Background and aims: The quantitative retrieval of soil organic carbon (SOC) storage, particularly for soils with a large potential for carbon sequestration, is of global interest due to its link with the carbon cycle and the mitigation of climate change. However, complex ecosystems with good soil qualities for SOC storage are poorly studied. Methods: The interrelation between SOC and various vegetation remote sensing drivers is understood to demonstrate the link between the carbon stored in the vegetation layer and SOC of the top soil layers. Based on the mapping of SOC in two horizons (0–30 cm and 30–60 cm) we predict SOC with high accuracy in the complex and mountainous heterogeneous páramo system in Ecuador. A large SOC database (in weight % and in Mg/ha) of 493 and 494 SOC sampling data points from 0–30 cm and 30–60 cm soil profiles, respectively, were used to calibrate GPR models using Sentinel-2 and GIS predictors (i.e., Temperature, Elevation, Soil Taxonomy, Geological Unit, Slope Length and Steepness (LS Factor), Orientation and Precipitation). Results: In the 0–30 cm soil profile, the models achieved a R² of 0.85 (SOC%) and a R² of 0.79 (SOC Mg/ha). In the 30–60 cm soil profile, models achieved a R² of 0.86 (SOC%), and a R² of 0.79 (SOC Mg/ha). Conclusions: The used Sentinel-2 variables (FVC, CWC, LCC/C_ab, band 5 (705 nm) and SeLI index) were able to improve the estimation accuracy between 3–21% compared to previous results of the same study area. CWC emerged as the most relevant biophysical variable for SOC prediction.

The water of high Andean lakes is strongly affected by anthropic activities. However, due to its complexity this ecosystem is poorly researched. This study analyzes water quality using Sentinel-2 (S2) images in high Andean lakes with apparent different eutrophication states. Spatial and temporal patterns are assessed for biophysical water variables from automatic products as obtained from versions of C2RCC (Case 2 Regional Coast Color) processor (i.e., C2RCC, C2X, and C2X-COMPLEX) to observe water characteristics and eutrophication states in detail. These results were validated using in situ water sampling. C2X-COMPLEX appeared to be an appropriate option to study bodies of water with a complex dynamic of water composition. C2RCC was adequate for lakes with high transparency, typical for lakes of highlands with excellent water quality. The Yambo lake, with chlorophyll-a concentration (CHL) values of 79.6 ± 5 mg/m³, was in the eutrophic to hyper-eutrophic state. The Colta lake, with variable values of CHL, was between the oligotrophic to mesotrophic state, and the Atillo lakes, with values of 0.16 ± 0.1 mg/m³, were oligotrophic and even ultra-oligotrophic, which remained stable in the last few years. Automatic S2 water products give information about water quality, which in turn makes it possible to analyze its causes.

Background: Soil organic carbon (SOC) affects essential biological, biochemical, and physical soil functions such as nutrient cycling, water retention, water distribution, and soil structure stability. The Andean páramo known as such a high carbon and water storage capacity ecosystem is a complex, heterogeneous and remote ecosystem complicating field studies to collect SOC data. Here, we propose a multi-predictor remote quantification of SOC using Random Forest Regression to map SOC stock in the herbaceous páramo of the Chimborazo province, Ecuador.Results: Spectral indices derived from the Landsat-8 (L8) sensors, OLI and TIRS, topographic, geological, soil taxonomy and climate variables were used in combination with 500 in situ SOC sampling data for training and calibrating a suitable predictive SOC model. The final predictive model selected uses nine predictors with a RMSE of 1.72% and a R²of 0.82 for SOC expressed in weight %, a RMSE of 25.8 Mg/ha and a R²of 0.77 for the model in units of Mg/ha. Satellite-derived indices such as VARIG, SLP, NDVI, NDWI, SAVI, EVI2, WDRVI, NDSI, NDMI, NBR and NBR2 were not found to be strong SOC predictors. Relevant predictors instead were in order of importance: geological unit, soil taxonomy, precipitation, elevation, orientation, slope length and steepness (LS Factor), Bare Soil Index (BI), average annual temperature and TOA Brightness Temperature.Conclusions: Variables such as the BI index derived from satellite images and the LS factor from the DEM increase the SOC mapping accuracy. The mapping results show that over 57% of the study area contains high concentrations of SOC, between 150 and 205 Mg/ha, positioning the herbaceous páramo as an ecosystem of global importance. The results obtained with this study can be used to extent the SOC mapping in the whole herbaceous ecosystem of Ecuador offering an efficient and accurate methodology without the need for intensive in situ sampling.

El presente libro describe los aspectos técnicos-informáticos del desarrollo de un sistema web que se encargan del registro y gestión de encomiendas y boletos para clientes y administradores de las empresas de transporte interprovincial. La investigación realizada hace referencia a información necesaria con el fin de orientar al personal en la concepción, planteamiento, análisis, programación e instalación del sistema web. Es de notar que la redacción propia de este documento, está orientada a personal con conocimientos en sistemas y tecnologías de información, conocimientos de programación en entorno web, administradores de base de datos, responsables del mantenimiento e instalación del sistema en el servidor o servidores escogidos por el desarrollador. Se establecen tres fases importantes: La primera fase describe el aspecto de planificación, esta fase muestra los requerimientos del sistema, el estudio de factibilidad y todo lo referente a información básica para poder partir con el desarrollo de un sistema informático. La segunda fase detalla el cómo se realizará el proceso de desarrollo del sistema y como se ha llevado a cabo la planificación. La tercera fase es la implantación donde se especifica la instalación y la implementación del software. En conclusión, esta investigación proporciona a los responsables técnicos del sistema las herramientas necesarias que les permitan cumplir de manera eficiente las tareas de configuración del sistema y sean de apoyo conciso para cualquier cambio que se requiera en la etapa de producción del sistema.

High-Andean lakes are strategic freshwater ecosystems whose monitoring is essential for effective water resource management. However, their optical complexity limits the applicability of conventional methods. In this study, the water quality conditions of the Ozogoche lakes, located in Sangay National Park (PNS), were assessed using Sentinel-2 (S2), Landsat-8 OLI (L8), and Landsat-9 (L9) imagery processed with automated water products from the Case 2 Regional Coast Colour (C2RCC) processor, including the C2RCC, C2X-COMPLEX, and C2X versions. Comparisons between in situ chlorophyll-a (Chl-a) measurements and satellite-derived products confirmed that C2RCC achieved the lowest error (RMSE = 0.68 mg/m³). The multitemporal analysis (2016–2024) of Chl-a, total suspended solids (TSSs), and the diffuse attenuation coefficient (kd_z90max) revealed interannual variations. The results consistently classified the lakes as ultra-oligotrophic, providing an integrated perspective of their environmental quality. This study demonstrates the reliability of C2RCC products for monitoring high-Andean aquatic ecosystems and underscores the potential of remote sensing to overcome accessibility and cloud cover constraints, delivering valuable insights for the sustainable management of water resources in protected areas.

La calidad de las aguas de las lagunas altoandinas de Ecuador ha sido escasamente estudiada mediante teledetección debido a múltiples factores. Entre estos se destaca la dificultad de acceso, que limita la obtención de datos de campo necesarios para la calibración y validación de modelos. Adicionalmente, la alta nubosidad y el elevado riesgo de sunglint debido a la proximidad de estas lagunas a la línea ecuatorial, agravado por el viento frecuente, complican aún más la adquisición y uso de imágenes útiles. En este trabajo, se evaluó la concentración de clorofila-a en dos cuerpos de agua: la laguna oligotrófica de Atillo y la hipereutrófica de Yambo. Para ello, se compararon datos in situ con productos automáticos derivados de imágenes Sentinel-2, procesadas mediante cuatro métodos de corrección atmosférica: ACOLITE y las tres variantes de C2RCC (C2RCC, C2X y C2X-COMPLEX). Los resultados indican que, en Atillo, el mejor rendimiento se obtuvo con la versión estándar de C2RCC, seguida del modelo chl_oc2 implementado en ACOLITE. Por el contrario, en Yambo, los mejores estadísticos correspondieron a C2X-COMPLEX, seguido del modelo chl_re_bramich de ACOLITE. Si bien ACOLITE mostró resultados ligeramente inferiores en términos estadísticos en ambas lagunas, su capacidad para corregir eficazmente el sunglint lo convierte —junto con C2RCC— en una herramienta valiosa para el monitoreo de la eutrofización en estos sistemas. Cabe destacar que el uso de software libre (ACOLITE y C2RCC) e imágenes de acceso gratuito (Sentinel-2) facilita la implementación de programas de seguimiento temporal y análisis espacial de clorofila-a en estos lagos altoandinos, ofreciendo una alternativa viable para el análisis de su estado trófico.