珊瑚礁遥感研究进展

珊瑚礁是生物多样性和初级生产力最高的海洋生态系统之一,对人类社会与海洋生态环境的健康和可持续发展有重要作用,而珊瑚礁又是中国南海主要的国土类型,国家因此越来越重视对南海珊瑚礁的规划、管理、建设与保护。珊瑚礁的调查与探测则是进行珊瑚礁活动的基础与依据,而遥感则在珊瑚礁的大范围探测方面具有很大的潜力,所以国内外已经存在很多利用遥感对珊瑚礁进行调查与探测的研究与应用。本文将按照被动遥感和主动遥感的顺序,客观地阐述国内外珊瑚礁遥感研究与应用的进展,探讨珊瑚礁遥感研究与应用的发展趋势,并尝试总结中国珊瑚礁遥感的机遇和挑战。其中被动遥感包括珊瑚礁地形与水深的遥感、珊瑚礁底质与地貌的遥感、珊瑚礁岸线变化与稳定性的遥感以及珊瑚礁环境的遥感等,而主动遥感则包括珊瑚礁水深的机载激光雷达遥感、珊瑚礁地貌的船载声学遥感和珊瑚礁地形的星载微波遥感等。结果发现,国内珊瑚礁遥感研究与应用的整体水平落后于国外:虽然在部分数据处理方面具有比国外更先进的技术,但相应的应用基础研究仍然达不到国外的广度与深度。因此,国内的珊瑚礁遥感研究仍需要鼓励珊瑚礁学者更多的参与与合作,以便在硬件设备和数据处理等方面加强针对珊瑚礁遥感的研究,进而融合多种手段而实现珊瑚礁遥感的工程化应用。     

Artificial Neural Network (ANN) Based Inversion of Benthic Substrate Bottom Type and Bathymetry in Optically Shallow Waters - Initial Model Results

Ocean-colour remote sensing in optically shallow waters is influenced by contribution from the water column depth as well as by the substrate type. Therefore, it is required to include the contribution from the water column and substrate bottom type for bathymetry estimation. In this report we demonstrate the use of Artificial Neural Network (ANN) based approach to spectrally distinguish various benthic bottom types and estimate depth of substrate bottom simultaneously in optically shallow waters. We have used in-water radiative transfer simulation modeling to generate simulated top-of-the-water column reflectance the four major benthic bottom types viz. sea grass, coral sand, green algae and red algae using Hydrolight simulation model. The simulated remote sensing reflectance, for the four benthic bottom types having benthic bottom depth up to 30 m were generated for moderately clear waters. A multi-layer perceptron (MLP) type neural network was trained using the simulated data. ANN based approach was used for classification of the benthic bottom type and simultaneous inversion of bathymetry. Simulated data was inverted to yield benthic bottom type classification with an accuracy of ~98% for the four benthic substrate types and the substrate depth were estimated with an error of 0% for sea grass, 1% for coral sand and 1–3% for green and red algae up to 25 m, whereas for substrate bottom deeper than 25 m depth the classification errors increased by 2–5% for three substrate bottom types except sea grass bottom type. The initial results are promising which needs validation using the in-situ measured remote sensing reflectance spectra for implementing further on satellite data.     

An improved atmospheric correction algorithm for hyperspectral remotely sensed imagery

There is an increased trend toward quantitative estimation of land surface variables from hyperspectral remote sensing. One challenging issue is retrieving surface reflectance spectra from observed radiance through atmospheric correction, most methods for which are intended to correct water vapor and other absorbing gases. In this letter, methods for correcting both aerosols and water vapor are explored. We first apply the cluster matching technique developed earlier for Landsat-7 ETM+ imagery to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data, then improve its aerosol estimation and incorporate a new method for estimating column water vapor content using the neural network technique. The improved algorithm is then used to correct Hyperion imagery. Case studies using AVIRIS and Hyperion images demonstrate that both the original and improved methods are very effective to remove heterogeneous atmospheric effects and recover surface reflectance spectra.     

Shoreline and coral reef ecosystem changes in gulf of Mannar, Southeast coast of India

Changes in shoreline, coral reef and seafloor have been mapped using remote sensing satellite data of IRS LISS-III (1998), IRS LISS-II (1988), Survey of India Topographic sheet (1969), Naval Hydrographic Chart (NHO) 1975 and bathymetry data (1999) with ARC-INFO and ARC-VIEW GIS. The analysis of multi-date shoreline maps showed that 4.34 and 23.49 km2 of the mainland coast and 4.14 and 3.31 km² areas of island coast have been eroded and accreted, respectively, in the Gulf of Mannar. The analysis of multi-date coral reef maps showed that 25.52 km² of reef area and 2.16 km² of reef vegetation in Gulf of Mannar have been lost over a period of ten years. The analysis of multi-date bathymetry data indicates that the depth of seafloor has decreased along the coast and around the islands in the study area. The average reduction of depth in seafloor has been estimated as 0.51m over a period of twenty four years. The increased suspended sediment concentration due to coastal and island erosion, and raised reef due to emerging of coast by tectonic movement are responsible for coral reef degradation in the Gulf of Mannar. Validation by ground truth has confirmed these results.     

航天高光谱遥感器CHRIS的水体图像大气校正

CHRIS(Compact High Resolution Imaging Spectrometer)是欧空局于2001年10月发射的PROBA-1卫星上搭载的探索性高光谱遥感器,它具备高空间分辨率、多角度观测、高光谱成像等特点,为水质遥感监测提供不可多得的数据源。基于卫星遥感图像定量监测水质,一个关键步骤就是进行精确的大气校正,提取水面反射率。相比陆地遥感图像,水面反射率是弱信号,对大气校正的要求更高。6S(Second Simulation of SatelliteSignal in the Solar Spectrum)和MODTRAN(MOderate resolution TRANsmittance code)是两种常用的大气辐射传输模型。本文选取基于6S的REMS(Remote Sensing Environmental Monitoring System)和基于MODT-RAN的ACORN(Atmospheric CORrection Now)两种大气校正软件,对太湖梅梁湾的三景不同成像角度CHRIS图像进行大气校正,将大气校正后的图像水体反射率与地面同步实测水体反射率进行比较分析。结果表明,经过大气校正的CHRIS图像得到的水面反射率与实测反射率波形十分地接近,在全部波长范围内的相关系数达到90%。分析实测的水体反射率角度特征,发现图像的角度特征更明显。三个观测角度下反射率之间的各差值都呈现出在绿光波段较大,在红光和近红外波段偏小的特点,这和实测结果相符。ACORN校正后的图像的角度特征更好地与实测结果吻合。     

海岸带地理环境遥感监测综述

海岸带作为连接海洋和陆地系统的特殊地理地带,与人类的生存与发展密切相关,但其自然和生态环境极其脆弱和敏感。气候变化和人类活动给海岸带环境带来了巨大压力,导致其生态环境不断恶化。随着技术的发展,近年来遥感技术已成为海岸带地理环境监测的重要手段之一,在海岸带规划、管理和保护中扮演着举足轻重的角色。本文对遥感技术在海岸带地理环境监测典型应用(土地利用/覆盖、土壤质量、植被、海岸线、水色、水深和水下地形及灾害)中的主要数据源、方法、结果和局限性进行归纳和总结,并对其未来发展提出展望。     

湖泊遥感研究进展与展望

湖泊遥感作为一门新型交叉学科,是湖泊科学和遥感科学的重要分支.本文探讨了湖泊遥感科学的研究对象、内容和方法,通过梳理国内外总体研究进展,总结出湖泊遥感的5个发展趋势:(1)关注问题,从兴趣导向发展到问题导向;(2)观测手段,从地基遥感/中分辨率卫星发展到高分辨率/高光谱/无人机;(3)算法算力,从单机版经验/机理模型发...     

Temperature and emissivity separation and mineral mapping based on airborne TASI hyperspectral thermal infrared data

Thermal infrared remote sensing (8–12 μm) (TIR) has great potential for geologic remote sensing studies. TIR has been successfully used for terrestrial and planetary geologic studies to map surface materials. However, the complexity of the physics and the lack of hyperspectral data make the studies under-investigated. A new generation of commercial hyperspectral infrared sensors, known as Thermal Airborne Spectrographic Imager (TASI), was used for image analysis and mineral mapping in this study. In this paper, a combined method integrating normalized emissivity method (NEM), ratio algorithm (RATIO) and maximum–minimum apparent emissivity difference (MMD), being applied in multispectral data, has been modified and used to determine whether this method is suitable for retrieving emissivity from TASI hyperspectral data. MODTRAN 4 has been used for the atmospheric correction. The retrieved emissivity spectra matched well with the field measured spectra except for bands 1, 2, and 32. Quartz, calcite, diopside/hedenbergite, hornblende and microcline have been mapped by the emissivity image. Mineral mapping results agree with the dominant minerals identified by laboratory X-ray powder diffraction and spectroscopic analyses of field samples. Both of the results indicated that the atmospheric correction method and the combined temperature–emissivitiy method are suitable for TASI image. Carbonate skarnization was first found in the study area by the spatial extent of diopside. Chemical analyses of the skarn samples determined that the Au content was 0.32–1.74 g/t, with an average Au content of 0.73 g/t. This information provides an important resource for prospecting for skarn type gold deposits. It is also suggested that TASI is suitable for prospect and deposit scale exploration.     

基于CHRIS数据的三峡坝区水体叶绿素浓度遥感监测

本文探讨利用新一代微卫星遥感数据CHRIS/PROBA定量反演三峡坝区叶绿素(Chl)浓度的方法。首先对CHRIS/PROBA高光谱影像进行去条带、几何校正、辐射校正、大气校正等预处理,得到水体像元的遥感反射率;然后结合三峡坝区水质,分析了悬浮物对叶绿素浓度反演的影响,采用半经验回归方法建立了叶绿素浓度反演算法;最后在对算法验证的基础上,将模型应用到经过一系列预处理的影像中,得到三峡坝区叶绿素浓度的遥感反演结果,并对反演结果进行了分析。分析表明,CHRIS/PROBA影像在三峡坝区水质的遥感监测中是可用的,且反演结果精度较高。     

陆基（地基、岸基）水环境遥感的提出、实践和初步应用

断面监测是准确掌握中国地表水水质和水环境变化特征,开展水环境成因机制分析、评价评估、治理修复和管理考核的重要基石。提高监测立体化、自动化、智能化水平是未来水生态环境监测的重要方向,可以切实提高中国生态环境监测现代化能力。本文针对全国地表水环境断面监测,首次提出陆基（地基、岸基）水环境遥感概念,有效补充和完善传统的卫星遥感和断面监测技术方法。通过与杭州海康威视数字技术股份有限公司（简称“海康威视”）开展合作研发,自主研制了国产高光谱成像仪,于2020-07-31—2020-08-17在太湖开展了复杂天况和水况场景下陆基（地基、岸基）水环境遥感实践应用,构建了透明度、悬浮物、总氮、总磷等关键水质参数高精度遥感反演算法,反演精度可达80%及以上。将相关算法植入高光谱成像仪中获得关键水质参数高频动态变化过程,精细刻画其时间演化过程。太湖陆基（地基、岸基）水环境遥感实践表明,在全国地表水监测断面架设国产高光谱成像仪开展关键水质参数高频精准观测具有广泛应用前景和市场推广价值,可以与卫星和无人机遥感形成天—空—地立体化遥感监测体系,结合断面人工巡测和自动观测开展协同监测。     

闪电河流域水循环和能量平衡遥感综合试验

遥感试验是进行遥感原理的验证、遥感模型与反演方法的发展、遥感产品的真实性检验,推动卫星计划的论证实施及其观测在地球系统科学中应用的重要途径.闪电河流域水循环和能量平衡遥感综合试验以滦河上游闪电河流域为核心试验区,以地球表层系统的水循环过程和能量平衡为研究对象,旨在通过天—空—地—体化的观测手段,针对不同典型地表类型开展...     

大气PM2.5遥感制图研究进展

遥感技术具有时空大范围、低成本的独特优势,已经成为定量监测大气PM_(2.5)污染时空分布的重要手段。本文综述了大气PM_(2.5)遥感制图的进展:首先,对大气PM_(2.5)遥感反演方法进行了归纳,以及总结了现有大气PM_(2.5)遥感反演验证方法的适用条件与局限性;其次,对卫星反演大气PM_(2.5)合成产品偏差校正和大气PM_(2.5)无缝制图进行了梳理;最后总结了大气PM_(2.5)遥感制图的前沿研究方向。     

从高光谱遥感影像提取植被信息

遥感可以快速有效地监测大面积植被的种类、特性、长势等各类信息。高光谱遥感数据因其特有的高光谱分辨率特性使其在植被生态环境领域具有极大的应用潜力。植被信息作为生态环境评价的重要参数对区域生态环境的监测和建设具有重要的意义。本文基于云南省鹤庆县北衙的高光谱遥感数据用SAM方法对植被信息进行了提取,参考光谱使用ASD光谱辐射仪采集的植被光谱曲线。文中对高光谱遥感影像的辐射定标和大气校正进行了研究,针对影响光谱辐射仪采集的主要因素采取了相应的措施,并对光谱曲线分类及参考光谱曲线的选取进行了研究。将选取出的参考光谱曲线与大气校正后的遥感影像进行SAM匹配提取出植被信息,经过与实地调查资料比较并计算总体精度和kappa系数,计算结果达到预期精度。最后将分类结果转换为矢量图,经过投影转换为大地坐标后制作出北衙植被分布图。     

高光谱热红外遥感：现状与展望

高光谱热红外数据中蕴含着丰富的长波光谱信息,可以更精细的揭示地气耦合过程导致的辐射变化,反映热红外谱段特有的地物诊断特征,同时高光谱特性也可以为热红外关键特征参数的病态反演问题提供更合理的假设和约束条件,具有重要的研究价值和应用前景。高光谱热红外遥感技术自诞生起,在吸纳多光谱热红外遥感技术的基础上迅速发展,成为热红外遥感领域的重要研究方向和突破点。然而,当前高光谱热红外遥感存在着可用数据不足,处理方法传统,反演精度有限,应用难以有效实施等问题。为进一步明晰高光谱热红外遥感的研究进展和现存挑战,本文在高光谱热红外相关文献深入分析的基础上,梳理了高光谱热红外研究的发展脉络和热点,介绍了现有国内外主要的高光谱热红外传感器,分析了高光谱大气效应校正、地表温度和发射率分离以及地气关键特征参数一体化反演的现状和问题,总结了相关典型行业应用,展望了高光谱热红外的发展方向,以期为未来高光谱热红外研究工作的开展提供借鉴和帮助。     

大气气溶胶成分遥感研究进展

大气气溶胶成分的复杂变化导致其在气候变化评估中具有很高的不确定性。气溶胶成分遥感利用遥感观测的气溶胶光学—微物理参数,定量估计整层大气气溶胶主要成分含量,具有实时快速、空间覆盖、保持气溶胶自然状态等特点。本文介绍了近年来气溶胶成分遥感在理论基础和观测研究方面的进展情况。首先,在简要回顾反演算法发展的基础上,以目前较先进的成分遥感分类模型(包括黑碳、棕色碳、沙尘、非吸光有机物、细粒子无机盐、海盐和水)为例,详细分析了气溶胶成分遥感反演的思路。据此提出了基于气溶胶综合光学—微物理特性(包括光学吸收/散射、粒径尺度、形状等敏感性特征参数)的气溶胶成分遥感识别方法。之后,结合气溶胶混合方式,讨论了复折射指数计算方法及其对成分反演的影响,并给出了利用同步化学采样观测验证气溶胶成分遥感的一些结果示例。最后,结合观测手段拓展、成分模型优化、反演精度提升、应用能力推广等4个方向,展望了大气气溶胶成分遥感的发展趋势,及其在全球气候变化评估等领域的应用。     

基于大气温度和水汽含量改进HJ-1B地表温度反演

为了提高地面气象站稀少地区地表温度遥感反演的精度,本文基于多源遥感数据的优势,首先利用MODIS影像获取研究区像元尺度上平均大气水汽含量;然后利用同时相的HJ-1B影像估算区域地表比辐射率,再采用温度-植被指数法获取近地表大气温度;最后将以上3个参数输入单窗体算法,改进其地表温度反演的精度。研究结果表明,改进单窗体算法反演地表温度与地面实测温度的偏差小于1 K,为地面气象站点稀少的植被覆盖区域提供了一种可行的精确遥感反演地表温度方法。     

Spectral characterization of coastal sediments using Field Spectral Libraries,Airborne Hyperspectral Images and Topographic LiDAR Data (FHyL)

Beach dune systems are important for coastal zone ecosystems as they provide natural sea defences that dissipate wave energy. Geomorphological models of this near-shore topography require site-specific sediment composition, grain size and moisture content as inputs. Hyperspectral, field radiometry and LiDAR remote sensing can be used as tools by providing synoptic maps of these properties. However, multi-remote sensing of near-shore beach images can only be interpreted if there are adequate bio-geophysical or empirical models for information extraction. Our aim was thus to model the effects of varying sediment properties on the reflectance in both field and laboratory conditions within the FHyL (Field Spectral Libraries, Airborne Hyperspectral Images and Topographic LiDAR) procedure, using a multisource dataset (airborne Hyperspectral – MIVIS and topographic LiDAR – Hawk-eye II and field radiometry). The methodology consisted of (i) acquisition of simultaneous multi-source datasets (airborne Hyperspectral – MIVIS and topographic LiDAR – Hawk-eye) (ii) hyperspectral measurements of sediment mixtures with varying physical characteristics (moisture, grain size and minerals) in field and laboratory conditions, (iii) determination and quantification of specific absorption features, and (iv) correlation between the absorption features and physical parameters cited above.Results showed the potential of hyperspectral signals to assess the effect of moisture, grain-size and mineral composition on sediment properties.     

Detecting anomalous CO2 flux using space borne spectroscopy

Over the time-scale, earth's atmospheric CO₂ concentration has varied and that is mostly determined by balance among the geochemical processes including burial of organic carbon in sediments, silicate rock weathering and volcanic activity. The best recorded atmospheric CO₂ variability is derived from Vostok ice core that records last four glacial/interglacial cycles. The present CO₂ concentration of earth's atmosphere has exceeded far that it was predicted from the ice core data. Other than rapid industrialization and urbanization since last century, geo-natural hazards such as volcanic activity, leakage from hydrocarbon reservoirs and spontaneous combustion of coal contribute a considerable amount of CO₂ to the atmosphere. Spontaneous combustion of coal is common occurrence in most coal producing countries and sometimes it could be in an enormous scale. Remote sensing has already proved to be a significant tool in coalfire identification and monitoring studies. However, coalfire related CO₂ quantification from remote sensing data has not endeavoured yet by scientific communities because of low spectral resolution of commercially available remote sensing data and relatively sparse CO₂ plume than other geological hazards like volcanic activity. The present research has attempted two methods to identify the CO₂ flux emitted from coalfires in a coalmining region in north China. Firstly, a band rationing method was used for column atmospheric retrieval of CO₂ and secondly atmospheric models were simulated in fast atmospheric signature code (FASCOD) to understand the local radiation transport and then the model was implemented with the inputs from hyperspectral remote sensing data. It was observed that retrieval of columnar abundance of CO₂ with the band rationing method is faster as less simulation required in FASCOD. Alternatively, the inversion model could retrieve CO₂ concentration from a (certain) source because it excludes the uncertainties in the higher altitude.     

Optimization of Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery,in situ data with chemometrics to evaluate nutrients in the Shenandoah River,Virginia

Abstract

Phosphorus and nitrogen have a strong influence on water resource and remote sensing technology has demonstrated that water quality monitoring over a greater range of temporal and spatial scales can be used to overcome these constraints. This research was designed to demonstrate the feasibility of combining remotely-sensed water quality observation and chemometric techniques to estimate water quality in the Shenandoah River. We used Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) imagery, combined with a partial least squares analysis to characterize the spatial distribution of nutrients in the Sheanadoah river. ARCHER retrievals for phosphorous with cross-validation show high sensitivity in estimating water quality in the Shenandoah River with the Bentonville in the South Fork, with an R2 of 0.93 sensitivity. Using the significance level of 0.05, data from the summer of 2014 showed that the p-value was 0.00 for both nitrogen and phosphorous. Results show retrieval method is transferable.     

Application of hyperspectral remote sensing reflectance data to photochemical rate calculations in the Duplin River,a tidal river on the coast of Georgia,USA

Estuaries are photochemically dynamic environments with high carbon loads and relatively small areas. The small area poses problems for large-scale satellite-based remote sensing calculations, where the resolution is too coarse to distinguish land from water. Airborne remote sensing instruments have the potential to reveal the dynamics of these areas with fine-scale resolution. In June 2006, hyperspectral remote sensing imagery, using an AISA Eagle instrument, was collected over the tidal Duplin River, Georgia, USA. A dark-water updated version of the SeaUV algorithm was applied to the AISA remote sensing image to determine diffuse attenuation constants in the ultraviolet and calculate surface photochemical production rates of two inorganic products – carbon monoxide (CO) and carbon dioxide (CO₂). For an average day in June at the study site, the modeled photoproduction rates for CO₂ and CO averaged ~7 × 10^?1 nmol C/day/cm³ and ~3.5 × 10^?2 nmol C/day/cm³, respectively.