This study developed a model based on Support Vector Machines (SVM) and Normalized Difference Vegetation Index (NDVI) time series to classify citrus areas in Álamo, Veracruz, Mexico. MODIS images (MOD13Q1, 250 m resolution) from 2003 to 2022 were used, processed using radiometric correction, noise filtering, and temporal harmonization. Training areas were classified into four categories: citrus, natural vegetation, grasslands, and urban areas, using 3,759 time series, 50 % of which were positive for citrus. The SVM model (RBF kernel: γ = 0.1, C = 10) achieved an accuracy of 91.4 % using 5-fold cross-validation, with 88% success in citrus and 93.9 % in non-citrus samples. The results showed an average NDVI of 0.74 for citrus, distinguishable from weeds (0.87), although with challenges in small plots due to spatial resolution. The estimates coincided with official data (SIACON) in 2021 (...

This study developed a model based on Support Vector Machines (SVM) and Normalized Difference Vegetation Index (NDVI) time series to classify citrus areas in Álamo, Veracruz, Mexico. MODIS images (MOD13Q1, 250 m resolution) from 2003 to 2022 were used, processed using radiometric correction, noise filtering, and temporal harmonization. Training areas were classified into four categories: citrus, natural vegetation, grasslands, and urban areas, using 3,759 time series, 50 % of which were positive for citrus. The SVM model (RBF kernel: γ = 0.1, C = 10) achieved an accuracy of 91.4 % using 5-fold cross-validation, with 88% success in citrus and 93.9 % in non-citrus samples. The results showed an average NDVI of 0.74 for citrus, distinguishable from weeds (0.87), although with challenges in small plots due to spatial resolution. The estimates coincided with official data (SIACON) in 2021 (...

This research studies a Mexican SME dedicated to manufacturing ecological cleaning and personal care products. A logistics approach allowed us to analyze its supply chain and identify areas of opportunity. The methodology included data collection, supply chain analysis, logistics evaluation, management, review of warehouse logistic indicators, and the SCOR model’s implementation at three process levels (superior, configuration, and elements), each evaluated by key performance indicators. Each indicator was divided into performance attributes (flexibility, assets, speed of service, reliability in compliance, and costs). The DNA Logistik tool was applied to detect the maturity level and risk of logistics operations. As a result, the relevance of five logistics functions in the supply chain (supply, production, storage, transportation, and omnichannel sales) was identified. In addition, t...

This research studies a Mexican SME dedicated to manufacturing ecological cleaning and personal care products. A logistics approach allowed us to analyze its supply chain and identify areas of opportunity. The methodology included data collection, supply chain analysis, logistics evaluation, management, review of warehouse logistic indicators, and the SCOR model’s implementation at three process levels (superior, configuration, and elements), each evaluated by key performance indicators. Each indicator was divided into performance attributes (flexibility, assets, speed of service, reliability in compliance, and costs). The DNA Logistik tool was applied to detect the maturity level and risk of logistics operations. As a result, the relevance of five logistics functions in the supply chain (supply, production, storage, transportation, and omnichannel sales) was identified. In addition, t...