Thermal Infrared Remote Sensing Research Articles

Exploration of Offshore Oil and Gas Resources Using Thermal Infrared Remote Sensing

abstract:Remote sensing technology is playing anincreasingly important role in the investigation and exploration of oil and gasresources. Using thermal infrared remote sensing technology to detect offshoreoil and gas resources is one of new methods, but there are many uncertainties. Inthis paper, MODIS data are used to explore oil and gas resources availabilityin the North Yellow Sea Basinthrough extracting the temperature anomaly areas. Result shows that this methodcan be effective in assisting in exploring undersea oil and gas resources.

Actualities and Development Trends of The Study on Land Surface Temperature Retrieving from Thermal Infrared Remote Sensing

Regional or global land surface temperature can only be got by remote sensing technology,which is a very important parameter in many applications.Land surface temperature retrieval is a hot and difficult problem in the research of thermal infrared remote sensing,in which atmospheric correction,temperature and emissivity separation must be considered.Many research have been developed in recent years,which can be classified to 5 categories including single band method,split-window method,multi-bands temperature and emissivity separation methods,multi-angles retrieval method,and combination of multi-angles and channels,but these methods have both advantages and disadvantages.How to improve retrieval precision and models applicability are the future development trends for land surface temperature retrieval,and synthetic application of multi information by theory combined with experiment methods is the inevitable request.

SOME THINKING ON QUANTIATIVE THERMAL INFRARED REMOTE SENSING

SOME THINKING ON QUANTIATIVE THERMAL INFRARED REMOTE SENSING

Advances in the Study of Near Surface Air Temperature Retrieval from Thermal Infrared Remote Sensing

Near surface air temperature is an important environment variable in many earth system models,because it is a key factor in the energy and water exchanges between land surface and atmosphere.Detailed measurements of spatial and temporal variations of near surface air temperature are critical for the effective understanding of climate,hydrology,ecology,agriculture and terrestrial life processes.Traditionally meteorological observation could provide accurate air temperature data at the point scale,but most earth system models need gridded input variables.Satellite remote sensing provides a straightforward and consistent way to observe air temperature at regional and global scales with more spatially detailed information than meteorological data.This paper systematically reviews the air temperature retrieving algorithms for thermal remote sensing data,which include TVX approaches,statistical approaches,neural network approaches and energy balance approaches.The main advantages and limitations of these four methods are also discussed.Finally,the development tendencies of estimating air temperature by remote sensing are pointed out,such as intensive research on thermal radiant transfer model,spatial-temporal scaling of air temperature and improvement of cloud detection.

Retrieval of an Available Water-Based Soil Moisture Proxy from Thermal Infrared Remote Sensing. Part I: Methodology and Validation

Abstract A retrieval of available water fraction ( fAW) is proposed using surface flux estimates from satellite-based thermal infrared (TIR) imagery and the Atmosphere–Land Exchange Inversion (ALEXI) model. Available water serves as a proxy for soil moisture conditions, where fAW can be converted to volumetric soil moisture through two soil texture dependents parameters—field capacity and permanent wilting point. The ability of ALEXI to provide valuable information about the partitioning of the surface energy budget, which can be largely dictated by soil moisture conditions, accommodates the retrieval of an average fAW over the surface to the rooting depth of the active vegetation. For this method, the fraction of actual to potential evapotranspiration ( fPET) is computed from an ALEXI estimate of latent heat flux and potential evapotranspiration (PET). The ALEXI-estimated fPET can be related to fAW in the soil profile. Four unique fPET to fAW relationships are proposed and validated against Oklahoma Mesonet soil moisture observations within a series of composite periods during the warm seasons of 2002–04. Using the validation results, the most representative of the four relationships is chosen and shown to produce reasonable (mean absolute errors values less than 20%) fAW estimates when compared to Oklahoma Mesonet observations. Quantitative comparisons between ALEXI and modeled fAW estimates from the Eta Data Assimilation System (EDAS) are also performed to assess the possible advantages of using ALEXI soil moisture estimates within numerical weather predication (NWP) simulations. This TIR retrieval technique is advantageous over microwave techniques because of the ability to indirectly sense fAW—and hence soil moisture conditions—extending into the root-zone layer. Retrievals are also possible over dense vegetation cover and are available on spatial resolutions on the order of the native TIR imagery. A notable disadvantage is the inability to retrieve fAW conditions through cloud cover.

Estimating Broadband Emissivity of Arid Regions and Its Seasonal Variations Using Thermal Infrared Remote Sensing

Surface emissivity in the thermal infrared region is an important parameter for determining the surface radiation budget in climate, weather, and hydrological models. This paper focuses on estimating the spatial and temporal variations of the surface emissivities using thermal infrared remotely sensed data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellite. We developed a regression approach to use the ASTER and MODIS data for estimating the broadband emissivity (BBE; 8-13.5 mum). The regressions were calibrated using a library of spectral emissivity data for terrestrial materials. We applied these regressions to ASTER and MODIS data to obtain emissivity maps for several arid regions of the Earth. In the 8-9-mum band for sparsely or nonvegetated desert areas, emissivity values between 0.66 and 0.96 have been observed, which are due to the low emissivity of quartz-rich sands at these wavelengths. As a result, the range of BBE is between 0.86 and 0.96. The seasonal variation over a two-year period and the dependence on land cover/soil type were also investigated.

Feasible study on the integration system for the space monitoring of major earthquakes and volcanoes in terrestrial land

With the rapid development of space technology, earth observation technology and sky observatory technology, they have played a more and more important part in monitoring and predicting of earthquakes and volcanoes in the terrestrial land. In recent years, the related agencies have done the experiments and researches on monitoring and predicting of earthquakes and volcanoes in the forewarning period by means of many approaches, such as satellite thermal infrared remote sensing (TIRS), Global Positioning System (GPS), differential interferometric synthesis aperture radar (D-INSAR), astronomical time-latitude residual anomaly, and Geographic Information Systems (GIS), etc. A quite large number of research foundation has been built in the fundamental theories and application methods. The experiments and researches have shown that these technology is efficient methods for high frequency crust movement. If the existed separate scientific forces and results are possibly assembled together to form a more complete integration monitoring system with the combination of space, sky observation, ground, deep geology and macro anomaly, it will come into a new stage of monitoring and predicting of earthquakes and volcanic eruptions.

The Application of Thermal Infrared Remote Sensing to the Investigation of the Pollution of the Huangpu River

The Application of Thermal Infrared Remote Sensing to the Investigation of the Pollution of the Huangpu River