Evaluation of ecological capability and land use planning for different uses of land with a new model of EMOLUP in Jahrom County, Iran

doi:10.1007/s11707-021-0957-y

Front. Earth Sci.

2023, Vol. 17

Issue (2) : 561-575 https://doi.org/10.1007/s11707-021-0957-y

RESEARCH ARTICLE

Evaluation of ecological capability and land use planning for different uses of land with a new model of EMOLUP in Jahrom County, Iran

Parviz JOKAR, Masoud MASOUDI(

)

Department of Natural Resources and Environmental Engineering, School of Agriculture, Shiraz University, Shiraz 7144113131, Iran

Download: PDF(2807 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Land use planning is one of the basic principles of sustainable development in a region and in a country. The main objective of this paper is to test a new model of land use planning in order to evaluate ecological suitability and prioritize different land uses in Jahrom County placed in Fars Province, Iran. Hence two main steps were prepared for the new model of Eco-Socio-economic Model of Land Use Planning (EMOLUP). Step 1 includes ecological capability evaluation of different land uses including forest, rangeland, agriculture, conservation, and development. This step is composed of the geometric mean method instead of the Boolean method; and step 2 includes land use planning and prioritizing for the various uses mentioned above. This step is composed of intersecting ecological capability maps and land use planning, based on two scenarios (economic and social). It was compared with qualitative and current quantitative methods. Also, current land use is employed for calibrating and modifying the models. The results of ecological suitability evaluation showed that the EMOLUP model has more accuracy in the process of comparison than other current methods. Accordingly, revised method using the geometric mean (with overall accuracy > 72 and kappa index > 0.55 for all land uses and rangeland with overall accuracy = 32 and kappa index = 0.02) is better than Boolean models, and the method of the calibrated geometric mean (with overall accuracy > 87 and kappa index > 0.73 for all land uses) is the best among different used models. It should be noted that the arithmetic mean has the lowest accuracy (with overall accuracy < 45 and kappa index < 0.24 for all land uses). Also, the results of prioritizing and land use planning showed that the quantitative method with two socio-economic scenarios (result based on average of EPM erosion model = 0.3 that means 30% of modification in whole study area land uses) is the best method for land use planning in the study area.

Keywords EMOLUP Model geomean Boolean prioritizing land use capability

Corresponding Author(s): Masoud MASOUDI

Online First Date: 02 November 2022 Issue Date: 04 August 2023

Cite this article:

Parviz JOKAR,Masoud MASOUDI. Evaluation of ecological capability and land use planning for different uses of land with a new model of EMOLUP in Jahrom County, Iran[J]. Front. Earth Sci., 2023, 17(2): 561-575.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-021-0957-y
https://academic.hep.com.cn/fesci/EN/Y2023/V17/I2/561

Fig.1 Location of the study area in Iran.

Tab.1 The indicators used in the model of land evaluation of EMOLUP (Masoudi, 2018) for agriculture and natural resources or four classes’ models (a) and for development and ecotourism or three classes’ models (b) and conservation Use (c)

Tab.2 Suitability classes in capability maps and models for 4 classes’ uses (a) and models for 3 classes’ uses (b) regarding the scores ranges of polygons in the model of EMOLUP (Masoudi, 2018)

Tab.3 Example of scenarios designed for the study area (a) and Relative values (0?10) assigned to different land uses according to capability classes of the land with taking into consideration of different scenarios (b)

Tab.4 Validation of the models by EPM model to compare with current land use (a) and validation of the models by comparing with current land use and development (b)

Tab.5 Overall Accuracy, Inclass and Kappa coefficients in the used models

Fig.2 Ecological capability maps prepared with best accuracy (a) and percent of land under different capability classes for different methods of every use (b).

Tab.6 Validation of land use planning methods

Fig.3 Final map of land use planning by two scenarios.

Tab.7 Percent area of current and optimized land uses

1	Hammad A, Abu A Tumeizi (2012). Land degradation: socioeconomic and environmental causes and consequences in the Eastern Mediterranean.Land Degrad Dev, 23(3): 216–226 https://doi.org/10.1002/ldr.1069
2	Panah S K, Alavi Dapper M, De R, Goossens M Masoudi (2001). The use of TM thermal band for land cover/land use mapping in two different environmental conditions of Iran.J Agric Sci Technol, 3(1): 27–36
3	E, Asadifard M, Masoudi S F, Afzal Shamsi S R Fallah (2019). Evaluating the ecological potential for rangeland use by various land-use planning methods in Firozabad County. Rangeland, 13: 14−25 (in Persian)
4	G Ayalew (2015). A geographic information system based physical land suitability evaluation to groundnut and sweet potato in East Amhara, highlands of Ethiopia.J Biol Agric Healthc, 5(1): 33–38
5	A R, Babaee M Ownegh (2006). Evaluation of development potential and land use planning of Posht-e-Kooh watershed. J Agric Sci Nat Resour, 13: 127−137 (in Persian)
6	R V Benthem (2013). Land Evaluation for Rain Fed Agriculture in the Mediterranean Peyne area, Southern France. Dissertation for the Master’s Degree. Utrecht: Utrecht University
7	R G Congalton (1991). A review of assessing the accuracy of classifications of remotely sensed data.Remote Sens Environ, 37(1): 35–46 https://doi.org/10.1016/0034-4257(91)90048-B
8	Gregorio A, Di L J M Jansen (1998). Land Cover Classification System (LCCS): Classification Concepts and User Manual. For software version 1.0
9	M, Elaalem A, Comber P Fisher (2010). Land suitability analysis comparing Boolean logic with fuzzy analytic hierarchy process. In: Accuracy 2010 Symposium, July 20–23, Leicester: 245–247
10	S R Fallahshamsi (2004). Economic evaluation of different land uses in Kalibar-chai Forest-covered Watershed, using Linear Programming and Geographical Information Systems. Dissertation for the Doctroal Degree. Tehran: Tehran University (in Persian)
11	S R Fallahshamsi (1997). Accuracy assessment of satellite based maps using sampling. Dissertation for the Master’s Degree. University of Tehran (in Persian)
12	FAO (1976). A framework for land evaluation. Food and Agriculture Organization of the United Nations, Soils Bulletin 32
13	L, Feng X, Zhu X Sun (2014). Assessing coastal reclamation suitability based on a fuzzy-AHP comprehensive evaluation framework: a case study of Lianyungang, China.Mar Pollut Bull, 89(1–2): 102–111 https://doi.org/10.1016/j.marpolbul.2014.10.029 pmid: 25455377
14	N Froja (2013). Fuzzy-GIS development of land evaluation system for agricultural production in northwest Libya. Dissertation for the Doctoral Degree. Edinburgh: Heriot-Watt University
15	Z Gavrilovic (1998). The use of empirical method (erosion potential method) for calculating sediment production and transportation in studied or torrential streams. In: International Conference on River Regime. New York: John Wiley and Sons
16	M, Gharakhlou H R, Pourkhabbaz M J, Amiri Sabokbar H Faraji (2009). Ecological capability evaluation of qazvin region for determining urban development potential points using geographic information system. Regional urban Studies Res, 1(2): 51−68 (in Persain)
17	R, Ghorbani M R, Pourmohammadi H Mahmoodzadeh (2014). Environmental approach in modeling Land use change in Tabriz city using multi-temporal satellite images, MCE and Markov chain (1984–2038). Urban Studies, 2: 13−30 (in Persian)
18	H R, Jahantigh M, Masoudi P Jokar (2019). A quantitative approach to land use planning using GIS – a case study of Chabahar County, Iran.Eur J Environ Sci, 9(1): 12–20 https://doi.org/10.14712/23361964.2019.2
19	P, Jokar M, Masoudi F Karimi (2021). An MCE-based innovative approach to evaluating ecotourism suitability using GIS.Cuadernos de Investigacion Geografica, 47(2): 545–556 https://doi.org/10.18172/cig.4291
20	Y, Khosravi M, Kalantari N Kouhestani (2012). Spatial analysis of the degree of land suitability for agricultural and natural resources activities using FAO Model and GIS.J Conser Utiliz Nat Res, 1(3): 9–29
21	C P Kindleberger (1967). French Planning. In: Milikan M F, ed. National Economic Planning.New York: Columbia University Press, 279–303
22	C, Kosmas J, Poesen H Briassouli (1999). Key indicators of desertification at the Environmentally Sensitive Areas (ESA) scale, the Medalus Project: Mediterranean Desertification and Land Use. Manual on Key Indicators of Desertification and Mapping Environmentally Sensitive Areas to Desertification
23	H L, Liao Q H Wu (2013). Multi objective optimization by learning automata.J Global Optim, 55(2): 459–487 https://doi.org/10.1007/s10898-012-9973-5
24	M Makhdoum (2006). Principles of Land Use Planning (7th ed). Tehran: University of Tehran (in Persian)
25	M, Makhdoum A, Darvishsefat H, Jafarzadeh A Makhdom (2009). Environmental Evaluation and Planning by Geographic Information System. Iran: University of Tehran (in Persian)
26	Ullah K Masel (2014). Urban land-use planning using Geographical Information System and Analytical Hierarchy Process: case study Dhaka city. Dissertation for the Master’s Degree. Lund: Lund University
27	M Masoudi (2018). Land Use Planning Using Computer‏. Tehran: Payam Noor University Publisher (in Persian)
28	M, Masoudi P Jokar (2015). Land-use planning using a quantitative model and geographic information system (GIS) in Shiraz Township, Iran.Ecopersia, 3: 959–974
29	M, Masoudi P, Jokar Poor E Ramazani (2020). A GIS-based quantitative model for land use planning in Larestan County, Iran.EQA-Inter J Environ Qual, 40: 19–30
30	M, Masoudi P, Jokar M Sadeghi (2017). Land use planning using a quantitative model and geographic information system (GIS) in Darab County, Iran.J Materials Environ Sci, 8(8): 2975–2985
31	M, Masoudi R Zare (2019). Different irrigation methods and their comparisons based on the parametric evaluation method in Khosouyeh Dam Subbasin, Iran.J Resourc Eco, 10(5): 504–510 https://doi.org/10.5814/j.issn.1674-764x.2019.05.005
32	I L McHarg (1969). Design with Nature. New York: Wiley
33	M, Mokarram A R Zarei (2021). Determining prone areas to gully erosion and the impact of land-use change on it by using multiple-criteria decision-making algorithms in arid and semi-arid regions.Geoderma, 403: 115379 https://doi.org/10.1016/j.geoderma.2021.115379
34	A Najafifar (2012). The role of land use planning in optimal management of Zagros Forests (case study: Sarab Darrehshahr catchment, Ilam Province). Iranian J Forest Poplar Res, 19: 510−522 (in Persian)
35	A, Najafinezhad Soleimanabad L, Pishdad A Salmanmahini (2013). Comparison of the efficiency of systematic and multi objective land allocation methods for land use planning using Geographic Information System. J AppRS & GIS Techn Nat Res Sci, 4: 1−11 (in Persian)
36	G Nakos (1984). The land resource survey of Greece: a tool for land use planning and policy. In: Policy Analysis for Forestry Development. Proceedings of the International Conference held in Thessaloniki, Greece (IUFRO-Division 4), 439–450
37	J, Nouri R Sharifipour (2004). Ecological capability evaluation of rural development by means of GIS.Iranian Journal of Environmental Health Science and Engineering, 6: 81–90
38	R V O’Neill (1989). Perspectives in hierarchy and scale. In: Rougharden J, May R M, Levin S A, eds. Perspectives in Ecological Theory. Princeton: Princeton University Press
39	M, Oyinloye O Kufoniyi (2013). Application of IKONOS satellite images in monitoring of urban landuse change in Ikeja, GRA, Lagos, Nigeria.Inter J Eng Sci Invent, 2: 1–10
40	G, Pan J Pan (2012). Research in crop land suitability analysis based on GIS.Computer Computing Tech Agricul, 5: 314–325 https://doi.org/10.1007/978-3-642-27278-3_33
41	T, Pan Y, Zhang F, Su V, Lyne F, Cheng H Xiao (2021). Practical efficient regional land-use planning using constrained multi-objective genetic algorithm optimization.ISPRS Inter J Geo-Inform, 10(2): 100 https://doi.org/10.3390/ijgi10020100
42	H R, Pourkhabbaz S, Javanmardi Sabokbar H A Faraji (2014). Suitability analysis for determining potential agricultural land use by the multi-criteria decision making models SAW and VIKOR-AHP (Case study: Takestan-Qazvin Plain).J Agr Sci Tech, 16(5): 1005–1016
43	D G Rossiter (1996). A theoretical framework for land evaluation.Geoderma, 72(3–4): 165–190 https://doi.org/10.1016/0016-7061(96)00031-6
44	M, Sanaee Shamsi S R, Fallah Asemanjerdi H Ferdowsi (2010). Multi-criteria land evaluation, using WLC and OWA strategies to select suitable site of forage plantation (case study: Zakherd, Fars). Rangeland, 4: 216−227 (in Persian)
45	C, Steinitz P, Parker L Jordan (1976). Hand drawn overlays: their history and prospective uses.Landscape Architecture, 9: 444–455
46	R Storie (1987). Storie index soil rating. OaHand University of California, division of agricultural sciences, special publication, 32(3)
47	H, Yohannes T Soromessa (2018). Land suitability assessment for major crops by using GIS-based multi-criteria approach in Andit Tid watershed, Ethiopia.Cogent Food Agricul, 4(1): 147048 https://doi.org/10.1080/23311932.2018.1470481
48	H Zareian (2009). Study of vertebrate fauna of “Kuh-e-Gorm” as non-hunting area in Fars province using Geographic Information System (GIS). Dissertation for the Master’s Degree. Shiraz: Shiraz University (in Persian)

[1]	Yi ZHANG, Peng LI, Xiaojun LIU, Lie XIAO, Tanbao LI, Dejun WANG. The response of soil organic carbon to climate and soil texture in China[J]. Front. Earth Sci., 2022, 16(4): 835-845.
[2]	Xiaolu TANG, Li SHENG, Yinkang ZHOU. Exploring complex urban growth and land use efficiency in China’s developed regions: implications for territorial spatial planning[J]. Front. Earth Sci., 2022, 16(4): 1040-1051.
[3]	Guihua LIU, Britta SCHMALZ, Qi ZHANG, Shuhua QI, Lichao ZHANG, Shiyu LIU. Assessing effects of land use and land cover changes on hydrological processes and sediment yield in the Xunwu River watershed, Jiangxi Province, China[J]. Front. Earth Sci., 2022, 16(3): 819-833.
[4]	Jing YE, Zhijie HOU, Haiyan MING, Yehuai CHENG. Ecological security pattern-based simulation for land use structure change: a case study in Ezhou City, China[J]. Front. Earth Sci., 2021, 15(3): 526-542.
[5]	Zhuokun PAN, Yueming HU, Guangxing WANG. Detection of short-term urban land use changes by combining SAR time series images and spectral angle mapping[J]. Front. Earth Sci., 2019, 13(3): 495-509.
[6]	Ying XIONG, Fen PENG, Bin ZOU. Spatiotemporal influences of land use/cover changes on the heat island effect in rapid urbanization area[J]. Front. Earth Sci., 2019, 13(3): 614-627.
[7]	Kun JIA, Jingcan LIU, Yixuan TU, Qiangzi LI, Zhiwei SUN, Xiangqin WEI, Yunjun YAO, Xiaotong ZHANG. Land use and land cover classification using Chinese GF-2 multispectral data in a region of the North China Plain[J]. Front. Earth Sci., 2019, 13(2): 327-335.
[8]	Jicai NING, Zhiqiang GAO, Ran MENG, Fuxiang XU, Meng GAO. Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta[J]. Front. Earth Sci., 2018, 12(2): 444-456.
[9]	Jianguo LI, Wenhui YANG, Qiang LI, Lijie PU, Yan XU, Zhongqi ZHANG, Lili LIU. Effect of reclamation on soil organic carbon pools in coastal areas of eastern China[J]. Front. Earth Sci., 2018, 12(2): 339-348.
[10]	Ellen WOHL. The significance of small streams[J]. Front. Earth Sci., 2017, 11(3): 447-456.
[11]	Chong PENG, Hao XIAO, Yu LIU, Jingjing ZHANG. Economic structure and environmental quality and their impact on changing land use efficiency in China[J]. Front. Earth Sci., 2017, 11(2): 372-384.
[12]	Hui ZHANG, Qiao WANG, Guangyu LI, Hanpei ZHANG, Jue ZHANG. Losses of Ecosystem Service Values in the Taihu Lake Basin from 1979 to 2010[J]. Front. Earth Sci., 2017, 11(2): 310-320.
[13]	Junyong AI, Lan FENG, Xiaowei DONG, Xiaodong ZHU, Yangfan LI. Exploring coupling coordination between urbanization and ecosystem quality (1985–2010): a case study from Lianyungang City, China[J]. Front. Earth Sci., 2016, 10(3): 527-545.
[14]	Xin YANG, Yu ZHAO, Rui CHEN, Xinqi ZHENG. Simulating land use change by integrating landscape metrics into ANN-CA in a new way[J]. Front. Earth Sci., 2016, 10(2): 245-252.
[15]	Cui JIN, Xiangming XIAO, Jinwei DONG, Yuanwei QIN, Zongming WANG. Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China[J]. Front. Earth Sci., 2016, 10(1): 49-62.

Viewed

Full text

Abstract

Cited

Shared

Discussed