<p dir="ltr">This study introduces a methodology wherein daily values are linearly interpolated to achieve uniform temporal resolution across various data sets, including spectral and environmental information. This approach facilitates further analysis using machine learning techniques to estimate biomass. The proposed Best Friend Frame (B.F.F.) data set integrates Unmanned Aerial Systems (UAS) data, weather data, weather indices, soil hydrological group classifications, and topographic information. Two different biomass estimations were created to enhance versatility: one averaged per management practice and another averaged per physical experimental plot size. Additionally, SuperDove satellite data were combined with identical environmental data as that of the UAS.</p><p dir="ltr">UAS flights were conducted at the ACRE field in 2022 and 2023. The UAS data were captured at a height of 30 meters, yielding a ground sample distance of 2 cm/pixel per flight. Satellite data were sourced from the Planet SuperDove product. The images were processed using Crop Image Extraction (CIE) and calibrated with Vegetation Index Derivation (VID). Spatial resolution was defined as the experimental plot size per year per crop type (soybean or corn). Topographic data were derived from Indiana LiDAR data, and soil information was obtained from the USDA SSURGO dataset.</p><p dir="ltr">The B.F.F. framework can be utilized with various models to identify which environmental inputs influence biomass accumulation throughout the growing season.</p>

The purpose of this study was to develop and field test an approach based upon soft systems methodology for assessing constraints and anxieties faced by farmers utilizing recession farming. The approach in this study was based on soft systems methodology with the intent of constructing root-definitions for recession farming systems. The field testing of the approach utilized three recession farming systems in northeast Thailand. The root-definitions obtained using this approach, characterized two of the recession farming systems as capitalistic using an intensive, high input mode of production with limited land and labor. The third system was characterize as subsistent agriculture with few inputs. It was concluded that the approach developed in this study accurately identified constraints and differences between recession farming systems. The rich picture developed from the farmer's information was adequate to construct the root-definitions. It is recommended that this approach be tested in another region, using indigenous personnel trained to conduct group interviews.

Grazing by domestic livestock is one of the primary ways by which humans have modified landscapes. At low stocking rates livestock grazing can modify vegetation community composition, but at high stocking rates grazing can also reduce vegetation productivity and initiate soil erosion, leading to land degradation. The country of Iceland has undergone severe land degradation over the past 1100 years, with over half of the former vegetation cover being lost, and the remainder having depleted productivity. This work focuses upon the role that grazing by domestic livestock played in this degradation, and how the interactions between farm management, vegetation cover and climate affected grazing patterns in space and time. The aims of the research were achieved by constructing an environmental simulation model, called Búmodel, which allowed a cross-disciplinary approach that integrated landscape ecology, environmental archaeology and historical analysis. Búmodel was loosely coupled with GIS so that spatially based model inputs and outputs could be displayed and analysed in map form. The purpose of Búmodel was to predict spatial and temporal patterns of vegetation biomass production and utilisation (through grazing and hay-making) with a view to commenting on vegetation degradation in the pre-modern period (pre-1900 AD). The model was parameterised using contemporary and historical Icelandic agricultural data. Model validation was undertaken using sensitivity tests and comparison with data from an independent grazing experiment in the north of Iceland. Búmodel was then applied to two contrasting study areas: Vestur- Eyjafjallahreppur, a farming community on the south coast of Iceland, and Hofstaðir, a farm estate in the north east of the country, situated inland by Lake Mývatn. These applications demonstrated the importance of farm management in avoiding land degradation and in ameliorating the impact of climate. They also established the usefulness of Búmodel as a tool for the investigation of human and environmental interactions in Iceland.

A Dissertation submitted to the Faculty of Science, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Science. Johannesburg, 2016. / The economy of Bokoni was centred on farming, with terrace agriculture playing a fundamental role in the construction and location of village sites. This dissertation examined the recursive relationship between soil chemistry and site location at three Bokoni sites: Doornkop, Khutwaneng and Kranskloof. These sites represent the three different phases of occupation in Bokoni. Analysis focused on the correlation of Ca, Mg, K, P, NH4, NO3, CEC and %C to the site contexts. At a macro scale there are substantial similarities with regards to the geology and the soil chemistry; suggesting a strong preference for locating village sites on relatively nutrient rich clay soils. On a more localised scale chemical analysis of the different contexts of these sites (i.e. domestic areas, central enclosures, terraces and non-archaeological areas) explored the agricultural potential of the soil in the various areas. These analyses showed a distinct difference in agricultural potential of soils in stone walled areas. This profile was the result of the nutrient contribution from the underlying soils in combination with either enrichment at the time of occupation, or the ongoing influence of the stone walled structures on the soils. The enrichment of soil in residential sites, whether intentional or accidental, could explain why Bokoni villagers continually reused sites during the earlier part of the sequence, before violence repeatedly disrupted settlement, and thus choice of settlement location, in the area. / LG2017

Submitted by Angela Maria de Oliveira (amolivei@uepg.br) on 2018-07-24T12:17:51Z No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Denise do Rocio Maciel.pdf: 4875592 bytes, checksum: 80eb2f6302787108c4d5c5db66be9efc (MD5) / Made available in DSpace on 2018-07-24T12:17:51Z (GMT). No. of bitstreams: 2 license_rdf: 811 bytes, checksum: e39d27027a6cc9cb039ad269a5db8e34 (MD5) Denise do Rocio Maciel.pdf: 4875592 bytes, checksum: 80eb2f6302787108c4d5c5db66be9efc (MD5) Previous issue date: 2018-03-12 / O uso de sistemas agrícolas que consideram a dimensão espacial atribuída pelo uso de Informações Geográfica (IG) traz benefícios a agricultura. Aplicações que usam IG se deparam com dificuldades de usabilidade provenientes pela expansão de seu uso, crescimento da quantidade de dados geográficos, advento da internet, a diversidade e aumento no número de usuários. Dentre as necessidades de pesquisa relacionada a sistemas agrícolas se tem o desenvolvimento de método de avaliação que considere especificidades das informações geográficas. A fim de solucionar a problemática, este trabalho apresenta o UsaGeo, método para avaliação de usabilidade em sistemas agrícolas. O método apresenta resultados quantitativos e qualitativos, exige um especialista em usabilidade e acessibilidade para sua execução e é composto por quatro fases. O UsaGeo foi aplicado em quatro casos de estudo e constatou-se que identificou problemas relacionados as informações geográficas que dificilmente seriam detectados por métodos recorrentemente citados na literatura. A aplicação do UsaGeo na agricultura permite a criação de produtos de software com maior usabilidade, aumenta a taxa de adoção desses sistemas por parte dos agricultores, incrementa produtividade para setor e gera acréscimo na expansão e exploração do uso de informações geográficas. / The use of agricultural systems that consider the spatial dimension attributed by the use of Geographic Information (GI) brings benefits to agriculture. Applications that use GI face usability difficulties due to the expansion of its use, growth in the amount of geographic data, the advent of the Internet, diversity and increase in the number of users. Among the research needs related to agricultural systems is the development of an evaluation method that considers the specificities of the geographic information. In order to solve the problem, this work presents the UsaGeo, method for usability evaluation in agricultural systems. The method presents quantitative and qualitative results, requires a specialist in usability and accessibility for its execution and consists of four phases. UsaGeo was applied in four case studies and it was found that it identified problems related to the geographical information that would be difficult to be detected by methods recurrently cited in the literature. The application of UsaGeo in agriculture allows the creation of software products with greater usability, increases the rate of adoption of these systems by farmers, increases productivity for the sector and generates an increase in the expansion and exploitation of the use of geographical information..

abstract: Design is a fundamental human activity through which we attempt to navigate and manipulate the world around us for our survival, pleasure, and benefit. As human society has evolved, so too has the complexity and impact of our design activities on the environment. Now clearly intertwined as a complex social-ecological system at the global scale, we struggle in our ability to understand, design, implement, and manage solutions to complex global issues such as climate change, water scarcity, food security, and natural disasters. Some have asserted that this is because complex adaptive systems, like these, are moving targets that are only partially designed and partially emergent and self-organizing. Furthermore, these types of systems are difficult to understand and control due to the inherent dynamics of "wicked problems", such as: uncertainty, social dilemmas, inequities, and trade-offs involving multiple feedback loops that sometimes cause both the problems and their potential solutions to shift and evolve together. These problems do not, however, negate our collective need to effectively design, produce, and implement strategies that allow us to appropriate, distribute, manage and sustain the resources on which we depend. Design, however, is not well understood in the context of complex adaptive systems involving common-pool resources. In addition, the relationship between our attempts at control and performance at the system-level over time is not well understood either. This research contributes to our understanding of design in common-pool resource systems by using a multi-methods approach to investigate longitudinal data on an innovative participatory design intervention implemented in nineteen small-scale, farmer-managed irrigation systems in the Indrawati River Basin of Nepal over the last three decades. The intervention was intended as an experiment in using participatory planning, design and construction processes to increase food security and strengthen the self-sufficiency and self-governing capacity of resource user groups within the poorest district in Nepal. This work is the first time that theories of participatory design-processes have been empirically tested against longitudinal data on a number of small-scale, locally managed common-pool resource systems. It clarifies and helps to develop a theory of design in this setting for both scientific and practical purposes. / Dissertation/Thesis / Doctoral Dissertation Environmental Social Science 2018

Smallholder livestock keeping and agriculture systems in the sub-Saharan Africa (SSA) seem to be caught into poverty traps, in as much as they cannot any longer provide ecosystem services on which local communities depend for their survival. I used a regime shifts framework to carry out a thorough assessment of these two case studies in arid and semi-arid lands and smallholder by identifying relevant traps and alternate desirable regimes. Using systems analysis and modelling, I drew casual loop diagrams of the two case studies, which helped me to identify the feedback loops that maintain the systems in undesirable traps and the external driving forces of change. A set of interventions points or leverage points were identified to change the dynamics of the systems and shift them towards more desirable regimes. Essentially, a structural change of both systems is called for if sustainable livelihoods in the rural areas of the SSA are to be seriously envisaged. Human capital investments present the main opportunity for facilitating escape from poverty by transforming farmers to non-farmers and livestock keepers to non-livestock keepers.

Thesis (M.Soc.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008. / Full text also available online. Scroll down for electronic link.

abstract: One of the greatest 21st century challenges is meeting the needs of a growing world population expected to increase 35% by 2050 given projected trends in diets, consumption and income. This in turn requires a 70-100% improvement on current production capability, even as the world is undergoing systemic climate pattern changes. This growth not only translates to higher demand for staple products, such as rice, wheat, and beans, but also creates demand for high-value products such as fresh fruits and vegetables (FVs), fueled by better economic conditions and a more health conscious consumer. In this case, it would seem that these trends would present opportunities for the economic development of environmentally well-suited regions to produce high-value products. Interestingly, many regions with production potential still exhibit a considerable gap between their current and ‘true’ maximum capability, especially in places where poverty is more common. Paradoxically, often high-value, horticultural products could be produced in these regions, if relatively small capital investments are made and proper marketing and distribution channels are created. The hypothesis is that small farmers within local agricultural systems are well positioned to take advantage of existing sustainable and profitable opportunities, specifically in high-value agricultural production. Unearthing these opportunities can entice investments in small farming development and help them enter the horticultural industry, thus expand the volume, variety and/or quality of products available for global consumption. In this dissertation, the objective is three-fold: (1) to demonstrate the hidden production potential that exist within local agricultural communities, (2) highlight the importance of supply chain modeling tools in the strategic design of local agricultural systems, and (3) demonstrate the application of optimization and machine learning techniques to strategize the implementation of protective agricultural technologies. As part of this dissertation, a yield approximation method is developed and integrated with a mixed-integer program to estimate a region’s potential to produce non-perennial, vegetable items. This integration offers practical approximations that help decision-makers identify technologies needed to protect agricultural production, alter harvesting patterns to better match market behavior, and provide an analytical framework through which external investment entities can assess different production options. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2017

Orientador: Enrique Ortega Rodriguez / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-19T16:40:26Z (GMT). No. of bitstreams: 1 Takahashi_Fabio_D.pdf: 40746551 bytes, checksum: 8bd4dcf5734dccf888245cfdc1891ae1 (MD5) Previous issue date: 2012 / Resumo: Este estudo utilizou a metodologia emergética para avaliar 39 culturas agrícolas de manejo convencional e 15 culturas agrícolas de manejo orgânico com o objetivo de traçar um perfil da sustentabilidade de alguns produtos da agricultura brasileira. Todas as avaliações foram arquivadas em um banco de dados que pode ser acessado em uma página web dinâmica que foi desenvolvida para divulgar os resultados deste trabalho e permitir que o usuário crie suas próprias avaliações emergéticas de sistemas agrícolas. Na primeira etapa da análise dos resultados, os sistemas foram agrupados em 5 categorias; a) oleaginosas b) grãos c) frutas d) hortaliças, raízes e tubérculos e) hortaliças orgânicas. Técnicas de mineração de dados foram utilizadas para interpretar todo o conjunto de resultados com o objetivo de encontrar relações entre os indicadores emergéticos que classificassem os sistemas de acordo com o manejo e em categorias sugeridas por especialistas de acordo com os valores dos índices emergéticos. A avaliação emergética mostra o melhor desempenho das culturas orgânicas quando comparadas com as culturas de manejo convencional. A mineração de dados se mostrou uma ferramenta eficiente para avaliação de todos os resultados encontrados nesse trabalho, pois foi possível encontrar relações dos indicadores emergéticos que descrevem o comportamento dos sistemas e os classificam em grupos encontrados pela clusterização (sistemas convencionais e sustentáveis; sistemas orgânicos e sustentáveis; sistemas insustentáveis) e também em categorias de acordo com os indicadores emergéticos propostos por especialistas / Abstract: This study used the emergy methodology for assessing 39 conventional crops and 15 organic crops in order to draw a profile of sustainability of some products of Brazilian agriculture. All evaluations were stored in a database that can be accessed in a dynamic web page developed to disseminate the results of this study and allow the user to create his own evaluation of agricultural systems. In the first step of analysis of the results, the systems were grouped into 5 categories: a) oil plants b) fruits c) grains d) vegetables and tubers e) organic. Data mining techniques were used to interpret the whole set of results in order to find relationships among the emergy indicators to classify the systems according to the management and groups established by experts in accordance with the values of emegy indices. The emergy evaluation shows a better performance of organic crops compared with conventional crops. Data mining has proven an effective tool for evaluation of all results found in this study. It was possible to find relations of emergy indicators that describe the behavior of systems and classify them into groups found by clustering ( conventional and sustainable systems; organic and sustainable systems; unsustainable systems) and also into categories according to emergy indicators proposed by experts / Doutorado / Engenharia de Alimentos / Doutor em Engenharia de Alimentos