Xinjiang Agricultural Sciences ›› 2022, Vol. 59 ›› Issue (2): 451-457.DOI: 10.6048/j.issn.1001-4330.2022.02.023
• Prataculture·Storage and Preservation Processing·Microbes • Previous Articles Next Articles
YUN Jing1(), ZHENG Fengling1(
), AN Shazhou2(
), Asiya Manlike1, LI Chao1, 1, TIAN Cong1
Received:
2021-01-18
Online:
2022-02-20
Published:
2022-03-22
Correspondence author:
ZHENG Fengling, AN Shazhou
Supported by:
贠静1(), 郑逢令1(
), 安沙舟2(
), 阿斯娅·曼力克1, 李超1, 艾尼玩·艾麦尔1, 田聪1
通讯作者:
郑逢令,安沙舟
作者简介:
贠静(1979-),女,新疆和静人,助理研究员,研究方向为草地资源与生态,(E-mail) 49265543@qq.com
基金资助:
CLC Number:
YUN Jing, ZHENG Fengling, AN Shazhou, Asiya Manlike, LI Chao, , TIAN Cong. Hyperspectral Inversion of Leaf Area Index in Mountain Steppe Ecosystems Based on the PROSAIL Model[J]. Xinjiang Agricultural Sciences, 2022, 59(2): 451-457.
贠静, 郑逢令, 安沙舟, 阿斯娅·曼力克, 李超, 艾尼玩·艾麦尔, 田聪. 基于PROSAIL模型的山地草原叶面积指数高光谱反演[J]. 新疆农业科学, 2022, 59(2): 451-457.
模型参数 Model parameter | 单位 Unit | 范围 Range | 步长 Step length | 分布类型 Distribution type | |
---|---|---|---|---|---|
叶片模型:Prospect-4 | |||||
N | 叶片结构指数 | / | 1.3~2 | 0.1 | Uniform |
LCC | 叶片叶绿素含量 | μg/cm2 | 20~50 | / | Gaussian(x:33,SD:5) |
Cm | 叶片干物质含量 | g/cm2 | 0.004 5~0.005 5 | 0.000 5 | Uniform |
Cw | 等效水厚度 | cm | 0.007~0.014 | 0.001 | Uniform |
冠层模型:4SAIL | |||||
LAI | 叶面积指数 | m2/m2 | 0.1~1.80 | / | Gaussian(x:0.84,SD:0.3) |
αsoil | 土壤比例因子 | / | 0.1~1 | 0.1 | Uniform |
ALA | 平均叶倾角 | ° | 40~70 | 5 | Uniform |
HotS | 热点参数 | m/m | 0.05~0.5 | 0.05 | Uniform |
skyl | 散射光占比 | % | 5 | 固定值 | / |
θs | 太阳天顶角 | ° | 20~40 | 5 | / |
θv | 观测天顶角 | ° | 0 | 固定值 | / |
φ | 太阳-仪器方位角 | ° | 0 | 固定值 | / |
Table 1 PROSPECT-4 and 4SAIL model parameter settings
模型参数 Model parameter | 单位 Unit | 范围 Range | 步长 Step length | 分布类型 Distribution type | |
---|---|---|---|---|---|
叶片模型:Prospect-4 | |||||
N | 叶片结构指数 | / | 1.3~2 | 0.1 | Uniform |
LCC | 叶片叶绿素含量 | μg/cm2 | 20~50 | / | Gaussian(x:33,SD:5) |
Cm | 叶片干物质含量 | g/cm2 | 0.004 5~0.005 5 | 0.000 5 | Uniform |
Cw | 等效水厚度 | cm | 0.007~0.014 | 0.001 | Uniform |
冠层模型:4SAIL | |||||
LAI | 叶面积指数 | m2/m2 | 0.1~1.80 | / | Gaussian(x:0.84,SD:0.3) |
αsoil | 土壤比例因子 | / | 0.1~1 | 0.1 | Uniform |
ALA | 平均叶倾角 | ° | 40~70 | 5 | Uniform |
HotS | 热点参数 | m/m | 0.05~0.5 | 0.05 | Uniform |
skyl | 散射光占比 | % | 5 | 固定值 | / |
θs | 太阳天顶角 | ° | 20~40 | 5 | / |
θv | 观测天顶角 | ° | 0 | 固定值 | / |
φ | 太阳-仪器方位角 | ° | 0 | 固定值 | / |
查找表尺寸 Look up table size | 代价函数 Cost function | 最优解占比 Optimal solution ratio(%) | RMSE | NRMSE | R2 |
---|---|---|---|---|---|
1 000 | RMSE | 3 | 0.26 | 18.87 | 0.50 |
10 000 | RMSE | 3 | 0.26 | 18.58 | 0.50 |
30 000 | RMSE | 3 | 0.25 | 18.45 | 0.50 |
50 000 | RMSE | 3 | 0.25 | 18.49 | 0.50 |
Table 2 Performance of LAI inversion of cost function under four kinds of LUT size
查找表尺寸 Look up table size | 代价函数 Cost function | 最优解占比 Optimal solution ratio(%) | RMSE | NRMSE | R2 |
---|---|---|---|---|---|
1 000 | RMSE | 3 | 0.26 | 18.87 | 0.50 |
10 000 | RMSE | 3 | 0.26 | 18.58 | 0.50 |
30 000 | RMSE | 3 | 0.25 | 18.45 | 0.50 |
50 000 | RMSE | 3 | 0.25 | 18.49 | 0.50 |
代价函数 Cost function | 噪声占比 Noise ratio(%) | 样本占比 Sample to sample ratio(%) | RMSE | NRMSE | R2 |
---|---|---|---|---|---|
K(x)={log(x)^2} | 3 | 3 | 0.23 | 17.08 | 0.55 |
K(x)=x{log(x)}-x | 2 | 2 | 0.24 | 17.35 | 0.55 |
Kullback-leibler | 1 | 3 | 0.25 | 18.10 | 0.55 |
Pearson chi-square | 1 | 1 | 0.25 | 18.13 | 0.55 |
Hellinger distance | 4 | 4 | 0.25 | 18.17 | 0.54 |
Least absolute error | 0 | 10 | 0.25 | 18.36 | 0.45 |
Geman and McClure | 0 | 10 | 0.25 | 18.52 | 0.47 |
RMSE | 1 | 3 | 0.26 | 18.99 | 0.54 |
K(x)=-log(x)+x | 0 | 1 | 0.47 | 34.06 | 0.52 |
Table 3 LAI inversion statistics for the optimal NRMSE of cost function
代价函数 Cost function | 噪声占比 Noise ratio(%) | 样本占比 Sample to sample ratio(%) | RMSE | NRMSE | R2 |
---|---|---|---|---|---|
K(x)={log(x)^2} | 3 | 3 | 0.23 | 17.08 | 0.55 |
K(x)=x{log(x)}-x | 2 | 2 | 0.24 | 17.35 | 0.55 |
Kullback-leibler | 1 | 3 | 0.25 | 18.10 | 0.55 |
Pearson chi-square | 1 | 1 | 0.25 | 18.13 | 0.55 |
Hellinger distance | 4 | 4 | 0.25 | 18.17 | 0.54 |
Least absolute error | 0 | 10 | 0.25 | 18.36 | 0.45 |
Geman and McClure | 0 | 10 | 0.25 | 18.52 | 0.47 |
RMSE | 1 | 3 | 0.26 | 18.99 | 0.54 |
K(x)=-log(x)+x | 0 | 1 | 0.47 | 34.06 | 0.52 |
小组 Group | 样方数 Square number | 描述 Describe |
---|---|---|
A | 50 | 种类数≤2 |
B | 240 | 种类数≤3 |
C | 391 | 种类数≤4 |
D | 427 | 全部样方 |
Table 4 Quadrats grouped according to the species number (n=427)
小组 Group | 样方数 Square number | 描述 Describe |
---|---|---|
A | 50 | 种类数≤2 |
B | 240 | 种类数≤3 |
C | 391 | 种类数≤4 |
D | 427 | 全部样方 |
代价函数 Cost function | A (n=50) | B (n=240) | C (n=391) | D (n=427) | ||||
---|---|---|---|---|---|---|---|---|
RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | |
K(x)={log(x)}^2 | 0.20 | 0.71 | 0.22 | 0.58 | 0.23 | 0.55 | 0.23 | 0.55 |
Kullback-leibler | 0.21 | 0.72 | 0.23 | 0.58 | 0.25 | 0.55 | 0.25 | 0.55 |
RMSE | 0.22 | 0.72 | 0.24 | 0.58 | 0.26 | 0.54 | 0.26 | 0.54 |
Table 5 Effects of species changes on LAI inversion accuracy with PROSAIL
代价函数 Cost function | A (n=50) | B (n=240) | C (n=391) | D (n=427) | ||||
---|---|---|---|---|---|---|---|---|
RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | |
K(x)={log(x)}^2 | 0.20 | 0.71 | 0.22 | 0.58 | 0.23 | 0.55 | 0.23 | 0.55 |
Kullback-leibler | 0.21 | 0.72 | 0.23 | 0.58 | 0.25 | 0.55 | 0.25 | 0.55 |
RMSE | 0.22 | 0.72 | 0.24 | 0.58 | 0.26 | 0.54 | 0.26 | 0.54 |
[1] |
Darvishzadeh R, Atzberger C, Skidmore A K, et al. Leaf area index derivation from hyperspectral vegetation indices and the red edge position[J]. International Journal of Remote Sensing, 2009, 30(23):6199-6218.
DOI URL |
[2] | 童庆禧, 张兵, 张立福. 中国高光谱遥感的前沿进展[J]. 遥感学报, 2016, 20(5):689-707. |
TONG Qingxi, ZHANG Bing, ZHANG Lifu. Current progress of hyperspectral remote sensing in China[J]. Journal of Remote Sensing, 2016, 20(5):689-707. | |
[3] | Verrelst J, Rivera G P, Leonenko G, et al. Optimizing LUT-based radiative transfer model inversion for retrieval of biophysical parameters using hyperspectral data[C]// Geoscience and Remote Sensing Symposium.IEEE, 2012: 7325-7328. |
[4] |
Masemola C, Cho M A, Ramoelo A. Comparison of Landsat 8 OLI and Landsat 7 ETM+ for estimating grassland LAI using model inversion and spectral indices:case study of Mpumalanga, South Africa[J]. International Journal of Remote Sensing, 2016, 37(18):4401-4419.
DOI URL |
[5] |
SI Yali, Schlerf M, Zurita-Milla R, et al. Mapping spatio-temporal variation of grassland quantity and quality using MERIS data and the PROSAIL model[J]. Remote Sensing of Environment, 2012, 121:415-425.
DOI URL |
[6] |
Atzberger C, Darvishzadeh R, Immitzer M, et al. Comparative analysis of different retrieval methods for mapping grassland leaf area index using airborne imaging spectroscopy[J]. International Journal of Applied Earth Observation and Geoinformation, 2015, 43:19-31.
DOI URL |
[7] | 杨灿灿, 吴见, 王春, 等. 基于HJ-1B影像的内蒙古草地叶面积指数反演[J]. 测绘工程, 2015, 24(5):29-32. |
YANG Cancan, WU Jian, WANG Chun, et al. Research on leaf area index quantitative inversion of grassland in Inner Mongolia based on HJ-1B data[J]. Engineering of Surveying and Mapping, 2015, 24(5):29-32. | |
[8] | 昌梦雨, 魏晓楠, 王秋悦, 等. 植物叶绿素含量不同提取方法的比较研究[J]. 中国农学通报, 2016, 32(27):177-180. |
CHANG Mengyu, WEI Xiaonan, WANG Qiuyue, et al. A comparative study on different extraction methods for plant chlorophyll[J]. Chinese Agricultural Science Bulletin, 2016, 32(27):177-180. | |
[9] | 朱高龙. 基于LAI-2200的草地LAI测量与聚集度系数分析[J]. 农业机械学报, 2016, 47(5):307-314. |
ZHU Gaolong. Validation of grassland leaf area index and clumping index retrievals from LAI-2200[J]. Transactions of the Chinese Society of Agricultural Machinery, 2016, 47(5):307-314. | |
[10] |
Jacquemoud S, Verhoef W, Baret F, et al. PROSPECT+SAIL models: A review of use for vegetation characterization[J]. Remote Sensing of Environment, 2009, 113(S1):S56-S66.
DOI URL |
[11] |
Verrelst J, Romijn E, Kooistra L. Mapping vegetation density in a heterogeneous river floodplain ecosystem using pointable CHRIS/PROBA data[J]. Remote Sensing, 2012, 4(9):2866-2889.
DOI URL |
[12] |
Leonenko G, Los S, North P. Statistical distances and their applications to biophysical parameter estimation: Information measures, M-estimates, and Minimum contrast methods[J]. Remote Sensing, 2013, 5(3):1355-1388.
DOI URL |
[13] | GU Chengyan, DU Huaqiang, MAO Fangjie, et al. Global sensitivity analysis of PROSAIL model parameters when simulating Moso bamboo forest canopy reflectance[J]. International Journal of Remote Sensing, 2016, 37(22):5270-5286. |
[14] |
Darvishzadeh R, Atzberger C, Skidmore A, et al. Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011, 66(6):894-906.
DOI URL |
[15] |
Verrelst J, Rivera J P, Leonenko G, et al. Optimizing LUT-based RTM inversion for semiautomatic mapping of crop biophysical parameters from Sentinel-2 and -3 data: Role of cost functions[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(1):257-269.
DOI URL |
[16] |
Rivera J P, Verrelst J, Leonenko G, et al. Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model[J]. Remote Sensing, 2013, 5(7):3280-3304.
DOI URL |
[17] |
Darvishzadeh R, Skidmore A, Schlerf M, et al. Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland[J]. Remote Sensing of Environment, 2008, 112(5):2592-2604.
DOI URL |
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