Conference Paper

Estimation of Land Surface Temperature and Soil Moisture Levels of Umarkot District Sindh

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Abstract

Soil moisture plays an important role for understanding hydrology and climate. Soil moisture is a key variable in hydrological process, as the availability of moisture content in soil controls the mechanism between the land surface and atmospheric processes. Accurate estimation of soil moisture is crucial in environmental studies. Soil moisture can be measured by variety of remote sensing techniques. Combination of Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) can be used as indicator for surface soil moisture monitoring. For In situ measurements of soil moisture, the District Umarkot of Sindh was visited and a total of 24 samples were collected and analyzed. Soil moisture was calculated using the dry mass technique. Initial weight was carried out then the samples were heated at 105 °C for 18 hrs to calculate the dry weight. A relationship was be developed between ground and satellite based observed soil moisture measurements. Validation of satellite based and in situ measurement was carried out. It was found that maximum soil moisture for depths (0-15cm, 15-30cm, 30-45cm) is (19.80%, 19.20%, 21.20%) respectively.The relationship between satellite based soil moisture and in situ measurements was significant (R2>0.70).

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Monitoring evapotranspiration (ET) at large scales is important for assessing climate and anthropogenic effects on natural and agricultural ecosystems. This paper describes techniques used in evaluating ET with remote sensing, which is the only technology that can efficiently and economically provide regional and global coverage. Some of the empirical/statistical techniques have been used operationally with satellite data for computing daily ET at regional scales. The more complex numerical simulation models require detailed input parameters that may limit their application to regions containing a large database of soils and vegetation properties. Current efforts are being directed towards simplifying the parameter requirements of these models. Essentially all energy balance models rely on an estimate of the available energy (net radiation less soil heat flux). Net radiation is not easily determined from space, although progress is being made. Simplified approaches for estimating soil heat flux appear promising for operational applications. In addition, most ET models utilize remote sensing data in the shortwave and thermal wavelengths to measure key boundary conditions. Differences between the radiometric surface temperature and aerodynamic temperature can be significant and progress in incorporating this effect is evident. Atmospheric effects on optical data are significant, and optical sensors cannot see through clouds. This has led some to use microwave observations as a surrogate for optical data to provide estimates of surface moisture and surface temperature; preliminary results are encouraging. The approaches that appear most promising use surface temperature and vegetation indices or a time rate of change in surface temperature coupled to an atmospheric boundary layer model. For many of these models, differences with ET observations can be as low as 20% from hourly to daily time scales, approaching the level of uncertainty in the measurement of ET and contradicting some recent pessimistic conclusions concerning the utility of remotely sensed radiometric surface temperature for determining the surface energy balance.
Article
The relationship between remotely sensed surface temperature (T) and normalized difference vegetation index (NDVI) was studied over China with 10‐day composite Advanced Very High Resolution Radiometer (AVHRR) data at 8‐km spatial resolution. Results showed that the slope of the relationship between T and NDVI (T/NDVI slope) could be determined effectively during the growing season with a certain range of NDVI. The derived T/NDVI slope from image windows was significantly correlated to in situ soil moisture (r = 0.77, p<0.01). Based on determination of wet and dry edges of T/NDVI space and the relationship between soil moisture and the T/NDVI slope, a new approach was proposed to estimate distributed soil moisture. Using the approach, the derived soil moisture approximated the conditions recorded on the ground.
Article
Air temperature is an important descriptor of terrestrial environmental conditions across the earth. Standard meteorological observations generally provide reasonable descriptions of temporal variations in air temperature for the site sampled but may not describe the spatial heterogeneity typically encountered in this variable over larger land areas. If a reasonable estimate of spatial patterns of air temperature can be derived from satellite remote sensing, this pattern, in combination with the temporal precision of ground measurements, should significantly improve our knowledge of terrestrial environmental conditions.
Article
Remote sensing has been successfully used in the exploration of natural resources such as groundwater. Satellite data with different spatial, spectral and temporal characteristics have been evaluated for their potential use in groundwater detection in arid and semi-arid regions. However, distortions and noises caused by the presence of the atmosphere in the radiometric wave transmission become serious impediments for quantitative analysis and measure-ment work. In the present study, oasis and desert ecotone (ODE), a nonlinear ecological transitional belt, in Qira, Xinjiang Uyghur Autonomous Region of China was selected for this research. The ODE boundary was defined on the basis of widely collected information from the study area, including environ-mental, sociological and economic data. A model of groundwater level distribution using remote sensing (GLDRS), which empirically relates satellite sensor spectral radiance with groundwater level, is developed via in situ measurement and field examination of soil moisture and groundwater. Next, the second simulation of the satellite signal in the solar spectrum (6S), a code enabling simulations of radiative transfer process on the Sun–target–sensor path, is used to reduce uncertainties in the calculation of groundwater level. Then, groundwater level is evaluated using 6S atmospheric corrected and uncorrected Landsat-7 Enhanced Thematic Mapper (ETM)z images respectively along with isochronous meteorological information. Greater correspondence between field examined and satellite monitoring data is obtained from 6S atmospheric corrected image (correlation coefficient is 0.94) than from the uncorrected image (correlation coefficient is 0.83).
Article
Soil moisture is one of the few directly observable hydrological variables that has an important role in water and energy budgets necessary for climate studies. At the present time there is no practical approach to measuring and monitoring soil moisture at the frequency and scale necessary for these large scale analyses. Current and developing satellite systems have not addressed this important question. A solution utilizing passive microwave remote sensing is presented here and an optimum system, soil moisture estimation algorithms and a microwave simulation model are described.
Article
We hypothesize that the spatial and temporal variation in large-scale soil moisture patterns can be described by a small number of spatial structures that are related to soil texture, land use, and topography. To test this hypothesis, an empirical orthogonal function (EOF) analysis is conducted using data from the 1997 Southern Great Plains field campaign. When considering the spatial soil moisture anomalies, one spatial structure (EOF) is identified that explains 61% of the variance, and three such structures explain 87% of the variance. The primary EOF is most highly correlated with the percent sand in the soil among the regional characteristics considered, but the correlation with percent clay is largest if only dry days are analyzed. When considering the temporal anomalies, one EOF explains 50% of the variance. This EOF is still most closely related to the percent sand, but the percent clay is unimportant. Characteristics related to land use and topography are less correlated with the spatial and temporal variation of soil moisture in the range of scales considered.
Article
Spatially distributed estimates of evaporative fraction and actual evapotranspiration are pursued using a simple remote sensing technique based on a remotely sensed vegetation index (NDVI) and diurnal changes in land surface temperature. The technique, known as the triangle method, is improved by utilizing the high temporal resolution of the geostationary MSG-SEVIRI sensor. With 15 min acquisition intervals, the MSG-SEVIRI data allow for a precise estimation of the morning rise in land surface temperature which is a strong proxy for total daytime sensible heat fluxes. Combining the diurnal change in surface temperature, dTs with an interpretation of the triangular shaped dTs − NDVI space allows for a direct estimation of evaporative fraction. The mean daytime energy available for evapotranspiration (Rn − G) is estimated using several remote sensors and limited ancillary data. Finally regional estimates of actual evapotranspiration are made by combining evaporative fraction and available energy estimates. The estimated evaporative fraction (EF) and actual evapotranspiration (ET) for the Senegal River basin have been validated against field observations for the rainy season 2005. The validation results showed low biases and RMSE and R2 of 0.13 [−] and 0.63 for EF and RMSE of 41.45 W m− 2 and R2 of 0.66 for ET.
Article
We used a radiation-transfer equation estimate of July surface temperatures (Ts) in China's Yongding River basin based on thermal infrared Landsat TM images from 1987 and 2005 and Landsat ETM+ images from 2000. Based upon the Ts–NDVI relationship space, we analyzed the scatterplot of Ts versus NDVI to calculate a temperature–vegetation dryness index (TVDI). We used a linear regression model between soil moisture and TVDI to estimate soil moisture to depths of 10 and 20 cm. We produced a land use and cover type map by classification of the Landsat images, and used the map to study the influence of land use and cover type changes on soil moisture. Some areas of farmland in 1987 had been converted into grassland by 2000, and soil moisture mainly increased, with increases ranging from 20 to 60%. From 2000 to 2005, most of the grassland in the northern part of the study area and some grassland in the central area were converted into farmland, and soil moisture decreased by up to 60%. Soil moisture decreased most obviously in areas where forest was converted into grassland, with decreases ranging from 60 to 100% in most areas.
Article
Vegetation coverage and surface temperature are important parameters in describing the characteristics of land cover, which in combination can provide information on vegetation and soil moisture conditions at the surface. This paper aims to estimate spatial and temporal patterns of soil moisture in the Loess Plateau, China. Using Terra/MODIS images for each 10-day period in 2004 covering the semi-arid North Shaanxi Loess Plateau, a simplified land surface dryness index (Temperature–Vegetation Dryness Index, TVDI) developed by Sandholt [Sandholt, I., Rasmussena, K, Andersenb, J., 2002. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment 79, 213–224.] was used to determine the relationship between surface temperature and vegetation index. From the analysis, it can be inferred that the trend in seasonal change of TVDI is high values in the dry season (spring or summer) and low values in the rainy season (autumn or winter). Moreover, the land surface moisture of each watershed had its seasonal characteristics. The relationship between TVDI and land cover types indicated that water-retention in forest and shrub areas was better than cropland and rangeland in relatively wet conditions, and rangeland was better than forest and shrub areas in dry conditions.
Article
A simplified land surface dryness index (Temperature–Vegetation Dryness Index, TVDI) based on an empirical parameterisation of the relationship between surface temperature (Ts) and vegetation index (NDVI) is suggested. The index is related to soil moisture and, in comparison to existing interpretations of the Ts/NDVI space, the index is conceptually and computationally straightforward. It is based on satellite derived information only, and the potential for operational application of the index is therefore large. The spatial pattern and temporal evolution in TVDI has been analysed using 37 NOAA-AVHRR images from 1990 covering part of the Ferlo region of northern, semiarid Senegal in West Africa. The spatial pattern in TVDI has been compared with simulations of soil moisture from a distributed hydrological model based on the MIKE SHE code. The spatial variation in TVDI reflects the variation in moisture on a finer scale than can be derived from the hydrological model in this case.
Article
Using a new technique referred to as the triangle method, surface soil water content and fractional vegetation cover were derived from surface radiant temperature measurements and normalized difference vegetation index (NDVI). Application of the technique is made with reference to NS001 multispectral scanner measurements made by a C-130 aircraft over the Mahantango Watershed in Pennsylvania. The derived surface soil water content values were compared with those obtained from the Push Broom Microwave Radiometer (PBMR) aboard the same aircraft and with in-situ ground measurements. A large disparity was found to exist between all three measurements, suggesting that the surface becomes decoupled from the deeper substrate in regions of rapid drying, where large vertical gradients in soil water content may exist near the surface.
Article
Directional reflectance measurements were made over a semidesert gramma (Bouteloua spp.) grassland at various times of the growing season. Azimuthal strings of view angle measurements from + 40° to − 40° were made for various solar zenith angles and soil moisture conditions. The sensitivity of the normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI) to these bidirectional measurements was assessed for purposes of improving remote temporal monitoring of vegetation activity. The NDVI response from the grassland canopy was strongly anisotropic about nadir view angles while the SAVI response was symmetric about nadir. This occurred for all sun angles, soil moisture condition, and grass densities. This enabled variations in SAVI-view angle response to be minimized with a cosine function. It is expected that this study will aid in improving the characterization of vegetation temporal activity from Landsat TM, SPOT, AVHRR, and the Earth Observing System MODIS sensor.
Article
Since the mid 70's the LANDSAT series of satelites has acquired visible and near-infrared observations of the earth at a frequency and spatial resolution suitable for agriculture assessment purposes. More recently satellite systems have acquired high precision thermalinfrared data relating to surface thermal properties and moisture status. A data set from the Heat Capacity Mapping Mission [1] illustrates the potential applications of such data for inferring evapotranspiration on a regional scale. Methods described previously [2] are utilized to estimate evapotranspiration rates, yielding results which are consistent with surface measurements of pan evaporation.
Article
An estimate of evapotranspiration is developed by relating variations of satellite-derived surface temperature to a vegetation index computed from satellite visible and near-infrared data. The method requires independent estimates of evapotranspiration for a completely vegetated area and for a nonvegetated area, although such areas need not appear in the satellite data. A regional estimate of evapotranspiration is derived despite the lack of precise estimates for individual satellite measurements. The method requires spatial variability in the satellite data: it does not apply in uniform areas. In addition, a property is identified which permits discrimination of cirrus clouds from areas of varying soil moisture
Field Estimation of Soil Water Content: A Practical Guide to Methods, Instrumentation, and Sensor Technology
  • S Evett
  • L Heng
  • P Moutonnet
  • M Nguyen
Evett, S., Heng, L., Moutonnet, P., & Nguyen, M. (2008). Field Estimation of Soil Water Content: A Practical Guide to Methods, Instrumentation, and Sensor Technology. IAEA: Vienna.