• Title/Summary/Keyword: Soil Sensing

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A Perspective on Radar Remote Sensing of Soil Moisture

  • Park, Sang-Eun
    • Korean Journal of Remote Sensing
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    • v.27 no.6
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    • pp.761-771
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    • 2011
  • The sensitivity of microwave scattering to the dielectric properties and the geometric structure of soil surfaces makes radar remote sensing a challenge for a wide range of environmental issues directly related to the condition of natural surfaces. Especially, the potential for retrieving soil moisture with a high spatial and/or temporal resolution represents a significant contribution to hydrological and ecological modeling. This paper aims to review the current state of the art in SAR technology and methodological issues towards the discovery of a new potential accurate monitoring of soil moisture changes. In this paper, important parameters or constraints significantly affect the sensitivity of the measurements to soil moisture, such as roughness statistics, spatial resolution, and local topography, are discussed to improve the applicability of SAR remote sensing techniques. This study particularly intends to discuss important notes for developing smart and reliable methods capable of retrieving geophysical information.

Characterizing the strain transfer on the sensing cable-soil interface based on triaxial testing

  • Wu, Guan-Zhong;Zhang, Dan;Shan, Tai-Song;Shi, Bin;Fang, Yuan-Jiang;Ren, Kang
    • Smart Structures and Systems
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    • v.30 no.1
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    • pp.63-74
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    • 2022
  • The deformation coordination between a rock/soil mass and an optical sensing cable is an important issue for accurate deformation monitoring. A stress-controlled triaxial apparatus was retrofitted by introducing an optical fiber into the soil specimen. High spatial resolution optical frequency domain reflectometry (OFDR) was used for monitoring the strain distribution along the axial direction of the specimen. The results were compared with those measured by a displacement meter. The strain measured by the optical sensing cable has a good linear relationship with the strain calculated by the displacement meter for different confining pressures, which indicates that distributed optical fiber sensing technology is feasible for soil deformation monitoring. The performance of deformation coordination between the sensing cable and the soil during unloading is higher than that during loading based on the strain transfer coefficients. Three hypothetical strain distributions of the triaxial specimen are proposed, based on which theoretical models of the strain transfer coefficients are established. It appears that the parabolic distribution of specimen strain should be more reasonable by comparison. Nevertheless, the strain transfer coefficients obtained by the theoretical models are higher than the measured coefficients. On this basis, a strain transfer model considering slippage at the interface of the sensing cable and the soil is discussed.

An Improved Method for Monitoring of Soil Moisture Using NOAA-AVHRR Data

  • Fu, June;Pang, Zhiguo;Xiao, Qianguang
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.195-197
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    • 2003
  • Soil moisture is a crucial variable in research works of hydrology, meteorology and plant sciences. Adequate soil moisture is essential for plant growth; excesses and deficits of soil moisture must be considered in agricultural practices. There are already several remote sensing methods used for monitoring soil moisture, such as thermal inertia, vegetation water-supplying index, crop water stress index and multi-factor regression. In this paper, an improved method has been discussed which is based on the thermal inertia. We analyzed the problems of monitoring soil moisture using satellites at first, and then put forward an simplified method which directly uses land surface temperature differences to measure soil moisture. Also we have taken the influence of vegetation into account, and import NDVI into the model. The method was used in the study of soil moisture in Heilongjiang Province, China, and we draw the conclusion by the experiments that the model can evidently increase the precision of monitoring soil moisture.

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ESTIMATION OF SOIL MOISTURE WITH AIRBORNE L-BAND MICROWAVE RADIOMETER

  • Chang, Tzu-Yin;Liou, Yuei-An
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.26-28
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    • 2008
  • Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

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Remote Sensing Information Models for Sediment and Soil

  • Ma, Ainai
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.739-744
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    • 2002
  • Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

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A soil surface information obtained by remote sensing technology (Remote Sensing 기법에 의한 토양정보추출(지역환경 \circled1))

  • 박종화;전택기
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2000.10a
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    • pp.507-512
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    • 2000
  • The main objective of this study is to provide a soil surface information, which represent a soil reflectance spectrum, by remote sensing technology. The soil reflectance of the soil was measured using a spectroradiometer in the wavelength range from 300nm to 1100nm. Measurements of soil reflectance have been made in four different soils. The results suggest that the reflectance properties of soils are related to their mineral composition and soil moisture. Increasing soil moisture resulted in an decrease in the rate of reflectance which leads to parallel curves of soil reflectance spectra. The soil line representing the relationship between red and near-infrared soil reflectance is characterized by soil types.

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Radar Remote Sensing of Soil Moisture and Surface Roughness for Vegetated Surfaces

  • Oh, Yi-Sok
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.427-436
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    • 2008
  • This paper presents radar remote sensing of soil moisture and surface roughness for vegetated surfaces. A precise volume scattering model for a vegetated surface is derived based on the first-order radiative transfer technique. At first, the scattering mechanisms of the scattering model are analyzed for various conditions of the vegetation canopies. Then, the scattering model is simplified step by step for developing an appropriate inversion algorithm. For verifying the scattering model and the inversion algorithm, the polarimetric backscattering coefficients at 1.85 GHz, as well as the ground truth data, of a tall-grass field are measured for various soil moisture conditions. The genetic algorithm is employed in the inversion algorithm for retrieving soil moisture and surface roughness from the radar measurements. It is found that the scattering model agrees quite well with the measurements. It is also found that the retrieved soil moisture and surface roughness parameters agree well with the field-measured ground truth data.

Spectral Reflectance of Soils Related to the Interaction of Soil Moisture and Soil Color Using Remote Sensing Technology (RS 기법을 이용한 토양수분과 토양 색에 관련된 토양의 분광반사)

  • 박종화
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.5
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    • pp.77-84
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    • 2003
  • Recent advances in remote sensing techniques provide the potential for monitoring soil color as well as soil moisture conditions at the spatial and temporal scales required for detailed local modeling efforts. Soil moisture as well as soil color is a key feature used in the identification and classification of soils. Soil spectral reflectance has a direct relationship with soil color, as well as to other parameters such as soil moisture, soil texture. and organic matter. We evaluate the influence of seven soil properties, soil color and soil moisture, on soil spectral reflectance. This paper presents the results obtained from the ground-truth spectral reflectance measurements in the 300-1100 nm wavelength range for various land surfaces. The results suggest that the reflectance properties of soils are related to soil color, soil texture, and soil moisture. Increasing soil moisture content generally decreases soil reflectance which leads to parallel curves of soil reflectance spectra across the entire shortwave spectrum. We discuss the relationships between the soil reflectance and the Munsell Soil Color Charts which contain standard color chips with colors specified by designations for hue, value, and chroma.

USING TRMM SATELLITE C BAND DATA TO RETRIEVE SOIL MOISTURE ON THE TffiETAN PLATEAU

  • Chang Tzu-Yin;Liou Yuei-An
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.737-740
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    • 2005
  • Soil moisture, through its dominance in the exchange of energy and moisture between the land and atmosphere, plays a crucial role in influencing atmospheric circulation. To identify the crucial role, it is a common agreement that knowledge of land surface processes and development of remote sensing techniques are of great important scientific issues. This research uses TRMM satellite C band (10.65 GHz) data to retrieve soil moisture on the Tibetan Plateau in Mainland China. Two retrieval schemes that are implemented include the t-(J) model and the R model. The latter one is developed based on a land surface process and radiobrightness (R) model for bare soil and vegetated terrain. Compared with the in situ ground measurements, the soil moisture retrieved from the R model and the t-(J) model with vegetation information obviously appear more accurate than that derived from bare soil model. Retrieved soil moisture contents from the two inversion models, R model and t-(J) model, have a similar trend, but the former appears to be superior in terms of correlation coefficient and bias compared with in situ data. In the future, we will apply the R model with the TRMM 10.65 GHz brightness temperature to monitor long-term soil moisture variation over Tibet Plateau.

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A Geographic Information System(GIS) Approach for Modeling a Soil Erosion Map from Available Data

  • Yang, Young-Kyu;Miller, Lee-D.
    • Korean Journal of Remote Sensing
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    • v.2 no.1
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    • pp.23-33
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    • 1986
  • The Universal Soil Loss Equation (USLE) has been applied to the microcomputer based Geographic Information System (GIS) data planes to model a soil erosion map for a county. The conventional method applied by US Soil conservation Service (SCS) has been tedious and time consuming process on a mainframe computer which yields a multisectioned, hard to interprete, line printer map of the each county's soil loss. The new approach proved to be an economical and efficient tool for the natural resource managers in their decision malting in land conservation practice. They can simulate the variety of conservation practices and assess the cost and benefit without physically implementing the conservation measures.7he new approach also can produce all the other graphical and statistical reports.