Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0

This work was supported by the projects: "VIRTUOUS" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2019. Ref. 872181, "SUSTAINABLE" funded by the European Union's Horizon 2020 Project H2020-MSCA-RISE-2020. Ref. 101007702 and the "Project of Excellence" from Junta de Andalucia 2020. Ref. P18-H0-4700. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Timely and reliable information about crop management, production, and yield is considered of great utility by stakeholders (e.g., national and international authorities, farmers, commercial units, etc.) to ensure food safety and security. By 2050, according to Food and Agriculture Organization (FAO) estimates, around 70% more production of agricultural products will be needed to fulfil the demands of the world population. Likewise, to meet the Sustainable Development Goals (SDGs), especially the second goal of “zero hunger”, potential technologies like remote sensing (RS) need to be efficiently integrated into agriculture. The application of RS is indispensable today for a highly productive and sustainable agriculture. Therefore, the present study draws a general overview of RS technology with a special focus on the principal platforms of this technology, i.e., satellites and remotely piloted aircrafts (RPAs), and the sensors used, in relation to the 5th industrial revolution. Nevertheless, since 1957, RS technology has found applications, through the use of satellite imagery, in agriculture, which was later enriched by the incorporation of remotely piloted aircrafts (RPAs), which is further pushing the boundaries of proficiency through the upgrading of sensors capable of higher spectral, spatial, and temporal resolutions. More prominently, wireless sensor technologies (WST) have streamlined real time information acquisition and programming for respective measures. Improved algorithms and sensors can, not only add significant value to crop data acquisition, but can also devise simulations on yield, harvesting and irrigation periods, metrological data, etc., by making use of cloud computing. The RS technology generates huge sets of data that necessitate the incorporation of artificial intelligence (AI) and big data to extract useful products, thereby augmenting the adeptness and efficiency of agriculture to ensure its sustainability. These technologies have made the orientation of current research towards the estimation of plant physiological traits rather than the structural parameters possible. Futuristic approaches for benefiting from these cutting-edge technologies are discussed in this study. This study can be helpful for researchers, academics, and young students aspiring to play a role in the achievement of sustainable agriculture.European Commission 101007702 872181Junta de Andalucia P18-H0-470

Unmanned Aerial Vehicles (UAVs) in environmental biology: A Review

Acquiring information about the environment is a key step during each study in the field of environmental biology at different levels, from an individual species to community and biome. However, obtaining information about the environment is frequently difficult because of, for example, the phenological timing, spatial distribution of a species or limited accessibility of a particular area for the field survey. Moreover, remote sensing technology, which enables the observation of the Earth’s surface and is currently very common in environmental research, has many limitations such as insufficient spatial, spectral and temporal resolution and a high cost of data acquisition. Since the 1990s, researchers have been exploring the potential of different types of unmanned aerial vehicles (UAVs) for monitoring Earth’s surface. The present study reviews recent scientific literature dealing with the use of UAV in environmental biology. Amongst numerous papers, short communications and conference abstracts, we selected 110 original studies of how UAVs can be used in environmental biology and which organisms can be studied in this manner. Most of these studies concerned the use of UAV to measure the vegetation parameters such as crown height, volume, number of individuals (14 studies) and quantification of the spatio-temporal dynamics of vegetation changes (12 studies). UAVs were also frequently applied to count birds and mammals, especially those living in the water. Generally, the analytical part of the present study was divided into following sections: (1) detecting, assessing and predicting threats on vegetation, (2) measuring the biophysical parameters of vegetation, (3) quantifying the dynamics of changes in plants and habitats and (4) population and behaviour studies of animals. At the end, we also synthesised all the information showing, amongst others, the advances in environmental biology because of UAV application. Considering that 33% of studies found and included in this review were published in 2017 and 2018, it is expected that the number and variety of applications of UAVs in environmental biology will increase in the future

Drone and sensor technology for sustainable weed management: a review

Weeds are amongst the most impacting abiotic factors in agriculture, causing important yield loss worldwide. Integrated Weed Management coupled with the use of Unmanned Aerial Vehicles (drones), allows for Site-Specific Weed Management, which is a highly efficient methodology as well as beneficial to the environment. The identification of weed patches in a cultivated field can be achieved by combining image acquisition by drones and further processing by machine learning techniques. Specific algorithms can be trained to manage weeds removal by Autonomous Weeding Robot systems via herbicide spray or mechanical procedures. However, scientific and technical understanding of the specific goals and available technology is necessary to rapidly advance in this field. In this review, we provide an overview of precision weed control with a focus on the potential and practical use of the most advanced sensors available in the market. Much effort is needed to fully understand weed population dynamics and their competition with crops so as to implement this approach in real agricultural contexts

Improving field management by machine vision - a review

Growing population of people around the world and thus increasing demand to food products as well as high tendency for declining the cost of operations and environmental preserving cares intensify inclination toward the application of variable rate systems for agricultural treatments, in which machine vision as a powerful appliance has been paid vast attention by agricultural researchers and farmers as this technology consumers. Various applications have introduced for machine vision in different fields of agricultural and food industry till now that confirms the high potential of this approach for inspection of different parameters affecting productivity. Computer vision has been utilized for quantification of factors affecting crop growth in field; such as, weed, irrigation, soil quality, plant nutrients and fertilizers in several cases. This paper presents some of these successful applications in addition to representing an introduction to machine vision

Detecting Invasive Insects with Unmanned Aerial Vehicles

A key aspect to controlling and reducing the effects invasive insect species have on agriculture is to obtain knowledge about the migration patterns of these species. Current state-of-the-art methods of studying these migration patterns involve a mark-release-recapture technique, in which insects are released after being marked and researchers attempt to recapture them later. However, this approach involves a human researcher manually searching for these insects in large fields and results in very low recapture rates. In this paper, we propose an automated system for detecting released insects using an unmanned aerial vehicle. This system utilizes ultraviolet lighting technology, digital cameras, and lightweight computer vision algorithms to more quickly and accurately detect insects compared to the current state of the art. The efficiency and accuracy that this system provides will allow for a more comprehensive understanding of invasive insect species migration patterns. Our experimental results demonstrate that our system can detect real target insects in field conditions with high precision and recall rates.Comment: IEEE ICRA 2019. 7 page

UAS Application in Agriculture: A Review of Technologies Possible to Apply in Portugal

The world population has been significantly growing over the last years. Consequently, also the needs and search of raw materials and goods has been increasing. In this context, the production, in a sustainable way and in the needed quantities, of food is a source of concern and study. At the same time a big evolution in the Unmanned Aerial Vehicles (UAV) has been verified, both in terms at the level of the equipment, and the operational scenarios where they have been used. Portugal presents itself as a country where the agriculture and livestock activities have a very big predominance in the use of the available soil and the economy. However, the lack of studies and implementation of new technologies keeps on being a limiting factor to the increase of productivity, sustainable use of the available resources and of the value that agriculture adds to the national trade balance. The main objective of this dissertation was to show that it is possible to apply several new methods and techniques, more specifically UAVs, to the Portuguese agricultural scenario. For this extensive research was carried out and a set of studies with the potential to be adapted and implement in Portugal were selected, encompassing different cultures and activities associated with them. After the chosen studies had been exposed and carefully analysed it was possible to perceive that the application of UAS’ in Portuguese agriculture would be a great added value insofar as it could lead to savings of several million euros both in increasing productivity, as well as in reducing costs with chemicals and field tests that are becoming obsolete. The saving of limited natural resources, namely water is also a very important factor.A população mundial tem vindo a crescer de forma muito significativa ao longo dos últimos anos. Consequentemente, também as necessidades e a procura de matérias-primas e bens têm aumentado. Neste contexto, a produção, de forma sustentável e nas quantidades necessárias, de bens alimentares é fonte de preocupação e estudo. Paralelamente tem-se verificado uma evolução bastante grande nos Veículos Aéreos Não Tripulados (UAV), quer ao nível do equipamento em si, quer ao dos cenários operacionais nos quais têm vindo a ser empregues. Portugal apresenta-se como um país em que as atividades agropecuárias têm uma predominância muito grande no uso do solo disponível e na economia. No entanto, a falta de estudos e da implementação de novas tecnologias continuam a ser fatores limitativo ao aumento de produtividade, do aproveitamento sustentável dos recursos disponíveis e do valor que a agricultura agrega à balança comercial nacional. O objetivo principal desta dissertação foi mostrar que é possível aplicar diversos novos métodos e técnicas, e mais especificamente UAV, ao cenário agrícola português. Para tal foi efetuada uma extensa pesquisa e selecionado um conjunto de estudos considerados relevantes e com potencial de serem adaptados e implementados em Portugal, englobando diversas culturas e atividades a elas associadas. Com este propósito e depois de os estudos escolhidos terem sido expostos e cuidadosamente analisados foi possível perceber que a aplicação de UAS na agricultura portuguesa seria uma grande mais-valia na medida em que poderia conduzir à poupança de diversos milhões de euros tanto no aumento de produtividade, assim como na redução dos custos em químicos e testes de campo que se estão a tornar obsoletos. Poderá também contribuir para a poupança de recursos naturais, nomeadamente de água

New strategies for row-crop management based on cost-effective remote sensors

Agricultural technology can be an excellent antidote to resource scarcity. Its growth has led to the extensive study of spatial and temporal in-field variability. The challenge of accurate management has been addressed in recent years through the use of accurate high-cost measurement instruments by researchers. However, low rates of technological adoption by farmers motivate the development of alternative technologies based on affordable sensors, in order to improve the sustainability of agricultural biosystems. This doctoral thesis has as main objective the development and evaluation of systems based on affordable sensors, in order to address two of the main aspects affecting the producers: the need of an accurate plant water status characterization to perform a proper irrigation management and the precise weed control. To address the first objective, two data acquisition methodologies based on aerial platforms have been developed, seeking to compare the use of infrared thermometry and thermal imaging to determine the water status of two most relevant row-crops in the region, sugar beet and super high-density olive orchards. From the data obtained, the use of an airborne low-cost infrared sensor to determine the canopy temperature has been validated. Also the reliability of sugar beet canopy temperature as an indicator its of water status has been confirmed. The empirical development of the Crop Water Stress Index (CWSI) has also been carried out from aerial thermal imaging combined with infrared temperature sensors and ground measurements of factors such as water potential or stomatal conductance, validating its usefulness as an indicator of water status in super high-density olive orchards. To contribute to the development of precise weed control systems, a system for detecting tomato plants and measuring the space between them has been developed, aiming to perform intra-row treatments in a localized and precise way. To this end, low cost optical sensors have been used and compared with a commercial LiDAR laser scanner. Correct detection results close to 95% show that the implementation of these sensors can lead to promising advances in the automation of weed control. The micro-level field data collected from the evaluated affordable sensors can help farmers to target operations precisely before plant stress sets in or weeds infestation occurs, paving the path to increase the adoption of Precision Agriculture techniques

Trenutni status i perspektiva primjene daljinskih istraživanja u upravljanju poljoprivrednim usjevima

Knowledge of the spatial distribution of agricultural crops and crop rotation is necessary for the understanding of the farming practices concerning the long-term sustainability of agricultural production. Agricultural crops are increasingly subject to drought due to the effects of global climate change, and the same is true for Croatia due to the constant rise in mean annual temperatures and uneven rainfall distribution. Remote sensing methods have proven to be superior in the detection and monitoring of drought compared to conventional methods of observation from meteorological stations. Information on the condition of crops in the early stages of development indicates potential irregularities in the development of agricultural crops. The objective of this paper is to provide a perspective for the application of remote sensing in crop management using state-of-the-art methods. Analysis of the possible implementation of these methods in Croatia was performed on a macro- and micro-level. Spatial classification, cropland suitability multicriteria analysis, drought assessment, weed detection and crop density calculation were evaluated according to the necessary equipment and data processing segments. Remote sensing application in crop management offers a potential basis for better crop management both at the macro-level for land use planning and at the micro-level for family farms.Poznavanje prostorne raspodjele poljoprivrednih usjeva i plodoreda neophodno je za razumijevanje poljoprivredne prakse za dugoročnu održivost poljoprivredne proizvodnje. Poljoprivredni usjevi su sve više izloženi suši zbog učinaka globalnih klimatskih promjena, a isto vrijedi i za Hrvatsku zbog stalnog porasta srednjih godišnjih temperatura i neujednačenoj količini padalina. Metode daljinskog istraživanja pokazale su se superiornima u otkrivanju i praćenju suše u usporedbi s konvencionalnim metodama promatranja s meteoroloških postaja. Podaci o stanju usjeva u ranim fazama razvoja ukazuju na potencijalne nepravilnosti u razvoju poljoprivrednih usjeva. Cilj ovog rada je pružiti perspektivu primjene daljinskog istraživanja u upravljanju usjevima korištenjem najsuvremenijih metoda. Analiza moguće primjene ovih metoda u Hrvatskoj provedena je na makro i mikro razini. Prostorna klasifikacija, multikriterijska analiza pogodnost usjeva, procjena suše, otkrivanje korova i izračun gustoće usjeva analizirani su u odnosu na potrebnu opremu i segmente obrade podataka. Primjena daljinskog istraživanja u upravljanju usjevima nudi potencijalnu osnovu za bolje upravljanje usjevima kako na makro razini za planiranje uporabe zemljišta, tako i na mikro razini za obiteljska poljoprivredna gospodarstva

Intelligent thermal image-based sensor for affordable measurement of crop canopy temperature

Crop canopy temperature measurement is necessary for monitoring water stress indicators such as the Crop Water Stress Index (CWSI). Water stress indicators are very useful for irrigation strategies management in the precision agriculture context. For this purpose, one of the techniques used is thermography, which allows remote temperature measurement. However, the applicability of these techniques depends on being affordable, allowing continuous monitoring over multiple field measurement. In this article, the development of a sensor capable of automatically measuring the crop canopy temperature by means of a low-cost thermal camera and the implementation of artificial intelligence-based image segmentation models is presented. In addition, we provide results on almond trees comparing our system with a commercial thermal camera, in which an R-squared of 0.75 is obtained.This research was funded by the Agencia Estatal de Investigación (AEI) under project numbers: AGL2016-77282-C3-3-R, and PID2019-106226-C22 AEI/https://doi.org//10.13039/501100011033. FPU17/05155, FPU19/00020 have been granted by Ministerio de Educación y Formación Profesional. The authors would like to acknowledge the support of Miriam Montoya Gómez in language assistance