The objective of this work is the analysis of the sea surface temperature (SST), estimating of the NOAA / AVHRR data, near the Peruvian coast for their application in the determination of the thermal fronts and in the study of El Niño phenomenon. The study of area is location between the geographies coordinate, (90º W, 0ºS) left upper corner and (70º W, 20º S) right lower corner. The crude image data level 1b LAC and GAC from AVHRR sensor of the NOAA polar orbit satellite’s series has been derived of the NOAA archive active. The Pacha Ricaj software has been designed for read and display the crude image, inverse, geometric corrections execute, cloud filter and SST estimate. The resulting derives are the diary and monthly SST images. In the Peruvian coast, the SST is less in magnitude than off the coast. In this imagines has been observed many cloud over sea and land that have disa...

El Niño Southern Oscillation (ENSO) indices and satellite-recorded Normalized Difference Vegetation Index (NDVI) will be used to construct a drought onset prediction model for North Coast of Peru through a multiple linear regression. Monthly NDVI and ENSO indices anomaly data for the period July 1981 to December 2003 were used to develop the model. The objective of the work, first part, is to do a description of how and where the data are obtained and it does calculate their anomalies. NDVI anomaly time series, in the period 1981-2003 were compared with El Niño Southern Oscillation (ENSO) indices. A visual inspection of the anomalies plot shows a correlation in the 82-83 and 97-98 Niños. NDVI of the Loreto region in the jungle of Peru doesn’t show any change in relation to ENSO indixs.

In this work has been implemented the model of atmospheric correction denominated “Simplified Method for the Atmospheric Correction” (SMAC). It consists of determining the relation between the reflectance calculated on the top of the atmosphere and the reflectance calculated at the surface of the soil using mathematical algorithms of radiative transference, Rayleigh`s scattering, scattering of aerosols, and others. One has compared the values of reflectance in the top of the atmosphere and the reflectance of the surface of the ground, obtaining like result a linear relation of the these two amounts with a value of he slope equal to 1.44. The value of slope greater than 1 indicates that an acceptable atmospheric correction has been made. In order to validate the model has been obtained the values of the reflectance of the surface of the ground using the 5S model, obtaining a coefficie...

The objective of this work is the estimation of the temperature of the sea surface in the Eastern Pacific Ocean of the Southern Hemisphere from the images of the meteorological satellite of polar orbit NOAA-14 (National Administration of Atmospheric Oceanography). The study area ranges from the Peruvian coast, 70 ° W to 90 ° W of geographic longitude and from 2 ° S to 22 ° S of geographic latitude. This parameter will be applied in the determination of thermal fronts or fishing fronts. The original HRPT (High Resolution Picture Transmition) format image data is from January 1999. During the initial processing of the image data, the original HRPT format (16 bits) has been converted into another BURL format (Bradford University Research Limited) (10 bits) of interest to us. The threshold technique has been used on channels 1 and 5 for the removal of clouds. The size of the original ima...

The calibration of the original HRPT and LAC images, corresponding to channels 1 and 2 of the AVHRR sensor of the NOAA-14 satellite in polar orbit has been undertaken with the purpose of estimating the Normalized Difference Vegetation Index (NDVI) above Peru. The imagery data used were obtained from IMARPE, ABTEMA, INPE and SAA, and are in binary 16 bits per pixel format for the 5 channels. Reflectance images for channels 1 and 2 images have been obtained in 16 bits (data type: integers). Afterwards, the NDVI is obtained using an equation in which the information from the reflectance images is used. The imagery data product of the vegetation indices are obtained for every day from January to Febrary 1999. We pretend to obtain monthly and 10-day images to get an average NDVI using the method of compound máxima. Finally, we are preparing a time series for this parameter from January 1980 ...