巽他陆架末次冰期植被之谜

郁金勇, 李丽, 贺娟, 贾国东. 巽他陆架末次冰期植被之谜[J]. 海洋地质与第四纪地质, 2021, 41(4): 129-141. doi: 10.16562/j.cnki.0256-1492.2020103101
引用本文: 郁金勇, 李丽, 贺娟, 贾国东. 巽他陆架末次冰期植被之谜[J]. 海洋地质与第四纪地质, 2021, 41(4): 129-141. doi: 10.16562/j.cnki.0256-1492.2020103101
YU Jinyong, LI Li, HE Juan, JIA Guodong. The mystery of the Sunda shelf vegetation during the last glacial period[J]. Marine Geology & Quaternary Geology, 2021, 41(4): 129-141. doi: 10.16562/j.cnki.0256-1492.2020103101
Citation: YU Jinyong, LI Li, HE Juan, JIA Guodong. The mystery of the Sunda shelf vegetation during the last glacial period[J]. Marine Geology & Quaternary Geology, 2021, 41(4): 129-141. doi: 10.16562/j.cnki.0256-1492.2020103101

巽他陆架末次冰期植被之谜

  • 基金项目: 国家重点研发计划“国际大洋钻探南海航次后科学研究”(2018YFE0202402);国家自然科学基金“南海沉积物中支链四醚膜脂的组成和碳同位素特征及其对古气候研究的启示”(41673042),“晚渐新世—中中新世东亚低纬区降水演化历史及其全球影响”(41876042),“长江口外藻类生物标志化合物氢同位素与海洋盐度关系的研究”(41776049);上海市科委国际合作项目“国际大洋钻探计划合作研究”(20590780200)
详细信息
    作者简介: 郁金勇(1997—),男,硕士研究生,主要从事海洋生物地球化学和古气候研究,E-mail:1931656@tongji.edu.cn
    通讯作者: 李丽(1974—),女,教授,主要从事海洋生物地球化学和古气候研究,E-mail:lilitju@tongji.edu.cn
  • 中图分类号: P736.2

The mystery of the Sunda shelf vegetation during the last glacial period

More Information
  • 末次冰期低海平面时期出露的巽他陆架植被变化对全球碳循环影响有着重要影响,但目前植被重建结果仍存在很大争议。利用巽他陆架区域现有末次冰期的碳同位素和植物孢粉记录进行了古植被重建。与全新世相比,末次冰期时热带雨林的分布范围向赤道方向收缩,呈现不均匀的带状分布,而远离赤道的区域草本植物扩张。赤道辐合带的向南移动和热带太平洋的类El Niño状态导致的巽他陆架区域整体降水减少是造成这种现象的重要原因。山地在冰期植被垂直分布结构的演化中起着重要作用。在湿而冷的区域,山地雨林向下扩展;而在干而冷的区域,山地扮演着雨林避难所的角色。巽他陆架古植被重建工作仍面临着隐域性植被、植被指标局限性等难点。

  • 泥石流作为我国自然灾害重要类型之一,具有暴发突然、波及范围广、破坏性大等特点。泥石流易发性评价也从最早的定性分析发展到定量分析,一直以来是国内外地学专家学者研究的热点[1-2],其评价质量的好坏与评价指标的选取、评价模型的确定有着密不可分的关系[3-8]。地形地貌、地质构造及人类活动等是泥石流易发性的主要影响因素,也成为其评价指标选取的重要参考依据[9-10]。常用的泥石流易发性评价模型有专家系统模型(层次分析、专家打分)、数理统计模型(信息量、证据权和逻辑回归等)和机器学习模型(决策树、随机森林、神经网络和支持向量机等)[11-18],这些模型各有所长,同时也存在一定的缺陷。相对于专家系统模型受人为因素影响明显、机器学习模型存在参数调试较难等问题,信息量模型作为《地质灾害风险调查评价技术要求》(1∶50000)(试行)推荐的方法具有操作简单、应用广泛和客观性好等优势,能够科学的对各指标区间分级[19]

    东川区地质灾害发育,尤以泥石流分布广泛,危害最为严重,素有“世界泥石流天然博物馆”之称,是全国泥石流危害最严重的地区。据不完全统计,解放以来泥石流已造成人员伤亡300余人,直接经济损失近4亿元,并且对生态环境破坏明显,严重制约了东川经济与社会发展。因此,在东川建立科学合理的泥石流易发性评价模型,为泥石流精准防控提供支撑,意义重大[20-21]

    文中在对东川区地质灾害详细调查成果系统梳理基础上,细致分析东川泥石流流域特征、动力学特性与形成机理等,选取坡度、坡向、起伏度、曲率、工程岩组、距水系距离、距断层距离和土地利用类型9个评价指标,基于信息量模型和GIS平台技术,以小流域为单元对东川泥石流进行了易发性评价,以期为东川防灾减灾工作提供参考。

    东川区位于云南省昆明市最北端,面积1858.79 km2,属侵蚀剥蚀构造地貌,地势呈东西高中间河谷低、南高北低的特征,最大相对高差达3600 m。区域上属金沙江流域,区域年降水量701~1163 mm,降水量的85%以上集中在5—10月。区内地层岩性以元古代昆阳群碎屑岩分布最广,约占全区面积的43.68%,古生代碎屑岩夹碳酸盐岩约占19.10%,古生代玄武岩、中生代碎屑岩约占32.36%,新生代黏土岩和松散碎石土等约占4.86%。区内地质构造复杂,主构造线为南北向的小江断裂带。复杂的地形地貌、特殊的地质背景及独特的气候条件导致了东川泥石流频发。

    通过收集东川区地质灾害详查、隐患排查和风险普查等数据,结合InSAR地质灾害隐患早期识别成果和精细化调查野外验证,系统梳理出研究区典型泥石流144条(图1),以此作为样本数据,开展研究区泥石流易发性定量评价。

    图 1.  研究区泥石流灾害点分布
    Figure 1.  Distribution of debris flow in study area

    DEM数据收集自阿拉斯加卫星设备,制作高程、坡度、坡向、起伏度和曲率5个评价指标;水系数据收集自OSM并与DEM提取水系进行比对制作距水系距离评价指标;地质数据收集自全国地质资料馆东川幅、会理幅、曲靖幅和武定幅20万地质图[22]制作工程岩组分类和距断层距离2个评价指标,土地类型数据收集自欧空局官网制作土地利用类型评级指标(表1)。

    表 1.  数据来源及类型
    Table 1.  Data source and types
    基础数据评价因子数据来源及制作数据格式
    DEM高程ASF
    (阿拉斯加
    卫星设备)
    12.5 m×12.5 m
    栅格数据
    坡度
    坡向
    起伏度
    曲率
    水系距水系距离DEM提取
    Open Street Map
    矢量数据
    地质数据工程岩组分类全国地质资料馆矢量数据
    距断层距离
    土地类型土地利用类型ESA WorldCover10 m栅格数据
    灾害点泥石流数量地质灾害详查、排查等矢量数据
     | Show Table
    DownLoad: CSV

    泥石流易发性常用栅格作为评价单元,虽易于划分和模型计算,但忽略其流域特性,不能有效反映真实的泥石流情况,无法建立合理的评价模型,得出精准的评价结果。文中以收集的12.5 m×12.5 m的DEM栅格数据为基础,利用ArcGIS10.8模型构建器将流域划分过程(填洼→流向→流量→提取河流网络→栅格河网矢量化→盆域分析→栅格转面)模块化,化繁为简,实现自动化生成流域,通过反复调整集水阈值,最终得到最符合实际的流域划分结果。将研究区划分为961个流域,其中平均流域面积为1.94 km2,最大流域面积为10.62 km2,最小流域面积为0.44 km2

    信息量模型的理论基础是信息论[23],运用概率论和数理统计的方法以信息熵的概念来分析各种评价指标作用下泥石流易发性的模型。通过各种评价指标与泥石流灾害点空间叠加分析,依托GIS平台计算其单个指标信息量,然后进行多个指标的加权叠加得到综合信息量,从而建立泥石流易发性评价模型,其信息量值越大,表明易发性越高。

    I=nj=1lnNj/NSj/S (1)

    式中:I——各种评价指标加权的总信息量,可作为泥石流 易发性指数;

    Nj—单个评价指标特定分级区间内含有泥石流的个数;

    N——泥石流总数量;

    Sj——单个评价指标特定分级区间内栅格数;

    S——总栅格数。

    泥石流的形成影响因素众多,其演化是一个复杂的多因素耦合作用的地质过程。东川自1961年中科院建立野外观测站至今,对东川泥石流动力地貌过程与区域演化规律、运动学与动力学特征、流体物理力学与流变特性等方面取得了一系列国际先进水平成果。本文在系统分析东川泥石流触发因素基础上,结合大量专家学者泥石流易发性评价研究成果进行了评价指标的优选,选取坡度、坡向、起伏度、曲率、工程岩组、距水系距离、距断层距离和土地利用类型9个评价指标。

    首先通过GIS平台得到各评价指标的状态分级[24-25],然后对其分级区间进行重分类,与泥石流灾害点图层进行空间叠加分析统计,计算各评价指标图层的信息量值;采用栅格转面-空间连接-面转栅格实现将各评价指标的状态分级信息量值赋值到栅格图层中,运用空间分析工具叠加各评价指标的信息量栅格图层获取总信息量值,并按流域单元划分总信息量栅格图层,以子流域总信息量的平均值作为该子流域的信息量值,并按自然间断法对其进行重分类,实现研究区的泥石流易发性分区。

    因各评价指标的状态分级对信息量模型精度影响较大,科学合理划分其状态分级至关重要。文中在处理各评价指标状态分级时首先采用自然间断法一般将其细分为10~15级,与泥石流灾害点图层进行叠加分析,得出其信息量值,然后优先将信息量值为零的分级与相邻分级合并,接着将信息量值相近的分级与相邻分级合并,最后计算归并后的分级信息值,从而实现最优各评价指标状态分级(图2表2)。

    图 2.  各评价因子状态分级图
    Figure 2.  State classification of the factors
    表 2.  各因素状态信息量表
    Table 2.  Weighted information values of each factor
    指标因子分级泥石流点比例信息量值指标因子分级泥石流点比例信息量值
    高程/m660~15000.20331.238744曲率−38~−10.2139−0.131543
    1500~20000.2598−0.577567−1~00.31140.430833
    2000~25000.2209−1.3803670~20.3838−0.205470
    2500~30000.1594−0.831065>20.0909−1.473365
    >30000.1566−1.729497工程岩组软岩组0.02771.255712
    坡度/(°)0~100.11371.315538较软岩组0.56470.067643
    10~200.21330.545702较坚硬岩组0.0693−0.220774
    20~300.2821−0.871237坚硬岩组0.3383−0.330859
    30~400.2553−1.206583距水系距离/m00.00371.322303
    >400.1356−2.2788882000.50220.624230
    坡向平坦(−1)0.00110.0000004000.2786−1.899977
    北(0~22.5)0.06380.084068>4000.2155−3.435165
    北东(22.5~67.5)0.12680.353573距断层距离/m<10000.61260.183653
    东(67.5~112.5)0.1360.3926721000~20000.2277−0.445741
    南东(112.5~157.5)0.1266−0.3378062000~30000.09330.041246
    南(157.5~202.5)0.1072−0.791193>30000.0664−1.158486
    南西(202.5~247.5)0.1119−0.214621土地利用类型林地0.28390.184122
    西(247.5~292.5)0.13790.269687灌木0.0024−1.048475
    北西(292.5~337.5)0.1269−0.266767草地0.48770.955946
    北(337.5~360)0.0618−0.394293耕地0.1166−0.437008
    起伏度/(°)0~200.26391.006637建筑用地0.0230−1.937148
    20~400.4084−0.577548裸地/稀疏植被区0.0822−0.994439
    40~600.2465−1.960151开阔水域0.0042−0.514259
    60~4410.0812−1.766161    
     | Show Table
    DownLoad: CSV

    (1)高程

    以研究区12.5 m精度的DEM栅格数据为基础,最高点为拱王山雪岭,海拔4344 m,最低点位于金沙江与小江交汇处,海拔660 m,高差大于3600 m。以660~4344 m为区间,将高程分为5级,见图2(a)。泥石流主要分布在660~3000 m,占泥石流总数量的84.34%,见图3(a)。

    图 3.  各指标分级分区面积和泥石流数量相关性统计图
    Figure 3.  Statistical charts of correlation between the area of factor and the number of debris flow points

    (2)坡度

    从0°起,以10°为间隔,将坡度分为5级,见图2(b)。泥石流点在坡度各分级均有分布,主要集中在20°~40°,见图3(b)。

    (3)坡向

    将坡向划为10个分级,见图2(c)。泥石流在南、西南、东南方向比例为34.57%,在北、北西、北东方向为37.93%,可见泥石流在北坡比例大于南坡,见图3(c)。

    (4)地形起伏度

    地形起伏度可以直观的反映山体的相对高差,是划分地貌类型的一个重要指标,同时还能有效地体现人类活动与地质灾害发育程度的相关性。借助ArcGIS平台提取出研究区地形起伏度在0~441 m,分为0~20 m平坦起伏、20~40 m微起伏、40~60 m小起伏,>60 m较大起伏4个分级,见图2(d)。泥石流在微起伏占比最高,为40.84%,见图3(d)。

    (5)曲率

    曲率主要是用来反映地形弯曲程度的指标,将曲率划为4个分级,见图2(e)。泥石流主要分布在曲率−1~2,占泥石流总数量的69.52%,见图3(e)。

    (6)工程岩组分类

    以研究区20万地质图为基础,根据地层岩性的工程地质特性,将研究区工程岩组划分为4大类,见图2(f)。泥石流主要分布在较软岩组内,占泥石流总数量的56.47%,见图3(f)。

    (7)距水系距离

    研究区水系发育,分布有小江流域和普渡河流域,均属金沙江水系。以研究区内河流为中心作200 m、400 m、>400 m缓冲区分析,见图2(g)。结果表明,在距河流400 m范围内泥石流点分布集中,占泥石流总数量的78.08%,见图3(g)。

    (8)距断层距离

    研究区位于川滇菱形块体内部小江断裂与普渡河断裂夹持地带,断层发育。以研究区1∶20万构造纲要图为基础,以断层为中心作1 km、2 km、3 km、>3 km缓冲区分析,见图2(h)。分析表明泥石流主要位于断层0~2 km范围内,占比84.03%,见图3(h)。

    (9)土地利用类型

    土地利用数据采用欧空局(ESA)发布的2020年10 m分辨率的全球土地利用(World Cover)数据。研究区土地利用主要包括林地、灌木、草地、耕地、建筑用地、裸地/稀疏植被区和开阔水域7类,见图2(i)。泥石流主要集中分布在林地、草地和耕地内,占比88.82%,见图3(i)。

    评价指标体系建立完成后,基于GIS平台将各评价指标状态分级(图2)与泥石流灾害点进行空间叠加分析,得出各评价指标状态分级区间内泥石流分布数量(图3),根据信息量模型公式进行各评价指标信息量值计算,然后通过栅格叠加分析计算总信息量值,以自然间断法将其划分为4个等级,得到研究区泥石流易发性分区图,见图4(a)。低易发区[−14.15,−5.60]、中易发区[−5.60,−2.72]、高易发区[−2.72,0.42]及极高易发区[0.42,8.10],占东川区全域栅格比例为18.49%、32.43%、33.30%和15.78%,其灾点占栅格频率比分别为0.038、0.150、0.542、4.843,极高易发区和高易发区内灾点频率比最高,符合客观事实。

    图 4.  泥石流易发性分区图
    Figure 4.  Zoning map of debris-flows susceptibility

    目前泥石流易发性定量评价多采用直接以栅格单元为评价单元,往往会出现单条泥石流流域内存在不同的易发性分区,忽略了泥石流单元的整体性,与实际的环境不相符合,对指导泥石流的精准防控不利。为真实反映泥石流的环境演变,解决单条泥石流流域内分区差异性,文中将基于栅格单元计算得来的泥石流易发性总信息量值以流域为单元进行划分,然后统计每个子流域范围内信息量值的平均值,作为研究区子流域单元信息量值,通过自然间断法将其划分为4个等级:低易发区[−7.85,−3.97]、中易发区[−3.97,−2.25]、高易发区[−2.25,−0.31]及极高易发区[−0.31,3.39],得到研究区泥石流易发性分区图,见图4(b)。

    研究区泥石流极高易发区和高易发区主要集中在小江流域沿岸的阿旺镇、铜都镇、拖布卡镇一带分布,占全域面积的37.27%,其中著名的蒋家沟、大小白泥沟、大桥河沟以及城市后山4条沟均位于极高易发区,与历史泥石流灾害点吻合度较高。

    极高易发区和高易发区内地质环境特征典型,主要表现在以下几点:(1)位于小江活动断裂附近,构造极为发育,地震频发;(2)工程岩组以较软岩组为主,受小江断裂等影响岩石极为破碎,为泥石流发生提供了物质来源;(3)地形陡峻,相对高差大,地貌以侵蚀剥蚀为主;(4)距离水系越近泥石流易发性越高;(5)主要集中在小江河谷一线,人类工程活动强烈,对地形地貌破坏作用明显。

    文中采用深度学习二分类中常用评价模ROC型曲线进行检验,构建以易发性分区累计百分比为横轴,泥石流灾点数累计百分比为纵轴,曲线下面积(AUC)表示易发性预测成功率,其值越接近1,代表准确率越高[26-28]。本次采用的信息量模型AUC为0.876,准确度较高(图5)。

    图 5.  ROC曲线
    Figure 5.  The curve of receiver operating characteristic

    (1)构建了云南东川泥石流易发性定量评价指标体系,对评价指标状态分级进行优化处理后发现:泥石流主要分布在高程660~3000 m、坡度20°~40°,曲率−1~2,地形集中在微起伏地形,工程岩组主要以较软岩组为主,距河流400 m内,断层在0~2 km,土地利用类型以林地、草地和耕地为主,而坡向对其影响不大。

    (2)东川泥石流极高易发区和高易发区主要集中在小江流域沿岸的阿旺镇、铜都镇、拖布卡镇一带分布,占全域面积的37.27%。

    (3)通过信息量模型可以很好建立东川泥石流易发性定量预测模型,ROC曲线检验模型AUC=0.876,准确度较高,建模结果与历史泥石流灾害点吻合度较高,较好地揭示了研究区泥石流易发性特征,为东川防灾减灾工作提供参考。

    文中在评价指标选取和状态分级过程中仍存在一些不足之处。评价指标选取和状态分级合并主观性较强,后续可引入类似ROC曲线等验证模型进行定量化评价,提高其合理性和科学性。

  • 图 1  巽他陆架“稀树草原廊道”假说(左)及现代植被分布(右)

    Figure 1. 

    图 2  巽他陆架及其周边地区已发表碳同位素记录汇总

    Figure 2. 

    图 3  巽他陆架及其周边地区已发表孢粉记录汇总

    Figure 3. 

    图 4  末次冰期巽他陆架植被分布

    Figure 4. 

    表 1  巽他陆架及周边地区末次冰期碳同位素变化记录

    Table 1.  Carbon isotope records in the Sunda shelf and surrounding areas during the last glacial period

    站位经纬度水深/m碳同位素值范围/‰参考文献
    湖泊/海洋记录BJ8-03-91GGC2°52′N,118°23′E2326–30.8~–32.9[11]
    SO189-144KL1°5′N,98°1′E481–28.8~–31.9[37]
    179627°11′N,112°5′E1968–28.4~–33.9[38]
    18252-39°14'N,109°23'E1273–27.3~–34.5[39]
    MD05-28947°2'N,111°33'E1982–29.1~–36.6[40]
    IDLE-MAT10-2B2°31′S,121°24′E137–32.8~–44.9[41]
    GEOB10053-78°41′S,112°52′E1375–24.2~–31.5[44]
    GEOB10069-39°36′S,120°55′E1250–24.6~–28.9[11]
    IDLE-TOW10-9B2°30′S,121°30′E154–25.0~–41.0[42]
    SO185153°37'S,119°21'E688–25.0~–29.6[16]
    陆地记录Niah洞穴3°49′N,113°46′E–22.9~–26.2[9]
    Gomantong洞穴5°32'N,118°5'E–26.1~–27.7[33]
    Bau Bau洞穴0°55'S,117°13'E–23.5~–27.8[33]
    Batu洞穴3°13′N,101°42′E–26.2~–22.6[9]
    Makangit洞穴10°28′N,119°27′E–19.5~–30.3[9]
    Gangub洞穴8°31′N,117°33′E–18.0~–26.3[9]
    Saleh洞穴3°1'S,115°59'E–17.2~–27.3[14]
    下载: 导出CSV

    表 2  巽他陆架及周边地区末次冰期孢粉记录

    Table 2.  Pollen records in the Sunda shelf and surrounding areas during the last glacial period

    站位经纬度水深/m草本植物比例/%参考文献
    湖泊/海洋记录179627°11′N,112°5′E196810~30[49]
    179641°5′N,98°1′E15565~20[50]
    182875°39′N,110°39′E59810~40[51]
    183004°21′N,108°39′E915~75[48]
    183024°09'N,108°34'E835~40[48]
    183232°47'N,107°53'E924~55[48]
    CG-26°23′N,110°09′E12391~35[19]
    NS07-256°40′N,113°33′E20060~20[52]
    CB-197°46′N,114°40′E17980~20[53]
    MD06-30756°28′N,125°49′E18781~18[61]
    G6-410°47′S,118°04′E351020~60[67]
    SHI-90145°46′S,126°58′E316320~55[68]
    BRA94-426°04'S,102°25'E25422~52[64]
    陆地记录Niah3°49′N,113°46′E0~35[54]
    Kelabit3°34'N,115°33'E5~40[55]
    Sentarum0°44'N,112°06'E5~20[56]
    NTSH7°52′N,99°28′E0~20[60]
    Nee Soon1°24′N,103°48′E5~30[59]
    Sim Sim2°25′N,98°47′E0~60[58]
    Di-Atas1°04'S,100°46'E0[57]
    Wanda2°33'S,121°23'E5~50[43]
    Tondano1°29'N,124°50'E0~95[63]
    Rawa6°11′S,105°59′E0~60[65]
    Bandung7°S,108°E0~70[62,66]
    Misedor1°N,117°E0~40[62]
    Halmahera2°N,128°E0~30[62]
    下载: 导出CSV
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出版历程
收稿日期:  2020-10-31
修回日期:  2021-01-07
刊出日期:  2021-08-28

目录

  • 表 1.  数据来源及类型
    Table 1.  Data source and types
    基础数据评价因子数据来源及制作数据格式
    DEM高程ASF
    (阿拉斯加
    卫星设备)
    12.5 m×12.5 m
    栅格数据
    坡度
    坡向
    起伏度
    曲率
    水系距水系距离DEM提取
    Open Street Map
    矢量数据
    地质数据工程岩组分类全国地质资料馆矢量数据
    距断层距离
    土地类型土地利用类型ESA WorldCover10 m栅格数据
    灾害点泥石流数量地质灾害详查、排查等矢量数据
     | Show Table
    DownLoad: CSV
  • 表 2.  各因素状态信息量表
    Table 2.  Weighted information values of each factor
    指标因子分级泥石流点比例信息量值指标因子分级泥石流点比例信息量值
    高程/m660~15000.20331.238744曲率−38~−10.2139−0.131543
    1500~20000.2598−0.577567−1~00.31140.430833
    2000~25000.2209−1.3803670~20.3838−0.205470
    2500~30000.1594−0.831065>20.0909−1.473365
    >30000.1566−1.729497工程岩组软岩组0.02771.255712
    坡度/(°)0~100.11371.315538较软岩组0.56470.067643
    10~200.21330.545702较坚硬岩组0.0693−0.220774
    20~300.2821−0.871237坚硬岩组0.3383−0.330859
    30~400.2553−1.206583距水系距离/m00.00371.322303
    >400.1356−2.2788882000.50220.624230
    坡向平坦(−1)0.00110.0000004000.2786−1.899977
    北(0~22.5)0.06380.084068>4000.2155−3.435165
    北东(22.5~67.5)0.12680.353573距断层距离/m<10000.61260.183653
    东(67.5~112.5)0.1360.3926721000~20000.2277−0.445741
    南东(112.5~157.5)0.1266−0.3378062000~30000.09330.041246
    南(157.5~202.5)0.1072−0.791193>30000.0664−1.158486
    南西(202.5~247.5)0.1119−0.214621土地利用类型林地0.28390.184122
    西(247.5~292.5)0.13790.269687灌木0.0024−1.048475
    北西(292.5~337.5)0.1269−0.266767草地0.48770.955946
    北(337.5~360)0.0618−0.394293耕地0.1166−0.437008
    起伏度/(°)0~200.26391.006637建筑用地0.0230−1.937148
    20~400.4084−0.577548裸地/稀疏植被区0.0822−0.994439
    40~600.2465−1.960151开阔水域0.0042−0.514259
    60~4410.0812−1.766161    
     | Show Table
    DownLoad: CSV