松嫩高平原土地利用格局变化时间尺度特征研究
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摘要
土地利用格局变化的时间尺度是其尺度依赖性和敏感性表达的重要基础。论文以松嫩高平原典型区域巴彦县为研究区,运用GIS、RS技术,结合Matlab编程,采用K-L变换将多波段的遥感影像提取为单波段图像作为原始信号数据,在研究区土地利用格局最优空间尺度下,应用快速傅里叶变换对小波分析模型进行改进,探寻研究区土地利用格局变化研究的适宜时间尺度,进而明确适宜时空尺度下土地利用格局变化的波动性特征,并采用土地利用转移矩阵对其时间尺度的划分结果进行检验。结果表明:1)研究区土地利用格局变化在10~20、30~40和40~50 a均有明显的波动性特征,表明10~20、30~40和40~50 a是研究区土地利用格局变化的3个重要时间尺度。2)1979—2015年研究区土地利用格局变化研究的最优时间分析尺度为36a,土地利用格局在12.33 a左右具有明显的波动性变化特征,可将研究区时间域划分为3个发展阶段:发展初期1979—1991年、发展中期1991—2003年、发展近期2003—2015年。3)在空间上,研究区土地利用格局变化的全局化时间尺度和土地利用格局变化的局部化时间尺度具有较高水平的一致性。4)论文建立的基于小波分析的土地利用格局变化时间尺度识别方法可行并具有准确性,研究区旱地、林地和建设用地等主要土地利用类型在1979、1991、2003和2015年4个重要时间节点上的变化发生了明显的趋势性转换。
The scale dependency and sensitivity are important characteristics of land use pattern change. Taking Bayan County in Songnen High Plain as the empirical study area, the paper extracts single band image data as the original signal from multi-band image with K-L transformation. On the optimal spatial scale of the land use pattern in the study area, the wavelet analysis model was improved with fast Fourier transform to explore the appropriate time scale of land use pattern change in the study area. The model can automatically identify the land use pattern change and clarify the volatility characteristics of land use pattern change on appropriate time and space scales. Land use transfer matrix was used to test the results of time scale. The conclusions are as follows. Firstly, the land use pattern change showed volatility characteristics on time scales of 10-20 years, 30-40 years and 40-50 years. The volatility of land use pattern change on time scale of 40-50 years was the most intensive one,followed by the volatility on time scale of 30-40 years, and the volatility on time scale of 10-20 years was the least. Secondly, the optimal time scale for analysis of land use pattern change is 36 years in the study area during 1979-2015. Land use pattern has obviously volatility characteristics around 12.33 years. The study area can be divided into three development stages: the early stage is from 1979 to 1991, the medium stage is from 1991 to 2003, and the recent stage is from 2003 to 2015. Thirdly, the global time scale and the local time scale of land use pattern change were highly consistent in the study area. Finally, the main land use types,such as dry land, woodland and construction land, underwent obvious trend of conversion in the years of 1979, 1991, 2003 and 2015.
The scale dependency and sensitivity are important characteristics of land use pattern change. Taking Bayan County in Songnen High Plain as the empirical study area, the paper extracts single band image data as the original signal from multi-band image with K-L transformation. On the optimal spatial scale of the land use pattern in the study area, the wavelet analysis model was improved with fast Fourier transform to explore the appropriate time scale of land use pattern change in the study area. The model can automatically identify the land use pattern change and clarify the volatility characteristics of land use pattern change on appropriate time and space scales. Land use transfer matrix was used to test the results of time scale. The conclusions are as follows. Firstly, the land use pattern change showed volatility characteristics on time scales of 10-20 years, 30-40 years and 40-50 years. The volatility of land use pattern change on time scale of 40-50 years was the most intensive one,followed by the volatility on time scale of 30-40 years, and the volatility on time scale of 10-20 years was the least. Secondly, the optimal time scale for analysis of land use pattern change is 36 years in the study area during 1979-2015. Land use pattern has obviously volatility characteristics around 12.33 years. The study area can be divided into three development stages: the early stage is from 1979 to 1991, the medium stage is from 1991 to 2003, and the recent stage is from 2003 to 2015. Thirdly, the global time scale and the local time scale of land use pattern change were highly consistent in the study area. Finally, the main land use types,such as dry land, woodland and construction land, underwent obvious trend of conversion in the years of 1979, 1991, 2003 and 2015.
引文
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[15]JAMES P M A,FLEMING R A,FORTIN M-J.Identifying significant scale-specific spatial boundaries using wavelets and null models:Spruce budworm defoliation in Ontario,Canada as a case study[J].Landscape Ecology,2010,25(6):873-887.
[16]宋戈,王越.松嫩高平原土地利用格局空间尺度识别及其关联关系研究[J].中国土地科学,2017,31(1):88-96.[SONG G,WANG Y.Study on spatial scale recognition and its relationships of land use pattern in Songnen High Plain.China Land Sciences,2017,31(1):88-96.]
[2]傅丽华,谢炳庚,何燕子,等.基于小波分析长株潭核心区土地利用变化尺度特征研究[J].地理科学,2012,32(1):60-65.[FU L H,XIE B G,HE Y Z,et al.Characteristics of land use change in Changsha-Zhuzhou-Xiangtan core area based on wavelet analysis.Scientia Geographica Sinica,2012,32(1):60-65.]
[3]倪九派,邵景安,李阳兵,等.近10年重庆土地利用平衡及未来情景分析[J].资源科学,2011,33(8):1591-1599.[NIJ P,SHAO J A,LI Y B,et al.Land-use balances over the recent 10-year and their future scenarios in Chongqing.Resources Science,2011,33(8):1591-1599.]
[4]李双成,蔡运龙.地理尺度转换若干问题的初步探讨[J].地理研究,2005,24(1):11-18.[LI S C,CAI Y L.Some scaling issues of geography.Geographical Research,2005,24(1):11-18.]
[5]DOVERS S R.A framework for scaling and framing policy problems in sustainability[J].Ecological Economics,1995,12(2):93-106.
[6]李双成,赵志强,高江波.基于空间小波变换的生态地理界线识别与定位[J].生态学报,2008,28(9):4313-4322.[LIS C,ZHAO Z Q,GAO J B.Identifying eco-geographical boundary using spatial wavelet transform.Actaecologica Sinica,2008,28(9):4313-4322.]
[7]秦承志,呼雪梅.栅格数字地形分析中的尺度问题研究方法[J].地理研究,2014,33(2):270-283.[QIN C Z,HU XM.Review on scale-related researches in gird-based digital terrain analysis.Geographical Research,2014,33(2):270-283.]
[8]GIBSON C C,OSTROM E,AHN T K.The concept of scale and the human dimensions of global change:A survey[J].Ecological Economics,2000,32(2):217-239.
[9]潘雅婧,王仰麟,彭建,等.基于小波与R/S方法的汉江中下游流域降水量时间序列分析[J].地理研究,2012,31(5):811-820.[PAN Y J,WANG Y L,PENG J,et al.Precipitation change in middle and lower reaches of Hanjiang river:Based on wavelet analysis and R/S analysis.Gecgraphical Research,2012,31(5):811-820.]
[10]桑燕芳,王中根,刘昌明.小波分析方法在水文学研究中的应用现状及展望[J].地理科学进展,2013,32(9):1413-1422.[SANG Y F,WANG Z G,LIU C M.Applications of wavelet analysis to hydrology:Status and prospects.Progress in Geography,2013,32(9):1413-1422.]
[11]QUIROZ R,YARLEQUéC,POSADAS A,et al.Improving daily rainfall estimation from NDVI using a wavelet transform[J].Environmental Modeling&Software,2011,26(2):201-209.
[12]朴英超,关燕宁,张春燕,等.基于小波变换的卧龙国家级自然保护区植被时空变化分析[J].生态学报,2016,36(9):2656-2668.[PIAO Y C,GUAN Y N,ZHANG C Y,et al.Analysis of temporal and spatial change in vegetation cover using wavelet transform method in Wolong Natural Reserve.Acta Ecologica Sinica,2016,36(9):2656-2668.]
[13]PERCIVAL D B,WANG M,OVERLAND J E.An introduction to wavelet analysis with applications to vegetation time series[J].Community Ecology,2004,5(1):19-30.
[14]MARTINEZ B,GILABERT M A.Vegetation dynamics from NDVI time series analysis using the wavelet transform[J].Remote Sensing of Environment,2009,113(9):1823-1842.
[15]JAMES P M A,FLEMING R A,FORTIN M-J.Identifying significant scale-specific spatial boundaries using wavelets and null models:Spruce budworm defoliation in Ontario,Canada as a case study[J].Landscape Ecology,2010,25(6):873-887.
[16]宋戈,王越.松嫩高平原土地利用格局空间尺度识别及其关联关系研究[J].中国土地科学,2017,31(1):88-96.[SONG G,WANG Y.Study on spatial scale recognition and its relationships of land use pattern in Songnen High Plain.China Land Sciences,2017,31(1):88-96.]