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Soils are at the crossroads of many existential issues that humanity is currently facing. Soils are a finite resource that is under threat, mainly due to human pressure. There is an urgent need to map and monitor them at field, regional, and global scales in order to improve their management and prevent their degradation. This remains a challenge due to the high and often complex spatial variability inherent to soils. Over the last four decades, major research efforts in the field of pedometrics have led to the development of methods allowing to capture the complex nature of soils. As a result, digital soil mapping (DSM) approaches have been developed for quantifying soils in space and time. DSM and monitoring have become operational thanks to the harmonization of soil databases, advances in spatial modeling and machine learning, and the increasing availability of spatiotemporal covariates, including the exponential increase in freely available remote sensing (RS) data. The latter boosted research in DSM, allowing the mapping of soils at high resolution and assessing the changes through time. We present a review of the main contributions and developments of French (inter)national research, which has a long history in both RS and DSM. Thanks to the French SPOT satellite constellation that started in the early 1980s, the French RS and soil research communities have pioneered DSM using remote sensing. This review describes the data, tools, and methods using RS imagery to support the spatial predictions of a wide range of soil properties and discusses their pros and cons. The review demonstrates that RS data are frequently used in soil mapping (i) by considering them as a substitute for analytical measurements, or (ii) by considering them as covariates related to the controlling factors of soil formation and evolution. It further highlights the great potential of RS imagery to improve DSM, and provides an overview of the main challenges and prospects related to digital

The Organic Law of Humanitarian Support, published in the Official Registry, Supplement 229, dated June 22, 2020, among other stipulations, instituted measures to face the consequences derived from the health crisis caused by the coronavirus or also called, covid-19. Within this regulation, specifically in its article 19, the figure of the Special Emerging Labor Contract is created, a new type of contract that is added to those already existing in the Ecuadorian Labor Code. Its purpose was to reactivate the economy, improve production in the country and guarantee employment, recognizing rights for both workers and employers. The general objective is to critically review the legal figure of the special emerging labor contract, in order to assess whether said contractual figure has fulfilled the purpose for which it has been created. Points such as the origin and need for the special emerging contract were analyzed; its characteristics, its violation of the principle of job stability and its advantages and disadvantages. A qualitative approach has been applied with scientific methods such as historical-logical, analytical and inductive, and this work was concluded, establishing the advantages and disadvantages of this new contractual modality in labor matters., La Ley Orgánica de Apoyo Humanitario, publicada en el Registro Oficial, Suplemento 229, de fecha 22 de junio de 2020, entre otras estipulaciones, instituyó medidas para afrontar las consecuencias derivadas de la crisis sanitaria producida por el coronavirus o también denominado, covid-19. Dentro de esta normativa, específicamente, en su artículo 19, se crea la figura del Contrato Especial Emergente de Trabajo, nueva modalidad de contrato que se suma a las ya existentes en el Código de Trabajo ecuatoriano. Su finalidad fue reactivar la economía, mejorar la producción en el país y garantizar el empleo, reconociendo derechos, tanto a los trabajadores, como a los empleadores. El objetivo general planteado es revisar críticamente la figura jurídica del contrato especial emergente de trabajo, a fin de evaluar si dicha figura contractual ha cumplido la finalidad para la cual, ha sido creada. Se analizaron puntos como el origen y necesidad del contrato especial emergente; sus características, su vulneración al principio de estabilidad laboral y sus ventajas y desventajas. Se ha aplicado un enfoque cualitativo con métodos científicos tales como, el histórico-lógico, el analítico y el inductivo, y, se concluyó este trabajo, estableciendo las ventajas y desventajas de esta nueva modalidad contractual en materia laboral.

The CBR for its acronym in English (California Bearing Ratio), is an important factor in the design of pavements, and in the evaluation of pavements. However, the execution of the test represents a high cost and time. For the determination of the CBR in situ, the ASTM standard and other authors have established correlations with the field test called DCP by its acronym for Dynamic Cone Penetration Test; allowing to relate the CBR in situ with the DCP value obtained in the field. However, since there is no relationship between these parameters applied to the city of Cuenca, and even to other parts of Ecuador, the use of existing correlations between the two parameters has been stopped. Therefore, the determination of the CBR is considered important, based on a correlation with the DCP test applied to soils in the city of Cuenca, and it is proposed to establish it through a statistical analysis of linear regression and validate it based on existing correlations in the literature. The present work gets two correlations, between the DCP and the CBR in situ with a determination coefficient R2 of 0.911; and between the DCP, the dry field density, and the CBR, obtaining an adjusted coefficient of determination R2 of 0.930. The correlation established between the CBR and DCP was compared with the expressions proposed in the specialized literature, and it was determined that it maintains a similar behavior, establishing that the correlation obtained is valid, and a fast and economical way to obtain the parameter CBR for different soils in our city.

Crop yield forecasting allows farmers to make decisions in advance to improve farm management and logistics during and after harvest. In this sense, crop yield potential maps are an asset for farmers making decisions about farm management and planning. Although scientific efforts have been made to determine crop yields from in situ information and through remote sensing, most studies are limited to evaluating data from a single date just before harvest. This has a direct negative impact on the quality and predictability of these estimates, especially for logistics. This study proposes a methodology for the early prediction of tomato yield using decision tree ensembles, vegetation spectral indices, and shape factors from images captured by multispectral sensors on board an unmanned aerial vehicle (UAV) during different phenological stages of crop development. With the predictive model developed and based on the collection of training characteristics for 6 weeks before harvest, the tomato yield was estimated for a 0.4 ha plot, obtaining an error rate of 9.28.