The coffee sector is working towards sector-wide commitments for sustainable production Yet, knowledge of where coffee is cultivated and its environmental impact remains limited, in part due to the challenges of mapping coffee using satellite remote sensing We recognize the urgency to capitalize on recent technological advances to improve remote sensing methods and generate more accurate, reliable, and scalable approaches to coffee mapping In this study, we provide a systematic review of satellite-based approaches to mapping coffee extent, which produced 43 articles in the peer-reviewed and gray literature We outline key considerations for employing effective approaches, focused on the need to balance data affordability and quality, classification complexity and accuracy, and generalizability and site-specificity We discuss research opportunities for improved approaches by leveraging the recent expansion of diverse satellite sensors and constellations, optical/Synthetic Aperture Radar data fusion approaches, and advances in cloud computing and deep learning algorithms We highlight the need for differentiating between production systems and the need for research in important coffee-growing geographies By reviewing the range of techniques successfully used to map coffee extent, we provide technical recommendations and future directions to enable accurate and scalable coffee maps

Review of Remote Sensing Methods to Map Coffee Production Systems

The objective of this study was to evaluate the growth and yield of macadamia nut (Macadamia integrifolia) cultivars in an intercropped system with irrigated coffee (Coffea arabica). The experiment was carried out in a completely randomized design with ten replicates. Six macadamia cultivars, from which three Brazilian (IAC 4-12B, IAC 4-20, and IAC 9-20) and three Hawaiian (HAES 344, HAES 660, and HAES 816) ones were used. In the first four years of production, evaluations were done for: plant height, canopy and stem diameter, number of nuts per plant, nut average weight, almond medium weight, nut production per plant, recovery rate, and almond production per plant. The Brazilian cultivars, especially IAC 4-20, showed a lower height, but with a larger canopy diameter. The Brazilian cultivars are more productive, among which IAC 4-12B is outstanding.

/pdf/crescimento-e-produtividade-de-nogueira-macadamia-em-3il6ixt43v.pdf

Crescimento e produtividade de nogueira-macadâmia em consórcio com cafeeiro arábica irrigado

A cafeicultura e uma das principais culturas agricolas do Brasil e realizar o mapeamento e monitoramento desta cultura e fundamental para conhecer sua distribuicao espacial. Porem, mapear estas areas utilizando imagens de Sensoriamento Remoto nao e uma tarefa facil. Sendo assim, este trabalho foi realizado com o objetivo de comparar o uso de diferentes variaveis e algoritmos de classificacao para o mapeamento de areas cafeeiras. O trabalho foi desenvolvido em tres areas diferentes, que sao bastante significativas na producao de cafe. Foram utilizados 5 algoritmos de aprendizagem de maquinas e 7 combinacoes de variaveis: espectrais, texturais e geometricas, associadas ao processo de classificacao. Um total de 105 classificacoes foram realizadas, 35 classificacoes para cada uma das areas. As classificacoes que nao usaram variaveis espectrais nao resultaram em bons indices de acuracia. Nas tres areas, o algoritmo que apresentou as melhores acuracias foi o Support vector machine, com acuracia global de 85,33% em Araguari, 87% em Carmo de Minas e 88,33% em Tres Pontas. Os piores resultados foram encontrados com o algoritmo Random Forest em Araguari, com acuracia global de 76,66% e com o Naive Bayes em Carmo de Minas e Tres Pontas, com 76% e 82% de acerto. Nas tres areas, variaveis texturais, quando associadas as espectrais, melhoraram a acuracia da classificacao. O SVM apresentou o melhor desempenho para as tres areas

/pdf/algoritmos-de-aprendizagem-de-maquina-e-variaveis-de-1tnwr1z069.pdf

Algoritmos de aprendizagem de máquina e variáveis de sensoriamento remoto para o mapeamento da cafeicultura

________________________________________________________ 13 RESUMEN __________________________________________________________ 15 LISTA DE FIGURAS __________________________________________________ 17 LISTA DE TABELAS __________________________________________________ 21 LISTA DE SIGLAS ____________________________________________________ 25 1 INTRODUÇÃO ___________________________________________________ 27 2 REVISÃO BIBLIOGRÁFICA _________________________________________ 31 2.1 A evolução da cafeicultura no Brasil ___________________________________ 31 2.2 As regiões cafeeiras abrangidas nesse estudo ___________________________ 32 2.2.1 A região Sul de Minas Gerais _________________________________________________________35 2.2.2 A região Cerrado Mineiro _____________________________________________________________36 2.3 A diferenciação do café por meio da certificação _________________________ 38 2.3.1 Os sistemas de certificação voltados a questões socioambientais aplicados na cafeicultura brasileira ___________________ ___________________________________________________________________38 2.3.2 O sistema de certificação orgânica _____________________________________________________39 2.3.3 O sistema de certificação Fair Trade ou Comércio Justo ___________________________________40 2.3.4 O sistema de certificação Utz Kapeh ___________________________________________________41 2.3.5 O sistema de Certificação Socioambiental Rainforest Alliance da RAS _______________________42 2.3.6 O sistema de certificação Café do Cerrado ______________________________________________46 2.3.7 O crescimento da certificação da cafeicultura ____________________________________________48 2.4 O sistema de Certificação Socioambiental da RAS _______________________ 49 2.4.1 A norma __________________________________________________________________________49 2.4.2 A acreditação das certificadoras _______________________________________________________53 2.4.3 A rotulagem ____ ___________________________________________________________________54

/pdf/impactos-socioambientais-da-certificacao-rainforest-alliance-47rzdxtifk.pdf

Impactos socioambientais da certificação Rainforest Alliance em fazendas produtoras de café no Brasil

Agrometeorological monitoring of coffee lands has conventionally been performed in the field using data from land-based meteorological stations and field surveys to observe crop conditions. More recent studies use satellite images, which assess large areas at lower costs. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor of the Earth satellite provides free images with high temporal resolution and vegetation specific products, such as the MOD13, which provides the Normalized Difference Vegetation Index (NDVI) processed in advanced. The objective of this study was to evaluate the relation between the NDVI spectral vegetation index and the meteorological and water balance variables of coffee lands of the south of Minas Gerais in order to obtain statistical models of this relationship. The study area is located in the municipality of Tres Pontas, Minas Gerais, Brazil. The statistical models obtained demonstrate a significant negative correlation between the NDVI and water deficit. NDVI values under 70% may represent a water deficit in the coffee plants. The models developed in this study could be used in the agrometeorological monitoring of coffee lands in the south of Minas Gerais.

/pdf/modis-images-for-agrometeorological-monitoring-of-coffee-2hoci8d5ph.pdf

Modis images for agrometeorological monitoring of coffee areas

Coffee is one of Brazilian most important cash crops due to the incomes generated by exportation. Southern Minas Gerais State represents approximately half of the total national production, although the greatest expansion of the crop has been observed in the western part of the state (“Triângulo Mineiro” and “Alto Paranaiba” regions). As a requirement for future planning, it is important to establish efficient methodologies to map and monitor these lands, with the possibility of an easier periodical updating of the information. In this work geotechnologies were used to evaluate changes, in space and time, of areas occupied by coffee plantations in Minas Gerais. Land use maps of study areas selected in the main producing regions of the state were generated for the years 2000 and 2003 using the GIS SPRING and Landsat images. The results of the quantitative comparison of these maps indicated different behaviours for the regions evaluated. In Sao Sebastiao do Paraiso and Machado, countries (south of Minas Gerais), a decrease of the areas occupied by coffee was observed, whereas in Tres Pontas, increased. In Patrocinio, western part of the state, the area occupied by the crop remained unaltered. Remote sensing and GIS were efficient in the evaluation of the spatial-temporal dynamics of coffee lands of Minas Gerais, providing a greater understanding of the different environments and information that can support regional land use planning.

Geothecnologies in the assessment of land use changes in coffee regions of the state of minas gerais in brazil

Avaliação de áreas cafeeiras no município de Campo do Meio em Minas Gerais, utilizando imagens CBERS e TM-LANDSAT

O objetivo deste trabalho foi fazer uma avaliacao espaco temporal das regioes cafeeiras de Machado e Patrocinio no estado de Minas Gerais, utilizando tecnicas de geoprocessamento e dados de sensores remotos. Mapas de uso da terra dos anos 2000 e 2003 dessas duas areas foram gerados com auxilio do software SPRING. Por intermedio do cruzamento dos dados percebeu-se que as culturas cafeeiras nesses dois ambientes tiveram comportamentos diferentes. Em Machado, o parque cafeeiro teve um pequeno decrescimo de cerca de 2% entre os anos avaliados, porem, percebe-se uma renovacao do parque, ja que existem cerca de 7% de areas novas sendo plantadas e 9% de areas sendo podadas ou retiradas da producao. Ja em Patrocinio, a area total de cafe plantada nao foi alterada, mas a area de cafe em producao aumentou significativamente, tendo provavelmente provocado um aumento tambem significativo na producao da regiao.

/pdf/dinamica-da-ocupacao-de-areas-cafeeiras-de-minas-gerais-3661ghwgwc.pdf

Dinâmica da ocupação de áreas cafeeiras de Minas Gerais utilizando geotecnologias.

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Geothecnologies in the assessment of land use changes in coffee regions of the state of minas gerais in brazil

Avaliação de áreas cafeeiras no município de Campo do Meio em Minas Gerais, utilizando imagens CBERS e TM-LANDSAT

Dinâmica da ocupação de áreas cafeeiras de Minas Gerais utilizando geotecnologias.