Evaluation of Ecological Environment in Jiangxi Province based on Improved Ecological Index

Tian LUO; Bofu ZHENG; Yun HUANG; Chengkang LUO; Jihong ZHANG; Zhong LIU; Wei WAN

doi:10.11873/j.issn.1004-0323.2025.2.0401

Remote Sensing Technology and Application, Volume. 40, Issue 2, 401(2025)

Evaluation of Ecological Environment in Jiangxi Province based on Improved Ecological Index

Tian LUO, Bofu ZHENG, Yun HUANG, Chengkang LUO, Jihong ZHANG, Zhong LIU, and Wei WAN^*

School of Resources and Environment， Nanchang University， Jiangxi Institute of Ecological Civilization， Nanchang330031， China

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Fig. 1. Geography of Jiangxi Province

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Fig. 2. Improved ecological sub-index

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Fig. 3. Spatial distribution of improved ecological index in Jiangxi Province from 2000 to 2020

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Fig. 4. The percentage of ecological environment grade area in Jiangxi Province from 2000 to 2020 based on IEI

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Fig. 5. The change trend of ecological environment in Jiangxi Province from 2000 to 2020 based on IEI

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Fig. 6. Improved Ecological Index of Jiangxi Province from 2000 to 2020

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Fig. 7. Ecological environment zoning of Jiangxi Province from 2000 to 2020 based on IEI

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Table 1. Table 1Calculation method of the improved ecological sub-index

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Table 1. Table 1Calculation method of the improved ecological sub-index

分指数	方法	公式	指标含义
生物丰度指数	参考《规范》计算公式^[8]	$\begin{array}{l} H Q I = (0.35 \times 林地 + 0.21 \times 草地 + 0.28 \times 湿地 + \\ 0.11 \times 耕地 + 0.04 \times 建设用地 + 0.01 \times 裸地) / R a \end{array}$ (1)	HQI为生境质量指数，无量纲；R_a为区域面积，km²；^‎无量纲
土地胁迫指数	通用土壤流失方程（USLE）得到不同程度的土地侵蚀面积^‎^[23-25]，再参考规范计算公式^[8]	$U S L E_{x} = R_{x} \cdot K_{x} \cdot L S_{x} \cdot C_{x} \cdot P_{x}$ (2) $\begin{array}{l} L S I = (0.40 \times 重度侵蚀面积 + 0.20 \times \\ 中度侵蚀面积 + 0.20 \times 建设用地面积 \\ + 0.20 \times 其他土地胁迫) / R a \end{array}$ (3)	USLE_x为栅格x的实际侵蚀量，t；R_x因子表示降雨侵蚀力因子，无量纲；K_x表示土壤可蚀性因子，无量纲；L表示坡长因子，无量纲；S_x表示坡度因子，无量纲；C_x表示植被覆盖因子，无量纲；P_x表示保持措施因子，无量纲。LSI为土地胁迫指数，无量纲
植被净初级生产力	使用CASA模型计算NPP^‎[26-27]	$N P P (x, t) = A P A R (x, t) \cdot ε (x, t)$ (4) $A P A R (x, t) = S O L (x, t) \cdot F P A R (x, t) \cdot 0.5$ (5) $ε (x, t) = T_{ε 1} (x, t) \cdot T_{ε 2} (x, t) \cdot W_{ε 1} (x, t) \cdot ε_{m a x}$ (6)	x为遥感影像中的某个像元；t是NPP累积的周期，逐月；NPP（x,t）是像元x在第t个月的净初级生产力增量，gC·m^-2；APAR(x, t)表示x像元在第t月植被吸收的光合有效辐射量，MJ·m^–²·month^–¹；，ε(x，t)表示像元x在t月的光能利用率，Gc·MJ^–¹
湿度指数	Landsat-5 TM和Landsat-8 OLI影像数据计算得到^[12]	$\begin{array}{l} W E T_{T M} = 0.0315 ρ_{1} + 0.2021 ρ_{2} + 0.3102 ρ_{3} \\ + 0.1594 ρ_{4} - 0.6806 ρ_{5} - 0.6109 ρ_{7} \end{array}$ (7) $\begin{array}{l} W E T_{O L I} = 0.1511 ρ_{1} + 0.1973 ρ_{2} + 0.3283 ρ_{3} \\ + 0.3407 ρ_{4} - 0.7117 ρ_{5} - 0.4559 ρ_{7} \end{array}$ (8)	WET为湿度指数，无量纲；ρ_i分别为TM、OLI影像的蓝、绿、红、近红、中红1、中红外2波段的地表反射率，无量纲
碳质气溶胶含量	与日常生活活动密切相关的空气污染物含量相加得到^[21]	$C A = O C + E C + B C + B r C$ (9)	CA为碳质气溶胶含量，μg·mˉ³；OC为有机碳含量，μg·mˉ³；EC为元素碳含量，μg·mˉ³；BC为黑碳含量，μg·mˉ³；BrC为棕色碳含量，μg·mˉ³
叶绿素a浓度	运用反演模型监测鄱阳湖流域的叶绿素a浓度^‎[22]	$Y = 0.0107 X^{2} + 0.9193 X + 0.1506$ (10)	X代表的是蓝波段/绿波段处的反射率值，无量纲；Y代表的是叶绿素a浓度，mg·L^–¹
景观指数	采用移动窗口法计算出各个景观指数^[28]，再用主成分分析法赋予权重^‎[3]	$F_{i} = {w_{i}}_{1} X_{1} + w_{i 2} X_{2} + w_{i 3} X_{3} + w_{i 4} X_{4} + w_{i 5} X_{5}$ (11) $F = α F_{i}$ (12)	F_i是各个主成分的得分，无量纲；X₁是斑块密度，X₂是最大斑块指数，X₃是聚集指数，X₄是蔓延度指数，X₅是香农多样性指数，无量纲；F是综合得分，无量纲；w_ij是主成分中各个变量的权重，无量纲；α表示第主成分的方差比，无量纲

Table 2. Table 2Weight of the improved ecological sub-index
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Table 2. Table 2Weight of the improved ecological sub-index
分指数分指数权重
生境质量指数 0.43
土地胁迫指数 0.36
植被净初级生产力 0.06
湿度指数 0.02
碳质气溶胶含量 0.01
叶绿素a浓度 0.02
景观指数 0.10

Table 3. Table 3Improved Ecological Sub-index of Jiangxi Province from 2000 to 2020

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Table 3. Table 3Improved Ecological Sub-index of Jiangxi Province from 2000 to 2020

指数	2000年	2005年	2010年	2015年	2020年
生境质量指数	73.77	73.64	73.34	72.98	71.89
植被净初级生产力	568.29	563.41	601.22	725.12	715.11
土地胁迫指数	0.02	0.02	0.02	0.02	0.02
景观指数	47.78	56.90	54.97	56.13	53.44
湿度指数	–0.09	–0.05	–0.08	–0.01	–0.01
碳质气溶胶含量	0.80	1.10	0.93	0.93	0.87
叶绿素a浓度	0.79	0.86	0.91	1.20	1.06

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Tian LUO, Bofu ZHENG, Yun HUANG, Chengkang LUO, Jihong ZHANG, Zhong LIU, Wei WAN. Evaluation of Ecological Environment in Jiangxi Province based on Improved Ecological Index[J]. Remote Sensing Technology and Application, 2025, 40(2): 401

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