MODIS observations of the bottom topography and its inter-annual variability of Poyang Lake

Using MODIS 250-m resolution data, we developed a novel approach to derive the bottom topography of Poyang Lake, the largest freshwater lake of China (> 3000 km² at maximum inundation) for every year between 2000 and 2009. The approach differs from other traditional methods (sonar, Lidar, optical inversion, and Radar) but takes advantage of the fast-changing nature of the lake's inundation area. On every image, the water/land boundary is effectively a topographic isobath after correction for the water level gradient. Thus, the ~ 10/year carefully selected MODIS images provided incremental topographic isobaths, from which bottom topography was derived every year. Such-derived topographic maps were validated using limited historical data and other consistency checks. Most of the lake bottom showed an elevation of 12 m to 17 m (referenced against the elevation reference of the Woosung Horizontal Zero). Significant inter-annual variability of the bottom topography from 2000 to 2009 was found for some of the lake's bottom, with more areas associated with bottom elevation increases than decreases. The changes and inter-annual variability in the bottom topography were attributed to the combined effect of human activities (e.g., sand dredging and levee construction) and weather events. One example was the increased bottom elevation from 2002 to 2003, which was apparently due to the excessive precipitation in 2002 and the impoundment of the Three-Gorges Dam in 2003. The 10-year record of the bottom topography of this highly dynamic lake provides baseline information to monitor the impact of future engineering and management activities, to estimate the lake's water and sediment budgets, and to aid ship navigation.     

基于遥感技术的鄱阳湖面积库容估算

首先使用基于图像间逻辑运算的水体提取方法提取出鄱阳湖水体;然后将提取的水体转化为矢量格式并统计得到鄱阳湖面积;最后,将提取出的矢量水面节点处的高程值进行插值得到的水面高程图与DEM相减,得到水深图,再根据水深图和栅格大小便可得到鄱阳湖的库容。实验结果表明,本文方法可以很好地提取出鄱阳湖水体,对于鄱阳湖面积与库容的估算,估算的结果与其他学者的结果相比偏大11%左右。文中提出的利用TM影像和DEM对鄱阳湖面积和库容进行估算的方法,可作为水域动态监测的一个新思路。     

Analysing changes of the Poyang Lake water area using Sentinel-1 synthetic aperture radar imagery

Poyang Lake is the largest freshwater lake in China. Monitoring changes of its water area is essential for the conservation of important wetlands and ecological resources, and plays an important role for sustainable water use and management. Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor images are widely used for mapping waterbodies, because of their sensitivity for spectral reflectance of water. However, studies using Landsat images have limited their investigations of changes of Poyang Lake to dry season due to the impairment by cloud cover. Further limited by the rather long 16 day revisit cycle, most existing studies build on the vague assumption that Poyang Lake undergoes only relatively slow changes during this season. MODIS, in contrast, provides a very short revisit period, but has been proven not to be able to assess the water area of Poyang Lake accurately due to low spatial resolution. Therefore, the contribution of this study is to investigate recent Poyang Lake water area changes both during high- and low-water period with unforeseen temporal and spatial resolution using Sentinel-1 synthetic aperture radar (SAR) imagery. More specifically, we aim at investigating Poyang Lake’s recent water area changes in intra-month scales. During the observation period from October 2014 to March 2016, October 2014 was the month with the largest max/min water coverage ratio. Water coverage of winter in 2014 and 2015 was completely different, as a severe drought happened in 2014 and an unusual winter flood happened in 2015. Thus, this study demonstrates the potential of using Sentinel-1 SAR data to reveal intra-month variations, benefiting from the sensor’s regular observation capabilities independent of weather conditions. It is shown that Sentinel-1 SAR data, with rapid availability and free-of-charge distribution policy, as well as relatively high spatial and temporal resolutions, is becoming an indispensable data source for a detailed monitoring of important inland waterbodies and wetlands.     

Unique phenomena in Lake Baikal,Russia, imaged and studied with SAR and multi-sensor images

Lake Baikal in the Russian Federation, the deepest freshwater lake in the world, has several unique hydrological and weather regimes and other natural phenomena, including local winds, giant ice rings and oil seeps. These phenomena leave pronounced footprints on the surface of the lake and in the ice cover. They can be imaged, mapped and studied by remote sensing, in particular, by synthetic aperture radar (SAR) and multi-sensor imagery. For the first time, a study of three different phenomena – local winds, oil seeps and ice rings – in Lake Baikal has been performed primarily using remote-sensing data and images. The multi-sensor imagery that was collected and analysed, including SAR and optical images, provides both new insight into and new information on these phenomena to help understand their nature.     

Satellite-based detection of water surface variation in China’s largest freshwater lake in response to hydro-climatic drought

Poyang Lake, the largest freshwater lake in China, is an important water resource and iconic ecosystem in a region that has been subjected to extreme drought in recent years. The lake’s inundation area is heavily influenced by basin rainfall and also by the Yangtze River’s water flows. Exploring the lake’s inundation variation in response to drought conditions is of great importance for developing effective management planning for local water resources and for mitigating future drought. Here we demonstrate how satellites can reflect the lake’s inundation changes and processes under typical hydro-climatic droughts. Using Moderate Resolution Imaging Spectroradiometer (MODIS) medium-resolution data collected between 2000 and 2011, we documented the tempo-spatial variation characteristics of water inundation areas and two typical droughts in 2006 and 2011. 2006 was a hydrologic drought year, which occurred due to an abnormal change in the Yangtze River’s water flows. A dramatic shrinkage of the inundation area mainly occurred in autumn and winter. In contrast, 2011 was a hydro-climatic drought year, which resulted from the complicated influence of both the Poyang Lake basin and Yangtze River. The lake shrinkage appeared more severe during spring–summer, when about 70% of the inundation area disappeared before July. The results should be valuable for ecological conservation and water resource management in the Poyang Lake region.     

Modelling spatial‐temporal change of Poyang Lake using multitemporal Landsat imagery

Poyang Lake is a seasonal lake, exchanging water with the lower branch of the Yangtze River. During the spring and summer flooding season it inundates a large area while in the winter it shrinks considerably, creating a large tract of marshland for wild migratory birds. A better knowledge of the water coverage duration and the beginning and ending dates for the vast range of marshlands surrounding the lake is important for the measurement, modelling and management of marshland ecosystems. In addition, the abundance of a special type of snail (Oncomelania hupensis), the intermediate host of parasite schistosome (Schistosoma japonicum) in this region, is also heavily dependent on the water coverage information. However, there is no accurate digital elevation model (DEM) for the lake bottom and the inundated marshland, nor is there sufficient water level information over this area. In this study, we assess the feasibility of the use of multitemporal Landsat images for mapping the spatial‐temporal change of Poyang Lake water body and the temporal process of water inundation of marshlands. Eight cloud‐free Landsat Thematic Mapper images taken during a period of one year were used in this study. We used the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) methods to map water bodies. We then examined the annual spatial‐temporal change of the Poyang Lake water body. Finally we attempted to obtain the duration of water inundation of marshlands based on the temporal sequence of water extent determined from the Landsat images. The results showed that although the images can be used to capture the snapshots of water coverage in this area, they are insufficient to provide accurate estimation of the spatial‐temporal process of water inundation over the marshlands through linear interpolation.     

鄱阳湖面积的卫星遥感估计及其与水位关系分析

鄱阳湖水位变幅巨大,近年来旱涝灾害严重,对其进行实时监测具有重要意义。MODIS遥感数据时间分辨率很高,在水体动态监测中具有明显优势。水体提取方法多种多样,在比较不同水体提取方法的基础上,最终选用改进的归一化水体指数(MNDWI)的方法进行鄱阳湖水体提取;利用2000~2010年40期MODIS数据分析了鄱阳湖这10 a的水面面积年际演变特征及季节性变化特征,同时结合同时期的水位数据,建立了鄱阳湖面积-水位关系的模型。与地形图量测结果的对比表明,遥感解译的鄱阳湖水体面积-水位关系与根据地形图分析建立的面积-水位关系具有较好的一致性。     

Towards a practical remote-sensing model of suspended sediment concentrations in turbid waters using MERIS measurements

A new empirical index, termed the normalized suspended sediment index (NSSI), is proposed to predict total suspended sediment (TSS) concentrations in inland turbid waters using Medium Resolution Imaging Spectrometer (MERIS) full-resolution (FR) 300 m data. The algorithm is based on the normalized difference between two MERIS spectral bands, 560 and 760 nm. NSSI shows its potential in application to our study region – Poyang Lake – the largest freshwater lake in China. An exponential function (R² = 0.90, p < 0.01) accurately explained the variance in the in situ data and showed better performance for the TSS range 10–524 mg l^?1. The algorithm was then validated with TSS estimates using an atmospheric-corrected MERIS FR image. The validation showed that the NSSI algorithm was a more robust TSS algorithm than the band-ratio algorithms. Findings of this research imply that NSSI can be successfully used on MERIS images to obtain TSS in Poyang Lake. This work provided a practical remote-sensing approach to estimate TSS in the optically and hydrologically complex Poyang Lake and the method can be easily extended to other similar waters.     

Monitoring coastal erosion at the Black Sea coasts in Turkey using satellite data: A case study at the Lake Terkos,north-west Istanbul

There is justifiable cause for concern over the adequacy of our water supplies. To control and protect aquatic ecosystems and drinking water supplies, continuous monitoring is essential. An example related to the careless attitudes towards the Lake Terkos, Istanbul, which create the danger of waterlessness for citizens was given in this study. The width of the natural land barrier between the Black Sea and the Lake Terkos has decreased over the years due to illegal sand excavation along the coastline of the sea very close to the northern part of the lake. As a result of this process the offshore bar formation along the coastline has been destroyed and even removed at different parts, which caused morphological changes of the coastline along some parts of the northern coasts of the sea. In this paper, the coastal erosion during a 14-year period was monitored by using multitemporal satellite sensor data and some suggestions for precautions were made.     

Lake-area mapping in the Tibetan Plateau: an evaluation of data and methods

Lake area derived from remote-sensing data is a primary data source, because changes in lake number and area are sensitive indicators of climate change. These indicators are especially useful when the climate change is not convoluted with a signal from direct anthropogenic activities. The data used for lake-area mapping is important, to avoid introducing unnecessary uncertainty into long-term trends of lake-area estimates. The methods for identifying waterbodies from satellite data are closely linked to the quality and efficiency of surface-water differentiation. However, few studies have comprehensively considered the factors affecting the selection of data and methods for mapping lake area in the Tibetan Plateau (TP), nor of evaluating their consequences. This study tests the dominant data sets (Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data) and the methods for automated waterbody mapping on 14 large lakes (>500 km²) distributed across different climate zones of the TP. Seasonal changes in lake area and data availability from Landsat imagery are evaluated. Data obtained in October is optimal because in this month the lake area is relatively stable. The data window can be extended to September and November if insufficient data is available in October. Grouping data into three-year bins decreases the effects of year-to-year seasonal variability and provides a long-term trend that is suitable for time series analysis. The Landsat data (Multispectral Scanner, MSS; Thematic Mapper, TM; Enhanced Thematic Mapper Plus, ETM+; and Operational Land Imager, OLI) and MODIS data (MOD09A1) showed good performance for lake-area mapping. The Otsu method is used to determine the optimal threshold for distinguishing water from non-water features. Several water extraction indices, namely NDWI_McFeeters, NDWI_Xu, and AWEI_non-shadow, yielded high overall classification accuracy (92%), kappa coefficient (0.83), and user’s accuracy (~90%) for lake-water classification using Landsat data. The MODIS data using NDWI_McFeeters and NDWI_Xu showed consistent lake area (r² = 0.99) compared with Landsat data on the corresponding date with root mean square error (RMSE) values of 86.87 and 103.33 km² and mean absolute error (MAE) values of 25.7 and 29.04 km², respectively. The MODIS data is suitable for great lake mapping, which is the case for the large lakes in the TP. Although automated water extraction indices exhibited high accuracy in separating water from non-water, visual examination and manual editing are still necessary. Combined with recent Chinese high-resolution satellites, these remotely sensed imageries will provide a wealth of data for studies of lake dynamics and long-term lake evolution in the TP.     

New method and error analysis of lake retrieval with MetOp-A AVHRR images on the Tibetan Plateau

Land-surface water is an important factor influencing the regional environment and climate and is a key factor in the Tibetan Plateau, which is one of the most sensitive regions to global changes. Because of the high elevation, complex topography, and erratic weather of the Tibetan Plateau, direct measurement of the area of every lake is largely unfeasible. Moreover, complex natural geographic conditions increase the difficulty of image processing and information extraction with remote sensing because they enhance the uncertainty of quantitative data retrieved with satellites. Methods based on spectral features do not generate the expected results of lake area over the Tibetan Plateau due to a lack of distinction between water and other land objects, especially snow, vegetation, and low cloud cover. Therefore, a new method to extract lake area from satellite images in the Tibetan Plateau is needed. In this article, an automatic method was proposed to evaluate lake area during the wet season (from 1 September to 31 October) on the Tibetan Plateau with multi-day Advanced Very High Resolution Radiometer (AVHRR) remote-sensing images on board the Meteorological Operational satellite-A (MetOp-A) satellite. The method considers both spectral and textural features of lakes and does not need a cloud mask as an input. In addition, the Mixture Tuned Matched Filtering (MTMF) algorithm was applied to decompose the mixed pixels to better identify lakes and estimate the lake area. Based on daily lake identifications, the wet season’s lake data were composited with the maximum value composition (MVC) method to determine the lake area. A comparison of our work with the manually interpreted results from Landsat Thematic Mapper (TM) images and observational reports demonstrates the accuracy and reliability of our approach. However, certain factors, i.e. the sensor zenith angle of the polar-orbit satellite and the topography, can affect the lake area extracted from the remote-sensing images.     

Remote sensing of glaciers in the tropical Andes: a review

While the tropical Andes of Venezuela, Colombia, Ecuador, Peru, Bolivia, northern Chile, and northern Argentina represent more than 95% of all tropical glaciers globally, they are relatively sparsely studied in general, and particularly by using remote-sensing approaches. However, studies from the 1930s used terrestrial imaging, and aerial photographs are available from the 1950s on. In this article, we review the literature on remote sensing of the glaciers in the tropical Andes, divided into the four climatic sub-regions: inner tropics, dry outer tropics, northern wet outer tropics, and southern wet outer tropics. The majority of studies used optical remote sensing, particularly Landsat and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery, although shadows produced by steep terrain and often dense cloud cover – within the Intertropical Convergence Zone (ITCZ) of the inner tropics – are challenges to data analyses. Microwave and lidar remote sensing have been successfully employed in some studies. The vast majority of glacier monitoring studies documented glacier recessions throughout the tropical Andes since the 1950s; most results are available for the Peruvian Andes, particularly the Cordillera Balance. Recent field tests explored the use of unmanned aerial systems (UAS) and lidar in glacier research; preliminary results are promising and have the potential to lead into new research directions.     

Monitoring the dynamics of wetland inundation by random sets on multi-temporal images

General models are required for better understanding the dynamics of wetland inundations and their water regimes. Extraction by imagery snapshots and use of a crisp data model do not value the inherent uncertainties in space and time. This study addresses parameterization of a mixed Gaussian random set model in a multi-temporal analysis. The model is applied to monitor annual variation of wetland inundation extents from a series of Landsat TM images in 2004 and HJ images in 2009 on the Poyang Lake national nature reserve (PLNNR) in China. We use related indices to represent spatial uncertainties of inundated areas and to delineate the transition zone between wetland vegetation and open water. The PLNNR water regime is investigated by accumulating a series of random sets during one year and determining the water covering days (WCD) at the pixel level. Random sets provide detailed spatial configurations of the WCD which has a strong negative correlation with the underwater DEM. Comparing 2004 and 2009, the study shows that almost half of the PLNNR area experienced drought. We conclude that the mixed Gaussian random set model with three components presented in this study serves as a general method to parameterize the random set model for large datasets. Moreover, it is well suited to capture detailed information on spatial temporal dynamic of wetland inundation and contributes to our understanding of wetlands water regimes from multi-temporal images.     

Land surface temperature and emissivity retrieval by integrating MODIS data onboard Terra and Aqua satellites

This paper presents an algorithm to retrieve land surface temperature (LST) and emissivity by integrating MODIS (Moderate Resolution Imaging Spectroradiometer) data onboard Terra and Aqua satellites. For a study area, there will be four pairs of day and night observations by MODIS onboard two satellites every day. Solar zenith angle, view zenith angle, and atmospheric water vapour have first been taken as independent variables to analyse their sensitivities to the same infrared channel measurements of MODIS on both Terra and Aqua satellites. Owing to their similar influences on the same MODIS band from Terra and Aqua satellites, four pairs of MODIS data from Terra and Aqua satellites can be thought of as MODIS measurement on a satellite at different viewing angles and viewing time. Comparisons between the retrieved results and in-situ measurements at three test sites (Qinghai Lake, Poyang Lake and Luancheng in China) indicate that the root mean square (rms) error is 0.66 K, except for the sand in Poyang Lake area. The rms error is less than 0.7 K when the retrieved results are compared with Earth Observing System (EOS) MODIS LST data products using the physics-based day/night algorithm. Emissivities retrieved by this algorithm are well compared to EOS MODIS emissivity data products (V5). The proposed algorithm can therefore be regarded as complementary and an extension to the EOS physics-based day/night algorithm.     

利用长时间序列Landsat分析博斯腾湖面积变化

目的 近年来博斯腾湖面积波动较大,影响当地经济发展,掌握博斯腾湖面积变化及其与气候变化的相关规律,以指导湖泊保护和可持续利用管理策略。方法 利用Landsat影像计算1988—2014年博斯腾湖面积,监测并分析湖水面积年际变化及空间变化趋势,探讨博斯腾湖流域年降水量、年均气温变化和人类活动对湖水面积的影响,并将监测结果与MODIS数据计算的2000—2014年湖水面积以及1987—2011年实测水位数据进行对比验证。结果 结果表明,以2002年为分界线,博斯腾湖面积变化分2个阶段:1)1988—2002年,湖水面积呈增加趋势,增加288.88 km²,增长了31.62%;2)2002—2014年呈减小趋势,减小281.56 km²,减少了23.42%。根据气候条件分布差异,将博斯腾湖流域分为山区和平原区,分析发现:1988—2002年,山区年降水量和气温上升,与湖水面积呈显著正相关;2002年后,山区年降水量相对下降,平原区气温升高,人类活动用水量增加。结论 湖水面积变化受流域气候与人类活动共同作用,1988—2002年主要受山区气候影响,2002年后湖水面积缩小可能是气温升高和人类活动用水量增加导致。     

一种无线传感器网络在鄱阳湖水环境信息监控系统中的应用

针对当前鄱阳湖水环境信息监控的现状,提出一种无线传感器网络系统方案。对鄱阳湖水域水环境信息进行自动化采集,实时远程监控。为环境监测提供全面、实时的水环境信息。     

Spectral mixture analysis for bi-sensor wetland mapping using Landsat TM and Terra MODIS data

Spatial and temporal resolution is essential for understanding the spatial and temporal characteristics and dynamics of wetland ecosystems. However, single satellite imagery with both high spatial resolution and high temporal frequency is currently unavailable. Instead, the development of a bi-sensor monitoring technique utilizing spatial details of middle-to-high resolution data and temporal details of coarse spatial resolution data is highly desirable. For the initial work on our time-series bi-sensor wetland mapping, the applicability of multiple endmember spectral mixture analysis (MESMA) using single-date bi-sensor imagery with different orbiting periods was investigated. Landsat-5 Thematic Mapper (TM) and Terra Moderate Resolution Image Spectrometer (MODIS) data were utilized in the Poyang Lake area in China and the Great Salt Lake area in the USA to examine three decisive elements in utilizing MESMA: (1) the method of optimal endmember selection; (2) the threshold between two- and three-endmember models; and (3) the treatment of shade fractions. As a result, we found that (1) the number of spectra for an endmember spectrum similar to other endmember spectra meeting the modelling restrictions of maximum and minimum land-cover fractions and root mean square error (RMSE) within a class (In_CoB), the number of spectra for an endmember spectrum similar to other endmember spectra meeting the modelling restrictions outside of a class (Out_CoB), the ratio of In_CoB to Out_CoB multiplied by the inverse number of spectra within the class (CoBI) and the endmember average RMSE (EAR) were optimal endmember selection methods for the TM maps, whereas CoBI, EAR and minimum average spectral angle (MASA) were optimal endmember selection methods for the MODIS maps; (2) the MODIS maps were more sensitive to change in the two- and three-endmember modelling thresholds than the TM maps; and (3) the addition of shade fractions to dark water fractions were an appropriate shade treatment. This research demonstrated how MESMA can be applied for multi-scale mapping of wetland ecosystems, how the difference in observation dates between the TM and MODIS data affects the agreement in land-cover fractions and how spectral similarity between dark water and shade affects the agreement in land-cover fractions.     

Recent land‐cover/use change associated with land degradation in the Lake Baringo catchment,Kenya, East Africa: evidence from Landsat TM and ETM+

Many parts of East Africa are experiencing dramatic changes in land‐cover/use at a variety of spatial and temporal scales, due to both climatic variability and human activities. Information about such changes is often required for planning, management, and conservation of natural resources. Several methods for land cover/change detection using Landsat TM/ETM+ imagery were employed for Lake Baringo catchment in Kenya, East Africa. The Lake Baringo catchment presents a good example of environments experiencing remarkable land cover change due to multiple causes. Both the NDVI differencing and post‐classification comparison effectively depicted the hotspots of land degradation and land cover/use change in the Lake Baringo catchment. Change‐detection analysis showed that the forest cover was the most affected, in some sections recording reductions of over 40% in a 14‐year period. Deforestation and subsequent land degradation have increased the sediment yield in the lake resulting in reduction in lake surface area by over 10% and increased turbidity confirmed by the statistically significant increase (t = ?84.699, p<0.001) in the albedo between 1986 and 2000. Although climatic variations may account for some of the changes in the lake catchment, most of the changes in land cover are inherently linked to mounting human and livestock population in the Lake Baringo catchment.     

基于TM影像的平原湖泊水体信息提取的研究

以洪泽湖Landsat TM影像为例,分析了利用单波段阈值法和多波段增强图阈值法进行水体信息提取的差异,从而确定出不同时期不同用途所采用的最佳水体综合提取方法,即综合利用多波段谱间关系(TM2+TM3TM4+TM5)和单波段TM5建立起适合于平原湖泊水域的水体提取方法。