Mediterranean forest mapping using hyper-spectral satellite imagery

Mediterranean forests are characterized by spatiotemporal heterogeneity that is associated with Mediterranean climate, floristic biodiversity and topographic variability. Satellite remote sensing can be an effective tool for characterizing and monitoring forest vegetation distribution within these fragmented Mediterranean landscapes. The heterogeneity of Mediterranean vegetation, however, often exceeds the resolution typical of most satellite sensors. Hyper-spectral remote sensing technology demonstrates the capacity for accurate vegetation identification. The objective of this research is to determine to what extent forest types can be discriminated using different image analysis techniques and spectral band combinations of Hyperion satellite imagery. This research mapped forest types using a pixel-based Spectral Angle Mapper (SAM), nearest neighbour and membership function classifiers of the object-oriented classification. Hyperion classification was done after reducing Hyperion data using nine selected band combinations. Results indicate that the selection of band combination while reducing the Hyperion dataset improves classification results for both the overall and the individual forest type accuracy, in particular for the selected optimum Hyperion band combination. One shortcoming is that the performance of the best selected band combination was superior in terms of both overall and individual forest type accuracy when applying the membership classifier of the object-oriented method compared to SAM and nearest neighbour classifiers. However, all techniques seemed to suffer from a number of problems, such as spectral similarity among forest types, overall low energy response of the Hyperion sensor, Hyperion medium spatial resolution and spatiotemporal and spectral heterogeneity of the Mediterranean ecosystem at multiple scales.     

A new approach of combining aerial photography with satellite imagery for landslide detection

Subsequent rainfall after a strong earthquake can easily trigger landslides. Aerial photography is always available after a strong earthquake but not always available in a timely manner after a subsequent rainfall following the earthquake. Sometimes, only panchromatic imagery is available because of its relatively low cost and large cover capacity. To detect multi-temporal landslides induced by earthquake and its post long-term effect, in company of other factors such as subsequent rainfall, traditionally, it needs to carry out image classification multi-times to calculate the variance information. Therefore, the accuracy will be affected by accumulated errors from multi-classification, and the process is very time-consuming. In this paper, a new semi-automatic approach combing aerial photograph with satellite imagery was proposed for rapid mapping of multi-temporal landslides. The approach can enhance the change information of each landslide event in one detection process. In addition, slope units were introduced to separate the detected conjoint landslides. Chenjiaba area, which located in the highest seismic intensity zone of Wenchuan earthquake in Beichuan, China, and had a strong rainfall 4 months later, was selected as a case study to demonstrate the usefulness of this methodology. Accuracy assessment was carried out by comparing those extracted ones with a manually prepared landslide inventory map. Correctly detected were 90.1 and 94.2 % for earthquake-induced landslides and new landslides, respectively. Results show that this approach is capable of mapping different temporal landslides efficiently and quickly.     

Study of regional linears in central Sicily by satellite imagery

New regional linears where discovered in Sicily using images produced by satellite-borne sensors. In particular a group of linears crossing both the Caltanissetta central basin and the “nappes” of the northern coast has been investigated.Several techniques of processing the remotely sensed data have been employed in order to enhance the lineations and to evaluate their character.The features observed from space have been compared to aerial stereo pairs and checked by ground control. It was found that the linears generally correspond to actual faulting on the “rigid” formations of the northern overthrusting area, whereas they are produced mainly by the alignment of morphological features on the “plastic” formations of Caltanisetta basin.The general geological and geophysical features of the Sicilian region are discussed and the implications of the new findings are introduced.A programme for further geological and geophysical studies is suggested.     

Optical satellite imagery for quantifying spatio-temporal dimension of physical exposure in disaster risk assessments

This work addresses the use of remote sensing imagery to quantify the built environment and its spatial and temporal changes. It identifies building footprint map, building location map and built-up area map as information products that can be used to quantify physical exposure, one of the variables required in disaster risk assessments. The paper also reviews urban land use maps and urban classes in land cover maps as potential source for deriving exposure information. The paper focuses on the latest generation of satellite-borne remote sensing imaging systems that deliver high-resolution optical imagery able to resolve buildings and other three-dimensional man-made constructions. This work also reviews the semantics, the spatial unit used to define physical exposure, image processing procedures and change techniques.     

Application of the GRACE satellite mission for solving geological and geographic problems

In this paper we provide a literature review of the geological and geographic problems that were successfully solved via the application of the Gravity Recovery And Climate Experiment (GRACE) satellite mission data. GRACE is a gravitational satellite mission whose purpose is the precise mapping of variations of the Earth’s gravity field. The data have high resolution, which provides the opportunity to solve many geological and geographical problems.     

非传统稳定同位素锗的测试进展及其地质应用

Ge具有亲硫、亲铁、亲石和亲有机质的特性,被广泛应用于矿床学、环境科学等学科。然而,由于测试技术和手段的限制,Ge同位素在地球科学中的应用还很有限,但已显示出较好的应用潜力。本文在综合前人研究成果的基础上,结合笔者最新的研究工作,对Ge同位素的测试技术和手段等方面做了较全面的总结,内容包括Ge同位素化学前处理方法的研究进展、Ge同位素测试过程中仪器产生的质量歧视的校正方法。同时,亦对自然界样品中Ge同位素的组成、Ge同位素分馏机制及应用等方面做了评述。     

Mapping of settlements in high-resolution satellite imagery using high performance computing

Classifying urban land cover from high-resolution satellite imagery is challenging, and those challenges are compounded when the imagery databases are very large. Accurate land cover data is a crucial component of the population distribution modeling efforts of the Oak Ridge National Laboratory’s (ORNL) LandScan Program. Currently, LandScan Program imagery analysts manually interpret high-resolution (1–5 m) imagery to augment existing satellite-derived medium (30 m) and coarse (1 km) resolution land cover datasets. For LandScan, the high-resolution image archives that require interpretation are on the order of terabytes. The goal of this research is to automate human settlement mapping by utilizing ORNL’s high performance computing capabilities. Our algorithm employs gray-level and local edge-pattern co-occurrence matrices to generate texture and edge patterns. Areas of urban land cover correlate with statistical features derived from these texture and edge patterns. We have parallelized our algorithms for implementation on a 64-node system using a single instruction multiple data programming model (SIMD) with Message Passing Interface (MPI) as the communication mode. Our parallel-configured classifier performs 30–40 times faster than stand-alone alternatives. We have tested our system on IKONOS imagery. The early results are promising, pointing towards future large-scale classification of human settlements at high-resolution.     

Extracting building stock information from optical satellite imagery for mapping earthquake exposure and its vulnerability

The paper focuses on automatic extraction of building stock information for quantifying physical exposure and its vulnerability from High and Very High Resolution (VHR) optical satellite imagery. We use two case studies. In Sana’a (Yemen), we use automatic techniques to extract the building stock as well as building height that is used to characterize its vulnerability. In Port-au-Prince (Haiti)—the area affected by the 2010 earthquake—we map the building stock based on a pre-disaster imagery, and we show the added value of area-based information when added to point-based damage assessment from visual change interpretation of post-disaster aerial images. This paper shows that VHR imagery can be used to locate and quantify the building stock and its height. This paper also shows that damages measured from changes detected from pre- and post-disaster imagery can in principle map and provide vulnerability information related to the structural fragility of the building stock.     

裂变径迹技术及其地质应用

裂变径迹技术以样品用量少、封闭温度低以及测年范围广等优势,被广泛应用于地质学研究中。完全退火或部分退火样品可有效记录岩体的冷却-剥露历史,限制构造活动起始时间,探讨上覆岩石的风化剥蚀历史与矿床保存变化之间的关系,定量化矿床隆升剥蚀量,实现找矿预测; 锆石裂变径迹封闭温度对应天然气生成温度区间,可运用于油气勘探研究计算中; 近年来结合元素含量分析的裂变径迹技术还可进行物源分析,LA-ICP-MS技术的引进为测量低U含量矿物的径迹带来了曙光。系统总结了磷灰石与锆石裂变径迹退火特性的研究成果,以及温度、化学成分、结晶各向异性及D_par值等因素对磷灰石径迹退火特性数据解释可能产生的影响,锆石径迹热稳定性的降低主要受制于辐射损伤效应。实验室退火特性研究为了解繁杂的径迹退火化学动力机制提供了重要的理论参考,但在实际的数据解释中需结合地质背景,以获得更为清晰的地质热事件演化研究时间格架。结合径迹测年在矿床、山体隆升剥蚀、盆地热史等研究的典型案例分析,以期为裂变径迹应用的相关研究提供参考。     

基于多时相卫星影像滨海卫星新城扩张的时空特征分析——以上海临港新城为例

基于多时相Landsat卫星影像,综合运用基于像元变化的直接比较法和基于光谱分类的分类后比较法(分类精度达85.83%),提取出临港新城2002~2015年三个时相的城镇用地信息,分析城市扩张的变化特征,并通过相关社会经济统计资料对城市扩张的驱动因子进行相关研究。结果表明,2009年成建区面积比2002年增加18.745km~2,为2002年的2.12倍,2015年成建区面积较2009年增加24.945km~2,为2009年的0.9倍,年增长面积是前一阶段的1.33倍,处于城市空间扩张的第二大阶段,发展较为快速。运用单一因子相关分析法,计算得到经济因子和城镇用地面积的相关系数略大于人口因子与城镇用地面积的相关系数,且均与城镇用地面积成显著的正相关,而政策作为经济建设的导向推动因子,因此认为该区域驱动力主要表现在政策因素作用下的社会经济发展。     

Assessment of different topographic corrections in AWiFS satellite imagery of Himalaya terrain

The influence of topographic effects in optical satellite imagery is not investigated very extensively in the Himalayan terrain. The topographic variability causes a problem of differential illumination due to steep and varying slopes in rugged Himalayan terrain. Therefore, topographic corrections are essential for qualitative and quantitative analysis of snow cover applications. The present paper discusses the implementation of different topographic correction models on AWiFS sensor onboard IRS P6 satellite images and the qualitative and quantitative comparative analysis in detail. Both the Lambertian and non-Lambertian assumptions have been considered in the present analysis with the aim to explore best suitable empirical model for rugged terrain. The main topographic methods implemented are:

Using high-resolution satellite imagery to provide a relief priority map after earthquake

After the earthquake occurrence, collecting correct information about the extent of damage is essential for managing critical conditions and allocating limited resources. The prepared building damage maps sometimes bring about waste of time required for rescuing individuals under the rubble by wrongly conducting rescue teams toward regions with a lower rescue priority. In this research, an algorithm based on using a proposed standard at database level was developed to prioritize damaged buildings by considering five key elements of land use type, the degree of damage to buildings, the land use differentiation index, time of the highest population density in each land use, and time of disaster’s incidence. The steps of the proposed method which was implemented in the MATLAB environment include: detecting buildings on the pre- and post-event imagery, implementing texture features for each candidate building, choosing the optimal features by genetic algorithm, determining the degree of building damage in three classes of negligible damage, substantial damage, and heavy damage by using the difference between chosen features as inputs of the designed neurofuzzy inference system. Data collected from field observations were compared to the output obtained from the proposed algorithm. This comparison presented a general accuracy of 88% and Kappa coefficient of 79% in the classification of buildings into three damage classes. The proposed standard then was used for classifying damaged buildings into relief priorities of high, medium, and low. Findings revealed that the relief priority map could be a basis for correct guidance of relief and rescue teams during crucial times following earthquakes.     

团簇同位素的基本原理与地质应用*

团簇同位素指的是含有2个及2个以上的重同位素结合在一起形成的同位素体。团簇同位素的数值定义为同位素体的相对丰度偏离随机分布状态的程度。测量该相对丰度较低的同位素体需要高精度的质谱仪,难点在于利用同位素组成已知的参考气体和不同同位素组成的加热气体,以获得绝对参考体系下的数值。团簇同位素体的相对丰度非常低,但是具有非常独特的物理和化学性质。比如碳酸盐矿物中¹³C¹⁸O¹⁶O的丰度对温度具有敏感性,而与矿物的全岩同位素以及矿物形成时期的流体性质无关,因此可以利用测量的碳酸盐团簇同位素来获得矿物的生长温度,再利用矿物的氧同位素(δ¹⁸O),根据传统的氧同位素温度计原理,可以进一步获得矿物的生长流体(水)的氧同位素。目前,团簇同位素温度计已经在古气候(温度)重建、古高度恢复、碳酸盐岩的成岩作用以及甲烷的成因分析等方面得到了广泛应用。评估深埋高温过程引起的C-O化学键重置对碳酸盐团簇同位素的影响、测试仪器产生对团簇同位素的非线性误差校正、以及其他丰度更低的团簇同位素体或大分子的团簇同位素的测量,是下一步的研究方向。     

Precipitation rate climatology related to different cloud types using satellite imagery over Iran

Cloud types have a substantial influence on precipitation. This paper presents a study of the monthly variations of daytime different cloud types over Iran using data collected from Moderate-resolution Imaging Spectroradiometer (MODIS) aboard Terra during 2001–2015, MODIS aboard Aqua during 2002–2015, International Satellite Cloud Climatology Project (ISCCP) H-series cloud type data during 2001–2009 and precipitation rate associated with different cloud types using Tropical Rainfall Measuring Mission (TRMM) satellite products during 2001–2009. Different cloud types were determined using MODIS cloud optical thickness and cloud top pressure data based on ISCCP algorithm. The results showed that stratocumulus and cumulus clouds have maximum occurrence frequency over marine areas especially southern seas. The maximum frequency of nimbostratus and deep convective occurrence occurred over mountainous regions particularly at the time of Aqua overpass and cirrus and cirrostratus are observed over southeast of Iran during warm months due to monsoon system. Altostratus cloud is extended in each month except January, at the time of Terra overpass while nimbostratus is seen at the time of Aqua overpass during warm months in the study area. Cumulus and altocumulus clouds have shown remarkable frequency in all months especially over marine regions during warm and fall months. The higher value of precipitation rate is related to altostratus with a rate approximately 7 mm/h at the time of Terra overpass during April. Altostratus has the maximum recorded precipitation rate except in Nov., Dec., Sep., and Jan. at the time of Terra overpass, whereas the maximum precipitation rate is linked to nimbostratus cloud activity (up to 5 mm/h) except for March, April, and Sep. at the time of Aqua overpass. Deep convective (up to 1.32 mm/h), cirrostratus (up to 1.11 mm/h), and cirrus (0.02 mm/h) are observed only in warm months. The results were compared with ISCCP cloud types so that precipitation rate classified from low to high and Spearman rank correlation was calculated. The results showed good agreement between these two cloud type data; however, there were few notable difference between them.     

Spectral wheat yield prediction modeling using SPOT satellite imagery and leaf area index

As wheat represents the main staple food and strategic crop in Egypt and worldwide and since remote sensing satellite imagery is the tool to obtain synoptic, multi-temporal, dynamic, and time-efficient information about any target on the Earth, the main objective of the current study is to use remote sensing satellite imagery to generate remotely sensed empirical preharvest wheat yield prediction models. The main input parameters of these models are spectral data either in the form of spectral reflectance data released from Satellite Pour l’Observation de la Terre (SPOT) 4 satellite imagery or in the form of spectral vegetation indices. The other input factor is leaf area index (LAI) that was measured by LAI Plant Canopy Analyzer. The four spectral bands of SPOT4 imagery are green, red, near-infrared, and middle infrared; the five vegetation indices that are forms of ratios between red and near-infrared bands are normalized difference vegetation index, ratio vegetation index, soil-adjusted vegetation index, difference vegetation index, and infrared percentage vegetation index. Another vegetation index is green vegetation index that is calculated through a ratio between green band and near-infrared band. Each of the above-mentioned factors was used as an input factor against wheat yield to generate wheat yield prediction models. All generated models are site-specific limited to the area and the environment and could be applicable under similar conditions in Egypt. The study was carried out in Sakha experimental station by using the dataset from two wheat season 2007/2008 and 2009/2010. The total wheat area was 1.3 ha cultivated by Sakha 93 cultivar. Modeling and validation process were carried out for each season independently. Modeled yield was tested against reported yield through two common statistical tests; the standard error of estimate between modeled yield and reported yield, and the correlation coefficient for a direct regression analysis between modeled and reported yield with each generated model. Generally, as shown from the correlation coefficient of the generated models, green and middle infrared bands did not show good accuracy to predict wheat yield, while the other spectral bands (red and near-infrared) bands showed high accuracy and sufficiency to predict yield. This was proven through the correlation coefficient of the generated models and through the generated models with the wheat crops for the two seasons. Accordingly, the green vegetation index that is generally calculated from green and near-infrared bands showed relatively lower accuracy than the rest of the vegetation index models that are calculated from red and near-infrared bands. LAI showed high accuracy to predict yield as shown from the statistical analysis. The models are applicable after 90 days from sowing stage and applicable in similar regions with the same conditions.     

LA-MC-ICP-MS锆石Hf同位素的分析方法及地质应用

本研究利用Thermo Finngan Neptune型多接收等离子质谱和Newwave UP213 激光剥蚀系统对两个国际锆石标准和一个实验室锆石标准进行了系统的测定.测得的TEMORA、GJ1和FM02锆石标准的176Hf/177Hf比值分别为0.282700±64(2SD,N=22),0.282008±25(2SD,N=26)和0.282967±44(2SD,N=27),该结果在误差范围内与文献报道值完全一致.采用不同的剥蚀直径对FM02锆石标准进行了对比测定,结果在误差范围内是一致的.从分析结果来看,GJ1和FM02的Hf同位素比值变化范围较小,是Hf同位素LA-MC-ICP-MS测试的理想标准锆石.文中还对四个不同地区的锆石Hf同位素进行了测定,结合前人研究,对其成因和物质来源进行了初步探讨.     

硒同位素测试技术进展及其地质应用

硒同位素作为非传统稳定同位素的重要组成部分,由于具多价态、多质量数、同位素分馏效应大的特点,已成为目前发展最迅速的同位素之一.本文在综合前人研究成果基础上,结合笔者最新的研究成果,对硒同位素的测试技术做了较全面总结,内容包括样品的化学前处理(TCF技术)、在线的氢化物发生器系统、质谱测试技术、参考物质的标定等,并就自然界中硒同位素的组成、分馏机制及应用潜力做了评述.     

双频激电法在地质勘查工作中的两个实例

本文由两个实际地质勘查工作的应用例子,通过双频激电法与可控源音频大地电磁法勘探工作结果的对比,介绍双频激电法在地质找矿工作中的应用效果。同时根据实际工作体会,指出双频激电法存在的主要问题。