An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.3. Framework of the OTBA Method
2.3.1. Multiresolution Segmentation
2.3.2. Crayfish Ditch Classification Based on a Decision-Tree Model
2.3.3. RCF Extraction by Topology
2.4. Performance Evaluations
3. Results
3.1. Optimal Scale Parameter and Image Segmentation Result
3.2. Classification Model and Result of Crayfish Ditch
3.3. RCF Map and Accuracy Assessment
3.4. RCF Mapping Based on Different Spatial, Spectral and Temporal Information
4. Discussion
4.1. The Sensitivity of Spatial, Spectral and Temporal Information on the OTBA Method
4.2. Advantages and Further Improvements
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Feature Category | Selected Features | Equations | Parameters | References |
---|---|---|---|---|
Spectral features | NDWI (Normalized difference water index) | Blue, Green, Red and NIR = surface reflectance values of Blue, Green, Red, NIR bands. #Pv = total number of pixels contained in the object Pv. = the image layer intensity value at pixel . = the darker direct neighbor to v, with · = the length of common border between v and u. | [52] | |
NDVI (Normalized difference vegetation index) | [53] | |||
CEWI (Coefficient enhanced water index) | [54] | |||
HRWI (High-resolution water index) | [55] | |||
Mean blue, green, red and NIR | [56] | |||
Brightness | ||||
Rel. border to brighter objects NIR | ||||
Geometric features | Border length | b0 = the length of outer border. bi = the length of inner border. u = the pixel size in coordinate system units. = the ratio length of v of the eigenvalues. = the ratio length of v of the bounding box. | [56] | |
Area | ||||
Length/Width | ||||
Shape index | ||||
Textural features | GLCM Entropy | i = the row number. j = the column number. = the normalized value in the cell . N = the number of rows or columns. | [56] | |
GLCM Mean | ||||
GLCM Std Dev | ||||
GLCM Homogeneity | ||||
GLCM Contrast |
Class | RCF | Non-RCF | Total | Producer’s Accuracy |
---|---|---|---|---|
RCF | 112 | 12 | 124 | 90.32% |
Non-RCF | 8 | 111 | 119 | 93.28% |
Total | 120 | 123 | 243 | |
User’s Accuracy | 93.33% | 90.24% | ||
Overall Accuracy | 91.77% |
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Wei, H.; Hu, Q.; Cai, Z.; Yang, J.; Song, Q.; Yin, G.; Xu, B. An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China. Remote Sens. 2021, 13, 4666. https://doi.org/10.3390/rs13224666
Wei H, Hu Q, Cai Z, Yang J, Song Q, Yin G, Xu B. An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China. Remote Sensing. 2021; 13(22):4666. https://doi.org/10.3390/rs13224666
Chicago/Turabian StyleWei, Haodong, Qiong Hu, Zhiwen Cai, Jingya Yang, Qian Song, Gaofei Yin, and Baodong Xu. 2021. "An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China" Remote Sensing 13, no. 22: 4666. https://doi.org/10.3390/rs13224666
APA StyleWei, H., Hu, Q., Cai, Z., Yang, J., Song, Q., Yin, G., & Xu, B. (2021). An Object- and Topology-Based Analysis (OTBA) Method for Mapping Rice-Crayfish Fields in South China. Remote Sensing, 13(22), 4666. https://doi.org/10.3390/rs13224666