Sustainable land-use optimization using NSGA-II: theoretical and experimental comparisons of improved algorithms

Springer Science and Business Media LLC - Tập 36 - Trang 1877-1892 - 2020
Peichao Gao1,2, Haoyu Wang2, Samuel A. Cushman3, Changxiu Cheng2,4, Changqing Song2, Sijing Ye2
1State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
2Faculty of Geographical Science, Beijing Normal University, Beijing, China
3Rocky Mountain Research Station, USDA Forest Service, Flagstaff, USA
4National Tibetan Plateau Data Center, Beijing, China

Tóm tắt

United Nations outlined 17 Sustainable Development Goals (SDGs), but at the current rate of progress most will not be achieved within the desired timeframe. Since a third of SDGs are directly related to land resources, it is crucial to improve the effectiveness and efficiency of land-use planning. In that regard, there is particular value in algorithmically optimizing land-use planning to better support sustainability. An ideal tool for such optimizations is the nondominated sorting genetic algorithm II (NSGA-II). Improved versions of NSGA-II have been actively developed for land-use problems, but no thorough evaluations and very few comparative studies have been performed. Thus, the objective is to conduct a thorough evaluation of and a systematic comparison between improved NSGA-II algorithms for sustainable land-use optimization. We identified both the most popular and the latest improved algorithms. A theoretical comparison was first made between them in terms of initialization, crossover, mutation, and archiving strategy. Then, a framework consisting of four hierarchal levels (principle, macro-criteria, micro-criteria, and indicators) was developed and applied to make a comprehensive comparison through experiments. The most popular algorithm was demonstrated to produce high-quality results and be computationally efficient, whereas the other performs better in the diversity of results, space efficiency, and the degree of optimization. Both algorithms exhibited excellent performance in handling constraints. Possible approaches to further improve the algorithms include borrowing ideas of scale optimization and gene flow. The proposed framework is capable of guiding further improvement by developers and algorithm selection by users.

Tài liệu tham khảo

Bai Y, Wong CP, Jiang B, Hughes AC, Wang M, Wang Q (2018) Developing China’s Ecological Redline Policy using ecosystem services assessments for land use planning. Nat Commun 9(1):3034 Bautista S, Enjolras M, Narvaez P, Camargo M, Morel L (2016) Biodiesel-triple bottom line (TBL): A new hierarchical sustainability assessment framework of principles criteria & indicators (PC&I) for biodiesel production. Part II-validation. Ecol Ind 69:803–817 Cao K, Batty M, Huang B, Liu Y, Yu L, Chen JF (2011) Spatial multi-objective land use optimization: extensions to the non-dominated sorting genetic algorithm-II. Int J Geogr Inf Sci 25(12):1949–1969 Caparros-Midwood D, Barr S, Dawson R (2015) Optimised spatial planning to meet long term urban sustainability objectives. Comput Environ Urban Syst 54:154–164 Central Government of China (2014) Official Reply of the State Council Concerning the Land-Use Planning of Lhasa. Available from https://www.gov.cn/zhengce/content/2018-08/31/content_5317975.htm. Accessed 22 Feb 2020 Chen X, Huang JC, Yang HX, Jq P (2019) Approaching low-energy high-rise building by integrating passive architectural design with photovoltaic application. J Clean Prod 220:313–330 Chen XQ, Wu JG (2009) Sustainable landscape architecture: implications of the Chinese philosophy of “unity of man with nature” and beyond. Landsc Ecol 24(8):1015–1026 Cushman SA, Lewis JS (2010) Movement behavior explains genetic differentiation in American black bears. Landsc Ecol 25(10):1613–1625 da Silva RT, Fleskens L, van Delden H, van der Ploeg M (2018) Incorporating soil ecosystem services into urban planning: status, challenges and opportunities. Landsc Ecol 33(7):1087–1102 Das P, Haimes YY (1979) Multiobjective optimization in water quality and land management. Water Resour Res 15(6):1313–1322 Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197 Duh J-D, Brown DG (2007) Knowledge-informed Pareto simulated annealing for multi-objective spatial allocation. Comput Environ Urban Syst 31(3):253–281 Duo B, Zhang YC, Kong LD, Fu HB, Hu YJ, Chen JM, Li L, Qiong A (2015) Individual particle analysis of aerosols collected at Lhasa City in the Tibetan Plateau. J Environ Sci 29:165–177 Fu BJ, Wang S, Zhang JZ, Hou ZQ, Li JH (2019) Unravelling the complexity in achieving the 17 Sustainable Development Goals. Nat Sci Rev 6(3):386–388 Gao P, Kupfer JA, Guo DS, Lei TL (2013) Identifying functionally connected habitat compartments with a novel regionalization technique. Landsc Ecol 28(10):1949–1959 Gao PC, Li ZL, Qin Z (2019) Usability of value-by-alpha maps compared to area cartograms and proportional symbol maps. J Spatial Sci 64(2):239–255 Gao PC, Wang XY, Wang HY, Cheng CX (2020) Viewpoint: a correction to the entropy weight coefficient method by Shen et al. for accessing urban sustainability [Cities 42 (2015) 186–194]. Cities 103:102742 Government of the Tibet Autonomous Region (2011) Land Use Plan of the Tibet Autonomous Region. Available from https://www.mnr.gov.cn/gk/ghjh/201811/t20181101_2324752.html. Accessed 22 Feb 2020 Gustafson EJ (2013) When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world. Landsc Ecol 28(8):1429–1437 Herrera-León S, Lucay FA, Cisternas LA, Kraslawski A (2019) Applying a multi-objective optimization approach in designing water supply systems for mining industries. The case of Chile. J Clean Prod 210:994–1004 Holland JH (1992) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. MIT press, Cambridge Hou YH, Zhong FY, Ren GX, Yang GH (2011) Evaluation of ecosystem services in Lhasa of Tibet. J Northwest For Univ 26(2):220–224 Hu HT, Fu BJ, Lü YH, Zheng ZM (2015) SAORES: a spatially explicit assessment and optimization tool for regional ecosystem services. Landsc Ecol 30(3):547–560 Huang J, Kang SC, Wang SX, Wang L, Zhang QG, Guo JM, Wang K, Zhang GS, Tripathee L (2013) Wet deposition of mercury at Lhasa, the capital city of Tibet. Sci Total Environ 447:123–132 ISO (2008) Part 11: Guidance on usability. ISO 9241: ergonomic requirements for office work with visual display terminals (VDTs). International Organization for Standardization, Geneva Iverson DC, Alston RM (1986) The genesis of FORPLAN: a historical and analytical review of forest service planning models. US Department of Agriculture Forest Service, Intermountain Research Station, Ogden Karakostas SM (2017) Bridging the gap between multi-objective optimization and spatial planning: a new post-processing methodology capturing the optimum allocation of land uses against established transportation infrastructure. Transp Plann Technol 40(3):305–326 Karimi A, Hockings M (2018) A social-ecological approach to land-use conflict to inform regional and conservation planning and management. Landsc Ecol 33(5):691–710 Kozek T, Roska T, Chua LO (1993) Genetic algorithm for CNN template learning. IEEE Trans Circuits Syst I: Fundam Theory and Appl 40(6):392–402 Kuang WH (2019) Mapping global impervious surface area and green space within urban environments. Sci China Earth Sci 62(10):1591–1606 Kuang WH (2020) Seasonal variation in air temperature and relative humidity on building areas and in green spaces in Beijing, China. Chin Geogra Sci 30(1):75–88 Kulczyk S, Woźniak E, Derek M (2017) Ecosystem services in tourism and recreation research–the example of fishing in the Great Masurian Lakes, Poland. Landsc Ecol 44:79–88 Land Portal Foundation (2019) Land and the Sustainable Development Goals (SDGs). Available from https://landportal.org/book/sdgs. Accessed 5 Dec 2019 Liberati MR, Rittenhouse CD, Vokoun JC (2019) Addressing ecological, economic, and social tradeoffs of refuge expansion in constrained landscapes. Landsc Ecol 34(3):627–647 Lin YP, Anthony J, Lin WC, Lien WY, Petway JR, Lin TE (2019) Spatiotemporal identification of roadkill probability and systematic conservation planning. Landsc Ecol 34(4):717–735 Liu G, Long W, Wang JC, Gao PC, He J, Luo ZY, Li L, Li YS (2018) Improving the throughput of transportation networks with a time-optimization routing strategy. Int J Geogr Inf Sci 32(9):1815–1836 Liu JG (2018) An integrated framework for achieving Sustainable Development Goals around the world. Ecol Econ Soc 1(2):11–17 Liu ZF, He CY, Yang YJ, Fang ZH (2020) Planning sustainable urban landscape under the stress of climate change in the drylands of northern China: A scenario analysis based on LUSD-urban model. J Clean Prod 244:118709 Masoomi Z, Mesgari MS, Hamrah M (2013) Allocation of urban land uses by multi-objective particle swarm optimization algorithm. Int J Geogr Inf Sci 27(3):542–566 McGarigal K, Wan HY, Zeller KA, Timm BC, Cushman SA (2016) Multi-scale habitat selection modeling: a review and outlook. Landsc Ecol 31(6):1161–1175 Ohls JC, Weisberg RC, White MJ (1974) The effect of zoning on land value. J Urban Econ 1(4):428–444 Opdam P, Luque S, Nassauer J, Verburg PH, Wu JG (2018) How can landscape ecology contribute to sustainability science? Landsc Ecol 33(1):1–7 Peng J, Hu XX, Wang XY, Meersmans J, Liu YX, Qiu SJ (2019) Simulating the impact of Grain-for-Green Programme on ecosystem services trade-offs in Northwestern Yunnan, China. Ecosyst Serv 39:100998 Pohjanmies T, Eyvindson K, Triviño M, Mönkkönen M (2017) More is more? Forest management allocation at different spatial scales to mitigate conflicts between ecosystem services. Landsc Ecol 32(12):2337–2349 Porta J, Parapar J, Doallo R, Rivera FF, Santé I, Crecente R (2013) High performance genetic algorithm for land use planning. Comput Environ Urban Syst 37:45–58 Qiu J (2008) China: the third pole. Nature 454(7203):393–396 Schlager KJ (1965) A land use plan design model. J Am Inst Plan 31(2):103–111 Shaygan M, Alimohammadi A, Mansourian A, Govara ZS, Kalami SM (2014) Spatial multi-objective optimization approach for land use allocation using NSGA-II. IEEE J Sel Topics Appl Earth Obs Remote Sens 7(3):906–916 Song MJ, Chen DM (2018a) A comparison of three heuristic optimization algorithms for solving the multi-objective land allocation (MOLA) problem. Ann of GIS 24(1):19–31 Song MJ, Chen DM (2018b) An improved knowledge-informed NSGA-II for multi-objective land allocation (MOLA). Geo-spatial Inf Sci 21(4):273–287 Su SL, Xiao R, Jiang ZL, Zhang Y (2012) Characterizing landscape pattern and ecosystem service value changes for urbanization impacts at an eco-regional scale. Appl Geogr 34:295–305 Sun XF, Gao L, Ren H, Ye YQ, Li A, Stafford-Smith M, Connor JD, Wu JG, Bryan BA (2018) China’s progress towards sustainable land development and ecological civilization. Landsc Ecol 33:1647–1653 Thomas JW, Franklin JF, Gordon J, Johnson KN (2006) The Northwest Forest Plan: origins, components, implementation experience, and suggestions for change. Conserv Biol 20(2):277–287 Vranken I, Baudry J, Aubinet M, Visser M, Bogaert J (2015) A review on the use of entropy in landscape ecology: heterogeneity, unpredictability, scale dependence and their links with thermodynamics. Landsc Ecol 30(1):51–65 Wallin DO, Swanson FJ, Marks B (1994) Landscape pattern response to changes in pattern generation rules: land-use legacies in forestry. Ecol Appl 4(3):569–580 Wan HY, Cushman SA, Ganey JL (2019) Improving habitat and connectivity model predictions with multi-scale resource selection functions from two geographic areas. Landsc Ecol 34(3):503–519 Wang SH, Gao S, Feng X, Murray AT, Zeng Y (2018) A context-based geoprocessing framework for optimizing meetup location of multiple moving objects along road networks. Int J Geogr Inf Sci 32(7):1368–1390 Wang XY, Gao PC, Song CQ, Cheng CX (2020) Use of entropy in developing SDG-based indices for assessing regional sustainable development: a provincial case study of China. Entropy 22(4):406 World Commission on Environment and Development (1987) Our Common Future. Oxford University Press, Oxford Wu JG (2013) Landscape sustainability science: ecosystem services and human well-being in changing landscapes. Landsc Ecol 28(6):999–1023 Wu XL, Murray AT, Xiao NC (2011) A multiobjective evolutionary algorithm for optimizing spatial contiguity in reserve network design. Landsc Ecol 26(3):425–437 Yue CT, Qu BY, Yu KJ, Liang J, Li XD (2019) A novel scalable test problem suite for multimodal multiobjective optimization. Swarm Evolut Comput 48:62–71 Zhang F, Yushanjiang A, Jing YQ (2019) Assessing and predicting changes of the ecosystem service values based on land use/cover change in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China. Sci Total Environ 656:1133–1144 Zhao SQ, Zhou DC, Zhu C, Qu WY, Zhao JJ, Sun Y, Huang D, Wu WJ, Liu SG (2015) Rates and patterns of urban expansion in China’s 32 major cities over the past three decades. Landsc Ecol 30(8):1541–1559 Zhou L, Xu K, Cheng X, Xu YY, Jia QB (2017) Study on optimizing production scheduling for water-saving in textile dyeing industry. J Clean Prod 141:721–727