Smart Agriculture ›› 2024, Vol. 6 ›› Issue (2): 28-39.doi: 10.12133/j.smartag.SA202310016
• Special Issue--Agricultural Information Perception and Models • Previous Articles Next Articles
SHEN Yanyan1,6,7, ZHAO Yutao1(), CHEN Gengshen2,3, LYU Zhengang1, ZHAO Feng4, YANG Wanneng2, MENG Ran5,6,7()
Received:
2023-10-23
Online:
2024-03-30
corresponding author:
About author:
SHEN Yanyan, E-mail: shenyy_rs@163.com
ZHAO Yutao, E-mail: zhaoyutao0408@163.com
Supported by:
SHEN Yanyan, ZHAO Yutao, CHEN Gengshen, LYU Zhengang, ZHAO Feng, YANG Wanneng, MENG Ran. Identification and Severity Classification of Typical Maize Foliar Diseases Based on Hyperspectral Data[J]. Smart Agriculture, 2024, 6(2): 28-39.
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URL: https://www.smartag.net.cn/EN/10.12133/j.smartag.SA202310016
Table 2
Vegetation index candidate set for hyperspectral identification and severity classification of maize leaf diseases
植被指数 | 计算公式 |
---|---|
归一化植被指数(Normalized Difference Vegetation Index, NDVI)[ | (3) |
结构无关色素指数(Structure Insensitive Pigment Index, SIPI)[ | (4) |
绿度指数(Green Index, GI)[ | |
损伤敏感光谱指数2(Damage Sensitive Spectral Index 2, DSSI2)[ | (5) |
归一化色素叶绿素指数(Normalized Pigment Chlorophyll Index, NPCI)[ | (6) |
改正型叶绿素吸收比值指数(Transformed Chlorophyll Absorption in Reflectance Index, TCARI)[ | (7) |
红边植被胁迫指数(Red edge Vegetation Stress Index, RVSI)[ | (8) |
比值指数(Datt5)[ | (9) |
比值指数4(Simple Ratio Index 4, SR4)[ | (10) |
梅里斯陆地叶绿素指数(MERIS Terrestrial Chlorophyll Index, MTCI)[ | (11) |
光化学植被指数(Photochemical Reflectance Index, PRI)[ | (12) |
衰老反射指数(Senescence Reflectance Index, SRI)[ | (13) |
水分指数(Water Index, WI)[ | (14) |
归一化水分指数(Normalized Difference Water Index, NDWI)[ | (15) |
疾病水分胁迫指数2(Disease Water Stress Index, DWSI2)[ | (16) |
水分胁迫指数(Water Stress Index, WSI)[ | (17) |
健康指数(Health Index, HI)[ | (18) |
烈度指数(Severity Index, SI)[ | (19) |
R 730和R 706一阶导数比值(D 730/D 706)[ | (20) |
R 715和R 705一阶导数比值(D 715/D 705)[ | (21) |
红边和绿光反射率一阶导数最大值比值(Ratio Between the Maxima of the First Derivatives of Reflectances at the Red Edge and Green regions, EGFR)[ | (22) |
红边和绿光反射率一阶导数最大值的归一化比值(Normalized Ratio Between the Maxima of the First Derivatives of Reflectances at the Red Edge and Green Regions, EGFN)[ | (23) |
Table 4
Optimal spectral characteristics of maize disease species identification under different disease intensities
光谱特征 | 病害发展阶段 | 敏感特征 |
---|---|---|
敏感波段 | 轻度烈度 | 560、679、704、857、1 432 nm |
中度烈度 | 514、680、694、1 000、2 339 nm | |
重度烈度 | 519、680、760、982、2 219 nm | |
植被指数 | 轻度烈度 | TCARI、NPCI、D 730/D 706、D 715/D 705 |
中度烈度 | NPCI、MTCI、D 730/D 706、EGFN | |
重度烈度 | MTCI、SR4、EGFN、EGFR、WI |
Table 5
Accuracy of maize disease identification under different stages of development
病害发展阶段 | 光谱特征 | SVM | RF | DT | |||
---|---|---|---|---|---|---|---|
OA/% | Macro F 1 | OA/% | Macro F 1 | OA/% | Macro F 1 | ||
轻度烈度 | 敏感波段 | 56.39 | 0.46 | 53.89 | 0.41 | 44.78 | 0.33 |
植被指数 | 70.31 | 0.66 | 69.89 | 0.60 | 68.56 | 0.60 | |
中度烈度 | 敏感波段 | 60.41 | 0.48 | 68.06 | 0.48 | 67.92 | 0.50 |
植被指数 | 80.00 | 0.75 | 79.58 | 0.72 | 73.47 | 0.63 | |
重度烈度 | 敏感波段 | 61.96 | 0.54 | 70.83 | 0.59 | 64.58 | 0.52 |
植被指数 | 95.06 | 0.94 | 89.03 | 0.82 | 82.92 | 0.74 | |
全阶段 | 敏感波段 | 48.76 | 0.47 | 40.10 | 0.35 | 34.48 | 0.32 |
植被指数 | 77.51 | 0.77 | 71.34 | 0.70 | 71.83 | 0.72 |
Table 7
Accuracy of maize disease severity identification based on different methods
病害类型 | 光谱特征 | SVM | RF | DT | |||
---|---|---|---|---|---|---|---|
OA/% | Macro F 1 | OA/% | Macro F 1 | OA/% | Macro F 1 | ||
大斑病 | 敏感波段 | 54.25 | 0.46 | 60.00 | 0.52 | 55.00 | 0.46 |
植被指数 | 86.25 | 0.85 | 87.50 | 0.83 | 82.50 | 0.75 | |
小斑病 | 敏感波段 | 63.16 | 0.62 | 50.67 | 0.45 | 51.00 | 0.44 |
植被指数 | 70.35 | 0.70 | 60.00 | 0.54 | 54.33 | 0.47 | |
南方锈病 | 敏感波段 | 62.22 | 0.61 | 40.00 | 0.32 | 38.33 | 0.28 |
植被指数 | 71.39 | 0.69 | 67.50 | 0.55 | 59.17 | 0.47 |
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