Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

As more satellite-derived land cover products used in the study of global change,especially climate modeling,assessing their quality has become vitally important.In this study,we developed a distance metric based on the parameters used in weather research and forecasting(WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme(IGBP) classification scheme.We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer(MODIS) products,and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model.Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes,while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes.The degree of disagreement varied significantly among seven regions of China.The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly.High accuracy and fuzzy agreement occurred in the following classes:water,grassland,cropland,and barren or sparsely vegetated.Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals.Some classes need to be improved further;the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling.Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.     

Climatic regime shift and decadal anomalous events in China

Climatic time series from historical documents and instrumental records from China showed temporal and regional patterns in the last two to three centuries, including two multidecadal oscillations at quasi-20-year and quasi-70-year timescales revealed by signal analysis from wavelet transform. Climatic anomalous events on the decadal timescale were identified based on the two oscillations when their positive (or negative) phases coincide with each other to amplify amplitude. The coldest event occurred in the decade of 1965–1975 in eastern China, while the periods of 1920–1930, 1940–1950, and 1988–2000 appeared to be warmer in most parts of China. For the precipitation series in northern China, the dry anomalous event was found in the late 1920s, while the wet anomalous event occurred in the 1950s. A severe drought in 1927–1929 in northern China coincided with the anomalous warm and dry decade, caused large-scale famine in nine provinces over northern China. Climatic anomalous events with a warm-dry or cold-wet association in the physical climate system would potentially cause severe negative impacts on natural ecosystem in the key vulnerable region over northern China. The spatial pattern of summer rainfall anomalies in the eastern China monsoon region showed an opposite variations in phase between the Yellow River Valley (North China) and the mid-low Yangtze River Valley as well as accompanied the shift of the northernmost monsoon boundary. Climatic regime shifts for different time points in the last 200 years were identified. In North China, transitions from dry to wet periods occurred around 1800, 1875, and 1940 while the transitions from wet to dry periods appeared around 1840, 1910, and the late 1970s. The reversal transition in these time points can also be found in the lower Yangtze River. Climatic regime shifts in China were linked to the interaction of mid- and low latitude atmospheric circulations (the westerly flow and the monsoon flow) when they cross the Tibetan Plateau in East Asia.     

模式水平分辨率对祁连山区降水模拟影响的初步分析

利用中尺度模式MM5V3．6，针对祁连山地区2002年7月14～17日的一次降水过程，设计了一组不同水平分辨率的试验进行数值模拟。并将模式结果与实测资料进行对比，结果表明：高水平分辨率对降水中心位置的模拟较好，但同时会产生虚假降水中心，且模拟的降水中心量值一般都大于实测值。而低水平分辨率对降水量值的模拟较好，但对降水中心位置的模拟没有高水平分辨率的好。     

从地球系统的观点看气候突变

在地球的气候史中,经历了许多次气候突变事件。这些突变对地球表层系统的演变与进化产生了巨大影响。随着全球气候变暖的持续发展,人类赖以生存的气候环境正在经历重大变化。如何科学地理解和认识这些变化,尤其是气候突变。是人类寻求对策,应对气候变化,保护自己持续发展的科学基础。文中从地球系统的角度对气候突变的科学问题进行了探讨,认为对气候突变的研究不应仅局限于大气圈,而应该对地球系统的整体变化进行研究。     

油罐区砖砌防火堤的抗震验算

介绍了油罐区砖砌防火堤的抗震验算基本原理和方法,并按照验算方法实现其通用化计算。防火堤主要受到4种荷载作用,即自重惯性力及其引起的弯矩、堤内静液压力及其引起的弯矩、堤内动液压力及其引起的弯矩、自重引起的垂直力。按不同烈度要求计算得到4种荷载作用校核堤的截面抗力和地基强度。通过两个算例检验该方法在抗震鉴定中的应用。两个防火堤典型断面的截面强度、抗滑动及抗倾覆稳定性、地基强度验算结果分别符合抗震设防7度和8度要求。防火堤作为备用体系,其抗震验算程序的通用性具有实用意义。     

汶川地震灾后农田和森林植被恢复遥感监测

2008年汶川8.0级特大地震对当地的生态系统造成了极大的破坏,为了评估5年来灾区农田和森林植被的恢复情况,利用逐年机载高分辨率遥感影像,结合星载遥感数据和地面调查数据,开展了灾区农林植被恢复状况监测。在农田恢复监测方面,结合2008年地震发生后以及2013年5月中旬的机载高分辨率遥感数据,采用目视解译的方式对汶川地震中受损农田的恢复状况进行监测与评估,同时利用GVG(GPS、Video和GIS)农情采样系统的作物种植成数调查结果,分析了灾后作物种植结构的变化。结果表明,灾区1592 ha受损农田,5年后仅有约17.5%得到了恢复和耕种使用。就耕地利用强度而言,重灾区耕地利用率较高,作物种植结构没有发生重大变化。在森林恢复状况监测方面,对典型区(岷江干旱河谷区和盆周山地区的3个重点区域)采用目视解译方式识别出森林变化,并结合大区域尺度规一化植被指数(NDVI)时间序列变化分析,对整个灾区的森林损毁和恢复情况做出评价。监测结果显示,汶川县、什邡市和绵竹市的森林植被恢复情况总体较好,但是一些坡度较大的损毁区、次生灾害频发区的森林尚未恢复,大区域尺度的统计结果显示,地震重灾区的46381 ha重度损毁森林植被和177025 ha中度损毁森林植被区域,完全恢复的区域占13.52%和25.84%,部分恢复的区域都占到50%。在自然恢复较为困难的区域,如汶川县中部和东北部、都江堰市北部、彭州市北部、什邡市北部、绵竹市北部、安县北部及北川县南部等,需要加强人工干预。遥感监测方法既适用于震后的农田和森林恢复状况动态监测,也适用于其他自然灾害发生时对灾区农田和森林植被破坏状况进行应急监测,具有实际应用价值和良好的发展前景。     

基于灰色预测法的超市选址模型研究

超市的选址是企业战略决策的重要内容之一,影响超市选址的各种因子错综复杂,无法进行精确的定量分析。文中对影响超市选址的各种因子建立二级选址指标体系,进行权重分析,同时结合选址因子结构关系模糊、动态变化随机、浮动范围不确定等灰色特性,采用灰色预测法建立超市选址模型,并利用缓冲区分析、叠置分析等GIS空间分析方法,基于Supermapobjects组件进行了二次开发实验。     

基于Photoshop的数字正射影像匀光匀色技巧

随着数字正射影像(DOM)的应用日益广泛,匀光匀色已经成为影像处理中不可或缺的一个重要环节。本文以实际生产项目为例,总结了基于Photoshop软件的数字正射影像图匀光匀色技巧,以期进一步提高数字正射影像图的色彩质量。     

基于新陈代谢灰色模型的实时GPS卫星钟差预报研究

实时GPS卫星钟差的可靠性预报是GPS实现实时精密单点定位的关键技术之一。传统的GM(1,1)模型不能及时更新新息数据,致使计算结果精度较差。本文首先介绍了常用的几个钟差模型,并利用新陈代谢GM(1,1)模型,与常用的二次多项式模型进行了对比。通过自编程序,依据某一IGS跟踪站实测的精密卫星星历数据,进行了实时的GPS卫星钟差预报,并与IGS事后精密钟差进行了比较。实验结果表明,基于该新陈代谢GM(1,1)模型估计的卫星钟差与IGS发布的最终精密钟差具有较好的有效性和一致性,这为实时GPS动态精密单点定位提供较高精度的卫星钟差产品。     

面向土地利用分类的多源遥感数据混合贝叶斯网络分类器

传统的离散型贝叶斯网络分类器是将所有变量视为离散变量,或对连续变量做离散化处理.可是离散化不可避免地存在信息损失,且在多源遥感数据的处理和分析中,连续变量的离散化会导致搜索空间的急剧增加和计算及存储量的极大开销.针对这些问题,开发了一种面向土地利用分类的多源遥感数据混合贝叶斯网络分类器,该分类器首先对问题领域的所有变量...