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Proceedings ArticleDOI

UAV-based remote sensing for vegetation cover estimation using NDVI imagery and level sets method

TLDR
A compact system for estimating vegetation in a certain area is proposed consisting of a small UAV platform with the ability of performing autonomous flights and recording the videos of the ground cover using a camera with a modified infrared filter lens for obtaining the composite NDVI videos.
Abstract
Vegetation is a key component of nearly all global ecosystems, having a role of regulating various biogeochemical cycles in nature, as well as maintaining the energy balance at the earth's surface and atmospheric boundary layer. Therefore, it is of wide importance to constantly monitor the changes in vegetation cover and structure, especially those that are due to human influence. Backed up by many global initiatives for vegetation preservation and monitoring, it is necessary to have a system to collect and analyse different vegetation indices and products. One of the most important parameters of calculating many of these indices, is the amount of the vegetation cover in a certain area. This paper proposes a compact system for estimating vegetation in a certain area. The proposed system consists of a small UAV platform with the ability of performing autonomous flights and recording the videos of the ground cover using a camera with a modified infrared filter lens for obtaining the composite NDVI videos. The video is analysed and processed to extract the most significant frames that form a mosaic representing the area recorded by the camera. Finally, a contour is calculated forming the boundary around the area on the mosaic image that contains pixels that represent vegetation or photosynthetic activity. The contour and the area inside the boundary can be used for segmentation and estimation of other vegetation indices.

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Citations
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Journal ArticleDOI

Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches

TL;DR: The CNN approach emerged as a promising technique as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected.
Journal ArticleDOI

Applications of unmanned aerial vehicles in fluvial remote sensing: An overview of recent achievements

TL;DR: In this article, the authors comprehensively review and document various crucial achievements driven by UAV-based remote sensing in fluvial environments, among a variety of other relevant applications, including riparian vegetation, hazardous aquatic algae blooms, submerged morphology, water-surface slope, sediment, flow velocity, and disasters, including flood inundation mapping.
Journal ArticleDOI

Development of an Unmanned Aerial Vehicle-Borne Crop-Growth Monitoring System

TL;DR: A crop-growth monitoring system which uses an unmanned aerial vehicle (UAV) as an operating platform capable of real-time online acquisition of various major indexes, e.g., the normalized difference vegetation index of the crop canopy, ratio vegetation index (RVI), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW).
Journal ArticleDOI

Assessment of the Possibility of Using Unmanned Aerial Vehicles (UAVs) for the Documentation of Hiking Trails in Alpine Areas.

TL;DR: The research was conducted in the Tatra National Park in Poland to verify the usability of UAVs to check the condition of hiking trails in alpine areas and shows the applicability of prepared products to the evaluation of the spatial reach and intensity of erosion along hiking trails.
References
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Journal ArticleDOI

Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle

TL;DR: The ability to generate quantitative remote sensing products by means of a helicopter-based UAV equipped with inexpensive thermal and narrowband multispectral imaging sensors is demonstrated, demonstrating comparable estimations, if not better, than those obtained by traditional manned airborne sensors.
Journal ArticleDOI

Remote sensing imagery in vegetation mapping: a review

TL;DR: An overview of how to use remote sensing imagery to classify and map vegetation cover is presented, focusing on the comparisons of popular remote sensing sensors, commonly adopted image processing methods and prevailing classification accuracy assessments.
Book

"Geometric Level Set Methods in Imaging, Vision, and Graphics"

TL;DR: This book discusses methods for preserving geometric deformable models for brain reconstruction, as well as methods for implicit active contour models, and some of the methods used in this book were adapted for this purpose.
Journal ArticleDOI

An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV) Imagery, Based on Structure from Motion (SfM) Point Clouds

TL;DR: This paper presents a technique for geometric correction and mosaicking of UAV photography using feature matching and Structure from Motion (SfM) photogrammetric techniques.
Journal ArticleDOI

Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods

TL;DR: The study conducted in two orchards highlighted that an inexpensive approach based on consumer-grade cameras on board a hand-launched unmanned aerial platform can provide accuracies comparable to those of the expensive and computationally more complex light detection and ranging (LIDAR) systems currently operated for agricultural and environmental applications.