Abstract
Mapping plucking areas of tea plantations is essential for tea plantation management and production estimation. However, on-ground survey methods are time-consuming and labor-intensive, and satellite-based remotely sensed data are not fine enough for plucking area mapping that is 0.5–1.5 m in width. Unmanned aerial vehicles (UAV) remote sensing can provide an alternative. This paper explores the potential of using UAV-derived remotely sensed data for identifying plucking areas of tea plantations. In particular, four classification models were built based on different UAV data (optical imagery, digital aerial photogrammetry, and lidar data). The results indicated that the integration of optical imagery and lidar data produced the highest overall accuracy using the random forest algorithm (94.39%), while the digital aerial photogrammetry data could be an alternative to lidar point clouds with only a ~3% accuracy loss. The plucking area of tea plantations in the Huashan Tea Garden was accurately measured for the first time with a total area of 6.41 ha, which accounts for 57.47% of the tea garden land. The most important features required for tea plantation mapping were the canopy height, variances of heights, blue band, and red band. Furthermore, a cost–benefit analysis was conducted. The novelty of this study is that it is the first specific exploration of UAV remote sensing in mapping plucking areas of tea plantations, demonstrating it to be an accurate and cost-effective method, and hence represents an advance in remote sensing of tea plantations.
Highlights
Tea plants grow globally, especially in China, India, Sri Lanka, and Kenya [1]
This study has demonstrated the ability of Unmanned aerial vehicles (UAV)-derived remote sensing data to identify and map the plucking area of tea plantations
This study developed a new approach for mapping the plucking area of tea plantations using UAV-derived remotely sensed data
Summary
Especially in China, India, Sri Lanka, and Kenya [1]. Tea plantation monitoring and management have traditionally relied on regular field surveys. This type of on-ground data collection is important because it provides first-hand information on tea plantations. These surveys are time- and labor-consuming and logically cannot be applied to large hilly or mountainous areas where tea plantations grow. The structural characteristics of tea plants, such as the tree height and leaf area index, cannot be obtained continuously using traditional methods, and these characteristics determine the yield of tea plantations
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