Abstract
Increasing urban demand and population growth in cities have led to an increase in demand for develo** new ways. Parchin–Pasdaran Road, which runs from the heart of Khojir National Park, is a big threat to this park. Despite these environmental threats, the development and creation of new highways is unavoidable. This research was carried out to study the effect of the road on Smith–Wilson evenness index and Simpson diversity index in Khojir National Park. The Land Management Units were created using the ArcGIS software. Using appropriate algorithm in artificial neural network structure and linear regression of species evenness and diversity was modelled. For modelling of species evenness and diversity, factors like bulk density, particle density, moisture content, porosity and distance from the road were used. Finally, considering that the amount of R2 in artificial neural network method was statistically significant for Smith–Wilson and Simpson (0.54), (0.71) and in the regression method, respectively (0.25), (0.75), was obtained, the neural network model was selected as the optimal model. Based on the analysis of sensitivity analysis, humidity factors at 5 and 10 cm from the soil surface, the actual 5 cm particle density on the Smith–Wilson index and the porosity at 10 cm from the soil surface had the most effect on the Russian Simpson index.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig4_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig5_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig6_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig7_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig8_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig9_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig10_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig11_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs40808-020-00799-6/MediaObjects/40808_2020_799_Fig12_HTML.png)
Similar content being viewed by others
References
Adeney JM, Christensen NL Jr, Pimm SL (2009) Reserves protect against deforestation fires in the Amazon’. PLoS ONE 4:e5014
Akinyemi AF, Kayaode IB (2010) Impact of human activities on the distribution of ungulates in Old Oyo National Park, Nigeria. Obeche J 28(2):106–111
Arsene CTC, Gabrys B, Al-Dabass D (2012) Decision support system for water distribution systems based on neural networks and graphs theory for leakage detection. Expert Syst Appl 39:13214–13224
Barber CP, Cochrane MA, Souza CM Jr, Veríssimo A (2012) Dynamic performance assessment of protected areas. Biol Conserv 149:6–14
Barber CP, Cochrane MA, Souza CM Jr, Laurance WF (2014) Roads, deforestation, and the mitigating effect of protected areas in the Amazon. Biol Conserv 177:203–209
Callan R (1999) The essence of neural networks. Prentice Hall, Upper Saddle River
Cañada E, Gascón J (2007) Gascón.Turismo y desarrollo. herramientas para una mirada crítica (laed.) Managua.Enlace
Canteriro M, Cordova-Tapia F, Brazeiro A (2018) Tourism impact assessment: a tool to evaluate the environmental impact of touristic activities in natural protected areas. Tour Manag Perspect 28:220–227
Chopra P, Sharma RK, Kumar M (2014) Regression models for the prediction of compressive strength of concrete with & without fly ash. Int J Latest Trends Eng Technol 3:400–406
Drumm A, Moore A (2005) Desarrollo del Ecoturismo Un manual para los profesionales de la conservación. Volumen 1, Segunda Edición Copyright © 2005 por The Nature Conservancy, Arlington, Virginia, USA
Fernandez F, Seco J, Ferrer A, Rodrigo MA (2009) Use of neuro fuzzy networks to improve wastewater flow-rate forecasting. Environ Model Softw 24:686–693
Gerrard JM, Gerrard PN, Bortolotti GR, Dzus EH (1992) A 24-year study of bald eagles on Besnard Lake, Saskatchewan. J Raptor Res 26:159–166
Iliadis LS, Maris F (2007) An artificial neural network model for mountainous water- resources management: the case of Cyprus mountainous watersheds. Environ Model Softw 22:1066–1072
Jahani A (2019a) Forest landscape aesthetic quality model (FLAQM): a comparative study on landscape modelling using regression analysis and artificial neural networks. J Forest Sci 65:61–69
Jahani A (2019b) Sycamore failure hazard classification model (SFHCM): an environmental decision support system (EDSS) in urban green spaces. Int J Environ Sci Technol 16:955–964
Jahani A, Feghhi J, Makhdoum M, Omid M (2016) Optimized forest degradation model (OFDM): an environmental decision support system for environmental impact assessment using an artificial neural network. J Environ Plan Manag 59(2):222–244
Jahani A, Mohamadi Fazel A (2016) Aesthetic quality modelling of landscape in urban green space using artificial neural network. J Nat Environ (Iran J Nat Resour) 69(4):951–963
Johnston FM, Johnston SW (2004) Impacts of road disturbance on soil properties and on exotic plant occurrence in subalpine areas of the Australian Alps. Arct Antarct Alp Res 36(2):201–207
Joppa LN, Bane SR, Pimm SL (2008) On the protection of protected areas. Proc Natl Acad Sci USA 105:6673–6678
Lama AK, Job H (2014) Protected areas and road development: sustainable development discourses in the Annapurna conservation areas, Nepal. Erdkunde 68(4):229–250
Lee MA, Davies L, Power SA (2012) Effects of roads on adjacent plant community composition and ecosystem function: an example from three calcareous ecosystems. Environ Pollut 163:273–280
Leondes C (1998) Fuzzy logic and expert systems applications. Academic Press, Los Angeles
Maier H, Jain RA, Dany GC, Sudhear KP (2010) Methods use for the development of neural networks for the prediction of water resource variables in river systems: current status and future direction. Environ Model Softw 25(8):891–909
Makhdoum MF (2002) Degradation model: a quantitative EIA instrument, acting as a decision support system (DSS) for environmental management. Environ Manag 30(1):151–156
Marion JL, Leung YF, Eagleston H, Burroughs K (2016) A review and synthesis of recreation ecology research findings on visitor impacts to wilderness and protected natural areas. J Forest 114(3):352–362
McHarg I (1969) Design with nature. Natural History Press, New York
Nasr M, Moustafa M, Seif H, ElKobrosy G (2012) Application of artificial neural network (ANN) for the prediction of ELAGAMY wastewater treatment plant performance-EGYPT. Alex Eng J 51(1):37–43
Nuruddin MF, Ullah Khan S, Shafiq N, Ayub T (2015) Strength prediction models for PVA fiber-reinforced high-strength concrete. J Mater Civ Eng 27:2–16
Picton P (2000) Neural networks, 2nd edn. Palgrave, New York
Potter KM, Cubbage FW, Schaberg RH (2005) Multiple-scale landscape predictors of benthic macroinvertebrate community structure in North Carolina. Landsc Urban Plan 71:77–90
Vali A, Ramesht MH, Seif A, Ghazavi R (2012) An assessment of the artificial neural networks technique to geomorphologic modelling sediment yield (case study Samandegan river system). Geogr Environ Plan J 44(4):5–9
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Pourmohammad, P., Jahani, A., Zare Chahooki, M.A. et al. Road impact assessment modelling on plants diversity in national parks using regression analysis in comparison with artificial intelligence. Model. Earth Syst. Environ. 6, 1281–1292 (2020). https://doi.org/10.1007/s40808-020-00799-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40808-020-00799-6