo, D., Pennetta, L., Piccarreta, M., Fallacara, G., Boenzi, F.: Spatial and temporal variations in soil erosion and deposition due to land-levelling in a semi-arid area of Basilicata (Southern Italy). Earth Surf. Proces. Landforms: J. British Geomorphol. Res. Group 33(3), 364–379 (2008)
D’Odorico, P., Bhattachan, A., Davis, K.F., Ravi, S., Runyan, C.W.: Global desertification: drivers and feedbacks. Adv. Water Resour 51, 326–344 (2013)
ESDAC. https://esdac.jrc.ec.europa.eu/content/support-practices-factor-p-factor-eu. Accessed on 15 Jan 2021
González Díaz, J.A., Celaya, R., Fernández García, F., Osoro, K., Rosa García, R.: Dynamics of rural landscapes in marginal areas of northern Spain: past, present, and future. Land Degrad Dev. 30, 141–150 (2019). https://doi.org/10.1002/ldr.3201
ISPRA. https://www.isprambiente.gov.it/it/servizi/sistema-carta-della-natura. Accessed on 14 Jan 2021
Kuo, K.T., Sekiyama, A., Mihara, M.: Determining C factor of universal soil loss equation (USLE) based on remote sensing. Int. J. Environ. Rural Dev. 7(2), 154–161 (2016)
Lanorte, A., et al.: Integrated approach of RUSLE, GIS and ESA Sentinel-2 satellite data for post-fire soil erosion assessment in Basilicata region (Southern Italy). Geomat. Natl. Hazards Risk 10(1), 1563–1595 (2018). https://doi.org/10.1080/19475705.2019.1578271
Lasanta, T., Sánchez-Navarrete, P., Medrano-Moreno, L.M., Khorchani, M., Nadal-Romero, E.: Soil quality and soil organic carbon storage in abandoned agricultural lands: Effects of revegetation processes in a Mediterranean mid-mountain area. Land Degrad Dev. 31, 2830–2845 (2020)
Las Casas, G., Scorza, F., Murgante, B.: New Urban Agenda and open challenges for urban and regional planning. In: Calabrò, F., Della Spina, L., Bevilacqua, C. (eds.) New Metropolitan Perspectives. ISHT 2018. Smart Innovation, Systems and Technologies, vol. 100. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-92099-3_33
Mitasova, H., Hofierka, J., Zlocha, M., Iverson, L.R.: Modelling topographic po-tential for erosion and deposition using GIS. Int. J. Geogr. Inf. Syst. 10(5), 629–641 (1996)
Mohamadi, M.A., Kavian, A.: Effects of rainfall patterns on runoff and soil erosion in field plots Int. Soil Water Conservat. Res. 3(4), 273–281 (2015). https://doi.org/10.1016/j.iswcr.2015.10.001
Nature Map. https://www.isprambiente.gov.it/it/servizi/sistema-carta-della-natura. Accessed on 10 Jan 2021
Nolè, G., Lasaponara, R., Lanorte, A., Murgante, B.: Quantifying Urban Sprawl with spatial autocorrelation techniques using multi-temporal satellite data. Int. J. Agric. Environ. Inf. Syst. 5(2), 19–37 (2014). https://doi.org/10.4018/IJAEIS.2014040102
Ord, J.K., Getis, A.: Local spatial autocorrelation statistics: distributional issues and an application. Geogr. Anal. 27, 286–306 (1995)
Pacheco, F.A.L., Sanches Fernandes, L.F., Valle Junior, R.F., Valera, C.A., Pissarra, T.C.T.: Land degradation: multiple environmental consequences and routes to neutrality. Curr. Opin. Environ. Sci. Heal. 5, 79–86 (2018). https://doi.org/10.1016/j.coesh.2018.07.002
Panagos, P., Borrelli, P., Meusburger, K., van der Zanden, E.H., Poesen, J., Alewell, C.: Modelling the effect of support practices (P-factor) on the reduction of soil. Environ. Sci. Policy 51 (2015). https://doi.org/10.1016/j.envsci.2015.03.012(2015)
Picuno, P., Cillis, G.,Statuto, D.: Investigating the time evolution of a rural landscape: How historical maps may provide environmental information when processed using a GIS. Ecol. Eng. 139 (2019). https://doi.org/10.1016/j.ecoleng.2019.08.010
Peeters, A., et al.: Getis–Ord’s hot- and cold-spot statistics as a basis for multivariate spatial clustering of orchard tree data. Comput. Electron. Agric. 111, 140–150 (2015). https://doi.org/10.1016/j.compag.2014.12.011
Renard, K.G., Foster, G.R., Weesies, G.A., Porter, J.P.: RUSLE: revised uni-versal soil loss equation. J. Soil Water Conserv. 46(1), 30–33 (1991)
Rodrigo-Comino, J., Martínez-Hernández, C., Iserloh, T., Cerdà, A.: The contrasted impact of land abandonment on soil erosion in mediterranean agriculture fields. Pedosphere (2017). https://doi.org/10.1016/S1002-0160(17)60441-7
Scorza, F., Casas, G.B.L., Murgante, B.: That’s ReDO: Ontologies and regional development planning. In: Murgante, B., et al. (eds.) Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol. 7334. Springer, Berlin, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31075-1_48
Santarsiero, V., Nolè, G., Lanorte, A., Tucci, B., Baldantoni, P., Murgante, B.: Evolution of soil consumption in the municipality of melfi (Southern Italy) in relation to renewable energy. In: Misra, S., et al. (eds.) ICCSA 2019. LNCS, vol. 11621, pp. 675–682. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24302-9_48
Soils database - Basilicata Region. http://www.basilicatanet.it/suoli/carta2.htm. Accessed on 02 March 2021
Spdep. https://cran.r-project.org/package=spdep. Accessed on 14 Feb 2021
Terranova, O., Antronico, L., Coscarelli, R., Iaquinta, P.: Soil erosion risk scenarios in the Mediterranean environment using RUSLE and GIS: an application model for Calabria (southern Italy). Geomorphology 112(3–4), 228–245 (2009)
THEIA Homepage. https://theia.cnes.fr/atdistrib/rocket/#/home. Accessed on 20 March 2021
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Cillis, G. et al. (2021). Soil Erosion and Land Degradation in Rural Environment: A Preliminary GIS and Remote-Sensed Approach. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12954. Springer, Cham. https://doi.org/10.1007/978-3-030-86979-3_48
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