Volume 39 Issue 4
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ZHOU Siyi, YIN Xiaojie, TANG Ruiquan, WU Pengfei. Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River[J]. Journal of Zhejiang A&F University, 2022, 39(4): 783-791. doi: 10.11833/j.issn.2095-0756.20210523
Citation: ZHOU Siyi, YIN Xiaojie, TANG Ruiquan, WU Pengfei. Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River[J]. Journal of Zhejiang A&F University, 2022, 39(4): 783-791. doi: 10.11833/j.issn.2095-0756.20210523

Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River

doi: 10.11833/j.issn.2095-0756.20210523
  • Received Date: 2021-07-28
  • Accepted Date: 2022-03-03
  • Rev Recd Date: 2022-02-28
  • Available Online: 2022-07-20
  • Publish Date: 2022-08-20
  •   Objective  The rocky desertification area in the upper reaches of the Yangtze River affects the ecological security of the whole basin. Under the comprehensive control of rocky desertification vigorously implemented by the state, the situation of rocky desertification has been significantly alleviated. But at present, there’s no evaluation method for eco-environmental quality in rocky desertification areas. The objective of this study is to carry out the real-time and quantitative evaluation of eco-environmental quality in rocky desertification areas.   Method  Based on Landsat 5, Landsat 7, and Landsat 8 satellite image data of Huize County, Yunnan Province in 2002, 2010, and 2018, the rocky desertification grades of the study area were divided, and the remote sensing ecological index (RSEI) was used to quantitatively evaluate and analyze the eco-environmental quality of the study area.   Result  (1) From 2002 to 2018, the overall rocky desertification situation in Huize County was significantly improved, and the rocky desertification area decreased by 583.33 km2. (2) There was a significant positive correlation between rocky desertification and eco-environmental quality (r2=0.688−0.873), indicating that RSEI was effective in evaluating eco-environmental quality in rocky desertification areas. (3) In 2002, 2010, and 2018, the average RSEI value in the study area was 0.458, 0.490, and 0.488 respectively, and the overall eco-environmental quality was at a medium level. The area of eco-environmental quality optimization in 16 years accounted for 27.42% of the total county area, and the area of ecological deterioration accounted for 15.09%. (4) The contribution of dryness index to RSEI was increasing, and the first principal component load value changed from −0.029 to −0.622, which was an important factor restricting the optimization of eco-environmental quality of Huize County.   Conclusion  From 2002 to 2018, the rocky desertification situation in Huize County was significantly improved, and the eco-environmental quality was at a medium level. The dryness index was an important factor restricting the optimization of eco-environmental quality. The protection of rocky desertification areas should be emphasized in the future. [Ch, 8 tab. 28 ref.]
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Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River

doi: 10.11833/j.issn.2095-0756.20210523

Abstract:   Objective  The rocky desertification area in the upper reaches of the Yangtze River affects the ecological security of the whole basin. Under the comprehensive control of rocky desertification vigorously implemented by the state, the situation of rocky desertification has been significantly alleviated. But at present, there’s no evaluation method for eco-environmental quality in rocky desertification areas. The objective of this study is to carry out the real-time and quantitative evaluation of eco-environmental quality in rocky desertification areas.   Method  Based on Landsat 5, Landsat 7, and Landsat 8 satellite image data of Huize County, Yunnan Province in 2002, 2010, and 2018, the rocky desertification grades of the study area were divided, and the remote sensing ecological index (RSEI) was used to quantitatively evaluate and analyze the eco-environmental quality of the study area.   Result  (1) From 2002 to 2018, the overall rocky desertification situation in Huize County was significantly improved, and the rocky desertification area decreased by 583.33 km2. (2) There was a significant positive correlation between rocky desertification and eco-environmental quality (r2=0.688−0.873), indicating that RSEI was effective in evaluating eco-environmental quality in rocky desertification areas. (3) In 2002, 2010, and 2018, the average RSEI value in the study area was 0.458, 0.490, and 0.488 respectively, and the overall eco-environmental quality was at a medium level. The area of eco-environmental quality optimization in 16 years accounted for 27.42% of the total county area, and the area of ecological deterioration accounted for 15.09%. (4) The contribution of dryness index to RSEI was increasing, and the first principal component load value changed from −0.029 to −0.622, which was an important factor restricting the optimization of eco-environmental quality of Huize County.   Conclusion  From 2002 to 2018, the rocky desertification situation in Huize County was significantly improved, and the eco-environmental quality was at a medium level. The dryness index was an important factor restricting the optimization of eco-environmental quality. The protection of rocky desertification areas should be emphasized in the future. [Ch, 8 tab. 28 ref.]

ZHOU Siyi, YIN Xiaojie, TANG Ruiquan, WU Pengfei. Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River[J]. Journal of Zhejiang A&F University, 2022, 39(4): 783-791. doi: 10.11833/j.issn.2095-0756.20210523
Citation: ZHOU Siyi, YIN Xiaojie, TANG Ruiquan, WU Pengfei. Evaluation of eco-environmental quality in typical rocky desertification areas in the upper reaches of the Yangtze River[J]. Journal of Zhejiang A&F University, 2022, 39(4): 783-791. doi: 10.11833/j.issn.2095-0756.20210523
  • 西南石漠化、西北荒漠化和黄土地区水土流失并称为中国最严重的三大生态问题[1],其中石漠化主要发生在中国的西南喀斯特区。这些地区本身土层较薄、涵养水源能力较差,加上不合理的人为活动,水土流失加剧、岩石出露加重、土地进一步退化[2]。位于长江上游的西南喀斯特区关乎整个长江流域的水安全、生物多样性安全,具有重要的生态屏障意义,而石漠化导致的当地生态系统功能退化,威胁了西南地区甚至整个长江流域的生态安全。因此,长江上游石漠化地区的生态环境问题是急需解决的重要议题。解决生态环境问题首先需要进行生态环境质量评价,进而分析具体情况找到解决方法。近年来,国内外研究学者针对生态环境质量评价进行了一系列研究[3-6]。自2013年徐秋涵[7]提出遥感生态指数(remote sensing ecological index,RSEI)以来,RSEI法已应用于城市、矿区、湿地、荒漠化和水土流失等地区的生态变化评价研究,在各类研究中均表现出很强的适用性[8-14]。使用RSEI法研究石漠化地区的生态环境质量,可为石漠化地区的定量化生态评价与监测提供借鉴,有助于及时调控人类活动的方向、强度、方式,对石漠化地区因地制宜的治理恢复有较强的指导意义。

    国家林业和草原局第3次石漠化监测报告表明:目前中国石漠化主要涉及8个省份,集中分布在贵州、云南、广西3省(自治区)[15]。云南省曲靖市地处珠江和长江上游,是长江、珠江水系的分水岭,生态区位十分重要。本研究以长江上游典型石漠化地区曲靖市会泽县为研究区,基于2002、2010、2018年遥感影像数据,采用RSEI法监测与评价研究区生态变化,结合不同等级石漠化空间分布数据,分析各等级石漠化地区的生态环境质量,以期为石漠化地区的定量化生态评价提供方法借鉴,为研究区石漠化治理和恢复生态环境提供数据支持。

    • 云南省曲靖市会泽县(25°48′~27°04′N,103°03′~103°55′E)位于云南省东北部、金沙江东岸、曲靖市西北部,是石漠化综合治理试点县和石漠化重点监测县。全县地势西高东低,由西向东阶梯状递减,平均海拔为2 220 m。立体气候分布明显,同时存在温带高原季风气候和南亚热带气候至寒温带气候,年平均气温为12.7 ℃,年降水量为800 mm。境内植被以亚高山灌丛、草甸、阔叶类混交林、亚热带稀树草原旱生植被为主。县境内碳酸盐岩分布广泛,多为灰岩和白云岩,为典型的喀斯特山区。

    • 遥感数据为2002年2月25日Landsat-7 ETM+、2010年2月7日Landsat-5 TM、2018年3月1日Landsat-8 OLI_TIRS等卫星影像数据。数字高程模型数据来自于地理空间数据云(http://www.gscloud.cn)。云南省地质图来自于中国科学院地球化学研究所(http://www.gyig.cas.cn/)的喀斯特数据中心。对原始影像进行辐射校正、大气校正、几何校正等预处理,结合行政区划矢量数据拼接影像并裁剪出研究区。

    • 基于植被覆盖度(VF)、岩石裸露率(RB)、坡度(s)等3个指标,通过综合分析法构建石漠化遥感监测指标体系[16-18]。计算归一化植被指数、归一化岩石指数,并采用像元二分模型分别计算植被覆盖度和岩石裸露率。按照表1分别对植被覆盖度、岩石裸露率、坡度赋值,依据公式计算石漠化综合指标(IR):IR=0.4VF+0.4RB+0.2s。采用决策树分类法划分石漠化等级:0≤IR≤1为无石漠化、1<IR≤2为潜在石漠化、2<IR≤4为轻度石漠化、4<IR≤6为中度石漠化、6<IR≤8为强度石漠化、8<IR≤10为极强度石漠化[18]。依据云南省地质图剔除非喀斯特区,得到石漠化等级分布图。

      赋值分级指标赋值分级指标
      植被覆盖度岩石裸露率坡度/(°)植被覆盖度岩石裸露率坡度/(°)
      00.70~1.000.0~0.30~1560.25~0.500.5~0.722~25
      20.60~0.700.3~0.415~1880.10~0.250.7~0.825~30
      40.50~0.600.4~0.518~22100.00~0.100.8~1.030~90

      Table 1.  Assignment of rocky desertification classification index

    • 采用遥感生态指数(IRSE)进行生态环境质量评价[7],该指数耦合了绿度、湿度、干度、热度4个指标,分别用归一化植被指数、湿度分量、建筑裸土指数、地表温度表示,通过主成分分析评价当地生态环境。

    • 植被状况是生态环境质量评价的重要方面。归一化植被指数(INDV)作为应用最广的植被指数,能够很好地反映土地上的植被覆盖状况[19]。计算公式为:INDV=(ρNIRρR)/(ρNIR+ρR)。其中:ρNIRρR分别为卫星影像数据的近红外和红外波段的反射率。

    • 缨帽变换得到的第三分量(湿度分量)与植被湿度、土壤湿度紧密相关[20]。利用湿度分量(W)代表湿度指标,计算公式为:W=C1ρB+C2ρG+C3ρR+C4ρNIR+C5ρSWIR1+C6ρSWIR2。其中:ρBρGρRρNIRρSWIR1ρSWIR2分别为卫星影像数据的蓝波段、绿波段、红波段、近红外波段、短波红外1波段、短波红外2波段的反射率。C1~C6为湿度分量的计算系数,对于TM[21]C1=0.031 5,C2=0.202 1,C3=0.310 2,C4=0.159 4,C5 =−0.680 6,C6=−0.610 9;对于ETM+[22]C1=0.262 6,C2=0.214 1,C3=0.092 6,C4=0.065 6,C5=−0.762 9,C6=−0.538 8;对于OLI[23]C1 =0.151 1,C2=0.197 3,C3=0.328 3,C4=0.340 7,C5 =−0.711 7,C6 =−0.455 9。

    • 研究区存在大量石漠化裸土地区,因此干度指标以裸土指数(IS)与建筑指数(IIB)的均值表示,记为建筑裸土指数(INDBS)[24-25]。干度指标对生态环境质量起负面作用。计算公式为:

    • 地表温度与植被的生长发育、城市热岛效应等密切相关,因此本研究采用地表温度表示热度指标。热度指标对生态环境质量起负面作用。地表温度的反演采用大气校正法[26]。把卫星传感器接收的辐射亮度Lλ 分为大气向上辐射亮度L、地面的真实辐射亮度经过大气层之后到达卫星传感器的能量、大气向下辐射到达地面后反射的能量L,得到公式:

      其中:ε为地表比辐射率;TS卫星传感器处的辐射亮度值;B(TS)为TS下的黑体辐射亮度值;τ为大气在热红外波段的透过率。黑体辐射亮度B(TS)的计算公式为:

      地表比辐射率(ε)的计算公式根据植被覆盖度(Fv)分为水体、城镇、自然3部分[27]εwater为水体地表比辐射率;εbuilding为城镇地表比辐射率;εnatural为自然地表比辐射率。

      地表真实温度(TLS)通过普朗克公式求得:

      其中:K1K2分别为定标参数。对于TM数据,K1=607.76 W·m−2·sr−1·μm−1K2=1 260.56 K;对于ETM+数据,K1=666.09 W·m−2·sr−1·μm−1K2 = 1 282.71 K;对于TIRS band10数据,K1=774.89 W·m−2·sr−1·μm−1K2=1 321.08 K。

    • 分别将绿度、湿度、干度、热度4个生态指标正规化,减少因数值大小不同带来的影响,使其值位于[0,1]。采用主成分变换分析集合4个指标的新影像,计算得到第一主成分载荷值(PC1)及相关统计结果。为了便于结果的对比分析,用1−PC1,获得初始遥感生态指数IRSE0,并将其正规化得到遥感生态指数IRSEIRSE值越大,生态环境质量越好,反之越差。即:

      以0.2为间隔将IRSE划分为5个区间[7],分别代表生态环境质量差(0~0.2)、较差(0.2~0.4)、中等(0.4~0.6)、良好(0.6~0.8)、优(0.8~1.0)。

    • 使用ArcGIS对会泽县进行均匀采样(1 km×1 km),去除非喀斯特地区后,共得到 2 366个采样点,获得对应点位的IRIRSE。为使石漠化综合指标大的值代表石漠化程度较低地区,对IR进行归一化,用1减去归一化后的IR,得到转换后的石漠化综合指标(IR0),对IR0IRSE进行相关性分析。

    • 表2可知:2002—2018年,研究区已石漠化地区(极强度、强度、中度、轻度石漠化)面积减少了583.33 km2,占全域面积的24.57%;无石漠化、潜在石漠化面积增加,轻度石漠化面积减少,中度、强度、极强度石漠化面积先增加后减少,研究区内石漠化程度整体得到改善。具体来看,2002—2010年,已石漠化地区面积总体减少了253.22 km2,主要为轻度石漠化面积减少(432.73 km2) ,年均降率为8.58%。2010—2018年,无石漠化面积显著增加,达284.48 km2,年均增率为10.13%;极强度石漠化面积减少了28.38 km2,年均降率为8.23%。

      石漠化等级面积/km2面积变化/km2年均增长/%
      2002201020182002—20102010—20182002—20182002—20102010—20182002—2018年
      极强度石漠化50.7857.1228.746.34−28.38−22.041.48−8.23−6.87
      强度石漠化 535.23578.16462.1642.93−116.00−73.070.97−2.76−1.82
      中度石漠化 669.23799.47679.75130.24−119.7210.522.25−2.010.20
      轻度石漠化 844.86412.13346.12−432.73−66.01−498.74−8.58−2.16−10.56
      潜在石漠化 170.52282.77328.40112.2545.63157.886.531.898.54
      无石漠化  103.47244.44528.92140.97284.48425.4511.3410.1322.62

      Table 2.  Area dynamics of different grade rocky desertification in rocky desertification of Huize Country

    • 2002—2018年研究区IRSE均值变化幅度不大,整体呈上升趋势,生态环境质量总体呈中等水平(表3)。16 a间生态等级为优和差的地区均有增加。与2012年相比,2018年研究区IRSE略有所下降,其中绿度指标、湿度指标均为正值,提示此两者对生态环境起到了积极的作用;干度指标、热度指标均为负值,提示此两者对环境起到了消极作用。同时,2002、2010年绿度、湿度的PC1之和大于干度、热度PC1之和的绝对值,表明绿度、湿度对生态环境的改善作用强于干度、热度的负面作用。2018年绿度、湿度的PC1之和小于干度、热度PC1之和的绝对值,表明干度、热度的负面作用强于绿度、湿度的改善作用。16 a间,负面作用的加强主要来自于干度指标,其PC1由−0.029变为−0.622。

      年份绿度湿度干度热度遥感生态指数
      均值±标准差PC1均值±标准差PC1均值±标准差PC1均值±标准差PC1
      20020.680±0.0920.3870.484±0.1020.6080.569±0.010−0.0290.495±0.112−0.6930.458±0.127
      20100.696±0.0870.3110.541±0.1460.6980.710±0.086−0.3480.498±0.125−0.5440.490±0.136
      20180.719±0.0950.4270.585±0.0790.3610.601±0.123−0.6220.462±0.124−0.5480.488±0.171

      Table 3.  Ecological indicators and loading scores in different years

      对不同年份不同生态环境等级地区进行面积统计(表4)可知:16 a间研究区生态环境恶化与优化并存,中等、较差和良好等级地区占比之和均超过了90%,但区域等级异动较大,优和差等级比例不断提高。其中,中等生态等级面积占比始终最高,但逐年来呈减少趋势,16 a间降率达14.53%。较差及以下等级面积先减少后增加,但整体变化幅度不大。良好及优等级面积增加,增幅达12.92%。由表5可知:2018年,生态等级为差的区域主要分布在迤车镇、马路乡、火红乡、矿山镇、者海镇、大井镇、娜姑镇、大海乡,优等级主要分布在老厂乡、五星乡、金钟镇、新街回族乡、待补镇、鲁纳乡。

      生态环境
      质量等级
      200220102018年
      面积/km2占比/%面积/km2占比/%面积/km2占比/%
      差 79.951.3768.341.17102.091.74
      较差1 943.5433.201 552.2926.522 015.8234.44
      中等2 970.3250.742 855.3748.772 119.9036.21
      良好841.5314.371 360.4923.241 368.8723.38
      优 18.690.3217.540.30247.354.23

      Table 4.  Area of leveled ecological assessment in the study area from 2002 to 2018

      乡镇各等级面积/km2乡镇各等级面积/km2
      较差中等良好较差中等良好
      金钟镇  5.83156.34200.83153.6045.70架车乡1.22118.83107.6751.388.84
      待补镇  2.9290.38117.22100.6226.36纸厂乡0.7427.5039.9722.788.58
      老厂乡  0.9833.1370.3740.4021.61者海镇6.41117.84120.26116.917.31
      新街回族乡1.0555.99103.2394.6519.10上村乡0.7757.07109.5798.155.61
      五星乡  1.1580.3163.5047.0816.03雨碌乡2.6272.1693.8264.035.17
      娜姑镇  6.06133.4779.7025.7013.00火红乡9.72121.3490.2642.374.99
      迤车镇  15.52203.46154.6276.3611.38乐业镇4.68143.64141.6668.863.60
      大桥乡  2.0268.5678.7456.3711.19田坝乡0.62105.33142.8579.652.63
      大海乡  10.71143.69106.5135.1910.28马路乡12.9275.8169.6331.392.11
      鲁纳乡  0.4833.9462.6171.4413.36大井镇6.0386.6899.2848.801.19
      矿山镇  9.6490.3567.6043.149.31

      Table 5.  Leveled ecological assessment area of each town in 2018

    • 基于遥感生态指数的5个等级,对会泽县2002和2018年遥感生态指数进行差值变化检测,按照级差符号的正、0、负依次归为生态变好、不变、变差。由表6可知: 2002—2018年,研究区生态环境质量等级变好面积为1 605.37 km2,占全域面积的27.42%;生态变差地区面积为883.58 km2,占全域面积的15.09%,可见研究区生态环境总体呈变好趋势。由表7可知:生态环境质量等级变好地区主要分布在老厂乡、五星乡、金钟镇、新街回族乡、待补镇、纳鲁乡、上村乡、架车乡、田坝乡等地。这些乡镇海拔较高,人类活动相对较少,全县范围内大力实施生态环境保护,如天然林保护、公益林补植补造、石漠化治理等,使得生态环境得到了极大改善[28]。生态环境质量等级变差地区主要分布在研究区东北部及西南部等地势较平坦的乡镇,包括纸厂乡、迤车镇、马路乡、火红乡、乐业镇、矿山镇、者海镇、大井镇、娜姑镇、大海乡。这些乡镇大力发展三大产业,国内生产总值猛增,城镇化发展迅速,建设用地激增,一定程度上影响了当地生态状况[28]

      类别级差级面积/ km2类面积/km2类占比/%类别级差级面积/ km2类面积/km2类占比/%
      变好 4 0.04 1 605.37 27.42 不变 0 3 365.08 3 365.08 57.48
      3 5.53 变差 −1 877.95 883.58 15.09
      2 136.80 −2 5.63
      1 1 463.00 −3 0.01

      Table 6.  Change of remote sensing ecological index in Huize Country from 2002 to 2018

      乡镇变好不变变差乡镇变好不变变差
      面积/km2占比/%面积/km2占比/%面积/km2占比/%面积/km2占比/%面积/km2占比/%面积/km2占比/%
      金钟镇  206.4736.72309.4955.0446.348.24架车乡97.8533.98169.0758.7221.027.30
      待补镇  136.3240.39170.6050.5530.589.06纸厂乡17.3817.4658.6458.8923.5523.65
      老厂乡  62.8737.7691.4254.9112.207.33者海镇113.0530.66196.0753.1759.6116.17
      新街回族乡113.8841.56141.2151.5318.936.91上村乡97.0935.81154.5556.9919.537.20
      五星乡  76.9636.99106.1050.9925.0112.02雨碌乡72.5430.50138.0958.0727.1711.43
      娜姑镇  40.8315.83166.9164.7150.1919.46火红乡37.1013.81169.2262.9862.3623.21
      迤车镇  62.6613.58258.8956.12139.7930.30乐业镇64.8317.89218.0860.1779.5321.94
      大桥乡  69.9932.27121.8656.1925.0311.54田坝乡112.0733.85199.0760.1319.946.02
      大海乡  58.6619.15190.7462.2556.9818.60马路乡19.6410.24115.0459.9657.1829.80
      鲁纳乡  71.2339.1799.0554.4811.556.35大井镇25.0310.34161.4166.7155.5422.95
      矿山镇  48.9222.23129.5758.8941.5518.88

      Table 7.  Area and percentage change of each remote sensing ecological index level in each town from 2002 to 2018

    • 表8可知:极强度石漠化地区,生态环境质量总体较差,强度、中度石漠化地区遥感生态指数等级以较差、中等为主,轻度、潜在石漠化地区等级主要表现为中等、良好,无石漠化地区,生态环境质量主要为良好,而非喀斯特地区,较差、中等、良好等级的占比均较大。可见石漠化与生态环境之间存在一定相关性。2002—2018年,无、潜在、轻度石漠化地区,生态环境均明显好转。其中,无石漠化和潜在石漠化地区,生态环境主要由中等、良好转为良好、优;轻度石漠化地区,生态环境主要由较差、中等、良好转为中等、良好。反之,强度、极强度石漠化地区生态环境质量逐步变差。其中,极强度石漠化地区,生态环境质量为差等级的面积增率达28.11%。这可能与干旱有关。16 a间研究区干度指标 的PC1由−0.029变为−0.622,而湿度指标PC1由0.608下降为0.361 (表3),均对IRSE产生负面作用,从而表现为以强度、极强度石漠化为代表的干旱地区生态环境质量恶化。因此,在生产建设、生态环境恢复中,应进一步注意石漠化严重地区的保护,减少人为破坏干扰。

      年份等级极强度石漠化强度石漠化中度石漠化轻度石漠化
      面积/km2占比/%面积/km2占比/%面积/km2占比/%面积/km2占比/%
      2002 差  2.97 5.85 9.72 1.82 2.92 0.44 1.34 0.16
      较差 34.32 67.59 277.76 51.90 228.80 34.19 145.61 17.23
      中等 11.61 22.86 207.10 38.69 341.36 51.01 491.45 58.17
      良好 1.80 3.54 39.99 7.47 94.17 14.07 202.98 24.03
      优  0.08 0.16 0.66 0.12 1.98 0.29 3.48 0.41
      2010 差  10.81 18.93 9.36 1.62 0.15 0.02 0.00 0.00
      较差 36.32 63.59 303.82 52.55 171.90 21.50 2.51 0.61
      中等 8.85 15.49 212.10 36.69 518.79 64.89 225.13 54.62
      良好 1.14 1.99 52.85 9.14 108.43 13.56 183.63 44.56
      优  0.00 0.00 0.03 0.00 0.20 0.03 0.86 0.21
      2018 差  9.76 33.96 24.58 5.32 0.86 0.13 0.00 0.00
      较差 14.24 49.55 290.26 62.80 276.22 40.63 5.85 1.69
      中等 4.70 16.35 135.33 29.28 346.45 50.97 202.41 58.48
      良好 0.04 0.14 11.86 2.57 55.77 8.20 134.79 38.94
      优  0.00 0.00 0.13 0.03 0.45 0.07 3.07 0.89

      Table 8.  Remote sensing ecological index changes under different rocky desertification grades in the study area

      年份 等级 潜在石漠化 无石漠化 非喀斯特
      面积/km2 占比/% 面积 /km2 占比/% 面积/km2 占比/%
      2002 差  0.03 0.02 0.06 0.06 57.74 1.65
      较差 10.64 6.24 7.19 6.95 1 256.30 35.76
      中等 83.47 48.95 43.87 42.40 1 817.59 51.74
      良好 74.91 43.93 51.85 50.11 376.65 10.72
      优  1.47 0.86 0.50 0.48 4.56 0.13
      2010 差  0.00 0.00 0.00 0.00 44.10 1.26
      较差 0.13 0.04 0.05 0.02 1 047.88 29.83
      中等 72.58 25.67 29.50 12.07 1 812.34 51.59
      良好 203.67 72.03 213.76 87.45 604.67 17.21
      优  6.39 2.26 1.13 0.46 3.85 0.11
      2018 差  0.00 0.00 0.00 0.00 63.18 1.80
      较差 0.35 0.11 0.66 0.12 1 443.74 41.10
      中等 47.96 14.60 58.44 11.05 1 342.83 38.22
      良好 217.78 66.32 386.57 73.09 568.28 16.18
      优  62.31 18.97 83.25 15.74 94.81 2.70

      分别计算2002、2010、2018年转换后IR0IRSE的相关性系数可知:2002年两者相关性系数为0.688,2010年为0.750,2018年为0.873,3期均在0.01水平上显著相关。可见,生态环境质量与石漠化之间存在正相关,随着石漠化改善,生态环境质量逐渐向好,即通过RSEI法进行石漠化地区生态环境质量评价具有很好的效果。

    • 本研究基于2002—2018年Landsat 5、 Landsat 7、Landsat 8卫星影像数据,划分会泽县石漠化等级,并利用遥感生态指数法定量评价会泽县生态环境质量。结果表明:①会泽县石漠化状况整体得到改善,已石漠化地区总面积减少了583.33 km2,其中,轻度石漠化地区面积减少432.73 km2。②干度指标的载荷值绝对值不断增大,PC1载荷值由−0.029变为−0.622,对IRSE的贡献度不断增加,主要为地势平坦地区的城镇化建设用地增加,成为制约会泽县生态环境质量优化的重要因素。③ 2002、2010、2018年遥感生态指数均值分别为0.458、0.490、0.488,生态环境质量整体表现为中等,生态环境呈优化趋势。④会泽县内生态环境质量优化面积占总面积的27.42%,主要分布在老厂乡、五星乡、金钟镇、新街回族乡、待补镇、纳鲁乡、上村乡、架车乡、田坝乡;生态环境质量变差地区面积占总面积的15.09%,分布在纸厂乡、迤车镇、马路乡、火红乡、乐业镇、矿山镇、者海镇、大井镇、娜姑镇、大海乡。⑤石漠化与生态环境质量呈显著正相关,相关性指数为0.688~0.873,表明通过遥感生态指数法评价长江上游典型石漠化地区的生态环境质量效果较好。

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