Application of remote sensing data for environmental monitoring in semiarid mountain areas : a case study in Yemen Mountains

Remote sensing has been proved to be a very useful technology in the investigation of surface parameters and environment monitoring when large areas is covered. In this paper, the complementarily between two optical remote sensing data Landsat TM and Radar Sat (OEM) were used to estimate and describes the affected surface temperature by elevation, slope and aspect of the land surface, in additional to effect of solar radiation on surface temperature and relation of elevation to wind speed. The two important factors related· temperature difference near surface (dT) function is the relationship between wind speed and the surface temperature, and the change of the temperature difference near surface dT function for each image was investigated. The information in this paper provides good background for Remote Sensing applications for monitoring the environment especially in the mountainous areas. An application for computing temperature map over Sana'a Basin in central mountainous in Yemen is presented

Decision support system for estimating actual crop evapotranspiration using remote sensing, GIS and hydrological models

Evapotranspiration (ET) is a major component of the hydrologic cycle and its accurate estimation is essential for hydrological studies. In the past, various estimation methods have been developed for different climatologically data, and the accuracy of these methods varies with climatic conditions. Therefore, Remote Sensing and GIS techniques with Hydrological Models are used to develop a friendly decision support system (DSS) for estimating of the Actual Crop ET. For given data availability and climatic conditions, the developed model estimates ET. The ET estimation methods are based on combination theory, radiation, temperature, and Remote Sensing methods; the model selects the best ET estimation method based on ASCE rankings. In order to evaluate the DSS, various tests were conducted with different data availability conditions for three climatological studies at the stations CAMA, NWRA, and Al-Irra. The decisions made by the model exactly matched the ASCE rankings. For the two climatic stations NWRA, and CAMA, ET values were estimated by all applicable methods using this models was developed for ERDAS Imagine and Arc-GIS software and were compared with the Penman-Monteith ET estimates, which were taken as the standard. Based on the weighted average standard error of the estimate, the modified SEBAL , and Biophysical model methods ranked first, respectively, for areas near the CAMA and NWRA stations. The SEBALID ranked first for Al-Irra station. The DSS model is developed as user tool for estimating ET under different data availability and climatic conditions

Evapotranspiration estimation using a normalized difference vegetation index transformation of two satellites data in arid mountain areas

Evapotranspiration (ET) was estimated using a normalized difference vegetation index (NDVI) of satellite data on central Yemen Mountains. A procedure was developed which equated the index to crop coefficients. Evapotranspiration estimates for fields for three dates of Landsat Thematic Mapper data were highly correlated with ground estimates. Service area estimates using landsat Thematic Mapper (TM) and NOAA Advanced Very High Resolution Radiometer (AVHRR) data agreed well with estimates based on National Water Resources Authority (NWRA) gauging station data. Comparisons of ET results with traditional ET models show good agreement. Sensitivity analyses show that the model is accurate even without atmospheric correction

Comparison of regional evapotranspiration using NOAA-AVHRR and LANDSAT-TM images: a case study in an arid area in the sana’a basin, republic of Yemen

Estimating evapotranspiration (ET) is of the highest importance for understanding and eventually intervening in the water cycle of natural systems. ET is one of the major factors influencing climate change, at local, regional and global levels, and net primary productivity models, but it is difficult to measure and predict. Remote sensing cannot provide a direct measurement of Evapotranspiration (ET), but it can provide a reasonably good estimate of the Evaporative Fraction (EF), defined as the ratio of ET and available energy. In this study, a surface energy balance method, which combines meteorological observations with spectral data derived from remote sensing measurements, was used to estimate the ET. The modified (SEBAL) Surface Energy Balance Algorithm for Land has been applied to data from the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA-14 satellite and from the Landsat Thematic Mapper (TM) for the estimation of the surface albedo, surface temperature (T 0), normalized difference vegetation index (NDVI), net radiation, soil heat flux and sensible heat flux to estimate Evapotranspiration and surface conditions, on 1st June 1998 for the Sana'a Basin in Yemen, which is an arid and semi-arid region, with a mountainous terrain condition. The actual ET was computed from field data during the satellite overpass and integrated for 24-h on a pixel-by-pixel basis for daily ET distribution and compared to the value obtained from the AVHRR and TM data. Being a mountainous basin, an attempt has been made to consider terrain effects in estimating net radiation by adding DEM information. As a result, a daily ET map over the Basin was used to analyze some observation data, such as radiation and surface temperature, and was compared with estimated data. The results showed that AVHRR gives some reasonable values; however, the TM data gives better results since the spatial resolution of TM is better than that of AVHRR

Estimating of regional evapotranspiration for arid areas using LANDSAT thematic mapper images data : a case study for grape plantation

In west southern mountains of Yemen grape crop has been considered as an important cash crop. Thus, water management for grape plantation in arid areas has become an important aspect to ensure a food produce. Except alfalfa, the water used by grape trees is greater than that of most crops. Conventional Point measurement of water needed by one Grape plantation cannot provide accurate estimate for all the orchards in a county. In fact, over a vast area, the point measurements technique is costly and unpractical. In this paper, a new approach is suggested to estimate detailed water requirement by grape plantation at a county scale. The proposed technique used LANDSAT-TM data and a modified SEBAL (Surface Energy Balance Algorithm for Land) to estimate evapotranspiration over grape plantation in wadi asser- Sana’a basin central Yemen mountains. The modified SEBAL model estimates evapotranspiration (ET) using the energy balance equations, for which the surface temperature and reflectance data from TM image data and metrological data from local weather station. The model calculates net radiation, soil and sensible heat flux, and evapotranspiration. Comparing the calculated results with those observed in point measurements in the field of Grape and alfalfa from the period 1995 to 1998 proves that the modified SEBAL also provides an accurate information. The average relative error between estimated and observed ET is 11.6%, and the average absolute error is 0.43 mm/day. This proposed technique has the potential to provide guidelines for various users, including government agencies on how to evaluate current water-usage schemes

The approaches for oasis desert vegetation information abstraction based on medium - Resolution Lansat TM image: A case study in desert wadi Hadramut Yemen

This paper present two issues namely; firest is oasis desert brightness inversion correction, and secondly, the classifying method of oasis desert vegetation through remote sensing image data., Oasis desert brightness inversion is known reduce the classification accuracy in medium-resolution images. In this study, the radiation correction and the brightness inversion adjustment models was analysis. The model's parameters were obtained from the image pixel values. The result of brightness inversion correction shows that the model can correct oasis desert brightness inversion. After brightness inversion correction, the vegetation's pixel value in brightness inversion area is similar with the pixel value of vegetation in other area. Brightness inversion correction increases classification accuracy. In the second part of this study, three methods are studied to derive oasis desert vegetations information, including vegetation index method, back propagation neural network method, and texture method. Three methods' classification accuracies are calculated and appraised. And a conclusion is drawn, which is the texture classification method is a good classification method. The accuracy of texture classification method can reach up to 82.31%

Estimation of evapotranspiration using fused remote sensing image data and energy balance model for improving water management in arid area

Remote sensing has proved to be very useful in the investigation of vegetation and hydrological monitoring, especially when studying vast areas. In this paper, the complement between two optical remote sensing data (Landsat TM and NOAA-AVHRR) and a Digital Elevation Model (DEM) is used to estimate hydrological parameters based on derived surface reflectance. These parameters which are used in the Modified Soil Energy Balance Algorithm for Land (M-SEBAL) model have been used to estimate net radiation, soil heat flux, sensible heat flux and evapotranspiration (ET) for Sana'a Basin in Yemen. The area is known for arid and semi-arid weather conditions with undulating topography. Image data from AVHRR on-board NOAA satellites with a large areal coverage, good temporal and spectral resolution are found to be very useful in generating some parameters required for the above process. However, the data have poor spatial resolution. On the other hand, image data from the Thematic Mapper on-board the Landsat satellite, with a high spatial and spectral resolution should be able to provide values for the parameters involved, but the area coverage is significantly reduced. This study has been carried out, using a data fusion technique in order to exploit the respective advantages of these two disparate sources of image data. A general framework is then proposed to generate ET maps for and and semi-arid regions. This is achieved by means of multi-temporal, multiresolution remote sensing data. Taking into account topographic effects, an attempt has also been made to incorporate DEM information for estimating the net radiation of the areas involved. An application for computing a daily ET map over Sana'a Basin, Yemen is presented. As a result, a daily ET map generated from meteorological observations was compared with estimated ET data simulated from remote sensing data. In conclusion, data from both remote sensing sources give reasonable values with the result from the TM being better than those obtained from the AVHRR. This is attributed to the differences in spatial resolution, in which TM data is higher than AVHRR. The fusion of the two shows improves spatial detail whilst maintaining the spectral signature close to the original

Estimation of evapotranspiration with modified SEBAL model using Landsat-TM and NOAA-AVHRR images in arid mountains area

This study examines the method for determining surface energy namely surface energy balance algorithm for land (SEBAL). This particular method utilized the combination of meteorological observations with information extracted from remote sensing data. The modified SEBAL model using data from Landsat TM and NOAA- A VHRR sensors, has been used to estimate net radiation, soil heat flux, sensible heat flux and ETfor Sana 'a Basin in Yemen. The area is known for arid and semi-arid weather condition with undulating topographic. Remote sensing data for year 95, 96 and 1998 were used as a primary image for this study. Actual ET was computed during satellite overpass and integrated for 24-h on pixel-by-pixel basis for daily ET distribution. Due to the topographic effects, an attempt has also been made to incorporated DEM information for estimating the net radiation. As a result, a daily ET map generated from metrological observation was compared with estimated ET data simulated from remote sensing data. In conclusion, data from both remote sensing give reasonable values with result from TM are better compare to those of AVHRR due to difference in spatial resolution, which TM data a higher spatial resolution than AVHRR