Seasonal and inter-annual relationships between vegetation and climate in central New Mexico, USA

Linear correlations between seasonal and inter-annual measures of meteorological variables and normalized difference vegetation index (NDVI) are calculated at six nearby yet distinct vegetation communities in semi-arid New Mexico, USA Monsoon season (June–September) precipitation shows considerable positive correlation with NDVI values from the contemporaneous summer, following spring, and following summer. Non-monsoon precipitation (October–May), temperature, and wind display both positive and negative correlations with NDVI values. These meteorological variables influence NDVI variability at different seasons and time lags. Thus vegetation responds to short-term climate variability in complex ways and serves as a source of memory for the climate system.     

Traction image method for irregular free surface boundaries in finite difference seismic wave simulation

In this study, we propose a new numerical method, named as Traction Image method, to accurately and efficiently implement the traction-free boundary conditions in finite difference simulation in the presence of surface topography. In this algorithm, the computational domain is discretized by boundary-conforming grids, in which the irregular surface is transformed into a 'flat' surface in computational space. Thus, the artefact of staircase approximation to arbitrarily irregular surface can be avoided. Such boundary-conforming gridding is equivalent to a curvilinear coordinate system, in which the first-order partial differential velocity-stress equations are numerically updated by an optimized high-order non-staggered finite difference scheme, that is, DRP/opt MacCormack scheme. To satisfy the free surface boundary conditions, we extend the Stress Image method for planar surface to Traction Image method for arbitrarily irregular surface by antisymmetrically setting the values of normal traction on the grid points above the free surface. This Traction Image method can be efficiently implemented. To validate this new method, we perform numerical tests to several complex models by comparing our results with those computed by other independent accurate methods. Although some of the testing examples have extremely sloped topography, all tested results show an excellent agreement between our results and those from the reference solutions, confirming the validity of our method for modelling seismic waves in the heterogeneous media with arbitrary shape topography. Numerical tests also demonstrate the efficiency of this method. We find about 10 grid points per shortest wavelength is enough to maintain the global accuracy of the simulation. Although the current study is for 2-D P-SV problem, it can be easily extended to 3-D problem.     

1993～2003年厦门市湿地动态变化及其驱动因素分析

通过对厦门市1993年TM遥感影像和2003年ETM 遥感影像的解译分析和数据统计,从湿地面积动态变化和湿地消长情况等方面,用单一土地利用动态度等指标对1993~2003年期间厦门市的湿地变化进行了研究。结果表明,1993~2003年期间厦门市天然湿地面积减少了2103hm2,其中有954hm2(滩涂864hm2)转变为非湿地,有1149hm2转变为人工湿地;而人工湿地面积增加了2775hm2,其中养殖场面积从1993年的5778hm2迅猛增加到2003年的9768hm2,年均增长率为6.91%,水库与水塘和盐田则分别减少了961hm2和254hm2。有27.74%、11.41%、9.33%和3.63%的养殖场面积分别是由非湿地、滩涂、盐田和水库与水塘转变而来的;有54.37%的盐田转变成了养殖场,有33.24%、30.24%的红树林转变为非湿地、养殖场,有10.35%、8.64%的滩涂转变为养殖场、非湿地。对社会经济驱动因素的分析表明,经济发展、人口增长和农业生产比较利益因素极大影响着厦门市湿地的动态变化。     

APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO REMOTE SENSING*

Remote sensing is a geographic analysis tool capable of producing large quantities of data in the spectral, temporal and spatial domains. Techniques for automating the image analysis process would be advanced by the inclusion of artificial intelligence techniques in the design of image processing systems. The remote sensing application which show promise for successful implementation of artificial intelligence techniques are intelligent onboard processing, advanced database interrogation, and the automated analysis of multispectral imagery.     

High spatial resolution hyperspectral mapping of in-stream habitats, depths, and woody debris in mountain streams

This article evaluates the potential of 1-m resolution, 128-band hyperspectral imagery for mapping in-stream habitats, depths, and woody debris in third- to fifth-order streams in the northern Yellowstone region. Maximum likelihood supervised classification using principal component images provided overall classification accuracies for in-stream habitats (glides, riffles, pools, and eddy drop zones) ranging from 69% for third-order streams to 86% for fifth-order streams. This scale dependency of classification accuracy was probably driven by the greater proportion of transitional boundary areas in the smaller streams. Multiple regressions of measured depths (y) versus principal component scores (x₁, x₂,…, x_n) generated R² values ranging from 67% for high-gradient riffles to 99% for glides in a fifth-order reach. R² values were lower in third-order reaches, ranging from 28% for runs and glides to 94% for pools. The less accurate depth estimates obtained for smaller streams probably resulted from the relative increase in the number of mixed pixels, where a wide range of depths and surface turbulence occurred within a single pixel. Matched filter (MF) mapping of woody debris generated overall accuracies of 83% in the fifth-order Lamar River. Accuracy figures for the in-stream habitat and wood mapping may have been misleadingly low because the fine-resolution imagery captured fine-scale variations not mapped by field teams, which in turn generated false “misclassifications” when the image and field maps were compared.The use of high spatial resolution hyperspectral (HSRH) imagery for stream mapping is limited by the need for clear water to measure depth, by any tree cover obscuring the stream, and by the limited availability of airborne hyperspectral sensors. Nonetheless, the high accuracies achieved in northern Yellowstone streams indicate that HSRH imagery can be a powerful tool for watershed-wide mapping, monitoring, and modeling of streams.     

改进的混合像元分解法用于快速水污染遥感评价研究

该文介绍了一种改进的混合像元分解方法。利用该方法对滇池的各类污染（叶绿素,营养盐等）进行快速评价,可以直接得出滇池各个区域所受各类污染的程度,从而给出滇池全区各类污染的情况分布。     

基于遥感与GIS技术的城镇体系空间特征的分形分析--以绍兴市为例

在遥感技术与GIS技术的支持下,采用分形几何理论对绍兴市城镇体系空间结构特征和形态特征进行分析,探讨城镇体系的演化规律。研究表明,绍兴市城镇体系无论在空间结构上还是在空间形态上都具有分形特征。城镇分布密度由绍兴市区向周围逐渐衰减,且分布不均衡,具有向交通线集中的趋势,形成了优化的空间结构。但1984～1997年间,空间结构的演化趋向于围绕绍兴市在半径方向上均匀分布,分形特性减弱。此外,各城镇基本是以各自的中心逐渐向外扩展,空间关联性大致不变。空间形态则日趋复杂,稳定性越来越低,发展的随意性越来越大。绍兴市区这一特点更明显。     

胶州湾北部滨海湿地分布特征及质量评价

以胶州湾北部滨海湿地为研究区域,运用RS和GIS技术提取湿地信息,研究时空变化特征,建立湿地定量评价系统,并对湿地质量进行分析。研究表明,自1997年到2007年,该地湿地类型变化较大,沿岸湿地退化现象严重,人为活动影响增大,非湿地面积大量增加,湿地质量不断下降。     

浙江沿海20年土地利用变化分析

在资料收集的基础上,利用遥感(RS)和地理信息系统(GIS)技术,结合经济社会因子和数学模型,以浙江沿海地区1990年、2000年和2010年的土地利用数据为基础,对20年间土地利用变化动态进行研究。利用灰色动态系统建立模型分析浙江沿海地区各类土地利用的变化趋势,在此基础上探讨其变化驱动力,揭示其变化的主要方式、原因及发展方向,预测未来土地利用的发展趋势,以期能为浙江省沿海地区土地利用规划提供科学依据。     

基于遥感影像的于田绿洲空间热环境分布特征

以新疆于田绿洲为例,以Landsat TM/ETM+为基础数据源,利用空间分析方法、3S技术方法等定量分析于田绿洲平均温度的分布特征,得出地表温度受下垫面类型的影响比较明显,地表土地类型的分布基本决定地温的总体分布;通过对温度相异图的研究,发现温度的分布同时也受到不同土地利用类型空间分布的影响;对克里雅河下游河段进行温度变化的趋势分析,得出在南北方向上,没有温度变化趋势,而在东西方向上,温度变化比较明显。同时也说明克里雅河对其河道两边的影响范围十分有限。