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PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems
摘要： Background: Driven by a huge improvement in automation, unmanned areal systems (UAS) are increasingly used for field observations and high-throughput phenotyping. Today, the bottleneck does not lie in the ability to fly a drone anymore, but rather in the appropriate flight planning to capture images with sufficient quality. Proper flight preparation for photography with digital frame cameras should include relevant concepts such as view, sharpness and exposure calculations. Additionally, if mapping areas with UASs, one has to consider concepts related to ground control points (GCPs), viewing geometry and way-point flights. Unfortunately, non of the available flight planning tools covers all these aspects. Results: We give an overview of concepts related to flight preparation, present the newly developed open source software PhenoFly Planning Tool, and evaluate other recent flight planning tools. We find that current flight planning and mapping tools strongly focus on vendor-specific solutions and mostly ignore basic photographic properties—our comparison shows, for example, that only two out of thirteen evaluated tools consider motion blur restrictions, and none of them depth of field limits. In contrast, PhenoFly Planning Tool enhances recent sophisticated UAS and autopilot systems with an optical remote sensing workflow that respects photographic concepts. The tool can assist in selecting the right equipment for your needs, experimenting with different flight settings to test the performance of the resulting imagery, preparing the field and GCP setup, and generating a flight path that can be exported as waypoints to be uploaded to an UAS. Conclusion: By considering the introduced concepts, uncertainty in UAS-based remote sensing and high-throughput phenotyping may be considerably reduced. The presented software PhenoFly Planning Tool (https://shiny.usys.ethz.ch/PhenoFlyPlanningTool) helps users to comprehend and apply these concepts.
关键词： Flight planning,Ground control point (GCP),High-throughput phenotyping,Viewing geometry,Low-altitude remote sensing,Mapping from imagery
更新于2025-09-23 15:23:52
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Image based leaf segmentation and counting in rosette plants
摘要： This paper proposes an efficient method to extract the leaf region and count the number of leaves in digital plant images. The plant image analysis plays a significant role in viable and productive agriculture. It is used to record the plant growth, plant yield, chlorophyll fluorescence, plant width and tallness, leaf area, etc. frequently and accurately. Plant growth is a major character to be analyzed among these plant characters and it directly depends on the number of leaves in the plants. In this paper, a new method is presented for leaf region extraction from plant images and counting the number of leaves. The proposed method has three steps. The first step involves a new statistical based technique for image enhancement. The second step involves in the extraction of leaf region in plant image using a graph based method. The third step involves in counting the number of leaves in the plant image by applying Circular Hough Transform (CHT). The proposed work has been experimented on benchmark datasets of Leaf Segmentation Challenge (LSC). The proposed method achieves the segmentation accuracy of 95.4% and it also achieves the counting accuracy of (cid:1)0.7 (DiC) and 2.3 (|DiC|) for datasets (A1, A2 and A3), which are better than the state-of-the-art methods.
关键词： Leaf count,Plant image analysis,Plant phenotyping,Leaf region extraction
更新于2025-09-23 15:23:52
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Optimized angles of the swing hyperspectral imaging system for single corn plant
摘要： During recent years, hyperspectral imaging systems have been widely applied in the greenhouses for plant phenotyping purposes. Current systems are typically designed as either top view or side view imaging mode. Top view is an ideal imaging angle for top leaves with flat leaf surfaces. However, most bottom leaves are either blocked or shaded. From side view, the entire plant structure is viewable. However, most leaf surfaces are not facing the camera, which impacts measurement quality. Besides, there could be advantages with certain tilted angle(s) between top view and side view. It’s interesting to explore the impact of different imaging angles to the phenotyping quality. For this purpose, a swing hyperspectral imaging system capable of capturing images at any angle from side view (0°) to top view (90°) by rotating the camera and the lighting source was designed. Corn plants were grown and allocated into 3 different treatments: high nitrogen (N) and well-watered (control), high N and drought-stressed, and low N and well-watered. Each plant was imaged at 7 different angles from 0° to 90° with an interval of 15°. The soil plant analysis development (SPAD) values and relative water content (RWC) ground truth measurements were used to establish treatment effects. The results showed that averaged plant-level Normalized Difference Vegetation Index (NDVI) values of plants in different treatments changed at different imaging angles. The results also indicated that for pixel-level NDVI distributions, the titled imaging angle of 75° was optimal to distinguish different water treatments, whereas, the tilted imaging angle of 15° was optimal to distinguish different N treatments. For pixel-level RWC distributions, the distribution difference between different water treatments was larger at higher imaging angles.
关键词： Pixel-level NDVI and RWC distributions,Optimal imaging angle,Swing hyperspectral imaging system,Plant phenotyping system,Tilted imaging angle
更新于2025-09-23 15:22:29
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Benefits, problems and challenges of plant factories with artificial lighting (PFALs): a short review
摘要： The benefits and problems to be solved and challenges for plant factories with artificial lighting (PFALs) are discussed. The benefits include high resource-use efficiency, high annual productivity per unit land area, and production of high-quality plants without using pesticides, regardless of weather. A major problem to be solved is high initial investment and operation costs. Challenges for the next-generation smart PFALs include the introduction of advanced technologies such as artificial intelligence with the use of big data, genomics and phenomics (or methodologies and protocols for noninvasive measurement of plant-specific traits related to plant structure and function).
关键词： resource-use efficiency (RUE),cultivation system module (CSM),standardization,smart LED lighting system,annual productivity,artificial intelligence,phenotyping
更新于2025-09-23 15:22:29
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Spatial Referencing of Hyperspectral Images for Tracing of Plant Disease Symptoms
摘要： The characterization of plant disease symptoms by hyperspectral imaging is often limited by the missing ability to investigate early, still invisible states. Automatically tracing the symptom position on the leaf back in time could be a promising approach to overcome this limitation. Therefore we present a method to spatially reference time series of close range hyperspectral images. Based on reference points, a robust method is presented to derive a suitable transformation model for each observation within a time series experiment. A non-linear 2D polynomial transformation model has been selected to cope with the specific structure and growth processes of wheat leaves. The potential of the method is outlined by an improved labeling procedure for very early symptoms and by extracting spectral characteristics of single symptoms represented by Vegetation Indices over time. The characteristics are extracted for brown rust and septoria tritici blotch on wheat, based on time series observations using a VISNIR (400–1000 nm) hyperspectral camera.
关键词： spectral tracking,time series,plant phenotyping,hyperspectral imaging,disease detection
更新于2025-09-23 15:22:29
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Comparing RGB-D Sensors for Close Range Outdoor Agricultural Phenotyping
摘要： Phenotyping is the task of measuring plant attributes for analyzing the current state of the plant. In agriculture, phenotyping can be used to make decisions concerning the management of crops, such as the watering policy, or whether to spray for a certain pest. Currently, large scale phenotyping in fields is typically done using manual labor, which is a costly, low throughput process. Researchers often advocate the use of automated systems for phenotyping, relying on the use of sensors for making measurements. The recent rise of low cost, yet reasonably accurate, RGB-D sensors has opened the way for using these sensors in field phenotyping applications. In this paper, we investigate the applicability of four different RGB-D sensors for this task. We conduct an outdoor experiment, measuring plant attribute in various distances and light conditions. Our results show that modern RGB-D sensors, in particular, the Intel D435 sensor, provides a viable tool for close range phenotyping tasks in fields.
关键词： INTEL D-435,RGB-D sensors,sensors in agriculture,INTEL SR300,empirical analysis,Microsoft Kinect,phenotyping,ORBBEC ASTRA S
更新于2025-09-23 15:22:29
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Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS
摘要： As one of the key crop traits, plant height is traditionally evaluated manually, which can be slow, laborious and prone to error. Rapid development of remote and proximal sensing technologies in recent years allows plant height to be estimated in more objective and efficient fashions, while research regarding direct comparisons between different height measurement methods seems to be lagging. In this study, a ground-based multi-sensor phenotyping system equipped with ultrasonic sensors and light detection and ranging (LiDAR) was developed. Canopy heights of 100 wheat plots were estimated five times during a season by the ground phenotyping system and an unmanned aircraft system (UAS), and the results were compared to manual measurements. Overall, LiDAR provided the best results, with a root-mean-square error (RMSE) of 0.05 m and an R2 of 0.97. UAS obtained reasonable results with an RMSE of 0.09 m and an R2 of 0.91. Ultrasonic sensors did not perform well due to our static measurement style. In conclusion, we suggest LiDAR and UAS are reliable alternative methods for wheat height evaluation.
关键词： remote sensing,plant breeding,crop,proximal sensing,phenotyping
更新于2025-09-23 15:21:21
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[IEEE 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) - Las Vegas, NV (2018.4.8-2018.4.10)] 2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) - Estimating Plant Centers Using A Deep Binary Classifier
摘要： Phenotyping is the process of estimating the physical and chemical properties of a plant. Traditional phenotyping is labor intensive and time consuming. These measurements can be obtained faster by collecting aerial images with an Unmanned Aerial Vehicle (UAV) and analyzing them using modern image analysis technologies. We propose a method to estimate plant centers by classifying each pixel as a plant center or not a plant center. We then label the center of each cluster as the plant location. We studied the performance of our method on two datasets. We achieved 84% precision and 90% recall on one dataset consisting of early stage plants and 62% precision and 77% recall on another dataset consisting of later stage plants.
关键词： Color Image Processing,Plant Phenotyping,CNN,Machine Learning
更新于2025-09-23 15:21:21
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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 - Sun Induced Fluorescence Calibration and Validation for Field Phenotyping
摘要： Reliable measurements of Sun Induced Fluorescence (SIF) require a good instrument characterization as well as a complex processing chain. In this paper, we summarize the state of the art SIF retrieval methods and measurements platforms for field phenotyping. Furthermore, we use HyScreen, hyperspectral-imaging system for top of canopy measurements of SIF, as an example of the instrument requirements, data process, and data validation needed to obtain reliable measurements of SIF.
关键词： Sun Induced fluorescence,hyperspectral measurements,retrievals method,field spectrometers,field phenotyping
更新于2025-09-23 15:21:01
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Visualising the Cardiovascular System of Embryos of Biomedical Model Organisms with High Resolution Episcopic Microscopy (HREM)
摘要： The article will briefly introduce the high-resolution episcopic microscopy (HREM) technique and will focus on its potential for researching cardiovascular development and remodelling in embryos of biomedical model organisms. It will demonstrate the capacity of HREM for analysing the cardiovascular system of normally developed and genetically or experimentally malformed zebrafish, frog, chick and mouse embryos in the context of the whole specimen and will exemplarily show the possibilities HREM offers for comprehensive visualisation of the vasculature of adult human skin. Finally, it will provide examples of the successful application of HREM for identifying cardiovascular malformations in genetically altered mouse embryos produced in the deciphering the mechanisms of developmental disorders (DMDD) program.
关键词： episcopic,phenotyping,HREM,high resolution episcopic microscopy,chick,imaging,embryo,3D,developmental biology,mouse
更新于2025-09-19 17:15:36