Spatial variability of soil organic matter and nutrients in paddy fields at various scales in southeast China

The present study examines the spatial dependency of soil organic matter and nutrients in paddy fields at three different scales using geostatistics and geographic information system techniques (GIS). The spatial variability of soil organic matter (SOM), total nitrogen (TN) and available phosphorus (AP) has been characterized using a total of 460, 131 and 64 samples that were, respectively, collected from the Hangzhou–Jiaxing–Huzhou (HJH) Plain (10 km), Pinghu county (1,000 m) and a test plot area (100 m) within the Pinghu county, Zhejiang province of the southeast China. Semivariograms showed that the SOM and TN had moderate spatial dependency on the large scale of HJH plain and moderate scale of Pinghu county with long spatial correlation distances. At the moderate scale of Pinghu county and the small scale of a test plot area, the AP data did not show any spatial correlation, but had moderate spatial dependency in HJH plain. Spherical and exponential variogram models were best fitted to all these soil properties. Maps of SOM and TN were generated through interpolation of measured values by ordinary kriging, and AP by lognormal kriging. This study suggests that precision management of SOM and TN is feasible at all scales, and precision management of AP is feasible at large scales.     

Using geostatistics and spectral analysis to study spatial patterns in the topography of southeastern Washington State,U.S.A.

Topography for four areas in the Palouse region of southeastern Washington State having different patterns and encompassing areas of about 900 ha each were quantitatively compared and described using two-dimensional semi-variograms and periodograms. The four areas studied were from the Garfield, La Crosse, Thornton, and Wilcox quadrangle topographic maps. Semivariance of elevation residuals were modelled using a combination of spherical, periodic, or linear semivariogram models. The range of the spherical component was interpreted as a relatively short-range scale of correlation which was not periodic. For each of the study areas a model was developed to describe the variation in range with orientation. Values for the range from this model reached maximum values of from about 700 m to 800 m at an orientation of from 35° to 55° (approximately northeast) in each study area. This orientation was interpreted as the dominant direction of non-periodic small-scale landscape features. The wavelength and amplitude of the periodic semivariogram component, which were highly correlated, were interpreted in terms of parallel northeast-trending ridges having relatively long scales of periodic correlation varying in size from about 1350 m to 2100 m. This attempt to identify the dominant orientation of periodic landscape features using models for the wavelength and amplitude was, however, not completely definitive. Two-dimensional spectral analysis provided significantly more detail concerning orientation and wavelengths of the periodic topographic patterns than the semivariogram analysis. In the Garfield study area, spectral analysis identified north-trending ridge systems separated by a wavelength of 1494 m and northeast-trending systems with a wavelength of 747 m. In the La Crosse study area, both north and northeast-trending patterns were identified having periodic spacings of 980 and 735 m. North-trending ridges separated by wavelengths of 996 m and northeast-trending ridges separated by wavelengths of 747 or 996 m were the predominant periodic features of topography in the Thornton study area. In the Wilcox study area, northeast-trending ridge systems separated by wavelengths of 373, 498, or 996 m were detected. A comparison of the results from geostatistical and spectral analysis of these complex topographic surfaces shows that each approach had significant strengths and weaknesses. Two-dimensional analysis with semivariograms was the only method which could be used for identifying the correlation scale and orientation of relatively small non-periodic landscape features. Two-dimensional spectral analysis accurately identified the predominant orientation of relatively large periodic features in topography, whereas semivariogram analysis was somewhat inconclusive. Also, semivariograms were generally unable to detect the presence of multiple or harmonic periodicities operating at different wavelengths along a given orientation.     

Assessment and integration of conventional,RTK-GPS and image-derived beach survey methods for daily to decadal coastal monitoring

Coastal monitoring across a broad range of time-scales was recognized in the latest report by the Intergovernmental Panel on Climate Change as key to better understanding the likely impacts of climate change at the coast. A unique and historic coastal monitoring program undertaken at the Collaroy–Narrabeen embayment in south-eastern Australia comprises: 1) 30 years of monthly conventional (Emery method) surveys of five cross-shore profile lines; 2) three years of monthly three-dimensional surveys of the entire embayment using RTK-GPS mounted to an all-terrain vehicle (ATV); and 3) four years of hourly shoreline measurements using coastal imaging technology (ARGUS). This study evaluates the strengths and limitations of conventional, RTK-GPS and image-derived surveys for coastal monitoring at daily to decadal coastal time-scales. High-accuracy RTK-GPS was used to first assess the accuracy of the conventional and image-derived survey methods. The magnitude of daily to decadal coastal variability was then characterized by calculating the temporal semivariogram of the integrated survey dataset. With both measurement errors and the degree of beach variability quantified, the corresponding signal-to-noise ratios (SNR) of each survey method at different time-scales were determined. The value of the simple and cost-effective Emery method was verified by this analysis, with measurement error significantly smaller than the degree of overall beach variability (SNR = 8.4). The accuracy, speed and efficiency of ATV-mounted RTK-GPS meanwhile make it suitable for three-dimensional beach surveys. Image-derived surveys were found to be an effective means of remotely measuring the considerable degree of beach variability identified at time-scales of less than one month. These measurements however become indistinguishable from survey noise (i.e. SNR ≤ 1) when considering typical weekly (or smaller) variations at large distances from the cameras.     

Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices

In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices.     

沈阳市土壤铅的空间分布及风险评价研究

经测定,沈阳市土壤铅含量范围为22～2910.600mg/kg,平均值是270.297mg/kg。铅污染比较严重且空间变化大,局地污染非常严重。利用地统计方法研究了沈阳市土壤铅的空间结构和分布特征。结果显示,沈阳市土壤铅具有较好的空间结构性,利用半方差函数的结果进行克里格插值得到土壤铅含量的分布图。沈阳市有6个土壤铅污染中心,其中以铁西区和太原街的污染比较突出。工业排放、汽车尾气和污灌是沈阳市铅污染的三大污染源。风险评价结果表明,铁西区属于极高风险区,儿童铅中毒的潜在风险非常大。