Comparison of segmentation methods on images of energy plants obtained by UAVs

Pap, Melinda; Király, Sándor

doi:10.1109/fiot.2018.8325601

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…In agricultural image processing it is known that the importance of the specific color channels largely depends on the task to perform. We have followed the work of the authors of (Pap, Kiraly, 2018) and experimented with the variation of color channels with the height information encoded in the DSM image. Therefore, we created a false-color image by replacing the green channel with the height information.…”

Section: Resultsmentioning

confidence: 99%

Investigating the Usability of Uav Obtained Multispectral Imagery in Tree Species Segmentation

Pap

Király

Moljak

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. A widely used form of renewable energy are bioenergy crops. One form of it is the energy forestry that includes short rotation coppice plantations in which fast growing species of tree or woody shrub are grown (e.g. poplar, willow). The accurate prediction of forest biomass and volume can be used for the evaluation of plant breeding efficiency as well. The automatic tracking of plant development by traditional methods is quite difficult and labor intensive. Since energy forestries often contain different trees for estimating their volume it is essential to find segments containing the same tree species in the image.We investigated the applicability of a low cost UAV and an intermediate cost UAV in the field of agricultural image segmentation that is the first stage of biomass estimation (Gatziolis et al., 2015, Gaulton et al., 2015).This paper is a case study that shows the results of several segmentation algorithms applied on imagery obtained by a low cost UAV with low-cost camera, and imagery gathered by a UAV and camera set that are of higher quality and price. In the case study, we have observed two small forestry areas that contained six different tree species and their hybrids. Our results show that more expensive, better-equipped drone shots do not necessary provide significantly better segmentation.

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Section: Resultsmentioning

confidence: 99%

Investigating the Usability of Uav Obtained Multispectral Imagery in Tree Species Segmentation

Pap

Király

Moljak

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The areas where major irrigation is needed can help the farmers save time and water resources. • Corps spraying [11] Crop spraying is essential in cases where diseases have been identified, and it is essential to reduce pesticide use without affecting crop yield. In conclusion, UAV-based systems can contribute to crop spray management.…”

Section: Fig 2 -Precision Agriculture Mapping [7]mentioning

confidence: 99%

Agricultural Production System Based On IOT

Ali¹,

Kamardin²,

Maidin³

et al. 2022

IJIE

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Internet of things (IoT) is not a single word, but it has gathered billions of devices in the same lane. The Internet of things has given the lives of things. Machines have a sense now like a human. It works remotely as the program has been settled inside the chip. The system has become so smart and reliable. The Internet of things has brought out changes in most of the sectors of humankind. Meanwhile, agriculture is the main strength of a country. The more the production of agricultural products increased, the world will be more completeness from food shortage. The production of agriculture can be increased when the IoT system can be entirely implemented in the agricultural sector. Most of the approaches for IoT based agriculture have been reviewed in this paper. Related to IoT based agriculture, most of the architecture and methodology have been interpreted and have been critically analyzed based on previous related work of the researchers. This paper will be able to provide a complete idea with the architecture and methodology in the field of IoT based agriculture. Moreover, the challenges for agricultural IoT are discussed with the methods provided by the researchers.

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A Review on UAV-Based Applications for Precision Agriculture

2019

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Emerging technologies such as Internet of Things (IoT) can provide significant potential in Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time environmental data. IoT devices such as Unmanned Aerial Vehicles (UAVs) can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. However, the actual proliferation and exploitation of UAVs in Smart Farming has not been as robust as expected mainly due to the challenges confronted when selecting and deploying the relevant technologies, including the data acquisition and image processing methods. The main problem is that still there is no standardized workflow for the use of UAVs in such applications, as it is a relatively new area. In this article, we review the most recent applications of UAVs for Precision Agriculture. We discuss the most common applications, the types of UAVs exploited and then we focus on the data acquisition methods and technologies, appointing the benefits and drawbacks of each one. We also point out the most popular processing methods of aerial imagery and discuss the outcomes of each method and the potential applications of each one in the farming operations.

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Comparison of segmentation methods on images of energy plants obtained by UAVs

Cited by 3 publications

References 17 publications

Investigating the Usability of Uav Obtained Multispectral Imagery in Tree Species Segmentation

Investigating the Usability of Uav Obtained Multispectral Imagery in Tree Species Segmentation

Agricultural Production System Based On IOT

A Review on UAV-Based Applications for Precision Agriculture

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