We have developed a simple photogrammetric method to identify heterogeneous areas of irrigated olive groves and vineyard crops using a commercial multispectral camera mounted on an unmanned aerial vehicle (UAV). By comparing NDVI, GNDVI, SAVI, and NDRE vegetation indices, we find that the latter shows irrigation irregularities in an olive grove not discernible with the other indices. This may render the NDRE as particularly useful to identify growth inhomogeneities in crops. Given the fact that few satellite detectors are sensible in the red-edge (RE) band and none with the spatial resolution offered by UAVs, this finding has the potential of turning UAVs into a local farmer’s favourite aid tool.

EMIR, currently entering into its fabrication and AIV phase, will be one of the first common user instruments for the GTC, the 10 meter telescope under construction by GRANTECAN at the Roque de los Muchachos Observatory (Canary Islands, Spain). EMIR is being built by a Consortium of Spanish and French institutes led by the Instituto de Astrofisica de Canarias (IAC). EMIR is designed to realize one of the central goals of 10m class telescopes, allowing observers to obtain spectra for large numbers of faint sources in an time-efficient manner. EMIR is primarily designed to be operated as a MOS in the K band, but offers a wide range of observing modes, including imaging and spectroscopy, both long slit and multiobject, in the wavelength range 0.9 to 2.5 μm. It is equipped with two innovative subsystems: a robotic reconfigurable multislit mask and disperssive elements formed by the combination of high quality diffraction grating and conventional prisms, both at the heart of the instrument. The present status of development, expected performances, schedule and plans for scientific exploitation are described and discussed. The development and fabrication of EMIR is funded by GRANTECAN and the Plan Nacional de Astronomia y Astrofisica (National Plan for Astronomy and Astrophysics, Spain).

Páramo ecosystems harbor important biodiversity and provide essential environmental services such as water regulation and carbon sequestration. Unfortunately, the scarcity of information on their land uses makes it difficult to generate sustainable strategies for their conservation. The purpose of this study is to develop a methodology to easily monitor and document the conservation status, degradation rates, and land use changes in the páramo. We analyzed the performance of two nonparametric models (the CART decision tree, CDT, and multivariate adaptive regression curves, MARS) in the páramos of the Chambo sub-basin (Ecuador). We used three types of attributes: digital elevation model (DEM), land use cover (Sentinel 2), and organic carbon content (Global Soil Organic Carbon Map data, GSOC) and a categorical variable, land use. We obtained a set of selected variables which perform well with both models, and which let us monitor the land uses of the páramos. Comparing our results with the last report of the Ecuadorian Ministry of Environment (2012), we found that 9% of the páramo has been lost in the last 8 years.

Ecosystem valuation (EV) of soil resources is essential for understanding changes in environmental services in monetary terms. A lack of this information, which includes economic indices, hinders the optimal management of natural resources. This study evaluated the influence of changes in the edaphic ecosystem on the EV of the zone of influence of the Ozogoche and Atillo lake systems in Ecuador. The classification was carried out through spectral indices and support vector machines (SVMs), and the EV was determined through opportunity costs including environmental service provisioning and indirect use. The land use and EV classification methods were performed efficiently; the degradation trend was constant. The Modified Water Difference Index was the most efficient in the extraction of water bodies, with an accuracy of 91%. The SVMs algorithm, in recognizing coverage in general, had an overall accuracy of 85%. The adjustment made to the SVMs algorithm to improve the selection of hyperparameters was effective; a robust architecture of the algorithm in terms of automation was achieved. Between 2000 and 2020, moorland, water and wetland degraded by 19%, 2% and 3.4%, respectively. In 2000, the EV as a function of avoided CO₂ content was USD 8.00 × 10⁶; in 2010 and 2020, it was USD 6.00 × 10⁶ and USD 5.00 × 10⁶, respectively.

In the face of escalating global average temperatures, it is urgent to identify mechanisms that can significantly curtail the emission of greenhouse gases. The construction industry plays a pivotal role in shaping these emissions, rendering the selection of environmentally conscious materials indispensable in the imminent future. In this context, attention is drawn to an interesting material from an ecological point of view: straw. Abundant as a natural byproduct exhibiting remarkable thermal properties, straw emerges as a good candidate for sustainable edification. In the present work, an in situ study of its thermal resistance is carried out, and it is found that it allows stable interior temperatures. The apparent thermal conductivity is analyzed in relation to the orientation of its fibers in the same building, and its low conductivity compared with traditional construction materials is confirmed. The relevance of this work lies in the fact that the building studied contains walls with different fiber orientations in the same room, with the same ambiental conditions. This ensures that the different thermal behaviors are exclusively due to the orientation of the fibers. When considering both orientations of the fibers, different values of thermal conductivity are discerned. Conductivity decreases when the direction of the heat flow is perpendicular to the fibers. However, due to the inherent geometry of the bales, their overall thermal behavior ultimately proves comparable.

The scarcity of information that allows for understanding the importance of natural resources from an economic approach is often a limitation to establishing parameters related to environmental investment in conservation plans. This study proposes a methodology that allows for modeling the variability of páramo land uses and the EV of the Chambo-Ecuador sub-basin from bioeconomic monitoring that links the economic rent of páramo land uses with remote sensing tools and geographic information systems. Multilayer Perception, Markov Chains, and Automata Cells algorithms were efficient for the detection of land uses in páramo; the normalized differential humidity index was the most relevant variable to identify crops, showing that leaf properties and water stress are linked to crop yields in the Andean region. The páramo decreased by 13% between 2000 and 2010, increasing its degradation to 19% between 2010 and 2020. A 28% reduction is expected between 2000 and 2030; the EV between 2000 and 2020 was $2.86 × 108 and $2.59 × 108 respectively. In 2030, EV is expected to decrease to $2.48 × 108. Transitions in land use and EV are associated with productive dynamics, which decrease environmental services, such as water retention and carbon storage, intensifying changes in the ecosystem climate.