Searching for ancient gold mines in Filippoi area,Macedonia, Greece,using Worldview-2 satellite imagery

The study area is located near the town of Filippoi, north of the city of Kavala in northern Greece, known from ancient times for its rich gold mines, situated inside hydrothermal alteration zones (Fe–Mn oxide minerals). A Very High-Resolution (0.5 m pixel size) image of Worldview-2 satellite was digitally enhanced, yielding target areas of potential ore existence and lineaments. Ground-truth that followed digital image processing, revealed abandoned ancient mines, slags and ore occurrences. Also, a number of lineaments delineated on the satellite image were verified as faults.     

森林资源监测中GF-2卫星影像波段配准误差分析

通过对GF-2卫星影像正射校正及波段模拟配准误差试验,分析GF-2卫星正射校正方法的选择以及不同配准误差下对GF-2卫星影像自动分类结果的影响;最后介绍GF-2遥感影像在森林资源监测应用中的初步测试。研究结果表明:正射校正时,当校正精度要求控制在RMS2时,控制点数量选择范围在85~95间较为合理,且控制点数在90个时,RMS值最小;经有理函数模型与卫片模型比较后,卫片模型校正精度较高;以目视判读为主时,实践中建议使用三次卷积重采样法输出结果最好;波段模拟配准误差试验中,配准误差与各地类面积变化间存在显著的线性关系;对于森林面积监测时,配准误差应小于0.3个像元。此研究可为新型国产卫星数据在森林资源监测中的应用提供参考。     

影像不同空间尺度对鲁甸植被分析的影响

针对植被指数和植被覆盖度与遥感影像空间尺度的关系对高分辨率影像在植被分析中的运用具有重要影响的问题,该文提出一种确定最佳分辨率的方法。以云南鲁甸县茨院乡为研究区,先对原始影像(Worldview-2)进行重采样处理,生成一系列低分辨率影像;计算13组数据的NDVI并利用像元二分模型反演出植被覆盖度;运用信息熵理论和按照局部方差的思路等两种方法,定量分析该区植被分析的最佳分辨率。实验结果表明,随着空间分辨率的降低,NDVI值域区间呈现收敛趋势;植被覆盖度分级图斑斑块数量急剧减少,而所占面积比则保持相对平稳;信息熵中的信息量也随之减少。分析结果认为,该区进行基于Worldview-2影像植被分析的最佳空间分辨率为12m。     

应用Slepian局部谱方法解算中国大陆重力场球谐模型

根据经典的球谐函数方法,为满足正交化要求,观测数据需要覆盖整个球面,而对于地表局部测量数据,则无法应用球谐方法解算重力场模型。针对此问题,采用Slepian局部谱分析方法解算中国大陆范围内的实测重力场变化数据,并以GOCE卫星球谐函数解作为已知模型,评估由于实际陆地重力测点的非均匀分布对球谐函数解的误差影响。通过计算多个阶次中国大陆局部范围的Slepian基函数分布;采用GOCE卫星获得重力场模型的前72阶球谐系数作为已知结果,评价实际测点非均匀分布的解算有效性,并针对中国大陆地区采用Slepian基函数进行解算,通过模型对比选择最优截段项数;针对2005—2008年中国大陆地区流动重力测量获得的重力场变化信号进行解算,获得了72阶重力场变化模型。     

Mapping the expansion of galamsey gold mines in the cocoa growing area of Ghana using optical remote sensing

Artisanal gold mining (galamsey) and cocoa farming are essential sources of income for local populations in Ghana. Unfortunately the former poses serious threats to the environment and human health, and conflicts with cocoa farming and other livelihoods. Timely and spatially referenced information on the extent of galamsey is needed to understand and limit the negative impacts of mining. To address this, we use multi-date UK-DMC2 satellite images to map the extent and expansion of galamsey from 2011 to 2015. We map the total area of galamsey in 2013 over the cocoa growing area, using k-means clustering on a cloud-free 2013 image with strong spectral contrast between galamsey and the surrounding vegetation. We also process a pair of hazy images from 2011 and 2015 with Multivariate Alteration Detection to map the 2011–2015 galamsey expansion in a subset, labelled the change area. We use a set of visually interpreted random sample points to compute bias-corrected area estimates. We also delineate an indicative impact zone of pollution proportional to the density of galamsey, assuming a maximum radius of 10 km. In the cocoa growing area of Ghana, the estimated total area of galamsey in 2013 is 27,839 ha with an impact zone of 551,496 ha. In the change area, galamsey has more than tripled between 2011 and 2015, resulting in 603 ha of direct encroachment into protected forest reserves. Assuming the same growth rate for the rest of the cocoa growing area, the total area of galamsey in 2015 is estimated at 43,879 ha. Galamsey is developing along most of the river network (Offin, Ankobra, Birim, Anum, Tano), with downstream pollution affecting both land and water.     

“高分二号”卫星在黄土地质灾害解译中的应用研究

黄土高原地区地质灾害多发频发,危害严重,应用亚米级的高分二号(GF-2)卫星影像数据,提取地质灾害信息,并对室内解译结果进行了野外查证。本文提出了以GF-2卫星数据为主要信息源,进行地质灾害解译的技术方案;并以宁夏南部黄土高原区为例,验证了该方法的适用性,为规模化地开展基于国产高分系列卫星的黄土高原地区地质灾害遥感解译提供了可行的技术方案;通过GF-2卫星影像与常用的国内外卫星数据用于地质灾害信息判释的对比研究,认为GF-2卫星影像对于地质灾害信息的识别能够满足地质灾害遥感解译的要求,GF-2卫星影像的应用具有较高的性价比和显著的经济社会效益。     

内蒙古东部春季三类沙尘天气气溶胶散射系数及其与PM10、能见度相关性分析

利用内蒙古东胜、锡林浩特两站2004~2006年春季（3~5月）积分浊度计的观测资料,结合同期PM10质量浓度、大气能见度等资料,分析了背景、扬沙、沙尘暴、强沙尘暴等不同强度沙尘天气气溶胶散射系数的分布特征,讨论了不同强度沙尘天气过程中散射系数、PM10、能见度的日变化规律,以及不同强度沙尘天气过程中散射系数与PM10质量浓度、散射系数与能见度的相关关系。结果表明:散射系数能够很好地反映沙尘天气强度;随沙尘天气强度增强,散射系数日变化从双峰型向单峰型转变;沙尘天气强度较弱时,PM10与散射系数的日变化不相似,强沙尘暴过程中PM10与散射系数的日变化有一定的相似性;能见度与散射系数日变化趋势相反;散射系数与PM10质量浓度呈正相关性,沙尘天气越强,相关性越好,背景、扬沙、沙尘暴、强沙尘暴相关系数分别为0.201、0.809、0.898和0.953;散射系数与能见度有指数相关关系,随沙尘天气强度增强二者相关性逐渐增强,背景、扬沙、沙尘暴、强沙尘暴相关系数分别为-0.773、-0.870、-0.918和-0.940。     

AMSR2辐射率资料同化对台风“山神”分析和预报的影响研究

在WRFDA-3DVar（Weather Research and Forecasting model's 3-dimensional variational data assimilation）的框架下,添加了新的探测器AMSR2（Advanced Microwave Scanning Radiometer 2）微波辐射率资料的同化模块,实现了AMSR2辐射率资料在中小尺度同化系统中的有效使用。台风"山神"（Son-Tinh）直接同化AMSR2资料的个例试验结果表明,AMSR2资料可以很好的探测出台风的形态,并且与没有同化该资料的控制试验相比,同化AMSR2辐射率资料可以有效提高模式分析场的质量,进一步提高了台风中心气压,最大风速和台风路径的预报。     

2013-2015年合肥市PM2.5重污染特征研究

综合利用中国环境监测网公布的合肥市2013-2015年大气污染物浓度数据和合肥市气象站的常规气象资料,以及激光雷达探测资料、公益性行业（气象）专项（GYHY201206011）获得的气溶胶离子成分分析结果,分析了合肥市PM_2.5重污染（日均浓度>150 μg/m3）特征。结果表明:（1）2013-2015年,合肥市PM_2.5浓度和重污染天数空间分布差异明显,东北部多、西南部少,1月各站差异最大。除了低浓度日（日均浓度≤35 μg/m3）,PM_2.5浓度都存在明显的日变化,午后低、早晚高,且随着污染程度加重,早上峰值出现时间推后。（2）重污染日臭氧以外的气态污染物浓度都显著上升。（3）重污染日常伴随着霾和轻雾天气,以稳定、小风天气为主,重污染日白天相对湿度偏高、风速偏小,600 m以下的消光系数显著增大且峰值高度降低。（4）重污染日PM_2.5中水溶性无机离子含量增高,其中NO₃-含量的占比增加最多,超过了SO₄2-的占比。      

Road condition assessment by OBIA and feature selection techniques using very high-resolution WorldView-2 imagery

Accurate information on the conditions of road asphalt is necessary for economic development and transportation management. In this study, object-based image analysis (OBIA) rule-sets are proposed based on feature selection technique to extract road asphalt conditions (good and poor) using WorldView-2 (WV-2) satellite data. Different feature selection techniques, including support vector machine (SVM), random forest (RF) and chi-square (CHI) are evaluated to indicate the most effective algorithm to identify the best set of OBIA attributes (spatial, spectral, textural and colour). The chi-square algorithm outperformed SVM and RF techniques. The classification result based on CHI algorithm achieved an overall accuracy of 83.19% for the training image (first site). Furthermore, the proposed model was used to examine its performance in different areas; and it achieved accuracy levels of 83.44, 87.80 and 80.26% for the different selected areas. Therefore, the selected method can be potentially useful for detecting road conditions based on WV-2 images.