Acta Prataculturae Sinica ›› 2021, Vol. 30 ›› Issue (10): 1-14.DOI: 10.11686/cyxb2020496
Jie SONG1,2(), Xue-lu LIU1,2()
Received:
2020-11-03
Revised:
2020-12-24
Online:
2021-09-16
Published:
2021-09-16
Contact:
Xue-lu LIU
Jie SONG, Xue-lu LIU. Improving the accuracy of forest identification in mountainous areas from multi-source remote sensing data——the Sunan County section of Qilian Mountains National Park as an example[J]. Acta Prataculturae Sinica, 2021, 30(10): 1-14.
产品号 Product ID | 获取时间 Acquisition date (月-日 Month-day) | 景中心坐标 Center coordinate | 太阳高度角 Sun elevation (°) | 太阳方位角 Sun azimuth (°) | 云覆盖量 Land cloud cover (%) |
---|---|---|---|---|---|
132034 | 7-12 | 37°28′28″ N 101°56′45″ E | 65.39 | 122.77 | 1.85 |
133033 | 8-21 | 38°54′16″ N 100°50′15″ E | 48.21 | 151.38 | 0.78 |
134033 | 7-28 | 38°54′15″ N 99°17′01″ E | 45.88 | 153.65 | 2.04 |
135033 | 7-17 | 38°54′16″ N 97°44′49″ E | 64.15 | 126.85 | 2.63 |
Table 1 The basic parameters of Landsat OLI images
产品号 Product ID | 获取时间 Acquisition date (月-日 Month-day) | 景中心坐标 Center coordinate | 太阳高度角 Sun elevation (°) | 太阳方位角 Sun azimuth (°) | 云覆盖量 Land cloud cover (%) |
---|---|---|---|---|---|
132034 | 7-12 | 37°28′28″ N 101°56′45″ E | 65.39 | 122.77 | 1.85 |
133033 | 8-21 | 38°54′16″ N 100°50′15″ E | 48.21 | 151.38 | 0.78 |
134033 | 7-28 | 38°54′15″ N 99°17′01″ E | 45.88 | 153.65 | 2.04 |
135033 | 7-17 | 38°54′16″ N 97°44′49″ E | 64.15 | 126.85 | 2.63 |
坡度等级 Slope gradient classes | 模型决定系数 Coefficient of determination (R2) | 均方根误差 Root mean square error (RMSE)(m) | ||
---|---|---|---|---|
校正前Before correction | 校正后After correction | 校正前Before correction | 校正后After correction | |
0°~5° | 0.62 | 0.66 | 2.83 | 1.84 |
5°~15° | 0.64 | 0.65 | 3.32 | 2.23 |
15°~25° | 0.66 | 0.67 | 6.74 | 3.51 |
25°~35° | 0.63 | 0.65 | 8.00 | 3.91 |
35°~58° | 0.65 | 0.67 | 12.59 | 3.48 |
Table 2 Accuracy comparison of GLAS derived canopy heights before and after topographic correction in different slope gradient classes
坡度等级 Slope gradient classes | 模型决定系数 Coefficient of determination (R2) | 均方根误差 Root mean square error (RMSE)(m) | ||
---|---|---|---|---|
校正前Before correction | 校正后After correction | 校正前Before correction | 校正后After correction | |
0°~5° | 0.62 | 0.66 | 2.83 | 1.84 |
5°~15° | 0.64 | 0.65 | 3.32 | 2.23 |
15°~25° | 0.66 | 0.67 | 6.74 | 3.51 |
25°~35° | 0.63 | 0.65 | 8.00 | 3.91 |
35°~58° | 0.65 | 0.67 | 12.59 | 3.48 |
OLI波段组合 OLI band combination | 依据光谱特征分类 Classification based on spectrum | 依据光谱和垂直结构综合特征分类 Classification based on spectrum and vertical structure | ||
---|---|---|---|---|
总体精度 Overall accuracy (%) | Kappa系数 Kappa coefficient | 总体精度 Overall accuracy (%) | Kappa系数 Kappa coefficient | |
近红外波段、红波段、绿波段NIR、Red、Green | 82.41 | 0.79 | 93.08 | 0.91 |
近红外波段、短波红外1、蓝波段NIR、SWIR1、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
短波红外1、近红外波段、红波段SWIR1、NIR、Red | 82.41 | 0.79 | 93.08 | 0.91 |
短波红外1、近红外波段、蓝波段SWIR1、NIR、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
红波段、绿波段、蓝波段Red、Green、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
Table 3 Comparison of classification results based on different features of different band combination and classification methods
OLI波段组合 OLI band combination | 依据光谱特征分类 Classification based on spectrum | 依据光谱和垂直结构综合特征分类 Classification based on spectrum and vertical structure | ||
---|---|---|---|---|
总体精度 Overall accuracy (%) | Kappa系数 Kappa coefficient | 总体精度 Overall accuracy (%) | Kappa系数 Kappa coefficient | |
近红外波段、红波段、绿波段NIR、Red、Green | 82.41 | 0.79 | 93.08 | 0.91 |
近红外波段、短波红外1、蓝波段NIR、SWIR1、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
短波红外1、近红外波段、红波段SWIR1、NIR、Red | 82.41 | 0.79 | 93.08 | 0.91 |
短波红外1、近红外波段、蓝波段SWIR1、NIR、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
红波段、绿波段、蓝波段Red、Green、Blue | 82.41 | 0.79 | 93.08 | 0.91 |
分类依据 Classification basis | 地类 Land type | 森林 Forest | 灌木 Shrub | 草地 Grassland | 农田 Farmland | 裸地 Bare land | 建设用地 Built-up area | 水域 Water | 用户精度 User accuracy (%) |
---|---|---|---|---|---|---|---|---|---|
光谱特征 Spectrum | 森林 Forest | 537 | 189 | 0 | 0 | 0 | 1 | 42 | 69.83 |
灌木 Shrub | 22 | 454 | 70 | 0 | 8 | 31 | 0 | 77.61 | |
草地 Grassland | 0 | 6 | 82 | 11 | 0 | 20 | 0 | 68.91 | |
农田 Farmland | 0 | 19 | 13 | 335 | 0 | 24 | 0 | 85.68 | |
裸地 Bare land | 0 | 6 | 0 | 0 | 273 | 30 | 0 | 88.35 | |
建设用地 Built-up area | 0 | 30 | 25 | 0 | 14 | 172 | 0 | 71.37 | |
水域 Water | 4 | 1 | 0 | 0 | 30 | 42 | 1136 | 93.65 | |
制图精度Producer accuracy (%) | 95.38 | 64.40 | 43.16 | 96.82 | 84.00 | 53.75 | 96.43 | - | |
光谱与垂直结构综合特征 Spectrum and vertical structure | 森林 Forest | 556 | 53 | 0 | 0 | 0 | 0 | 0 | 91.30 |
灌木 Shrub | 5 | 629 | 27 | 2 | 0 | 20 | 0 | 92.09 | |
草地 Grassland | 0 | 5 | 141 | 25 | 19 | 0 | 0 | 74.21 | |
农田 Farmland | 0 | 3 | 14 | 319 | 0 | 0 | 0 | 94.94 | |
裸地 Bare land | 2 | 15 | 8 | 0 | 271 | 17 | 0 | 86.58 | |
建设用地 Built-up area | 0 | 0 | 0 | 0 | 12 | 282 | 0 | 95.92 | |
水域 Water | 0 | 0 | 0 | 0 | 24 | 0 | 1178 | 98.00 | |
制图精度Producer accuracy (%) | 98.76 | 89.22 | 74.21 | 92.20 | 83.13 | 88.40 | 100.00 | - |
Table 4 Comparison of classification accuracy of different land types based on different classification characteristics
分类依据 Classification basis | 地类 Land type | 森林 Forest | 灌木 Shrub | 草地 Grassland | 农田 Farmland | 裸地 Bare land | 建设用地 Built-up area | 水域 Water | 用户精度 User accuracy (%) |
---|---|---|---|---|---|---|---|---|---|
光谱特征 Spectrum | 森林 Forest | 537 | 189 | 0 | 0 | 0 | 1 | 42 | 69.83 |
灌木 Shrub | 22 | 454 | 70 | 0 | 8 | 31 | 0 | 77.61 | |
草地 Grassland | 0 | 6 | 82 | 11 | 0 | 20 | 0 | 68.91 | |
农田 Farmland | 0 | 19 | 13 | 335 | 0 | 24 | 0 | 85.68 | |
裸地 Bare land | 0 | 6 | 0 | 0 | 273 | 30 | 0 | 88.35 | |
建设用地 Built-up area | 0 | 30 | 25 | 0 | 14 | 172 | 0 | 71.37 | |
水域 Water | 4 | 1 | 0 | 0 | 30 | 42 | 1136 | 93.65 | |
制图精度Producer accuracy (%) | 95.38 | 64.40 | 43.16 | 96.82 | 84.00 | 53.75 | 96.43 | - | |
光谱与垂直结构综合特征 Spectrum and vertical structure | 森林 Forest | 556 | 53 | 0 | 0 | 0 | 0 | 0 | 91.30 |
灌木 Shrub | 5 | 629 | 27 | 2 | 0 | 20 | 0 | 92.09 | |
草地 Grassland | 0 | 5 | 141 | 25 | 19 | 0 | 0 | 74.21 | |
农田 Farmland | 0 | 3 | 14 | 319 | 0 | 0 | 0 | 94.94 | |
裸地 Bare land | 2 | 15 | 8 | 0 | 271 | 17 | 0 | 86.58 | |
建设用地 Built-up area | 0 | 0 | 0 | 0 | 12 | 282 | 0 | 95.92 | |
水域 Water | 0 | 0 | 0 | 0 | 24 | 0 | 1178 | 98.00 | |
制图精度Producer accuracy (%) | 98.76 | 89.22 | 74.21 | 92.20 | 83.13 | 88.40 | 100.00 | - |
项目 Item | 森林 Forest | 灌木 Shrub | 草地 Grassland | 农田 Farmland | 裸地 Bare land | 建设用地 Built-up area | 水域 Water |
---|---|---|---|---|---|---|---|
调查及解译结果Inventory and interpretation results (hm2) | 69068 | 173283 | 74569 | 430 | 47230 | 492 | 2042 |
影像分类结果Image classification results (hm2) | 66883 | 157432 | 86444 | 403 | 53337 | 550 | 2065 |
相对精度Relative accuracy (%) | 96.84 | 90.85 | 86.26 | 93.78 | 88.55 | 89.43 | 98.90 |
平均相对精度Mean relative accuracy (%) | 92.09 |
Table 5 Area statistics and comparative analysis of different classified land types
项目 Item | 森林 Forest | 灌木 Shrub | 草地 Grassland | 农田 Farmland | 裸地 Bare land | 建设用地 Built-up area | 水域 Water |
---|---|---|---|---|---|---|---|
调查及解译结果Inventory and interpretation results (hm2) | 69068 | 173283 | 74569 | 430 | 47230 | 492 | 2042 |
影像分类结果Image classification results (hm2) | 66883 | 157432 | 86444 | 403 | 53337 | 550 | 2065 |
相对精度Relative accuracy (%) | 96.84 | 90.85 | 86.26 | 93.78 | 88.55 | 89.43 | 98.90 |
平均相对精度Mean relative accuracy (%) | 92.09 |
分类依据 Classification basis | 总体精度 Overall accuracy | 1770~2770 m海拔精度 Accuracy of altitude (%) | 2770~3770 m海拔精度 Accuracy of altitude (%) | 阴坡精度 Accuracy of shady slope (%) | 阳坡精度 Accuracy of sunny slope (%) | 半阴坡精度 Accuracy of half shady slope (%) | 半阳坡精度 Accuracy of half sunny slope (%) | |
---|---|---|---|---|---|---|---|---|
分类精度 Accuracy (%) | Kappa系数 Kappa coefficient | |||||||
随机样本Random sample | 65.52 | 0.43 | 68.14 | 63.99 | 73.77 | 72.59 | 69.72 | 72.67 |
海拔特征样本Altitude sample | 72.36 | 0.55 | 77.36 | 71.07 | - | - | - | - |
坡向特征样本Aspect sample | 87.44 | 0.75 | - | - | 91.55 | 82.11 | 91.48 | 85.34 |
海拔及坡向特征样本Altitude and aspect sample | 89.46 | 0.79 | 90.14 | 91.10 | 93.16 | 84.25 | 92.36 | 89.22 |
Table 6 Comparative analysis of the effect of terrain information on the accuracy of forest types classification
分类依据 Classification basis | 总体精度 Overall accuracy | 1770~2770 m海拔精度 Accuracy of altitude (%) | 2770~3770 m海拔精度 Accuracy of altitude (%) | 阴坡精度 Accuracy of shady slope (%) | 阳坡精度 Accuracy of sunny slope (%) | 半阴坡精度 Accuracy of half shady slope (%) | 半阳坡精度 Accuracy of half sunny slope (%) | |
---|---|---|---|---|---|---|---|---|
分类精度 Accuracy (%) | Kappa系数 Kappa coefficient | |||||||
随机样本Random sample | 65.52 | 0.43 | 68.14 | 63.99 | 73.77 | 72.59 | 69.72 | 72.67 |
海拔特征样本Altitude sample | 72.36 | 0.55 | 77.36 | 71.07 | - | - | - | - |
坡向特征样本Aspect sample | 87.44 | 0.75 | - | - | 91.55 | 82.11 | 91.48 | 85.34 |
海拔及坡向特征样本Altitude and aspect sample | 89.46 | 0.79 | 90.14 | 91.10 | 93.16 | 84.25 | 92.36 | 89.22 |
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