Detector Based Calibration of a Portable Imaging Spectrometer for CLARREO Pathfinder Mission

The Climate Absolute Refractivity and Reflectance Observatory (CLARREO) Pathfinder (CPF) mission is being developed to demonstrate SI-traceable retrievals of reflectance at unprecedented accuracies for global satellite observations. An Independent Calibration of the CPF sensor using the Goddard Laser for Absolute Measurement of Radiance (GLAMR) is planned to allow validation of CPF accuracies. GLAMR is a detector-based calibration system relies on a set of NIST-calibrated transfer radiometers to assess the spectral radiance from the GLAMR sphere source to better than 0.3 % (k=2). The current work describes the calibration of the Solar, Lunar Absolute Reflectance Imaging Spectroradiometer (SOLARIS) that was originally developed as a calibration demonstration system for the CLARREO mission and is now being used to assess the independent calibration being developed for CPF. The methodology for the radiometric calibration of SOLARIS is presented as well as results from the GLAMR-based calibration of SOLARIS. The portability of SOLARIS makes it capable of collecting field measurements of earth scenes and direct solar and lunar irradiance similar to those expected during the on-orbit operation of the CPF sensor. Results of SOLARIS field measurements are presented. The use of SOLARIS in this effort also allows the testing protocols for GLAMR to be improved and the field measurements by SOLARIS build confidence in the error budget for GLAMR calibrations. Results are compared to accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval

Maxmin convolutional neural networks for image classification

Convolutional neural networks (CNN) are widely used in computer vision, especially in image classification. However, the way in which information and invariance properties are encoded through in deep CNN architectures is still an open question. In this paper, we propose to modify the standard convo- lutional block of CNN in order to transfer more information layer after layer while keeping some invariance within the net- work. Our main idea is to exploit both positive and negative high scores obtained in the convolution maps. This behav- ior is obtained by modifying the traditional activation func- tion step before pooling. We are doubling the maps with spe- cific activations functions, called MaxMin strategy, in order to achieve our pipeline. Extensive experiments on two classical datasets, MNIST and CIFAR-10, show that our deep MaxMin convolutional net outperforms standard CNN

SECOND GLOBAL REPORT ON GASTRONOMY TOURISM

Traditional Mexican cuisine is a living cultural expression with a long tradition, age-old skills, culinary techniques and ancestral ingredients. Mexican gastronomy is one of the fruits of the sea and the earth; from wild and ield-grown origins, as well as Pre-Hispanic ingredients enriched by the mixing with European traditions. The ive regions include the north, centre, high plateau, south and southeast in which every cuisine is unique, and is characterized and supported by the ecosystem and culture. In 2010, Mexican Gastronomy was declared an Intangible Cultural Heritage of Humanity by UNESCO, and became one of the irst cuisines around the world to achieve this distinction. The basis of the Mexican gastronomy is native corn; therefore, its increasing volume is a fundamental issue in the context of the globalization of food and the introduction of genetically modiied maize

CHALLENGES FOR THE NEW RURALITY IN A CHANGING WORLD. PROCEEDINGS FROM THE 7TH INTERNATIONAL CONFERENCE ON LOCALIZED AGRI-FOOD SYSTEMS

The rise of wine tourism in Queretaro is part of a larger process of economic and social restructuring of rural areas in central Mexico. In addition to the regulation and provisioning services that rural areas provide to society, it highlights the importance of cultural services such as tourism that are highly appreciated by the inhabitants of large cities. This opens the way to a new distribution of the territory where the natural, cultural and symbolic capital are appropriated in many different ways. Multifunctionality of territory and pluriactivity of actors reveal the growing complexity of disputes over local resources.The State of Queretaro in central Mexico is a major producer of cheese and wine, whose production is associated with the legacy of Spanish colonization. It is an agro-industrial complex and tourism destination, located an hour and a half from Mexico City, the fourth largest megacity in the world. Taking advantage of the location, wineries and the local Ministry of Tourism developed the Wine and Cheese Route, which because of its originality is shown as an effective tool for local marketing. Wineries that make up the route are heterogeneous, ranging from multinational companies to small sized family businesses. All wineries contribute to the creation of a bucolic imaginary about the territory, which attracts thousands of visitors. The main beneficiaries of tourism are the largest producers of wine, which are better able to offer leisure services

Uncertainties for Pre- and Post-Launch Radiometric Calibration of Imaging Spectrometers for Multi-Sensor Applications

An important aspect to using imaging spectrometer data is the radiometric characterization and calibration of the sensors and validation of their data products and doing so with error budgets with known traceability. The radiometric accuracy of a given sensor is important for demonstrating the expected quality of data from the sensor. Known traceability allows data from multiple sensors to be directly comparable as will become more important in the near future with the expected launches of multiple imaging spectrometers from multiple countries, agencies, and commercial entities. The current work describes the state of pre- and post-launch radiometric absolute and relative uncertainties and their role in harmonising on-orbit data. Examples of prelaunch uncertainties based on the calibration of EnMAP and the calibration planned for the CLARREO Pathfinder Mission are presented highlighting recent work in the area of detector-based approaches using tunable laser sources. Post-launch calibration approaches for Pathfinder, EnMAP, CHIME, and DESIS including traditional vicarious calibration methods and the challenges of working with commercial data are presented. The vicarious calibration discussion relies on the example of the recently-available RadCalNet data to describe typical methods and challenges that will be faced when harmonising data between imaging spectrometers as well as with multispectral sensors

Turismo rural: ¿una oportunidad para la conservación del bosque de niebla?

El mundo contemporáneo experimenta intensos cambios que se debaten entre un proyecto de desarrollo económico unificado y las diversas crisis globales que enfrenta el planeta, derivadas de las intervenciones humanas sobre la naturaleza. Dichas crisis han afectado especialmente a los espacios rurales de los países periféricos, como por ejemplo, los latinoamericanos (FAO, 2014a), por lo que muchos gobiernos nacionales han encabezado la reestructuración productiva del campo como alternativa económica. Dentro de las principales reestructuraciones económicas del espacio rural se encuentran aquellos cambios basados en el principio de diversificación económica y productiva del campo que consisten en procesos de especialización territorial para la satisfacción de las nuevas necesidades del mercado (Arias, 2005). Debido ello emergen nuevas actividades productivas, que sustituyen o complementan las actividades rurales tradicionales. La integración de dichas actividades en las estructuras productivas se basa en la multifuncionalidad del territorio y la pluri actividad de los actores sociales (De Grammont, 2008), cuyos objetivos centrales son la revalorización del capital rural y la agregación de valor a las actividades tradicionales.Desde un enfoque interpretativo se discute el despliegue del turismo hacia los espacios forestales como una tendencia de las actividades recreativas en el contexto de la globalización. El objetivo fue analizar la relación entre turismo sostenible y bosque de niebla, desde la perspectiva de la conservación. De esta manera se concibe al turismo como un componente de modelos de gestión forestal sostenible, a partir de las dimensiones económica, social y ambiental. Para ello se esboza un modelo consistente en sistemas de información, ordenamiento territorial y comunicación. Se concluye que el turismo es una actividad ambivalente para los bosques de niebla, toda vez que entraña riesgos y oportunidades que pueden ser reducidos mediante procesos de ordenamiento, planificación y regulación

NASA Report on Cal/Val Activities

NASA report on Calibration/Validation activities, including recent launches of ICESat-2, GEDI and OCO-3

BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

Multimodal representation learning is gaining more and more interest within the deep learning community. While bilinear models provide an interesting framework to find subtle combination of modalities, their number of parameters grows quadratically with the input dimensions, making their practical implementation within classical deep learning pipelines challenging. In this paper, we introduce BLOCK, a new multimodal fusion based on the block-superdiagonal tensor decomposition. It leverages the notion of block-term ranks, which generalizes both concepts of rank and mode ranks for tensors, already used for multimodal fusion. It allows to define new ways for optimizing the tradeoff between the expressiveness and complexity of the fusion model, and is able to represent very fine interactions between modalities while maintaining powerful mono-modal representations. We demonstrate the practical interest of our fusion model by using BLOCK for two challenging tasks: Visual Question Answering (VQA) and Visual Relationship Detection (VRD), where we design end-to-end learnable architectures for representing relevant interactions between modalities. Through extensive experiments, we show that BLOCK compares favorably with respect to state-of-the-art multimodal fusion models for both VQA and VRD tasks. Our code is available at https://github.com/Cadene/block.bootstrap.pytorch

Characterization Approaches to Place Invariant Sites on SI-Traceable Scales

The effort to understand the Earth's climate system requires a complete integration of remote sensing imager data across time and multiple countries. Such an integration necessarily requires ensuring inter-consistency between multiple sensors to create the data sets needed to understand the climate system. Past efforts at inter-consistency have forced agreement between two sensors using sources that are viewed by both sensors at nearly the same time, and thus tend to be near polar regions over snow and ice. The current work describes a method that would provide an absolute radiometric calibration of a sensor rather than an inter-consistency of a sensor relative to another. The approach also relies on defensible error budgets that eventually provides a cross comparison of sensors without systematic errors. The basis of the technique is a model-based, SI-traceable prediction of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The effort effectively works to characterize the sites as sources with known top-of-atmosphere radiance allowing accurate intercomparison of sensor data that without the need for coincident views. Data from the Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), and Moderate Resolution Imaging Spectroradiometer (MODIS) are used to demonstrate the difficulties of cross calibration as applied to current sensors. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The radiance comparisons lead to significant differences created by the specific solar model used for each sensor. The paper also proposes methods to mitigate the largest error sources in future systems. The results from these historical intercomparisons provide the basis for a set of recommendations to ensure future SI-traceable cross calibration using future missions such as CLARREO and TRUTHS. The paper describes a proposed approach that relies on model-based, SI-traceable predictions of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The basis of the method is highly accurate measurements of at-sensor radiance of sufficient quality to understand the spectral and BRDF characteristics of the site and sufficient historical data to develop an understanding of temporal effects from changing surface and atmospheric conditions