Technical viability of high-resolution cartographic products with unmanned aerial vehicles and lightweight sensors applied to engineering

Los avances tecnológicos en sectores como el agronómico, forestal, arqueológico, civil, etc. están suponiendo una revolución debido a la utilización de nuevas tecnologías con la finalidad de optimizar recursos y minimizar los costes. Concretamente, el uso de las plataformas aéreas no tripuladas y los avances experimentados en los sensores a bordo de éstas, permiten obtener información actualizada, así como generar productos que ayuden a la toma de decisiones. En este sentido, cada vez más estas plataformas se están convirtiendo en herramientas con las cuales es posible obtener información en el momento que se desee y a menor coste, comparado con los satélites remotos o las plataformas tripuladas. La elección de usar uno u otro dependerá del análisis de todos los factores que influyen para alcanzar el objetivo. Esta Tesis Doctoral tiene como objetivo principal analizar la viabilidad de los productos cartográficos de alta resolución obtenidos mediante plataformas aéreas no tripuladas con sensores ligeros a bordo. En primer lugar, se ha realizado un recorrido de la evolución experimentada por estas plataformas y de la tipología de sensores que pueden ser integrados, así como algunas de las aplicaciones en las que se están empleando y el procedimiento fotogramétrico a seguir para obtener el producto final. A continuación, se ha evaluado la calidad a través de diferentes test o estándares cartográficos con el fin de analizar la viabilidad del producto generado. Del mismo modo, se han llevado a cabo varios estudios con diferentes configuraciones de vuelo y distintas combinaciones de parámetros que influyen en la planificación del mismo. El objetivo ha sido determinar cuál de ellas es la más adecuada en función de los requerimientos a satisfacer y de la calidad posicional. Los productos cartográficos generados con plataformas aéreas no tripuladas han demostrado que pueden ser aplicados en diferentes ramas de la ingeniería (agronómica y civil, en este caso) para la toma de decisiones que faciliten la gestión y ayuden a definir las actuaciones pertinentes a llevar a cabo.Technological advances in sectors such as agronomy, forestry, archaeology, civil engineering, etc. are assuming a revolution due to the use of new technologies in order to optimize resources and minimize costs. Specifically, the use of unmanned aerial platforms and the advances made in the sensors on board, allow us to obtain updated information, as well as to generate products that help decision making. In this sense, more and more these platforms are becoming tools with which it is possible to obtain information at the time you want and at a lower cost, compared to remote satellites or manned platforms. The choice of using one or the other will depend on the analysis of all the factors that influence the achievement of the objective. The aim of this PhD thesis is to analyze the viability of high-resolution cartographic products obtained from unmanned aerial platforms with light on-board sensors. Firstly, a tour of the evolution experienced by these platforms and the type of sensors that can be integrated, as well as some of the applications in which they are being used and the photogrammetric procedure to be followed to obtain the final product. Next, the quality was evaluated using different tests or cartographic standards in order to analyze the viability of the product generated. In the same way, several studies have been carried out with different flight configurations and different combinations of parameters that influence the planning of the flight. The objective has been to determine which of them is the most suitable according to the requirements to be satisfied and the positional quality. Cartographic products generated with unmanned aerial platforms have shown that they can be applied in different branches of engineering (agronomic and civil, in this case) for decision-making that facilitate management and help define the relevant actions to be carried out

Comparison of Errors Produced by ABA and ITC Methods for the Estimation of Forest Inventory Attributes at Stand and Tree Level in Pinus radiata Plantations in Chile

Airborne laser scanning (ALS) technology is fully implemented in forest resource assessment processes, providing highly accurate and spatially continuous results throughout the area of interest, thus reducing inventory costs when compared with traditional sampling inventories. Several approaches have been employed to estimate forest parameters using ALS data, such as the Area-Based Approach (ABA) and Individual Tree Crown (ITC). These two methodologies use different information processing and field data collection approaches; thus, it is important to have a selection criterion for the method to be used based on the expected results and admissible errors. The objective of this study was to compare the prediction errors of forest inventory attributes in the functioning of ABA and ITC approaches. A plantation of 500 ha of Pinus radiata (400–600 trees ha−1) in Chile was selected; a forest inventory was conducted using the ABA and ITC methods and the accuracy of both methods was analyzed. The ITC models performed better than the ABA models at low tree densities for all forest inventory attributes (15% MAPE in tree density—N—and 11% in volume—V). There was no significant difference in precision regarding the volume and basal area (G) estimations at medium densities, although ITC obtained better results for density and dominant height (Ho). At high densities, ABA performed better for all the attributes except for height (6.5% MAPE in N, 8.7% in G, and 8.9% in V). Our results showed that the precision of forest inventories based on ALS data can be adjusted depending on tree density to optimize the selected approach (ABA and ITC), thus reducing the inventory costs. Hence, field efforts can be greatly decreased while achieving better prediction accuracies

Positional Quality Assessment of Orthophotos Obtained from Sensors Onboard Multi-Rotor UAV Platforms

In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart

Modeling Major Rural Land-Use Changes Using the GIS-Based Cellular Automata Metronamica Model: The Case of Andalusia (Southern Spain)

The effective and efficient planning of rural land-use changes and their impact on the environment is critical for land-use managers. Many land-use growth models have been proposed for forecasting growth patterns in the last few years. In this work; a cellular automata (CA)-based land-use model (Metronamica) was tested to simulate (1999–2007) and predict (2007–2035) land-use dynamics and land-use changes in Andalucía (Spain). The model was calibrated using temporal changes in land-use covers and was evaluated by the Kappa index. GIS-based maps were generated to study major rural land-use changes (agriculture and forests). The change matrix for 1999–2007 showed an overall area change of 674971 ha. The dominant land uses in 2007 were shrubs (30.7%), woody crops on dry land (17.3%), and herbaceous crops on dry land (12.7%). The comparison between the reference and the simulated land-use maps of 2007 showed a Kappa index of 0.91. The land-cover map for the projected PRELUDE scenarios provided the land-cover characteristics of 2035 in Andalusia; developed within the Metronamica model scenarios (Great Escape; Evolved Society; Clustered Network; Lettuce Surprise U; and Big Crisis). The greatest differences were found between Great Escape and Clustered Network and Lettuce Surprise U. The observed trend (1999–2007–2035) showed the greatest similarity with the Big Crisis scenario. Land-use projections facilitate the understanding of the future dynamics of land-use change in rural areas; and hence the development of more appropriate plans and policies

Land Capability for Agriculture, Hermel District, Lebanon

For the purpose of mapping land capability by United States Department of Agriculture (USDA) criteria, this paper presents a validated model to map land capability at a scale of 1:20,000 using a digital elevation model and the available soil information for Hermel District (525.6 km2) in Lebanon. The model was validated through fieldwork and it indicates a good overall accuracy of 89% and the significance of the model for mapping land capability at a district level. The study shows that 11.5 km2 (2.2%), 284.6 km2 (54.2%), 66.8 km2 (12.7%), 147.9 km2 (28.1%) and 14.9 km2 (2.8%) of the region were categorized in I, II, III, IV, and V land classes respectively. The comparison between the zoning map already produced for Hermel city and the land capability map demonstrates that the land use patterns need to be modified according to identified land capability classes to sustain the remaining productive lands for future generations

Accurate ortho-mosaicked six-band multispectral UAV images as affected by mission planning for precision agriculture proposes

Weed mapping at very early phenological stages of crop and weed plants for site-specific weed management can be achieved by using ultra-high spatial and high spectral resolution imagery provided by multispectral sensors on-board an unmanned aerial vehicle (UAV). These UAV images cannot cover the whole field, resulting in the need to take a sequence of multiple overlapped images. Therefore, the overlapped images must be oriented and ortho-rectified to create an accurate ortho-mosaicked image of the entire field for further classification. Because the spatial quality of ortho-mosaicked images mainly depend on the flight altitude and percentage of overlap, this paper describes the effect of flight parameters using a multirotor UAV and a multispectral camera on the mosaicking workflow. The objective is to define the best configuration for the mission planning to generate accurate ortho-images. A set of flights with a range of altitudes (30, 40, 50, 60, 70, 80, and 90 m) above ground level (AGL) and two end-lap and side-lap settings (60–30% and 70–40%) were studied. The spatial accuracy of ortho-mosaics was evaluated taking into consideration the ASPRS test. The results showed that the best flight setting to keep the spatial accuracy in the bundle adjustment was 70–40% overlap and altitudes AGL ranging from 60 to 90 m. At these flight altitudes, the spatial resolution was quite similar, making it possible to optimize the mission planning, flying at a higher altitude and increasing the area overflow without decreasing the ortho-mosaic spatial quality. This study has relevant implications for further use in detecting weed seedlings in crops.This research was partly funded by the AGL2014-52465-C4-4R project (Spanish Ministry of Economy and Competition, FEDER Funds: Fondo Europeo de Desarrollo Regional). Research of Mr Torres-Sánchez and Dr Peña was financed by the FPI [grant number BES-2012-052424] and Ramón y Cajal [grant number RYC-2013-14874] Programs (Spanish MINECO funds), respectively.Peer reviewe

Assessing Optimal Flight Parameters for Generating Accurate Multispectral Orthomosaicks by UAV to Support Site-Specific Crop Management

This article describes the technical specifications and configuration of a multirotor unmanned aerial vehicle (UAV) to acquire remote images using a six-band multispectral sensor. Several flight missions were programmed as follows: three flight altitudes (60, 80 and 100 m), two flight modes (stop and cruising modes) and two ground control point (GCP) settings were considered to analyze the influence of these parameters on the spatial resolution and spectral discrimination of multispectral orthomosaicked images obtained using Pix4Dmapper. Moreover, it is also necessary to consider the area to be covered or the flight duration according to any flight mission programmed. The effect of the combination of all these parameters on the spatial resolution and spectral discrimination of the orthomosaicks is presented. Spectral discrimination has been evaluated for a specific agronomical purpose: to use the UAV remote images for the detection of bare soil and vegetation (crop and weeds) for in-season site-specific weed management. These results show that a balance between spatial resolution and spectral discrimination is needed to optimize the mission planning and image processing to achieve   every agronomic objective. In this way, users do not have to sacrifice flying at low altitudes to cover the whole area of interest completely