Satellite remote sensing of freshwater macrophytes and the influence of water clarity

In regions with thousands of lakes, large scale regional macrophyte surveys are rarely done due to logistical difficulties and high costs. We examined whether remote sensing can be used for regional monitoring of macrophytes in inland lakes using a field study of 13 lakes in Michigan, USA (nine model development lakes and four model testing lakes). Our objectives were: (1) to determine if different levels of macrophyte cover, different growth forms or specific species could be detected using the Landsat-5 TM sensor, and (2) to determine if we could improve predictions of macrophyte abundance and distribution in lakes by including sediment type or measures of water clarity (Secchi disk transparency, chlorophyll a, phytoplankton biovolume, or water color) in our models. Using binomial and multinomial logistic regression models, we found statistically significant relationships between most macrophyte measures and Landsat-5 TM values in the nine model development lakes (percent concordant values: 58–97%). Additionally, we found significant correlations between three lake characteristics and the TM values within lake pelagic zones, despite the inability of these variables to improve model predictions. However, model validation using four lakes was generally low, suggesting caution in applying these models to other lakes. Although the initial model development results suggest that remote sensing is a potentially promising tool for regionally assessing macrophytes, more research is necessary to refine the models in order for them to be applied to unsampled lakes.     

大亚湾水质遥感监测指标分析

我国沿海经济高速发展,对近海岸水质环境影响极大。传统的近海岸水质监测手段不仅成本大,而且空间信息有限,难以对相关海域进行全面、准确的监测与评价;利用遥感的手段进行近海岸水质监测可克服这些局限。利用遥感进行水质评价,需要建立相应的指标体系。论文以大亚湾为例,分析了大亚湾的水质环境现状,讨论了具有光学敏感性或热敏感性的水质因子特性,指出水温、悬浮物及叶绿素是大亚湾水质遥感监测与评价的首选指标。讨论了悬浮物、叶绿素的污染表征物特征,以及在近海岸、湖泊及河流水质研究中的重要指示意义,同时建议将叶绿素作为常规监测指标纳入我国海水水质评价体系。     

Pelagic zonation of water quality and phytoplankton in the Great Lakes

Analysis of aquatic ecosystem data collected from large water bodies must consider spatial variations. A suite of pelagic survey stations exists for the Laurentian Great Lakes, but little is known about their redundancy. We present a strategy to delineate the lakes into zones based on water quality and phytoplankton biovolume. Water samples were collected from 72 sites in two seasons (spring and summer) from 2007 to 2010 in all five lakes. Integrated samples were analyzed for phytoplankton biovolume and nine water quality parameters. We conducted cluster analysis, principal components analysis and non-metric multidimensional scaling methods for water quality and phytoplankton taxon-specific biovolume for the Great Lakes basin and for each lake separately. There were significant lake-to-lake differences, and based on lake-specific analyses, Lake Superior, Lake Michigan and Lake Erie were each divided into three zones; Lake Huron and Lake Ontario were each grouped into two zones. The zones identified by water quality and phytoplankton provide an understanding of spatial distributions for evaluating monitoring data.     

Remote sensing for lake research and monitoring – Recent advances

Lakes are important ecosystems providing various ecosystem services. Stressors such as eutrophication or climate change, however, threaten their ecological functions. National and international legislations address these threats and claim consistent, long-term monitoring schemes. Remote sensing data and products provide synoptic, spatio-temporal views and their integration can lead to a better understanding of lake ecology and water quality. Remote sensing therefore gains increasing awareness for analysing water bodies. Various empirical and semi-analytical algorithms exist to derive remote sensing indicators as proxies for climate change or ecological response variables. Nevertheless, most monitoring networks lack an integration of remote sensing data. This review article therefore provides a comprehensive overview how remote sensing can support lake research and monitoring. We focus on remote sensing indicators of lake properties, i.e. water transparency (suspended particulate matter, coloured dissolved organic matter, Secchi disc depth, diffuse attenuation coefficient, turbidity), biota (phytoplankton, cyanobacteria, submerged and emerged aquatic vegetation), bathymetry, water temperature (surface temperature) and ice phenology (ice cover, ice-on, ice-out). After a brief background introducing principles of lake remote sensing we give a review on available sensors and methods. We categorise case studies on remote sensing indicators with respect to lake properties and processes. We discuss existing challenges and benefits of integrating remote sensing into lake monitoring and ecological research including data availability, ready-to-use tools and accuracies.     

浒苔遥感监测研究进展

浒苔大规模集聚形成的绿潮灾害是海洋生态系统主要生态环境问题之一,基于卫星遥感影像监测浒苔及其扩展动态已成为一种及时有效的手段。对国内外浒苔遥感监测方面文献进行归纳整理,认为光学遥感数据、多波段比值法是最常用的遥感数据和监测方法。对遥感监测浒苔机理进行了阐述,并对分类方法进行评价认为监督分类法解译精度不高。目前单波段阈值法和多波段比值法应用广泛,但在监测漂浮浒苔和混合象元解译存在不足。辐射传输模型法能有效提高信息解译的精度,但还处于起步阶段。遥感监测浒苔灾害的未来发展需要提高影像空间分辨率,深入研究监测方法,进行多种平台和多源遥感数据相结合,并由定性走向定量,从而建立健全遥感监测预警系统。     

Using Satellite Remote Sensing to Estimate the Colored Dissolved Organic Matter Absorption Coefficient in Lakes

Given the importance of colored dissolved organic matter (CDOM) for the structure and function of lake ecosystems, a method that could estimate the amount of CDOM in lake waters over large geographic areas would be highly desirable. Satellite remote sensing has the potential to resolve this problem. We carried out model simulations to evaluate the suitability of different satellite sensors (Landsat, IKONOS, and the Advanced land Imager [ALI]) to map the amount of CDOM in concentration ranges that occur in boreal lakes of the Nordic countries. The results showed that the 8-bit radiometric resolution of Landsat 7 is not adequate when absorption by CDOM at 420 nm is higher than 3 m⁻¹. On the other hand, the 16-bit radiometric resolution of ALI, a prototype of the next generation of Landsat, is suitable for mapping CDOM in a wider range of concentrations. An ALI image of southern Finland was acquired on 14, July 2002 and in situ measurements were carried out in 15 lakes (18 stations). The results showed that there is a high correlation (R² = 0.84) between the 565 nm/660 nm ALI band ratio and the CDOM absorption coefficient in lakes. Analysis of 245 lakes in the acquired satellite image showed a normal distribution of CDOM concentration among the lakes. However, the size distribution of lakes was highly skewed toward small lakes, resulting in the CDOM concentration per unit lake area being skewed toward high values. We showed that remote sensing enables synoptic monitoring of the CDOM concentration in a large number of lakes and thus enables scaling up to the level of large ecosystems and biomes.     

1986—2019年新疆湖泊变化时空特征及趋势分析

干旱区湖泊是区域水资源系统的重要组成部分,不仅在维系区域生态系统平衡上发挥重要支撑作用,而且也对区域气候变化和人类活动具有重要的指示意义。基于Google Earth Engine(GEE)遥感云计算平台,以Landsat 5/7/8卫星遥感影像为主要数据源,分析了1986—2019年新疆维吾尔自治区湖泊数量以及面积变化的时空特征,并从气候要素变化、人类活动干扰等方面初步探讨了新疆湖泊变化的主要原因。结果表明：1986—2019年间,气温升高使得冰川积雪融水增加,新疆湖泊整体上呈现出扩张趋势。然而受人类活动的干扰程度以及地形海拔等因素,这种趋势存在显著的空间差异。全球变暖背景下,由于受到丰富稳定的雪冰融水的补给,受人为干扰较小的青藏高原北部地区湖泊呈现显著扩张。相反由于环天山地区强烈的人类活动以及冰川加速退缩影响,该区域湖泊面积持续高位波动状态。     

基于遥感与实地调查对潜在可造林区乔木林和灌草地的比较

气候变化引起祁连山东部地区可适植被类型改变,探究植被类型转换的效果对生态环境可持续发展十分重要,但其转换方式及效果仍有待研究,此外传统植被调查的方法有诸多局限性,不能满足大尺度持续的监测,而遥感监测可以弥补这一劣势。基于遥感和样地调查以祁连山生态交错区甘沟小流域为研究地点,对原有灌草地和植树造林的乔木林进行比较,探究二者土壤理化性质、草本植物多样性及植被归一化指数（NDVI）,增强植被指数（EVI）,植被水分指数（NDMI）,水分胁迫指数（MSI）,叶绿素红外指数（CI）,陆地叶绿素指数（MTCI）的差异。结果表明仅有水分相关指标有显著性差异,其中造林造成浅层土壤水分显著降低（P<0.01）,4-5月份MSI和NDMI造林区植被水分高于灌草地（P<0.01）,7-8月份两种植被类型水分指数以及其余指数无显著性差异,另外造林后的土壤有机质出现了轻微下降（P>0.05）。遥感指数和样地调查指标相关性分析中,土壤有机质和Shannon多样性指数与CI成正相关（P<0.05）,植被覆盖度与NDMI成负相关（P<0.05）,由于覆盖度较低的灌草地EVI和NDVI被高估,覆盖度和EVI与NDVI相关性不显著。综合遥感指数和实地调查分析,短时间造林时间内乔木林牺牲了部分土壤水分,提高了植被盖度,且目前造林并未对当地环境产生胁迫,但对生态环境的改善并不明显。基于遥感和样地调查揭示了潜在植被类型转换区原有灌草地和植树造林区的差异,并探讨遥感在小尺度范围内植被监测上的适用性,为植被建设和遥感监测植被状况提供借鉴。     

城市黑臭水体遥感监测与筛查研究进展

持续改善城市水环境,加强黑臭水体整治,不仅是“水污染防治行动计划(水十条)”的国家战略需求,也是人民群众的关注热点.国内外以往的研究侧重于黑臭水体的成因、评价方法和治理措施,而关于遥感手段监测黑臭水体的研究十分少见,很难满足国家的业务化监测需求.本文总结了黑臭水体遥感监测与筛查迫切需要解决的问题,包括完善城市黑臭水体的识别和分级标准,开展遥感监测黑臭水体的关键技术研究,构建城市黑臭水体遥感筛查体系.其中,重点归纳了核心关键技术,主要包括: 面向黑臭水体提取的高分影像预处理技术,城市水体提取技术,黑臭水体分类技术,基于星、空、地基遥感的黑臭水体识别与分级模型.本文总结基于高分遥感技术手段监测与筛查城市黑臭水体的研究进展、提出研究思路,将利于全面掌握黑臭水体的空间分布状况、治理进展情况,为城市黑臭水体整治提供有力的技术支撑.     

Primary production in a tropical reservoir in Sri Lanka*

Primary production was measured every 2 weeks during 16 months (N = 33) in Tissawewa, a tropical shallow reservoir in the lowlands of south-east Sri Lanka. Results are interpreted in relation to selected environmental conditions such as oxygen concentrations, water temperature, Secchi-disc depth, wind force, conductivity, and morphoedaphic index and water level fluctuations. Because of regularly reoccurring high wind speeds the water column is well mixed. Daily gross primary production per unit area was plotted as a function of the algal biomass per unit area over the euphotic zone. Chlorophyll-a concentration in the euphotic zone was taken as measure for the algal biomass. The literature comparisons showed that the primary productivity in Tissawewa was in the same range as in 29 tropical lakes and reservoirs, of which 27 were from Africa. The productivity of these 30 tropical lakes and reservoirs was compared with: (a) 27 lakes of which 25 were temperate lakes, and (b) 49 North American temperate lakes. Firstly, comparisons were made on an annual basis for the tropical water bodies, but restricted to May–September, the growing season, for temperate water bodies. The gross primary productivity of tropical water bodies was ca. three times higher than that of temperate water bodies. These differences were even more dramatic if the two geographical regions are compared on an annual basis, i.e. the tropical systems are ca. six times more productive than their temperate counterpart.     

An empirical approach for deriving specific inland water quality parameters from high spatio-spectral resolution image

Inland lake of Vembanad has benefited from continuous monitoring to evaluate water quality which has declined due to increased anthropogenic activities and climate change. Remote sensing techniques can be used to estimate and monitor inland water quality both spatially and temporally. An empirical model is presented in Vemaband lake that retrieves the specific water quality parameters through correlations between various spectral wavelengths of Sentinel-2MSI (S2MSI) with field-measured water quality parameters. This approach includes the combinations of various bands, band ratios, and band arithmetic computation of satellite sensors of spectral datasets. The specific inland water quality parameters such as chlorophyll-a (chl-a), total suspended solids (TSS), turbidity, and secchi disc depth (SDD) were retrieved from the developed water quality model through Sentinel-2A remote sensing reflectance. The result illustrates that Specific Inland Water Quality Parameters (SIWQP) strongly correlated with S2MSI reflection spectral wavelengths. The SIWQP models are constructed for TSS (R²?=?0.8008), Chl-a (R²?=?0.8055), Turbidity (R²?=?0.6329) and SDD (R²?=?0.7174).The spatial distribution of SIWQPs in Vembanad lake for March 2018 is mapped and shows the lake's water quality distribution. The research from Sentinel-2, MSI has potential and is appropriate in high spectral and spatial characteristics for retrieving and continuous monitoring of water quality parameters in the regional scale of inland water bodies.

     

Implementation of a hierarchical global vegetation classification in ecosystem function models

Abstract. We propose an alternative approach for the currently used biogeographic global vegetation classifications. A hierarchical vegetation classification system is proposed for consistent and routine monitoring of global vegetation. Global vegetation is first defined into six classes based on plant canopy structure and dynamics observable by remote sensing from satellites. Additional biome variability is then represented through a remote sensing derived leaf area index map, and direct climate data sets driving an ecosystem model to compute and map net primary production and evapotranspiration. Simulation results from an ecosystem function model suggest that the six canopy structure-based classes are sufficient to represent global variability in these parameters, provided the spatio-temporal variations in Leaf Area Index and climate are characterized accurately. If a bioclimatically based classification is needed for other purposes, our six class approach can be expanded to a possible 21 classes using archived climatic zones. For example, tropical, subtropical, temperate and boreal labels are defined by absolute minimum temperature. Further separation in each class is possible through changes in water availability defined by precipitation and/or soils. The resulting vegetation classes correspond to many of the existing, conventional global vegetation schemes, yet retain the measure of actual vegetation possible because remote sensing first defines the six biome classes in our classification. Vegetation classifications are no longer an end product but a source of initializing data for global ecosystem function models. Remote sensing with biosphere models directly calculates the ecological functions previously inferred from vegetation classifications, but with higher spatial and temporal accuracy.     

The fauna and distribution of alderfly larvae (Sialidae, Megaloptera) in Northern Fennoscandia and its dependence on natural and anthropogenous factors

The results of a study of alderfly larvae (Sialidae, Megaloptera) from over 400 small lakes and ten large lakes and rivers in Northern Finland, Norway, and Murmansk oblast are presented. The distribution of five species of larvae in relation to the landscape, size of water bodies, hydrological type of water bodies, type of habitats, pH, water color, etc., is considered. Possessing a relatively higher plasticity and tolerance to environmental conditions, Sialis larvae were found more often and made the maximum contribution to the biomass of littoral macroinvertebrate communities in small north taiga and tundra lakes, slow water courses, on soft sediments, in vegetation, in weakly humic waters, and in circumneutral and weakly alkaline waters. High ecological plasticity, including pollution, is found in the larvae of S. morio Klingstedt and S. lutaria L.     

High-resolution satellite remote sensing of littoral vegetation of Lake Sevan (Armenia) as a basis for monitoring and assessment

Physics-based remote sensing in littoral environments for ecological monitoring and assessment is a challenging task that depends on adequate atmospheric conditions during data acquisition, sensor capabilities and correction of signal disturbances associated with water surface and water column. Airborne hyper-spectral scanners offer higher potential than satellite sensors for wetland monitoring and assessment. However, application in remote areas is often limited by national restrictions, time and high costs compared to satellite data. In this study, we tested the potential of the commercial, high-resolution multi-spectral satellite QuickBird for monitoring littoral zones of Lake Sevan (Armenia). We present a classification procedure that uses a physics-based image processing system (MIP) and GIS tools for calculating spatial metrics. We focused on classification of littoral sediment coverage over three consecutive years (2006–2008) to document changes in vegetation structure associated with a rise in water levels. We describe a spectral unmixing algorithm for basic classification and a supervised algorithm for mapping vegetation types. Atmospheric aerosol retrieval, lake-specific parameterisation and validation of classifications were supported by underwater spectral measurements in the respective seasons. Results revealed accurate classification of submersed aquatic vegetation and sediment structures in the littoral zone, documenting spatial vegetation dynamics induced by water level fluctuations and inter-annual variations in phytoplankton blooms. The data prove the cost-effective applicability of satellite remote-sensing approaches for high-resolution mapping in space and time of lake littoral zones playing a major role in lake ecosystem functioning. Such approaches could be used for monitoring wetlands anywhere in the world.     

Spring phytoplankton of 54 small lakes in southern Finland

The abundance and species composition of phytoplankton communities were studied rapidly following the spring ice-melt in 54 small Finnish lakes that form a unique mosaic of water bodies. Phytoplankton biomass and cell density varied among the study lakes with a factor 100 between the lowest and highest values. Highest biomass and densities of phytoplankton characterized small ( < 0.05 km²) lakes with moderate or high water colour (> 80 mg Pt l^–1). In contrast, biomass was low in clear-water lakes and lakes where water throughflow was strong. Typically one species dominated most phytoplankton communities, and usually comprised up to about 45% of the total phytoplankton biomass. Two-thirds of the 103 taxa observed were Chrysophyceans and Chlorophyceans. The most common taxa wereChlamydomonas spp. (Chlorophyceae) andCryptomonas ovata (Cryptophyceae).     

红树林生态系统遥感监测研究进展

随着现代遥感技术的迅速发展,遥感监测已经成为红树林生态系统变化监测的重要手段和方法。从遥感技术在生态系统变化监测应用领域入手,综述了国内外红树林遥感监测的发展历程,系统总结了遥感技术在红树林湿地动态、种间分类、群落结构(叶面积指数、冠幅、树高等)、生物量、灾害灾情(病虫害、风暴潮等)、景观格局动态、驱动力、红树林湿地保护与管理等领域应用现状,归纳了不同应用领域遥感监测的理论、方法及研究现状。指出我国在红树林遥感监测中存在的不足。提出红树林遥感监测应在分类标准体系规范化、分类精度提升、红树林生态学特征参数(物种多样性、优势度等)、生态系统环境空间演变过程及遥感监测的尺度效应方面加大研究力度。充分发挥区域综合监测模型在红树林生态系统变化遥感监测中的作用。     

土壤水分遥感监测研究进展

土壤水分是陆地表面参数化的一个关键变量。土壤水分含量随时空的转换而变化,在地-气界面间物质、能量交换中起着重要的作用,是农作物生长发育的基本条件和农作物产量预报的重要参数。遥感技术具有大面积同步观测,时效性、经济性强的特点,为大面积动态监测土壤水分提供了可能。总结了近年来国内外遥感监测土壤水分理论、方法的发展和应用,介绍了目前几种比较成熟和广泛应用的土壤水分遥感监测方法与模型,对比分析了各种监测方法的优缺点,指出了土壤水分遥感监测方法存在的不足,指明了今后发展的方向,展望了土壤水分遥感监测方法的发展趋势。     

Consistent patterns in diatom assemblages and diversity measures across water‐depth gradients from eight Boreal lakes from north‐western Ontario (Canada)

1. Until recently, the distribution of diatom species assemblages and their attributes (e.g. species richness and evenness) in relation to water depth have been identified but not quantified, especially across several lakes in a region. Here, we examined diatom assemblages in the surface sediment across a water‐depth gradient in eight small, boreal lakes in north‐western Ontario, minimally disturbed by human activities. 2. Surface‐sediment diatom assemblages were collected within each lake along a gentle slope from near‐shore to the centre deep basin of the lake, at a resolution of ～1 m water depth. Analysis of sedimentary samples provided an integrated view of assemblages that were living in the lake over several years and enabled a high‐resolution analysis of many lakes. The study lakes ranged in water chemistry, morphology and size and are located along an east–west transect approximately 250 km long in north‐western Ontario (Canada). 3. The majority of diatom species were distributed along a continuum of depth, with those taxa having similar habitat requirements forming distinct, though overlapping, assemblages. Three major zones of diatom assemblages in each lake were consistently identified: (i) a near‐shore assemblage of Achnanthes (sensu lato), Nitzschia, Cymbella (sensu lato) and other benthic species; (ii) a mid‐depth assemblage of small Fragilaria (sensu lato)/small Aulacoseira and various Navicula taxa; and (iii) a deep‐water assemblage of planktonic origin (mainly Discotella spp.). 4. The depth of the transition between assemblage zones varied between the eight lakes. The boundary between the deep‐water planktonic zone and the mid‐depth benthic zone varied according to water chemistry and was probably related to light attenuation. The boundary was deeper in lakes with the lower dissolved organic carbon and total phosphorus (TP) (i.e. less light attenuation) and vice versa. 5. Generally, species richness, species evenness and turnover rate of species as a function of depth were significantly lower in the planktonic assemblage zone in comparison with the two zones nearer the shore. Reproducibility of species and assemblage distributions across the depth gradient of the lakes illustrated that, despite potential for sediment transport, detailed ecological characterisation of diatom species can be gleaned from sedimentary data. Such data are often lacking, particularly for near‐shore benthic species.     

On the phytosociology and ecology of Isoëtes asiatica (Makino) Makino in oligotrophic water bodies of South Sakhalin

In 1989, in the southeast of the Sakhalin Island and south of the village Okhotskoye, Isoëtes asiatica (Makino) Makino and I. beringensis Kom. were detected in 24 oligotrophic lakes for the first time on Sakhalin. These are stands of the community of Isoëtetum asiaticae ass. nov. which in the majority of the lakes form a characteristic pioneer vegetation of the shallow littoral zones. In addition to poor-species dominance stands of both of the Isoëtes species, penetration stages of both of these species as well as stages rich in Comarum palustre, Eleocharis acicularis and Potamogeton species can be differentiated. Besides the structure of the species, the site conditions, particularly of the water bodies are described. The ion content is represented by absolute and relative ion field diagrams exemplified by 7 selected water bodies. The ion content is characterized by sodium and chloride which are prevailing, while calcium and magnesium as well as hydrogen carbonate and sulphate exist in low quantitative proportions only. The indicator values of individual characteristics and the complex characteristics of the Isoëtes lakes are discussed. The hydrochemical characteristics of the Sakhalin, Kuriles and Kamchatka Isoëtes waters are compared with the Isoëtes water bodies of North America and Europe. The danger to Isoëtes water bodies is discussed, necessary protective measures are defined.     

基于小波理论的干旱区内陆湖泊叶绿素a的TM影像遥感反演

叶绿素a(Chl-a)是衡量湖泊富营养化的重要指标,利用遥感技术动态监测面积较大的湖区水体中Chl-a浓度对了解湖区水质具有重要意义。以内蒙古乌梁素海为例,提出利用TM影像中的水体实测光谱进行小波去噪和光谱信号重构,并结合水质采样实测数据进行神经网络拟合,建立光谱反射率比值与Chl-a浓度的反演模型的方法。结果显示:小波理论和神经网络相结合的模型可以适用于估算乌梁素海Chl-a浓度,去噪后Chl-a浓度与光谱信号的相关系数(-0.575)较去噪前(-0.417)明显增强,去噪后的采样点光谱信号与Chl-a浓度之间表现出比原始信号更强的负相关性,证明了去噪后的观测值可进一步减弱随机误差的干扰和去除噪声,使观测数据更加逼近Chl-a浓度的真实情况,图像去噪重构结果显示重构后的光谱范围较之前有所缩窄,部分信号点得到了增强,但基本剖面结构并没有产生较大变化,反演模型的平均相对误差为0.142,与其他研究相比差别不大。反演得出的乌梁素海Chl-a浓度分布反映了污染源的分布,同时说明了乌梁素海Chl-a浓度在时空分布上呈现一定的差异,表现为丰水期呈现浅水区Chl-a浓度值高于湖心区,来水区高于其他湖区的分布趋势,枯水期乌梁素海中部呈现由西向东Chl-a浓度逐步降低的分布规律,西部呈均一化分布。反演模型基本可以满足实际预测的需要。但模型在具体应用中在影像数据采集、数据量及算法方面还有很大的改进空间,该方法的提出为干旱区大型内陆水体富营养化的实时定量遥感监测提供了新的解决方案。