Iranian Journal of Remote Sensing & GIS

The Effect of Atmospheric Moisture on the Estimation of the Temperature Inversion Characteristics from MODIS Images

H Kachar; M.R Mobasheri; A.A Abkar; M Rahimzadegan

Volume 7, Issue 2 , November 2015, , Pages 35-53

Abstract

Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion ... Read More Increase of temperature with height in the troposphere is called temperature inversion. Parameters such as strength and depth are characteristics of temperature inversion. Inversion strength is defined as the temperature difference between the surface and the top of the inversion and the depth of inversion is defined as the height of the inversion from the surface. The common approach in determination of these parameters is field measurements by Radiosonde. On the other hand the Radiosonde data are too sparse, so using satellite images is essential for modeling the temperature inversion. Necessary condition for the temperature inversion modeling using satellite images, examine the relationship between the brightness temperature difference with the temperature inversion strength and depth of the resulting data is Radiosonde. Temperature inversion phenomenon is common in Tehran. So Mehrabad airport weather station was selected as the 1st study area. Then correlation coefficients between Brightness temperature differences of different band pairs and the inversion depth and strength collected by Radiosonde were calculated. The results showed weak linear correlation. This could be due to the change of the atmospheric water vapor content and the relatively weak temperature inversion strength and depth occurred in Tehran. Proving this hypothesis is an innovation in the present work, in continuation of this research, the factors increasing the linear correlation coefficient was investigated. Due to the presence of deeper and stronger temperature inversion in Kermanshah, this region was chosen as the second studied region. The calculated correlation coefficients increased for Kermanshah all due to increase in the strength and depth of the temperature inversion in this region. Knowing that the amount of water vapor in the atmosphere in winter is less than warm seasons, Tehran and Kermanshah data were divided into two all seasons and cold seasons.Increase of correlation coefficients for both Tehran and Kermanshah in the cold season verifies the effect of atmospheric water content. For instance, the correlation coefficient between BT7.2-BT11 with strength and depth of inversion for Kermanshah for all season are 0.51 and 0.70 respectively. This for cold season was boosted to 0.78 and 0.85.

A Method for Detectors Stripe Noise Correction in Landsat5 TM Images

M.R Mobasheri; E Amraie

Volume 7, Issue 4 , November 2015, , Pages 45-60

Abstract

Detectors noises in satellite images are seen as either vertical or horizontal stripes. The directions of these stripes depend on the imaging technique (Pushbroom or Wiskbroom). The main reasons in appearance of stripe noises in TM images are; lack of matching between detectors, unsuitable calibration ... Read More

Introducing a Method for Replacement of MODIS Measured Radiance Fluxes Using Modified CRTM Model at the Local Scale

Volume 6, Issue 2 , August 2014

Abstract

In this study, a method for replacing MODIS measured flux densities using CRTM is introduced. For this, the Radiosonde measured temperature profiles in Bandar-abbass synoptic station along with night time flux densities measure by MODIS sensor on board of Aqua platform for the deep water region in the ... Read More

Snow covered surfaces show enormous variations in time and consequently need to be monitored using images with relatively high temporal resolution. For this MODIS sensor on board of Terra/Aqua is suitable. Different parameters affect the accuracy of Snow

Volume 6, Issue 1 , April 2014

Abstract

Snow covered surfaces show enormous variations in time and consequently need to be monitored using images with relatively high temporal resolution. For this MODIS sensor on board of Terra/Aqua is suitable. Different parameters affect the accuracy of Snow Covered Surface estimation (SCS) where the surface ... Read More

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Author = Mobasheri, M.R

The Effect of Atmospheric Moisture on the Estimation of the Temperature Inversion Characteristics from MODIS Images

Abstract

A Method for Detectors Stripe Noise Correction in Landsat5 TM Images

Abstract

Introducing a Method for Replacement of MODIS Measured Radiance Fluxes Using Modified CRTM Model at the Local Scale

Abstract

Snow covered surfaces show enormous variations in time and consequently need to be monitored using images with relatively high temporal resolution. For this MODIS sensor on board of Terra/Aqua is suitable. Different parameters affect the accuracy of Snow

Abstract