Many coastal regions in China are confronted with pressing problems of scarce land resources and heavy population. Over the past 30 years, considerable parts of coastal tidelands have been enclosed and reclaimed for agricultural land uses. To assess, plan, and implement large-scale reclamation programs, up-to-date and reliable information concerning the nature, areal extent, and physical and chemical characteristics of coastal saline lands is essential. This paper reports a remote sensing approach to detecting coastal saline land uses in Shangyu City, China, by using multi-temporal Landsat images. First, with the aid of resolution-sharpened Landsat-7 ETM+ images and their enhanced linear features, a visual interpretation is applied to extract individual dikes. Based on time series images and local government records, a spatial zoning procedure is then used to define six sub-zones with different historical years of reclamation. It shows that a total of 15,668 ha of coastal saline lands were enclosed and reclaimed from 1969 to 1996. Second, a modified land-use classification system for the study area is prescribed, and both unsupervised and supervised classifiers are performed for land-use classifications of grouped sub-zones. Information obtained from the spatial zoning, Tasseled Cap transformation and Normalized Difference Vegetation Index, is also utilized to facilitate the supervised classification process. Finally, a detailed land-use map is produced, with an overall classification accuracy of 77.8%. Results show that dominant agricultural land uses of sub-zones are changed with historical reclamation years, from saline lands with wildgrass (very recently reclaimed) to aqua-farm ponds, to cotton fields, and to paddy fields and orchards (very early reclaimed). This transform process is primarily affected by soil salinities, and according to a soil survey an electrical conductivity of saturation extract decreased from 7.3 ds/m in the saline land reclaimed in 1996 to below 2 ds/m in the land reclaimed before 1969. The study concludes that multi-temporal remotely sensed images are important and effective data sources for monitoring the rapid changes of coastal land uses.
In borehole electromagnetics, both cylindrical and planar interfaces are present, leading to nonseparable field equations. The problem is two‐dimensional (2-D), and the finite‐element method is usually employed for solution. In this paper, the Generalized Haskell Matrix/Layer Eigenstate Propagator method is introduced to this class of problems. In the method, the solution problem is decomposed into a set of one‐dimensional (1-D) problems, and then the 1-D solutions are combined to form the final solution. The method employs no approximation, other than discretization of a continuous system as in all computer methods. Induction logs are calculated for the 6FF40 tool and a number of models. Results agree well with those of the finite‐element method. An important case in induction‐log interpretation is studied; namely, a three‐layer formation traversed by a borehole, the center layer being an oil‐bearing (resistive) layer sandwiched between two conductive shoulder layers. Simulation shows that conventional correction methods ignoring borehole‐bed coupling can lead to resistivities that differ from the true resistivities by a factor of 2 or even higher.
In order to investigate the possibility of using low-frequency electromagnetic waves to detect and monitor oil contamination of soils, a series of laboratory measurements were performed. A new measurement system to monitor the resistivities of soil and sand samples while samples are being contaminated by diesel oil is presented. The frequency used in measurements is 100 kHz. Since the measurement system is composed of coil-type transmitters and receivers, there is no need for electrodes to be in contact with samples. The contamination process is simulated using diesel oil dripping on top of soil and sand samples. The conductivity distributions in samples along the sample length are recorded as a function of time. Water-wet sand and soil samples were measured during diesel oil contamination. The measured data show that the conductivities of soil and sand samples change during the contamination process. The change in resistivity for measured samples before and after diesel oil contamination is in the range of 20% to 50%, giving a reflection coefficient change in the low-frequency limit of 4.7% to 7%. This amount of change in the reflection coefficient makes it very challenging to detect and monitor oil contamination based on EM reflection from the contaminants. The results suggest that EM methods based on propagation and induction, such as tomography and borehole induction, could be used for this purpose.
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