1987—2022年新安江水库（千岛湖）水面面积时空变化及其与水位、蓄水量的响应关系

水面面积、水位、蓄水量是水库水资源管理的重要基础数据,遥感是湖库水体提取、水位和蓄水量估算的重要技术手段。由于不同水体提取方法的适用性差异、测高卫星数据的有限时间覆盖度和开源数据集的时空分辨率不足等原因,湖库水面面积、水位、蓄水量的长时序、高频率时空变化监测仍存在一定挑战。本研究以新安江水库为研究区,结合多源遥感、气象、水文和土地利用等数据,基于Google Earth Engine云平台,运用水体指数法,分析1987—2022年新安江水库水面面积时空变化特征,构建水位—水面面积、水位—蓄水量和水面面积—蓄水量响应关系,探究水面面积时空变化成因。结果表明:(1)Landsat 5、Landsat 8和哨兵2号数据的最佳水体提取指数分别为AWEI_sh和GNDWI,F1-score分别为91.93%、91.03%和93.14%。相比于开放数据集GSWED(32.61%)、JRC GSW(76.17%)和ReaLSAT(69.76%),基于最优水体指数的水体提取结果具有最高的F1-score(91.26%);(2)时间上,1987—2022年新安江水库水面面积呈显著上升...     

基于TM影像的水体透明度反演模型——以鄱阳湖国家自然保护区为例

以江西鄱阳湖国家自然保护区为例,研究基于Landsat TM 5影像的水体透明度反演模型.结合6个时期的影像与对应的13个实测塞氏盘深度(SDD)数据建立了SDD的自然对数变换值与蓝、红波段的自然对数变换值的线性组合之间的回归模型,即ln(SDD)=-4.016-0.722ln(blue)-0.587ln(red).此模型能够解释88%的水体透明度变化.利用另外12个样点进行模型的检验.检验结果显示实际量测值与模型反演值之间的相关系数为0.93,误差标准差等于0.22 m.因此我们认为此模型获得了可以接受的结果.     

基于多时相主被动遥感的漓江水面监测与水质参数反演(2016-2020年)

以漓江流域为研究区域,以2016-2020年Landsat 8 OLI、GF-1、Sentinel-2A及Sentinel-1A逐月影像为数据源,选用归一化水指数(NDWI)、改进型归一化水指数(MNDWI)、增强型水体指数(EWI)、归一化差值池指数(NDPI)、后向散射系数(S)与主被动遥感加权指数(JQ)提取漓江...     

Mapping water quality and substrate cover in optically complex coastal and reef waters: an integrated approach

Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs.     

Estimation of water clarity in Taihu Lake and surrounding rivers using Landsat imagery

In China, the increase in exogenous-source pollutants from rivers is one of the most important causes of lake eutrophication. The application of remote sensing technology to water quality monitoring of rivers connected to these lakes has special significance for lake management at regional scales. Many research studies have estimated water clarity using Landsat imagery. However, most of this work focused on lakes or reservoirs, for which abundant water-only pixels (i.e., pure pixels of water, PPW) were available. Few of these studies have addressed rivers, especially rivers with an average width less than 100 m. In our study, we sought to determine whether water clarity in the rivers connected to Taihu Lake could be estimated using Landsat imagery. We obtained 18 Enhanced Thematic Mapper Plus (ETM+) images from 2009 for 13 rivers ranging from an average of 37.3 to 173.6 m wide. Three field campaigns conducted in May 2009, September 2009, and January 2010 were used to obtain field measurements of Secchi disk depth (SDD). Our results suggested that the widely used model, a(TM1/TM3) + b(TM1) + c, was suitable for the estimation of SDD for Taihu Lake. The brightness of the panchromatic band of ETM+ showed significant correlations with TM1, TM3 and TM1/TM3 (p < 0.001). As a result, SDD in the lake could also be estimated using the Landsat panchromatic band. The multispectral image of ETM+ did not provide adequate PPW for estimation of water clarity in rivers. However, PPW derived from the panchromatic image captured about 93% of the variation in SDD, on average, for the every worst-case scenario in the 13 rivers. Using the PPW in rivers, a significant correlation was found between the brightness of the panchromatic image and SDD (R² = 0.64, p < 0.001). Our results demonstrate that the panchromatic image of Landsat, but not the multispectral image, can be used to estimate water clarity in rivers with an average width greater than 40 m in the Taihu basin.     

Surveying earth resources by remote sensing from satellites

This paper reviews the techniques and recent results of orbital remote sensing, with emphasis on Landsat and Skylab imagery. Landsat (formerly ERTS) uses electronic sensors (scanners and television) for repetitive observations with moderate ground resolution. The Skylab flights used a wider range of electro-optical sensors and returned film cameras with moderate and high ground resolution. Data from these programs have been used successfully in many fields. For mineral resources, satellite observations have proven valuable in geologic mapping and in exploration for metal, oil, and gas deposits, generally as a guide for other (conventional) techniques. Water resource monitoring with satellite data has included hydrologic mapping, soil moisture studies, and snow surveys. Marine resources have been studied, with applications in the fishing industry and in ocean transportation. Agricultural applications, benefiting from the repetitive coverage possible with satellites, have been especially promising. Crop inventories are being conducted, as well as inventories of timber and rangeland. Overgrazing has been monitored in several areas. Finally, environmental quality has also proven susceptible to orbital remote sensing; several types of water pollution have been successfully monitored. The effects of mining and other activities on the land can also be studied. The future of orbital remote sensing in global monitoring of the Earth's resources seems assured. However, efforts to extend spectral range, increase resolution, and solve cloud-cover problems must be continued. Broad applications of computer analysis techniques are vital to handle the immense amount of information produced by satellite sensors.Abbreviations SSRERTS Symposium on Significant Results Obtained from the Earth Resources Technology Satellite - TERTSS Third Earth Resources Technology Satellite-1 Symposium National Academy of Sciences-National Research Council Research Associate at NASA Goddard Space Flight Center, 1974/75.Goddard Space Flight Center     

基于Landsat与Sentinel-3A卫星数据的当惹雍错1988-2018年湖泊水位-水量变化及归因

湖泊变化是气候变化的指示器.为探索利用单一短时间尺度的卫星水位数据源估算长时间序列的湖泊水量变化的可行性,本文利用短时间尺度（2016—2018年） Sentinel-3A合成孔径雷达高度计（SRAL）作为唯一卫星水位数据源,以藏北高原内陆湖泊当惹雍错为例,结合基于Landsat光学遥感数据提取的1988—2018年的湖泊面积,综合分析2016—2018年间的非结冰期遥感湖泊面积与遥感湖泊水位变化,基于该时段范围的水位变化-面积变化关系和水量估算公式,估算1988—2018年湖泊水位水量变化与2001—2018年的年内变化,并结合GLDAS产品数据与雪线变化情况初步探讨湖泊变化的可能原因.结果表明：当惹雍错近30年湖泊面积扩张明显,湖泊水位、水量增加显著,相比1988年,2018年的湖泊面积、水位、水量分别增加21.1 km²、5.29 m、44.75亿m³.其中1988—1998年湖泊面积-水位-水量有所减少,2000—2018年间湖泊变化总体呈增加趋势.2001—2018年内湖泊面积、水位、水量变化呈现干湿季特征.1996—2014/2015年湖泊水量变化为38.3亿/35.5亿m³,水量变化趋势、变化量与以往对应时间段的研究结果具有较强的一致性.湖泊面积扩张主要发生在水下地形平缓的东南部和中西部区域.结合气候因素与雪线变化的分析表明,湖泊水量变化受降雨、气温影响复杂,长时间年际尺度上的湖泊水量增长与气温的一致性较降水量强,湖泊湿季受降水量与气温的影响都较大,其中2008—2018年的湿季降水量、气温与水量变化散点拟合的确定性系数R²分别为0.613、0.845.该研究表明Sentinel-3A合成孔径雷达数据在湖泊水量变化估算上的潜力,为利用单一且只具有短时段数据的卫星雷达数据估算长时间序列湖泊水量变化提供依据.     

基于FAI-L方法的巢湖水域藻华提取方法研究

近年来随着人类的活动日益加剧,水体富营养化问题已经严重威胁到湖泊生态安全。为了快速并准确地获取藻华爆发的范围,本文提出浮游藻类指数线性拟合模型（FAI linear fitting model, FAI-L）。在以往的研究中,NDVI(normalized difference vegetation index)已经广泛应用于藻华的识别中,且采用坡度计算获取NDVI阈值的方法也得到验证,相对于NDVI,FAI对环境条件的改变敏感度较低,且由于FAI增加了短红外波段,能够有效地降低部分大气和薄云的影响,对藻华的识别有较高的精度,但是FAI识别藻华的阈值如何确定的问题没有有效的解决办法。本文通过建立NDVI与FAI的线性拟合方程,利用NDVI阈值确定FAI阈值,能够有效地解决FAI阈值确定问题。通过Landsat8和Sentinel-2的提取结果显示：（1）FAI-L相对于NDVI提取结果在精度上有较大提升。采用该方法对于Landsat8影像的藻华提取精度为97.16%,相对于NDVI的提取精度（91.72%）提高了5.44%。（2）以Sentinel-2数据为基础探究FAI-L的适用性情...     

Publications received by the Editor

Abstract

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m.

Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.     

Fine scale mapping of fractional tree canopy cover to support river basin management

Management of water, regionally, nationally and globally will continue to be a priority and complex undertaking. In riverine systems, biotic components like flora and fauna play critical roles in filtering water so it is available for human use and consumption. Preservation of ecosystems and associated ecosystem functions is therefore vital. In highly regulated large river basins, natural ecosystems are often supported through provision of environmental flows. Flow delivery, however, should be underpinned by rigorous monitoring to identify and prioritise biotic water requirements. Currently, large-scale monitoring solutions are scaled from remote sensing data via measurement of field evapotranspiration for woody tree vegetation species. However, as there is generally a mismatch between field data collection area and remote sensing pixel size, new methods are required to proportion tree evapotranspiration based on tree fractional canopy area per pixel. We present a novel method to derive tree fractional canopy cover (FTCC) at 20 m resolution in semi-arid and arid floodplain areas. The method employs LiDAR as a canopy area field measurement proxy (10 m resolution). We used Sentinel-1 and Sentinel-2 (radar and multispectral imagery) in a Random Forest analysis, undertaken to develop a predictive FTCC model trained using LiDAR for two regions in the Murray–Darling Basin. A predictor model combining the results of both regions was able to explain between 71%–85% of FTCC variation when compared to LiDAR FTCC when output in 10% increments. Development of this method underpins the advancement of woody vegetation monitoring to inform environmental flow management in the Murray–Darling Basin. The method and fine scale outputs will also be of value to other catchment management concerns such as altered catchment water yields related to bushfires and as such has application to water management worldwide.     

Assessment of water body change and sedimentation rate in Moulay Bousselham wetland,Morocco, using geospatial technologies

Coastal lagoons have significant biodiversity and ecologic and socio-economic interest. Several resident and migratory birds live in coastal lagoons as well as fish and other aquatic biota. Over the years, lagoons worldwide have been subject to considerable sediment deposition coming especially from soil erosion due of agricultural activities, and the lagoon's inflows have resulted in an accelerated sedimentation which can drastically affect the aquatic ecosystem balance. A new, fast, and cost-effective approach was developed, using water surface change as a proxy, to evaluate the sediment deposition rate. In the current research, this methodology was applied in the Moulay Bousselham Lagoon in Morocco, and a combination of Landsat 8 and Landsat 5 imagery acquired at four points in time over 30 years(1985-2015) was used. Following geometric correction and enhancement, the interpretation of the acquired images provided important insight on the current conditions of the water surface change using the Normalized Difference Water Index(NDWI). Several iterations were done to determine a suitable threshold for effective water surface detection. In order to validate the automatically extracted water surface features, many band combinations of Landsat and Sentinel 2 were used as references to run the accuracy assessment. The results show that the Moulay Bousselham Lagoon lost 17.60%(106 ha) of its water surface area, and 530,000 m^3 to 1,060,000 m^3 of its water volume during the last three decades.Converting water surface loss into sedimentation returned a rate of 0.58 cm/yr. These results have been confirmed by previous field work using sedimentological approaches. Proper management should be applied to sustain the vitality of this lagoon environment.     

Water quality monitoring: a combined approach to investigate gradients of change in the Great Barrier Reef, Australia

For the managers of a region as large as the Great Barrier Reef, it is a challenge to develop a cost effective monitoring program, with appropriate temporal and spatial resolution to detect changes in water quality. The current study compares water quality data (phytoplankton abundance and water clarity) from remote sensing with field sampling (continuous underway profiles of water quality and fixed site sampling) at different spatial scales in the Great Barrier Reef north of Mackay (20 degrees S). Five transects (20-30 km long) were conducted from clean oceanic water to the turbid waters adjacent to the mainland. The different data sources demonstrated high correlations when compared on a similar spatial scale (18 fixed sites). However, each data source also contributed unique information that could not be obtained by the other techniques. A combination of remote sensing, underway sampling and fixed stations will deliver the best spatial and temporal monitoring of water quality in the Great Barrier Reef.     

Remote sensing of snow and ice / La télédétection de neige et de glace

Abstract

Monitoring of snow and ice on the Earth's surface will require increasing use of satellite remote sensing techniques. These techniques are evolving rapidly. Active and passive sensors operating in the visible, near infrared, thermal infrared, and microwave wavelengths are described in regard to general applications and in regard to specific USA or USSR satellites. Meteorological satellites (frequent images of relatively crude resolution) and Earth resources satellites such as Landsat (less frequent images of higher resolution) have been used to monitor the areal extent of seasonal snow, but problems exist with cloud cover or dense forest canopies. Snow mass (water equivalent) can be measured from a low-flying aircraft using natural radioactivity, but cannot yet be measured from satellite altitudes. A combination of active and passive microwave sensors may permit this kind of measurement, but not until more is known about radiation scattering in snow. Satellite observations are very useful in glacier inventories, correcting maps of glacier extent, estimating certain mass balance parameters, and monitoring calving or surging glaciers. Ground ice is virtually impossible to monitor from satellites; ice on rivers and lakes can be monitored only with very high-resolution sensors. Microwave sensors, due to their all-weather capability (the ability to see through clouds) provide exciting data on sea ice distribution. Analysis of digital tapes of satellite data requires the archiving and scanning of huge amounts of data. Simple methods for extracting quantitative data from satellite images are described.     

Monitoring turbidity with IRS-1A data

This study was undertaken to determine the application of Indian Remote Sensing Satellite 1A–Linear Imaging Self scanning (IRS-1A–LISS-I) spectral digital data for estimating turbidity in an inland water body. IRS-1A–LISS-I spectral digital data for 20 October 1988 for the Tawa Reservoir were analysed and compared with field measurements of turbidity and used to develop simple and multiple regression equations to estimate turbidity in the surface water. The turbidity values were positively correlated with increasing wavelength LISS-I bands, 1, 2 and 3 of the visible region of the spectrum. Simple linear regression analyses indicate that LISS-I band 3 (0·62–0·68 μm) is the best for prediction purpose. Multiple regression equations have higher correlations (r=0·91). For validation, the equations were tested using LISS-I data for 28 September 1988 for the Tawa Reservoir. IRS-1A–LISS-I data provide a solid foundation for further development of remote sensing as a practical tool in monitoring water quality. The regression technique has strong potential for the future application of IRS-1A–LISS-I data in monitoring water quality of inland water bodies and estuaries. © 1997 John Wiley & Sons, Ltd.     

Management of Cultural Heritage Sites Using Remote Sensing Indices and Spatial Analysis Techniques

Sustainable management and exploitation policies as well as suitable conservation and mitigation strategies are mandatory to preserve cultural heritage and to reduce threats, weathering phenomena, and human actions that may produce significant deterioration and alteration of cultural heritage and “its environment”. In this context, remote sensing technologies can offer useful data to timely update information and documentation and set up reliable tools for systematic monitoring of cultural properties. In this study, multi-temporal and multi-sensor satellite data from Corona, Landsat, Spot, Quickbird, and Sentinel-2A have been exploited along with spatial analysis to investigate the area of the Theban temples at west Luxor (Egypt), severely threatened by uncontrolled urban sprawl. The results from our analyses showed that the urban expansion continuously occurred during the whole investigated period causing an increasing in urban areas around (1) 1.316 km² from 1967 to 1984, (2) 1.705 km² from 1984 to 2000, (3) 0.978 km² from 2000 to 2003, (4) 2.314 km² from 2003 to 2011, and (5) 1.377 km² from 2011 to 2017. The random urban expansion caused bad sewage networks and high groundwater depth which in turn affected the archaeological areas directly (as evident on a landscape view) and indirectly by causing changes (growing) in the level of ground water depth and increasing and accelerating weathering phenomena. The quantification and mapping of urban sprawl enabled us not only to quantify and spatially characterize urban sprawl but also to create a model to mitigate the impact and provide some operational recommendations to protect the archaeological site. Outcomes from our analysis pointed out that today the tremendous availability of advanced remote sensing data has opened new prospectives unthinkable several years ago.     

基于Landsat 8光学影像的巴基斯坦Awaran M_w7.7地震形变监测及参数反演研究

2013年9月24日巴基斯坦俾路支省(Balochistan)境内的阿瓦兰县(Awaran)发生了Mw7.7级地震.本文利用覆盖该地区的Landsat 8数据,基于影像配准的方法获取了该次地震的同震形变场,并运用地统计的方法对形变结果进行精度评定.针对传统四叉树算法中近场和远场中采样密度的不均匀性,以及噪音区域对数据降采样和反演结果收敛性的影响,本文提出了改进的四叉树算法对点的密度和形变梯度进行合理兼顾.最后利用光学影像获取的形变结果和数据的精度水平,基于Okada弹性半空间形变模型反演了该地震的震源参数和断层滑动分布.结果表明,地震断层北倾47°,滑动以左旋走滑为主,断层的西南部兼具少量的倾滑运动分量,断层滑动主要集中分布在断层面0~15km深度范围,最大滑动量达10m.反演获得的地震标量矩为4.68×1020 N·m,震级约为Mw7.75级.本文的研究结果可以为该地区的地壳应力变化研究和地震灾害评估提供依据,同时为Landsat 8光学影像应用于地震的形变研究提供参考.     

On the dynamics and morphology of extensive tidal mudflats: Integrating remote sensing data with an inundation model of Cook Inlet, Alaska

A new method of integrating satellite remote sensing data and inundation models allows the mapping of extensive tidal mudflats in a sub-Arctic estuary, Cook Inlet (CI), Alaska. The rapid movement of the shorelines in CI due to the large tides (~10 m range) is detected from a series of Landsat imagery taken at different tidal stages, whereas GIS tools are used to identify the water coverage in each satellite image and to extract the coordinates of the shoreline. Then, water level along the shoreline for each satellite image is calculated from the observed water level at Anchorage and the statistics of an inundation model. Several applications of the analysis are demonstrated: 1. studying the dynamics of a tidal bore and the flood/ebb processes, 2. identifying climatic changes in mudflats morphology, and 3. mapping previously unobserved mudflat topographies in order to improve inundation models. The method can be used in other regions to evaluate models and improve predictions of catastrophic floods such as those associated with hurricane storm surges and tsunamis.     

MODIS Terra Collection 6 fractional snow cover validation in mountainous terrain during spring snowmelt using Landsat TM and ETM+

Daily swath MODIS Terra Collection 6 fractional snow cover (MOD10_L2) estimates were validated with two‐day Landsat TM/ETM + snow‐covered area estimates across central Idaho and southwestern Montana, USA. Snow cover maps during spring snowmelt for 2000, 2001, 2002, 2003, 2005, 2007, and 2009 were compared between MODIS Terra and Landsat TM/ETM + using least‐squared regression. Strong spatial and temporal map agreement was found between MODIS Terra fractional snow cover and Landsat TM/ETM + snow‐covered area, although map disagreement was observed for two validation dates. High‐altitude cirrus cloud contamination during low snow conditions as well as late season transient snowfall resulted in map disagreement. MODIS Terra's spatial resolution limits retrieval of thin‐patchy snow cover, especially during partially cloudy conditions. Landsat's image acquisition frequency can introduce difficulty when discriminating between transient and resident mountain snow cover. Furthermore, transient snowfall later in the snowmelt season, which is a stochastic accumulation event that does not usually persist beyond the daily timescale, will skew decadal snow‐covered area variability if bi‐monthly climate data record development is the objective. As a quality control step, ground‐based daily snow telemetry snow‐water‐equivalent measurements can be used to verify transient snowfall events. Users of daily MODIS Terra fractional snow products should be aware that local solar illumination and sensor viewing geometry might influence fractional snow cover estimation in mountainous terrain. Cross‐sensor interoperability has been confirmed between MODIS Terra and Landsat TM/ETM + when mapping snow from the visible/infrared spectrum. This relationship is strong and supports operational multi‐sensor snow cover mapping, specifically climate data record development to expand cryosphere, climate, and hydrological science applications. Copyright © 2013 John Wiley & Sons, Ltd.     

基于Hyperion数据的太湖水体叶绿素a浓度遥感估算

通过对2004年8月19日太湖Hyperion高光谱遥感数据的处理和分析,文章首先采用比值和一阶微分处理技术进行了叶绿素a浓度的估算．为了弥补此两种方法在模型的适用性和通用性方面的不足,本文尝试了利用混合光谱分析模型进行太湖水体叶绿素a浓度的提取和成图．实验结果说明高光谱遥感数据Hyperion可以进行水体叶绿素a浓度的监测,并且作为高光谱处理技术之一的混合光谱分析技术是水体叶绿素a浓度估算的另一条佳径．     

青藏高原内陆湖泊变化的遥感制图

青藏高原上的内陆湖泊群是气候变化的敏感指示器,获取近几十年来湖泊变化的动态信息对研究区域气候及环境变化具有重要的意义.本文讨论了多时相遥感湖泊变化研究中的几个关键问题--湖泊变化季节性因素、湖泊变化信息的提取以及大区域湖泊变化的分析方法,并利用Landsat长时间序列遥感数据,制作青藏高原1970s,1990s,200...