基于地质统计学影像纹理的海南沙漠化监测研究

海南省东部地区在沙漠化监测上呈现两大难点:一是海滩沙地与沙漠化土地在影像上呈现近乎相同的光谱特征,基于传统的遥感影像光谱分类方法无法得到实际的沙漠化面积;二是该地区属于热带沿海地区,常规的监测指标体系与实际情况相去甚远,必须寻求其他的手段来进行沙漠化程度的分级。基于不同沙地类型在地表空间结构上的差异,本文提出将地质统计学纹理方法应用到沙漠化监测中,通过变异函数纹理来加大各种不同类别沙地间的区别,提高样本选择的分离度。结果表明,运用变异函数纹理结合光谱波段的最大似然分类方法能够很好地界定海滩沙地和沙漠化土地的不同等级,依据分类结果计算得到的沙漠化土地面积与统计数据吻合较好,总精度达到92.4%,证明了地质统计学纹理在实现该地区遥感沙漠化监测方面的有效性,同时也为其他地区沙漠化监测找到一个可资借鉴的方法。     

利用 GIS地理统计模块预测海南岛植被指数季节性变化趋势

虽然采用遥感图像提取的植被指数在空间上能较好的反映作物的状况,但其不能预测植被指数在空间上的变化范围,如果能从整体上了解不同市县在不同季节的平均植被指数值,就可以对该区域整体植被状态进行量化分析,也就可以从大范围内进行植被指数的预测分析.利用地理信息系统(GIS)和地统计学相结合的地理统计分析模块(ArcGIS Geostatistical Analyst),根据MODIS遥感数据提取的每季度不同市县平均NDVI植被指数,采用Kriging插值的方法分析了海南岛归一化植被指数(NDVI)季节性变化趋势,并     

Spatial autocorrelation of West Nile virus vector mosquito abundance in a seasonally wet suburban environment

The objective of this study is to quantify and model spatial dependence in mosquito vector populations and develop predictions for unsampled locations using geostatistics. Mosquito control program trap sites are often located too far apart to detect spatial dependence but the results show that integration of spatial data over time for Cx. pipiens-restuans and according to meteorological conditions for Ae. vexans enables spatial analysis of sparse sample data. This study shows that mosquito abundance is spatially correlated and that spatial dependence differs between Cx. pipiens-restuans and Ae. vexans mosquitoes.      

Local interpolation of coseismic displacements measured by InSAR

Coseismic displacements play a significant role in characterizing earthquake causative faults and understanding earthquake dynamics. They are typically measured from InSAR using pre- and post-earthquake images. The displacement map produced by InSAR may contain missing coseismic values due to the decorrelation of ASAR images. This study focused on interpolating missing values in the coseismic displacement map of the 2003 Bam earthquake using geostatistics with the aim of running a slip distribution model. The gaps were grouped into 23 patches. Variograms of the patches showed that the displacement data were spatially correlated. The variogram prepared for ordinary kriging (OK) indicated the presence of a trend and thus justified the use of universal kriging (UK). Accuracy assessment was performed in 3 ways. First, 11 patches of equal size and with an equal number of missing values generated artificially, were kriged and validated. Second, the four selected patches results were validated after shifting them to new locations without missing values and comparing them with the observed values. Finally, cross validation was performed for both types of patch at the original and shifted locations. UK results were better than OK in terms of kriging variance, mean error (ME) and root mean square error (RMSE). For both OK and UK, only 4 out of 23 patches (1, 5, 11 and 21) showed ME and RMSE values that were substantially larger than for the other patches. The accuracy assessment results were found to be satisfactory with ME and RMSE values close to zero. InSAR data inversion demonstrated the usefulness of interpolation of the missing coseismic values by improving a slip distribution model. It is therefore concluded that kriging serves as an effective tool for interpolating the missing values on a coseismic displacement map.     

SRTM resample with short distance‐low nugget kriging

The shuttle radar topography mission (SRTM), was flow on the space shuttle Endeavour in February 2000, with the objective of acquiring a digital elevation model of all land between 60° north latitude and 56° south latitude, using interferometric synthetic aperture radar (InSAR) techniques. The SRTM data are distributed at horizontal resolution of 1 arc‐second (～30 m) for areas within the USA and at 3 arc‐second (～90 m) resolution for the rest of the world. A resolution of 90 m can be considered suitable for the small or medium‐scale analysis, but it is too coarse for more detailed purposes. One alternative is to interpolate the SRTM data at a finer resolution; it will not increase the level of detail of the original digital elevation model (DEM), but it will lead to a surface where there is the coherence of angular properties (i.e. slope, aspect) between neighbouring pixels, which is an important characteristic when dealing with terrain analysis. This work intents to show how the proper adjustment of variogram and kriging parameters, namely the nugget effect and the maximum distance within which values are used in interpolation, can be set to achieve quality results on resampling SRTM data from 3” to 1”. We present for a test area in western USA, which includes different adjustment schemes (changes in nugget effect value and in the interpolation radius) and comparisons with the original 1” model of the area, with the national elevation dataset (NED) DEMs, and with other interpolation methods (splines and inverse distance weighted (IDW)). The basic concepts for using kriging to resample terrain data are: (i) working only with the immediate neighbourhood of the predicted point, due to the high spatial correlation of the topographic surface and omnidirectional behaviour of variogram in short distances; (ii) adding a very small random variation to the coordinates of the points prior to interpolation, to avoid punctual artifacts generated by predicted points with the same location than original data points and; (iii) using a small value of nugget effect, to avoid smoothing that can obliterate terrain features. Drainages derived from the surfaces interpolated by kriging and by splines have a good agreement with streams derived from the 1” NED, with correct identification of watersheds, even though a few differences occur in the positions of some rivers in flat areas. Although the 1” surfaces resampled by kriging and splines are very similar, we consider the results produced by kriging as superior, since the spline‐interpolated surface still presented some noise and linear artifacts, which were removed by kriging.     

Estimating and simulating the degree of serpentinization of peridotites using hyperspectral remotely sensed imagery

The mineral products resulting from the process of serpentinization, by which primary magnesium silicate minerals in peridotites are replaced by hydrous serpentine-group minerals, are of economic importance since Alpine-type peridotites are the host rocks for virtually all large asbestos deposits, which may be attributed mainly to the serpentine-group mineral chrysotile. Conventional field mapping of the distribution of highly serpentinized areas is time consuming and requires detailed sampling and laboratory analysis. In 0.4- to 2.5-m reflectance spectra of serpentinized peridotites, serpentinization is responsible for a decrease in contrast of olivine-pyroxene iron absorption features and an appearance and increase in OH^– absorption features near 1.4 m and 2.3 m associated with serpentine minerals. The degree of serpentinization is positively correlated with the depth of the 1.4-m and 2.3-m absorption features for samples containing more than 55 weight percent serpentine minerals. Small amounts of magnetite in a sample obscure the spectral contrast and decrease the overall brightness of weakly serpentinized samples. A methodology is used for mapping serpentine minerals in ultrabasic rocks from imaging spectrometer data, which includes (1) vegetation masking, (2) calculating the absorption band depth of the 2.3-m absorption feature in unmasked pixels, (3) translating this value into percent serpentine minerals using an empirical linear model, and (4) estimating the degree of serpentinization at the remaining locations using conditional simulation techniques or ordinary block kriging. From the results of this study, it can be concluded that mapping the degree of serpentinization from high-spectral resolution imagery is possible within marginal statistical fluctuations. Conditional simulation reproduces the spatial and statistical variability of the data set; however, it sacrifices the local accuracy. Direct estimation using ordinary kriging provides a better local estimate but does not honor the statistics and spatial dispersion of the original data.The spectral analyses presented in this publication were carried out at the Jet Propulsion Laboratory in Pasadena, California. The author would like to thank Mrs. Cindy Grove for her help in processing the samples. Dr. Harold Lang is thanked for advice in interpreting the spectra. The article benefitted from critical comments by Dr. Roger Clark and Dr. John Mustard, and various discussions with Prof. Salemon Kroonenberg and Prof. Andrea Fabbri. The Spectral Image Processing System (SIPS) developed at the Center for the Study of Earth from Space (CSES) of the University of Colorado, Boulder, was used for the GERIS data calibration. This article benefitted from a critical review by Dr. Daniel H. Knepper, Jr.     

Spatial relationships among species, above-ground biomass, N, and P in degraded grasslands in Ordos Plateau, northwestern China

We chose five communities, representing a mild to severe gradient of grassland desertification in a semi-arid area of Ordos Plateau, northwestern China, to explore the spatial relationships among plant species, above-ground biomass (AGB), and plant nutrients (N and P). Community 1 (C1) was dominated by Stipa bungeana; Community 2 (C2) by a mix of S. bungeana and the shrub Artemisia ordosica; Community 3 (C3) by A. ordosica; Community 4 (C4) by a mix of Cynanchum komarovii and C. komorovii; and Community 5 (C5) by C. komorovii. Quantitative methods, including geostatistics, were used to compare community composition, structure, and indicators of ecosystem function (i.e. AGB, plant N and P) in five 16-m² plots. The highest AGB, plant nitrogen (N) and plant phosphorus (P) were found in lightly degraded community C2. With increasing desertification effects from C3 to C5, the AGB, N, and P decreased significantly while plant density remained unchanged. The spatial variations of AGB were higher in shrub-dominated communities (C1 and C5) than in grass-dominated communities (C2–C4). Strong spatial relationships were detected within and among the communities, with stronger relationships between AGB and density than between AGB and species richness. Spatial patterns of plant N and P were different from those of AGB, reflecting different N and P contents of individual plants and different species that can redistribute soil resources in these communities. The AGB was positively correlated with soil nutrients (TOC, TN, TP, and IN), except for soil AP. We concluded that several specific aspects of ecosystem properties were directly associated with the conversion of the grass and shrub “functional types” in these degraded grasslands.     

Multiple-Point Statistics for Training Image Selection

Selecting a training image (TI) that is representative of the target spatial phenomenon (reservoir, mineral deposit, soil type, etc.) is essential for an effective application of multiple-point statistics (MPS) simulation. It is often possible to narrow potential TIs to a general subset based on the available geological knowledge; however, this is largely subjective. A method is presented that compares the distribution of runs and the multiple-point density function from available exploration data and TIs. The difference in the MPS can be used to select the TI that is most representative of the data set. This tool may be applied to further narrow a suite of TIs for a more realistic model of spatial uncertainty. In addition, significant differences between the spatial statistics of local conditioning data and a TI may lead to artifacts in MPS. The utilization of this tool will identify contradictions between conditioning data and TIs. TI selection is demonstrated for a deepwater reservoir with 32 wells.