Forestry applications of UAVs in Europe: a review
01 May 2017-International Journal of Remote Sensing (Taylor & Francis)-Vol. 38, Iss: 8, pp 2427-2447
TL;DR: The use of UAVs in forestry will increase, possibly leading to a regular utilization for small-scale monitoring purposes in Europe when recent technologies (i.e. hyperspectral imagery and lidar) and methodological approaches will be consolidated.
Abstract: Unfortunately, the fragmented regulations among EU countries, a result of the lack of common rules for operating UAVs in Europe, limit the chance to operate within Europe’s boundaries and prevent research mobility and exchange opportunities. Nevertheless, the applications of UAVs are expanding in different domains, and the use of UAVs in forestry will increase, possibly leading to a regular utilization for small-scale monitoring purposes in Europe when recent technologies i.e. hyperspectral imagery and lidar and methodological approaches will be consolidated.
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University of Basilicata1, King Abdullah University of Science and Technology2, James Hutton Institute3, Democritus University of Thrace4, Tel Aviv University5, Bar-Ilan University6, Clark University7, University of Palermo8, Academy of Sciences of the Czech Republic9, Tuscia University10, University of Coimbra11, Polytechnic University of Valencia12, University of California, Santa Barbara13, University of Tartu14, Newcastle University15, Swedish University of Agricultural Sciences16, University of Pannonia17, Hungarian Academy of Sciences18
TL;DR: An overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring is provided in order to identify future directions, applications, developments, and challenges.
Abstract: Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.
442 citations
TL;DR: A survey regarding the potential use of UAVs in PA is provided, focusing on 20 relevant applications, which investigate in detail 20 UAV applications that are devoted to either aerial crop monitoring processes or spraying tasks.
386 citations
TL;DR: Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions, and are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future.
Abstract: Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees representing various tree species and developmental stages were collected in June 2014 using a UAV remote sensing system equipped with a frame format hyperspectral camera and an RGB camera in highly variable weather conditions. Dense point clouds were measured photogrammetrically by automatic image matching using high resolution RGB images with a 5 cm point interval. Spectral features were obtained from the hyperspectral image blocks, the large radiometric variation of which was compensated for by using a novel approach based on radiometric block adjustment with the support of in-flight irradiance observations. Spectral and 3D point cloud features were used in the classification experiment with various classifiers. The best results were obtained with Random Forest and Multilayer Perceptron (MLP) which both gave 95% overall accuracies and an F-score of 0.93. Accuracy of individual tree identification from the photogrammetric point clouds varied between 40% and 95%, depending on the characteristics of the area. Challenges in reference measurements might also have reduced these numbers. Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions. These novel methods are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future.
306 citations
Cites background from "Forestry applications of UAVs in Eu..."
...The development of low-weight hyperspectral imaging sensors is likely to increase the use of spectral data collected from UAVs in forestry applications [34]....
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TL;DR: This paper performs a critical review on RS tasks that involve UAV data and their derived products as their main sources including raw perspective images, digital surface models, and orthophotos and focuses on solutions that address the “new” aspects of the U drone data including ultra-high resolution; availability of coherent geometric and spectral data; and capability of simultaneously using multi-sensor data for fusion.
Abstract: The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in almost every application (e.g., agriculture, forestry, and mining) that needs observed information from the top or oblique views. While they intend to be a general remote sensing (RS) tool, the relevant RS data processing and analysis methods are still largely ad-hoc to applications. Although the obvious advantages of UAV data are their high spatial resolution and flexibility in acquisition and sensor integration, there is in general a lack of systematic analysis on how these characteristics alter solutions for typical RS tasks such as land-cover classification, change detection, and thematic mapping. For instance, the ultra-high-resolution data (less than 10 cm of Ground Sampling Distance (GSD)) bring more unwanted classes of objects (e.g., pedestrian and cars) in land-cover classification; the often available 3D data generated from photogrammetric images call for more advanced techniques for geometric and spectral analysis. In this paper, we perform a critical review on RS tasks that involve UAV data and their derived products as their main sources including raw perspective images, digital surface models, and orthophotos. In particular, we focus on solutions that address the “new” aspects of the UAV data including (1) ultra-high resolution; (2) availability of coherent geometric and spectral data; and (3) capability of simultaneously using multi-sensor data for fusion. Based on these solutions, we provide a brief summary of existing examples of UAV-based RS in agricultural, environmental, urban, and hazards assessment applications, etc., and by discussing their practical potentials, we share our views in their future research directions and draw conclusive remarks.
301 citations
TL;DR: RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions and further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).
Abstract: In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).
156 citations
Cites background from "Forestry applications of UAVs in Eu..."
...Independent from the developments of LiDAR instruments, Unmanned Aerial Vehicles (UAVs) have found use as platforms for various types of sensors in forestry and many other fields [12,13]....
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...7 kg) and optional cameras the total system weights just under 25 kg; hence, it is possible to operate it under light UAV regulations in many European countries [13]....
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16,989 citations
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Abstract: Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA - or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance of ‘grey’ literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA methods are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.
3,809 citations
"Forestry applications of UAVs in Eu..." refers methods in this paper
...After a standard photogrammetric process (tie points extraction, dense matching, co-registration with ALS-DTM, dense matching), tree crowns were segmented using six scale parameters of object-based image analysis (OBIA, Blaschke 2010)....
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TL;DR: As the Association for Computing Machinery enters a new phase of its existence, it seems befitting to review the conditions in the computing field just prior to its organization and the events of the past six years of its life.
Abstract: As the Association for Computing Machinery enters a new phase of its existence, it seems befitting to review, briefly, the conditions in the computing field just prior to its organization and the events of the past six years of its life. Since its formation, in 1947, the Association has adhered to the originally established policy of informality. That is, meetings and discussions were encouraged and information was generally put out in mimeographed form and more formal publications were discouraged. The function of the organization was to maintain a mailing list of members paying only such dues as were necessary to cover the cost of printing or mimeographing and mailing. Such an organization served its purpose excellently, but times have changed.Prior to the formation of the Association, the automatic computing field, as such, hardly existed. Probably the first meeting of those interested in the field was held at the Massachusetts Institute of Technology in 1945. The occasion was to introduce the differential analyzer, designed by Dr. Vannevar Bush and Dr. Samuel H. Caldwell, to the public. This machine is a refinement of the original machine built by Dr. Bush in 1925. The earlier machine served as a pattern for several machines which were in operation in 1945, including those at the Aberdeen Proving Ground, the Moore School of Electrical Engineering, the General Electric Company and in Manchester, England.It is interesting to note that, at the time of this first meeting, other analog type machines were in operation. Network analyzers were employed to simulate power distribution systems and aid in their study. None of these machines employed digital representation but represented the values in analog form, such as voltage, current or angular position. Digital computation was possible only by hand operated calculators or by some business machines.Although automatic digital computation by machinery was the goal Charles Babbage strove to reach, it was not until the Hollerith rotary counter was suggested in 1890 and the International Business Machines Corporation began producing machines employing such counters for accounting purposes in the period from 1903 to 1905, that such goal was reached. The automatic multiplying punch machine was not produced until 1931.Computation by means of telephone relays was first introduced in the Bell System Complex Computer, known as Model I, in 1939. The method of employing the relays was suggested by Dr. George R. Stibitz and the machine was designed by Samuel B. Williams. This was not a fully automatic machine. The complex quantities for a single
2,011 citations
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...Floris et al. (2012) estimated the stand volume of an approximately 8 ha wide forest compartment, composed by spruce fire (P. abies L. Karst.)...
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