On the acquisition of high-resolution maps with open source software and commercials off-the-shelf quad-rotors

Mosaics are high-resolution images obtained aerially and employed in several scientific research areas, such for example, in the field of environmental monitoring and precision agriculture. Although many high resolution maps are obtained by commercial demand, they can also be acquired with commercial aerial vehicles which provide more experimental autonomy and availability. For what regard to mosaicing-based aerial mission planners, there are not so many - if any - free of charge software. Therefore, in this paper is presented a framework designed with open source tools and libraries as an alternative to commercial tools to carry out mosaicing tasks.

Contribute to the Study of Vertical Distribution of Conventional No-Till Seeders and Spatial Variability of Seed Depth Placement of Maize in Alentejo, Portugal

Entre os vários fatores que contribuem para a produção de uma cultura de milho, a distribuição vertical dos semeadores avaliada através da localização da semente em profundidade é um fator-chave, especialmente na técnica de sementeira direta. Simultaneamente, dada a complexidade dos ecossistemas naturais e agrícolas em sistemas de agricultura de conservação, a gestão diferenciada e localizada das parcelas assume um importante papel na análise e gestão da variabilidade das propriedades do solo e estabelecimento das culturas, nomeadamente utilizando informação geo referenciada e tecnologia expedita. Assim, o principal objetivo desta Tese foi a avaliação em culturas de milho da variabilidade espacial da localização de semente em profundidade e estabelecimento da cultura em sementeira direta usando sistemas convencionais de controlo de profundidade, tendo-se comparado com diferentes sistemas de mobilização e recorrendo a tecnologias de agricultura de precisão. Os ensaios decorreram na região Mediterrânea do Alentejo, em propriedades agrícolas no decorrer das campanhas de 2010, 2011, 2012 e 2015 em 6 diferentes campos experimentais. O trabalho experimental consistiu em ensaios com avaliações in loco do solo e cultura, consumo de combustível das operações e deteção remota. Os resultados obtidos indicam que não só o sistema de mobilização afetou a localização da semente em profundidade, como em sementeira direta a profundidade de sementeira foi afetada pelo teor de humidade do solo, resistência do solo à profundidade e velocidade da operação de sementeira. Adicionalmente observaram-se condições heterogéneas de emergência e estabelecimento da cultura afetadas por condições físicas de compactação do solo. Comparando os diferentes sistemas de mobilização, obteve-se uma significativa redução de combustível para a técnica de sementeira direta, apesar de se terem observado diferenças estatísticas significativas considerando diferentes calibrações de profundidade de sementeira Do trabalho realizado nesta Tese ressalva-se a importância que as tecnologias de agricultura de precisão podem ter no acompanhamento e avaliação de culturas em sementeira direta, bem como a necessidade de melhores procedimentos no controlo de profundidade dos semeadores pelo respetivos operadores ou ao invés, a adoção de semeadores com mecanismos ativos de controlo de profundidade. ABSTRACT Among the various factors that contribute towards producing a successful maize crop, seeders vertical distribution evaluated through seed depth placement is a key determinant, especially under a no-tillage technique. At the same time in conservation agriculture systems due to the complexity of natural and agricultural ecosystems site specific management became an important approach to understand and manage the variability of soil properties and crop establishment, especially when using geo spatial information and affording readily technology Thus, the main objective of this Thesis was to evaluate the spatial variability of seed depth placement and crop establishment in maize crops under no-tillage conditions compared to different tillage systems, using conventional seed depth control no till seeders and precision farming technologies. Trials were carried out in the Mediterranean region of Alentejo, in private farms along the sowing operations season over the years 2010, 2011, 2012 and 2015 in 6 different experimental fields. Experimental work covered field tests with in loco soil and crop evaluations, fuel operation evaluations and aerial sensing. The results obtained indicate that not only tillage system affected seed depth placement but under no till conditions seed depth was affected by soil moisture content, soil resistance to penetration and seeders forward speed. In addition uneven crop seedling and establishment depended on seed depth placement and could be affected by physical problems of compaction layers. Significant reduction in fuel consumption was observed for no till operations although significant differences observed according to different setting calibrations of seed depth control. According to the results, precision agriculture is an important tool to evaluate crops under no till conditions and seed depth mechanisms should be more accurate by the operators or is determinant the adoption of new active depth control technology to improve seeders performance.

3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts) were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level.

Utilização de veículo aéreo não tripulado de asa fixa no monitoramento e coleta de imagem de animais e ambientes em propriedades rurais

Este trabalho tem por finalidade mostrar a aplicação e a utilização de um aeromodelo elétrico de asa fixa, também conhecido como veículo aéreo não tripulado (VANT), com controle manual ou automático, para coleta de dados e imagens em propriedades rurais, com a premissa de auxiliar os gestores no processo de gestão e tomada de decisão. A metodologia utilizada para a realização das coletas foi feita por meio de voos programados em dias e condições diferentes, para verificação e análise de desempenho do aeromodelo. Os resultados obtidos com os voos foram acima do esperado, gerando excelentes imagens e dados confiáveis. Sendo assim, pôde-se concluir que a utilização de VANTs, em coletas de dados e imagens em propriedades rurais foi satisfatória e auxiliou os gestores no processo de gerenciamento e rotacionamento de animais no pasto, uma vez que as imagens permitiram uma boa visualização e o aeromodelo desenvolvido cumpriu o seu objetivo com bom desempenho e agilidade.

Modelos não lineares resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada

Os controladores eletrônicos de pulverização visam minimizar a variação das taxas de insumos aplicadas no campo. Eles fazem parte de um sistema de controle, e permitem a compensação da variação de velocidade de deslocamento do pulverizador durante a operação. Há vários tipos de controladores eletrônicos de pulverização disponíveis no mercado e uma das formas de selecionar qual o mais eficiente nas mesmas condições, ou seja, em um mesmo sistema de controle, é quantificar o tempo de resposta do sistema para cada controlador específico. O objetivo desse trabalho foi estimar os tempos de resposta para mudanças de velocidade de um sistema eletrônico de pulverização via modelos de regressão não lineares, estes, resultantes da soma de regressões lineares ponderadas por funções distribuição acumulada. Os dados foram obtidos no Laboratório de Tecnologia de Aplicação, localizado no Departamento de Engenharia de Biossistemas da Escola Superior de Agricultura \"Luiz de Queiroz\", Universidade de São Paulo, no município de Piracicaba, São Paulo, Brasil. Os modelos utilizados foram o logístico e de Gompertz, que resultam de uma soma ponderada de duas regressões lineares constantes com peso dado pela função distribuição acumulada logística e Gumbell, respectivamente. Reparametrizações foram propostas para inclusão do tempo de resposta do sistema de controle nos modelos, com o objetivo de melhorar a interpretação e inferência estatística dos mesmos. Foi proposto também um modelo de regressão não linear difásico que resulta da soma ponderada de regressões lineares constantes com peso dado pela função distribuição acumulada Cauchy seno hiperbólico exponencial. Um estudo de simulação foi feito, utilizando a metodologia de Monte Carlo, para avaliar as estimativas de máxima verossimilhança dos parâmetros do modelo.

A low-cost remote sensing system for agricultural applications

This research develops a low cost remote sensing system for use in agricultural applications. The important features of the system are that it monitors the near infrared and it incorporates position and attitude measuring equipment allowing for geo-rectified images to be produced without the use of ground control points. The equipment is designed to be hand held and hence requires no structural modification to the aircraft. The portable remote sensing system consists of an inertia measurement unit (IMU), which is accelerometer based, a low-cost GPS device and a small format false colour composite digital camera. The total cost of producing such a system is below GBP 3000, which is far cheaper than equivalent existing systems. The design of the portable remote sensing device has eliminated bore sight misalignment errors from the direct geo-referencing process. A new processing technique has been introduced for the data obtained from these low-cost devices, and it is found that using this technique the image can be matched (overlaid) onto Ordnance Survey Master Maps at an accuracy compatible with precision agriculture requirements. The direct geo-referencing has also been improved by introducing an algorithm capable of correcting oblique images directly. This algorithm alters the pixels value, hence it is advised that image analysis is performed before image georectification. The drawback of this research is that the low-cost GPS device experienced bad checksum errors, which resulted in missing data. The Wide Area Augmented System (WAAS) correction could not be employed because the satellites could not be locked onto whilst flying. The best GPS data were obtained from the Garmin eTrex (15 m kinematic and 2 m static) instruments which have a highsensitivity receiver with good lock on capability. The limitation of this GPS device is the inability to effectively receive the P-Code wavelength, which is needed to gain the best accuracy when undertaking differential GPS processing. Pairing the carrier phase L1 with the pseudorange C/A-Code received, in order to determine the image coordinates by the differential technique, is still under investigation. To improve the position accuracy, it is recommended that a GPS base station should be established near the survey area, instead of using a permanent GPS base station established by the Ordnance Survey.

On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

Efeitos diretos e indiretos de parâmetros dos semivariogramas referentes aos atributos químicos do solo sobre a produtividade de grãos de soja

In order to add value to soybens crops, and hence the marketing, medium and large producers have been using precision agriculture techniques (PA), as the Remote Sensing, Geographic Information Systems (GIS) and positioning satellite, to assist the management of crops. Thus, given the economic relevance of that culture to the southwest of Paraná State and Brazil, scientific studies to increase their productivity and profitability are of main importance. The objective of this study was to evaluate the correlation between the chemical soil properties and soybean yield for each estimated parameter of semivariogram (range, nugget and level effect), and the deployment of these correlations in direct and indirect effects, aiming to improve the mapping process of spatial variability of soil chemical properties for use in PA. The hypothesis is that not all attributes of soil used to estimate the semivariogram parameters has a direct effect on productivity, and that even in groups of plants within a larger area it is possible to estimate the parameters of the semivariograms. The experiment was conducted in a commercial area of 19.7 ha, located in the city of Pato Branco - PR, central geographic coordinates 26º 11 '35 "South, 52 43' 05" West longitude, and average altitude of 780 m. The area is planted with soybeans for over 30 years, currently being adopted to cultivate Brasmax Target RR - Don Mario 5.9i, with row spacing of 0.50 m and 13 plants m-1, totaling 260,000 plants ha-1. For georeferencing of the area of study and sampling points was used a couple of topographic ProMarkTM3 receptors, making a relative positioning to obtain the georeferenced coordinates. To collect data (chemical analyzes of soil and crop yield) were sampled 10 blocks in the experimental area, each with an area of 20 m2 (20 meters long x 1 meter wide) containing two spaced adjacent rows of 0.5 m. Each block was divided into 20 portions of 1 m2, and from each were collected four subsamples at a distance of 0.5 m in relation to the lines of blocks, making up a sample depth for 0-10 cm a sample to 10-20 cm for each plot, totaling 200 samples for each depth. The soybean crop was performed on the blocks depending on maturity, and in each block was considered a bundle at each meter. In the data analysis, it was performed a diagnosis of multicollinearity, and subsequently a path analysis of the main variables according to the explanatory variables (range of chemical attributes: pH, K, P, Ca, etc.). The results obtained by the path analysis of the parameters of the semivariogram of soil chemical properties, indicated that only the Fe, Mg, Mn, organic matter (OM), P and Saturation by bases (SB) exerted direct and indirect effects on soybean productivity, although they have not presented spatial variability, indicating that the distribution of blocks in the area was unable to identify the spatial dependence of these elements, making it impossible to draw up maps of the chemical attributes for use in PA.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Spatial variability of soil properties and yield of a grazed alfalfa pasture in Brazil.

2016

Calibration of Grassmaster II to estimate green and dry matter yield in Mediterranean pastures: effects of pasture moisture content

Accurate assessment of standing pasture biomass in livestock production systems is a major factor for improving feed planning. Several tools are available to achieve this, including the GrassMaster II capacitance meter. This tool relies on an electrical signal, which is modified by the surrounding pasture. There is limited knowledge on how this capacitance meter performs in Mediterranean pastures. Therefore, we evaluated the GrassMaster II under Mediterranean conditions to determine (i) the effect of pasture moisture content (PMC) on the meter’s ability to estimate pasture green matter (GM) and dry matter (DM) yields, and (ii) the spatial variability and temporal stability of corrected meter readings (CMR) and DM in a bio-diverse pasture. Field tests were carried out with typical pastures of the southern region of Portugal (grasses, legumes, mixture and volunteer annual species) and at different phenological stages (and different PMC). There were significant positive linear relations between CMR and GM (r2 = 0.60, P < 0.01) and CMR and DM (r2 = 0.35, P < 0.05) for all locations (n = 347). Weak relationships were found for PMC (%) v. slope and coefficient of determination for both GM and DM. A significant linear relation existed for CMR v. GM and DM for PMC >80% (r2= 0.57, P < 0.01, RMSE = 2856.7 kg ha–1, CVRMSE=17.1% to GM; and r2= 0.51, P < 0.01,RMSE = 353.7 kg ha–1, CVRMSE = 14.3% to DM). Therefore, under the conditions of this current study there exists an optimum PMC (%) for estimating both GM and DM with the GrassMaster II. Repeated-measurements taken at the same location on different dates and conditions in a bio-diverse pasture showed similar and stable patterns between CMR and DM (r2= 0.67, P < 0.01, RMSE = 136.1 kg ha–1, CVRMSE = 6.5%). The results indicate that the GrassMaster II in-situ technique could play a crucial role in assessing pasture mass to improve feed planning under Mediterranean conditions.

Evaluation of DUALEM, OptRx and Grassmaster II sensors for monitoring the spatial variability and the temporal stability of a Mediterranean pasture

Site-specific management (SSM) is a form of precision agriculture whereby decisions on resource application and agronomic practices are improved to better match soil and crop requirements as they vary in the field. SSM enables the identification of regions (homogeneous management zones) within the area delimited by field boundaries. These subfield regions constitute areas that have similar permanent characteristics. Traditional soil and pasture sampling and the necessary laboratory analysis are time-consuming, labour-intensive and cost prohibitive, not viable from a SSM perspective because it needs a large number of soil and pasture samples in order to achieve a good representation of soil properties, nutrient levels and pasture quality and productivity. The main objective of this work was to evaluate technologies which have potential for monitoring aspects related to spatial and temporal variability of soil nutrients and pasture green and dry matter yield (respectively, GM and DM, in kg/ha) and support to decision making for the farmer. Three types of sensors were evaluated in a 7ha pasture experimental field: an electromagnetic induction sensor (“DUALEM 1S”, which measures the soil apparent electrical conductivity, ECa), an active optical sensor ("OptRx®", which measures the NDVI, “Normalized Difference Vegetation Index”) and a capacitance probe ("GrassMaster II" which estimates plant mass). The results indicate the possibility of using a soil electrical conductivity probe as, probably, the best tool for monitoring not only some of the characteristics of the soil, but also those of the pasture, which could represent an important help in simplifying the process of sampling and support SSM decision making, in precision agriculture projects. On the other hand, the significant and very strong correlations obtained between capacitance and NDVI and between any of these parameters and the pasture productivity shows the potential of these tools for monitoring the evolution of spatial and temporal patterns of the vegetative growth of biodiverse pasture, for identifying different plant species and variability in pasture yield in Alentejo dry-land farming systems. These results are relevant for the selection of an adequate sensing system for a particular application and open new perspectives for other works that would allow the testing, calibration and validation of the sensors in a wider range of pasture production conditions, namely the extraordinary diversity of botanical species that are characteristic of the Mediterranean region at the different periods of the year.

Spatial variability of inceptisol and entisol soils and their effect on merlot grape must composition.

2012

Precision mapping

The nondestructive determination of plant total dry matter (TDM) in the field is greatly preferable to the harvest of entire plots in areas such as the Sahel where small differences in soil properties may cause large differences in crop growth within short distances. Existing equipment to nondestructively determine TDM is either expensive or unreliable. Therefore, two radiometers for measuring reflected red and near-infrared light were designed, mounted on a single wheeled hand cart and attached to a differential Global Positioning System (GPS) to measure georeferenced variations in normalized difference vegetation index (NDVI) in pearl millet fields [Pennisetum glaucum (L.) R. Br.]. The NDVI measurements were then used to determine the distribution of crop TDM. The two versions of the radiometer could (i) send single NDVI measurements to the GPS data logger at distance intervals of 0.03 to 8.53 m set by the user, and (ii) collect NDVI values averaged across 0.5, 1, or 2 m. The average correlation between TDM of pearl millet plants in planting hills and their NDVI values was high (r^2 = 0.850) but varied slightly depending on solar irradiance when the instrument was calibrated. There also was a good correlation between NDVI, fractional vegetation cover derived from aerial photographs and millet TDM at harvest. Both versions of the rugged instrument appear to provide a rapid and reliable way of mapping plant growth at the field scale with a high spatial resolution and should therefore be widely tested with different crops and soil types.

Analysis of simple hardware efficiency for temperature measurement in agriculture and environment

This work focuses basically on the design and analysis of simple and low cost hardware systems efficiency for temperature measurement in agricultural area. The main objective is to prove quantitatively, through statistical data analysis, to what extent a simple hardware designed with inexpensive components can be used safely in the indoor temperature measurement in farm buildings, such as greenhouses, warehouse or silos. To verify the of simple hardware efficiency, its data were compared with data from measurements with a high performance LabVIEW platform. This work proved that a simple hardware based on a microcontroller and the LM35 sensor can perform well. It presented a good accuracy but a relatively low precision that can be improved when performed some consecutive signal sampling and then used its average value. Although there are many papers that explain these components, this work has the distinction of presenting a data analysis in numerical form and using high performance systems to ensure critical data comparison.