Search published articles


Showing 2 results for Remote Sensing.
Application of Energy Balance Model and Landsat TM Sensor Data for Evapotranspiration Estimation
N. Moshtagh, R. Jafari, S. Soltani , N. Ramezani,
Volume 19, Issue 73 (11-2015)
Abstract

Spatial estimation of evapotranspiration (ET) rates is essential for agriculture and water resources management. This study aimed to estimate ET v an ET estimation algorithm called Surface Energy Balance Algorithms for Land (SEBAL) and also by using TM June 2009 satellite data in Damaneh region of Isfahan province. To calculate the ET, all the energy balance components and related parameters including net radiation, surface albedo, incoming and emitting shortwave and longwave radiation, surface emissivity, soil heat flux, sensible heat flux, NDVI vegetation index, Leaf Area Index(LAI),  and surface temperature were extracted from the geometrically and radiometrically corrected TM images. Results showed that ET rate was about 7.2 mm day-1 in agricultural areas, which was almost equal to 6.99 mm day-1 extracted from the FAO Penman-Monteith method in the synoptic weather station of Daran. Results here indicate that the extraction of ET rate which is almost equal to plant water requirements from remote sensing data can be used in selecting appropriate plants for agriculture and rehabilitation purposes in extensive arid and semi-arid regions of Isfahan province where severe droughts and water shortage are major problems.


Estimation of Soil Moisture using Downscaling Soil Moisture Method of Microwave Sensor and the SMAR Model (A Case Study: Rafsanjan Plain)
M. Farokhi, H. Ansary, A. R. Faridhosseini,
Volume 24, Issue 1 (5-2020)
Abstract
Estimation of soil moisture at various temporal and spatial scales is a key to the strategic management of water resources. Satellite-based microwave observations have coarse spatial resolution despite widespread and continuous of the provision surface soil moisture (SSM). In this study, the SSM data from the Advanced Microwave Scanning Radiometer 2 (AMSR2) 25km resolution were used and these products were downscaled by three parameters retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) to 1km resolution. In the next step, the integration of the SSM downscaling model with SMAR model was used to monitor the root zone soil moisture(RZSM) in the study area (Rafsanjan plain). In order to evaluate the performance of the proposed method, the SSM and the soil profile moisture were measured at 10 points in the Rafsanjan plain. Comparison of AMSR2 25k SSM and downscaled SSM with the field measurement data showed that the mean of total stations for the correlation coefficient(R) was increased from 0.540 to 0.739 and the mean absolute error(MAE) and the root mean square(RMSE) were reduced from 0.039 and 0.040 to 0.018 and 0.020, respectively. Moreover, the results obtained from the validation of the RZSM values showed that the proposed method could estimate the RZSM with high accuracy and indicate the variations.
 


Page 1 from 1     

© 2024 CC BY-NC 4.0 | JWSS - Isfahan University of Technology

Designed & Developed by : Yektaweb