Estimación del Factor C de la RUSLE en la microcuenca del rio Lodana, Ecuador, usando imágenes del satélite Sentinel 2

2020 ◽  
Vol ve2020 (2) ◽  
pp. 69-75
Author(s):  
Ángel Claudio Ruiz Vélez ◽  
◽  
Henry Antonio Pacheco Gil ◽  
Keyword(s):  
Del Rio ◽  
Factor C ◽  
Sentinel 2

scholarly journals Relación de firmas espectrales para la identificación de bosque seco en imágenes de satélite Sentinel 2, cuenca baja del río Chira, Región Piura

2020 ◽  
pp. 147
Author(s):  
C. Aldana ◽  
M. Revilla ◽  
J. Gonzales ◽  
Y. Saavedra ◽  
W. Moncada ◽  
...  
Keyword(s):  
Satellite Images ◽  
Dry Forest ◽  
Spectral Signature ◽  
Ecological State ◽  
Warm Climate ◽  
Spectral Signatures ◽  
Northern Peru ◽  
Del Rio ◽  
Sentinel 2

<p class="p1">El Niño phenomenon, droughts and the warm climate directly influence the good ecological state of the forests in the Piura Region. The objective is to relate the spectral signatures evaluated in the Sentinel-2 satellite images with the spectral signatures measured with the FieldSpec4 spectroradiometer, for the identification of dry forest in the lower basin of the Chira River, Piura región. The Sentinel-2 images corresponding to the 17MNR, 17MPR, 17MMQ, 17MNQ and 17MPQ tiles are pre-processed, mosaicked, resampled and cut with the SNAP software. Stacking of bands 2, 3, 4, 5, 6, 7, 8, 9, 11 and 12 generates a raster whose pixel reflectance values are related to their wavelengths. The classification of dry forest areas is done with the spectral signature measured with the FieldSpec4 spectroradiometer. The validation of the results is carried out by applying the non-parametric ANOVA and Mann-Whitney-Wilcoxon tests at four sampling points. The surface area of dry forest in the lower basin of the Chira River is 129 113.06 ha, which represents 3.8% of the total area of dry forest in northern Peru.</p>

scholarly journals Modelamiento hidráulico para el control y prevención de inundaciones mediante el uso de Hec-Ras 2d en la zona urbana del río Piura

2021 ◽  
Author(s):  
◽  
Gabriela Fiamma Alvarez Montero ◽  
Carlos Alvaro Moreno Cueva
Keyword(s):  
El Niño ◽  
El Nino ◽  
Del Rio ◽  
Sentinel 2

Los desastres ocasionados por las inundaciones son cada vez más comunes alrededor del mundo, tal como ocurre en la parte Occidental de América del Norte y Sur, debido a la presencia del Fenómeno “El Niño” (FEN), que provoca un aumento de las precipitaciones y caudales de los ríos provocando inundaciones. Por este motivo, en el presente trabajo se ha realizado la simulación numérica de inundación frente a eventos extremos como El Niño, con la finalidad de disminuir el área y nivel de inundación ante probables y distintos eventos en zonas cercanas a los cauces de ríos. Se ha empleado datos hidrológicos de caudales promedios y máximos instantáneos de un periodo de 40 años. Para la caracterización morfológica de la zona se ha empleado información de un modelo de elevación digital del terreno (DEM), obtenido del satélite SPOT-7, de resolución de 6x6m. La información hidrológica fue procesada mediante el método de Gumbel para obtener los caudales de simulación para periodos de retorno de 2, 5, 10, 50, 100 y 500 años. La modelación numérica fue realizada empleando HEC-RAS 5.0.7, con lo que se obtuvo el área de inundación para el FEN 2017 y se utilizó la imagen satelital SENTINEL-2 para validar el modelo. Asimismo, se modeló eventos extremos con periodos de retorno mayores a 10 años, ya que sus resultados son relevantes para la implementación de obras de protección ribereñas, en lugares estratégicos identificados por su mayor vulnerabilidad. Finalmente, dichas obras lograron mitigar el impacto generado al disminuir en un porcentaje el área inundada en la zona de estudio, desde la represa “Los Ejidos” hasta el puente Bolognesi en la provincia de Piura.

scholarly journals Towards the Assessment of Soil-Erosion-Related C-Factor on European Scale Using Google Earth Engine and Sentinel-2 Images

2021 ◽  
Vol 13 (24) ◽  
pp. 5019
Author(s):  
Dimitrios D. Alexakis ◽  
Stelios Manoudakis ◽  
Athos Agapiou ◽  
Christos Polykretis
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Spatial Scales ◽  
Google Earth ◽  
Vegetation Coverage ◽  
Time Step ◽  
Normalised Difference Vegetation Index ◽  
Google Earth Engine ◽  
Factor C ◽  
Sentinel 2

Soil erosion is a constant environmental threat for the entirety of Europe. Numerous studies have been published during the last years concerning assessing soil erosion utilising Remote Sensing (RS) and Geographic Information Systems (GIS). Such studies commonly employ empirical erosion models to estimate soil loss on various spatial scales. In this context, empirical models have been highlighted as major approaches to estimate soil loss on various spatial scales. Most of these models analyse environmental factors representing soil-erosion-influencing conditions such as the climate, topography, soil regime, and surface vegetation coverage. In this study, the Google Earth Engine (GEE) cloud computing platform and Sentinel-2 satellite imagery data have been combined to assess the vegetation-coverage-related factor known as cover management factor (C-factor) at a high spatial resolution (10 m) considering a total of 38 European countries. Based on the employment of the RS derivative of the Normalised Difference Vegetation Index (NDVI) for January and December 2019, a C-factor map was generated due to mean annual estimation. National values were then calculated in terms of different types of agricultural land cover classes. Furthermore, the European C-factor (CEUROPE) values concerning the island of Crete (Greece) were compared with relevant values estimated for the island (CCRETE) based on Sentinel-2 images being individually selected at a monthly time-step of 2019 to generate a series of 12 maps for the C-factor in Crete. Our results yielded identical C-factor values for the different approaches. The outcomes denote GEE’s high analytic and processing abilities to analyse massive quantities of data that can provide efficient digital products for soil-erosion-related studies.

Author response for "The NF‐κB transcription factor c‐Rel controls host defense against Citrobacter rodentium"

2019 ◽  
Author(s):  
Maik Luu ◽  
Rossana Romero ◽  
Jasmin Bazant ◽  
Elfadil Abass ◽  
Sabrina Hartmann ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Host Defense ◽  
Author Response ◽  
Citrobacter Rodentium ◽  
Factor C

Natural sesquiterpene lactones as inhibitiors of leukaemia-associated transcription factor c-Myb

Planta Medica ◽  
2010 ◽  
Vol 76 (12) ◽  
Author(s):  
C Schomburg ◽  
K Klempnauer ◽  
T Schmidt
Keyword(s):  
Transcription Factor ◽  
Sesquiterpene Lactones ◽  
Factor C

Role of the transcription factor c-Jun/AP–1 in response to β-Catenin signaling in the liver

2012 ◽  
Vol 50 (01) ◽  
Author(s):  
C Trierweiler ◽  
K Willim ◽  
HE Blum ◽  
P Hasselblatt
Keyword(s):  
Transcription Factor ◽  
Factor C

Acetylation of Myeloid-Specific Transcription Factor C/EBPα

2012 ◽  
Vol 224 (03) ◽  
Author(s):  
I Kuznetsova ◽  
K Welte ◽  
J Skokowa
Keyword(s):  
Transcription Factor ◽  
Specific Transcription Factor ◽  
Factor C
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