Article detail · 2015
Rice Growth Monitoring by Means of X Band Co polar SAR Feature Clustering and BBCH Scale
- Year
- 2015
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue IEEE Geoscience and Remote Sensing Letters
- Catalog match (ISSN) IEEE Geoscience and Remote Sensing Letters
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Precision agriculture research, which aims to monitor agricultural fields and to manage agricultural practice by considering overall environmental impacts, has gained momentum with the recent improvements in the remote sensing area. The objective of this letter, as a part of precision farming, is to implement Biologische Bundesanstalt, Bundessortenamt und CHemische Industrie (BBCH) scale assignment in plant growth monitoring by means of SAR. The proposed approach copes with structural heterogeneity in agricultural fields by grouping together similar morphologies. For this, densely cultivated paddy rice fields are analyzed using TerraSAR-X (TSX) co-polar SAR data. For generating structurally similar groups, K-means clustering is used in a polarimetric feature vector space, which is composed of backscattering intensities and polarimetric phase differences. This step is followed by a preliminary classification approach based on the temporal separability of the explanatory parameters. In the last step of the proposed methodology, assigned classes are updated based on the biological principles that are followed in rice cultivation. This letter provides the results of the proposed algorithm and compares them to the standard threshold-based approach in two independent agricultural areas. The results show the superiority of the feature-clustering-based classification compared with the standard approach in handling field heterogeneity.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
66 citations
OpenAlex cited_by_count (cache / database)
11 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Paddy Rice Phenology Classification Based on Machine Learning Methods Using Multitemporal Co Polar X Band SAR Images 2016
- Retrieval of vegetation height in rice fields using polarimetric SAR interferometry with TanDEM-X data 2017
- Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion 2017
- Polarization Impact in TanDEM X Data Over Vertical Oriented Vegetation The Paddy Rice Case Study 2015
- Estimation of Rice Crop Height From X and C Band PolSAR by Metamodel Based Optimization 2017
- Assessment of Paddy Rice Height: Sequential Inversion of Coherent and Incoherent Models 2018
- A Multi-Year Study on Rice Morphological Parameter Estimation with X-Band Polsar Data 2017
- Global sensitivity analysis of a morphology based electromagnetic scattering model 2015
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