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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Wheel-Based Lidar Data for Plant Height and Canopy Cover Evaluation to Aid Biomass Prediction
摘要： Biomass estimation is fundamental for a variety of plant ecological studies. Direct measurement of aboveground biomass by clipping and sorting is destructive, time-consuming and laborious, thus reducing the ability of extensive sampling. Various plant traits, such as plant height, canopy cover, and leaf and plant structure contribute towards its biomass. In this study, we focus on exploiting wheel-based LiDAR data over an agricultural field to perform growth monitoring and canopy cover estimation, which would play a crucial role in the future to develop a non-invasive technique for biomass prediction.
关键词： Biomass,plant traits,LiDAR data,plant height,canopy cover
更新于2025-09-23 15:22:29
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Image-based tracking of ripening in wheat cultivar mixtures: A quantifying approach parallel to the conventional phenology
摘要： Developing the quantitative methods independent of the conventional qualitative phenology is a vital necessity for evaluating the temporal trends in the crop growth cycle, particularly in the heterogeneous canopies of cultivar mixtures. A digital camera was used to take ground-based nadir images during two years (2014–15 and 2015–16) of a ?eld experiment conducted at the School of Agriculture, Shiraz University, Iran, for monitoring and quantifying the ripening trends in wheat cultivar mixtures with di?erent ripening patterns grown under two irrigation conditions. The experimental treatments consisted of 4 early- to middle-ripening wheat cultivars and their 10 mixtures, under post-well- and de?cit-irrigated conditions, arranged in a randomized complete block design with 3 replicates. Then the images were processed and three image-derived indices including CC (canopy cover), GR [(G-R)/G; RGB color system], and CCGR (CC × GR) were used as the quantifying criteria. The de- clining trends of these indices during ripening showed strong ?ts to binomial equations, based on which simple prediction models were suggested and validated. Furthermore, the split linear trends and their slopes were estimated to assess the short-term variations. Some agronomic aspects were also evidenced using the mixtures- monoculture diversions, and the relationship between CC and GR. The frameworks evaluated appear to provide reliable and simple solutions for quantifying the crop temporal trends parallel to the conventional phenology.
关键词： Ripening pattern,Phenotyping,Thermal time,Canopy cover,Digital camera
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Implementation of UAV-Based Lidar for High Throughput Phenotyping
摘要： High throughput phenotyping is rapidly gaining widespread popularity due to its ability to non-destructively extract plant traits, such as plant height, canopy density, leaf and plant structure, and so on. In this study, we focus on developing a UAV-based LiDAR system to acquire accurate time-series 3D point clouds for monitoring two specific plant traits – plant height and canopy cover – which are integral for enhancing crop genetic improvement to meet the needs of future generations. Furthermore, the obtained estimates are validated by comparing the results with those obtained from wheel-based LiDAR data.
关键词： High throughput phenotyping,UAV,plant height,canopy cover,LiDAR system
更新于2025-09-09 09:28:46