Assessment of chlorophyll-a variations in high- and low-flow seasons in Apalachicola Bay by MODIS 250-m remote sensing

Chlorophyll-a (chl-a) is considered as a primary indicator for water quality and foods for oyster growth in Apalachicola estuarine ecosystem. Assessment of chl-a concentration variation in response to river inflow is important for estuarine environmental research and management. In this study, remote sensing analysis has been conducted to evaluate the effects of river inflow on chlorophyll concentrations in Apalachicola Bay of Florida in the northeast Gulf of Mexico. A remote sensing model for chl-a was improved and applied to map spatial distributions of chl-a by using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m resolution imageries in high-flow and low-flow seasons in 2001 and 2008. Chl-a values approximately ranged from the minimum 6 μg/l to the maximum 29 μg/l in the study period. Maximum chl-a concentration in high-flow season was almost twice above that in low-flow season. The averaged mean and minimum chl-a level in the high-flow season were approximately 42 and 28 % higher than those in low-flow season, respectively. The remote sensing mapping of chl-a was able to show spatial variations of chl-a in the entire bay under different flow conditions, which indicated its advantage over the traditional field data sampling for monitoring water quality over a large area of estuary. The MODIS 250-m remote sensing regression model presented from this study can be used to support monitoring and assessment of the spatial chl-a distribution in the bay for environmental research and management in Apalachicola Bay.     

Selection of appropriate sampling stations in a lake through mapping

Much valuable information is obtained from water quality measurements and monitoring of lakes around the world. A powerful tool is the use of mapping techniques, as it offers potential use in water quality research. Both remote sensing techniques and traditional water quality monitoring are required to collect data at sampling stations. This study suggests another approach to determine the most appropriate distribution of sampling stations in water reservoirs that will be mapped for water quality parameters. Tests were conducted for the proposed approach for Secchi disc depth (SDD), chlorophyll-a, turbidity and suspended solids parameters in Lake Beysehir, Turkey. Results of analysis are available for a total of 30 sampling stations in August 2006. Ten sampling stations were used to model Lake Beysehir while the others were used for validation of the model. Sampling stations that offered the best representation of the lake for each parameter were determined. Then, the best representative sampling stations for all parameters in the study were determined. Moreover, in order to confirm the accuracy of these re-determined sampling stations, modelling was performed on the results of the analysis of June 2006, and it was found that the values obtained from the re-determined sampling stations were acceptable.     

综合遥感与地面观测的巢湖水体富营养化评价

提出一种将地面观测数据空间插值与遥感反演结合的湖泊富营养化评价方法与业务化运行模式。对叶绿素a等可反演参数利用遥感影像反演,并利用实测值校正获得高精度反演结果;对总磷等不易反演参数采用空间插值获取全湖区数据,采用综合营养指数法对巢湖富营养化状态进行反演,获得2015年5月12日巢湖富营养化状态空间分布情况。结果表明,巢湖全湖为轻度和中度富营养化状态,呈现出西半湖高于东半湖的总体空间分布趋势。结合相关数据对巢湖富营养化成因进行推断,认为南淝河等上游河流各类营养物质输入量较大是造成西半湖北部富营养化严重的主要成因;西南部杭埠河等河流氮磷输入量较大,但其他营养物质输入较少,使得该区域总体呈现出富营养化程度偏低的现象。     

Evaluating climate change effects on water and salt resources in Salt Lake, Turkey using multitemporal SPOT imagery

The main goal of this study is to investigate the dimension of climate change effects in Salt Lake and its vicinity in Turkey using satellite remote sensing data. The first stage of the study includes evaluation of the multitemporal climatic data on the Salt Lake Basin Area, Turkey for a period of 35 years (1970–2005). The changes in mean temperature and precipitation are evaluated for the study area by comparing two periods, 1970–1992 and 1993–2005. In the second stage, the effects of climate changes in the Salt Lake are investigated by evaluating water and salt reserve changes through seasonal and multitemporal SPOT imagery collected in 1987 and 2005. The climatic data and remotely sensed and treated satellite images show that water and salt reserve in Salt Lake has decreased between 1987 and 2005 due to drought and uncontrolled water usage. It is suggested that the use of water supplies, especially underground waters, around the Salt Lake should be controlled and the lake should regularly be monitored by current remote sensing data for an effective management of water and salt resources in the region.     

基于湖北省12个中小型湖泊的水环境遥感监测应用示范

以《湖北省水环境遥感监测示范系统》为数据处理平台,对2012—2014年湖北省大东湖水网、梁子湖水系和汤逊湖水系共计12个湖泊的水质类别以及营养状态级别进行遥感监测,并对比实测数据进行精度评价。结果表明:遥感监测的梁子湖、豹澥湖和严西湖水质相对较好,杨春湖、北湖和南湖水质相对较差且富营养化状况较为严重。该系统能很好地实现对水质优良达标湖泊以及富营养化湖泊的识别。对示范区域各湖泊水质类别和营养状态级别的遥感监测,基本上能满足业务化运行的需求。个别湖泊遥感监测精度较低,主要表现为遥感监测的湖泊水质类别和营养状态级别均要优于实测的结果。系统对于面积相对较大的湖泊遥感监测精度更高。     

Determination of chlorophyll-a amount in Golden Horn, Istanbul, Turkey using IKONOS and in situ data

The objective of this research was to explore an accurate and fast way of estimating chlorophyll-a amount, a water quality parameter (WQP), using IKONOS satellite sensor image and in situ measurements. Since the in situ data of WQPs are limited with the number of sampling locations, deriving a correlation between these measurements and remotely sensed image allows synoptic estimates of the related parameter over large areas even if the areas are in remote and inaccessible locations. In this study, simultaneously collected satellite image data and in situ measurements of chlorophyll-a were correlated using multivariate regression model. Different experiments were designed by changing the numbers and distributions of in situ measurements. Regression coefficients of each design and differences between model-derived data and in situ measurements were calculated to find out the optimum design to produce chlorophyll-a map of study region. Results illustrated that both the number and distribution of in situ measurements have impact on regression analysis, therefore should be selected attentively. Also, it is found that IKONOS imagery is an efficient and effective source to derive chlorophyll-a map of the large areas using limited number of ground measurements.     

基于卫星数据的灰霾污染遥感监测方法及系统设计

以中分辨率成像光谱仪为例,建立了卫星遥感参数和空气污染指标之间的联系,提出了基于卫星遥感的气溶胶光学厚度数据获得灰霾指数和灰霾污染时空气质量指数(AQI)等级的方法和相关的监测系统设计。结合在华北地区的监测结果,可以看出卫星遥感可以较好地反映灰霾污染程度的变化,有助于发现可能的传输通道,获得宏观的灰霾空间分布状况。在研究时段内,与地面空气质量监测站相比,88%的卫星遥感监测结果误差不大于1个AQI等级,平均的AQI等级偏差为0.7级,并分析了卫星遥感与地面监测之间差异的原因。     

巢湖蓝藻水华遥感监测初探

以巢湖为研究区,从2008年4月到11月,对巢湖水体的24个点位进行了连续的水体光谱测量,通过对蓝藻水华爆发程度与其光谱反射率之间关系的研究,确定遥感识别水华爆发级别的阈值,对四类不同爆发程度蓝藻水华光谱特征进行遥感识别,绘制巢湖蓝藻水华特征等级图。     

Land quality assessment and sustainable land use in Salt Lake (Tuz Gölü) specially protected area

Land quality assessment is of great important for decisions on sustainable land uses and the conservation of ecosystems of high biodiversity value. The main objective of this study was to determine properties of land quality of specially protected area of the Salt Lake using CORINE land quality assessment methodology and to propose a revision for this model. In addition to field study and laboratory analysis, digital soil map, digital elevation model, satellite image and climatic data were used and analyzed with remote sensing and geographic information systems techniques to generate actual land quality map and to form database for study area. Results show that 42.1% of the study area has high quality, 28.7% was classified as moderate quality and 4.0% was determined as low quality. On the other hand, some places classified as moderate quality, were not accurately classified. These places should be low land quality due to content of high salt concentration. Therefore, to resolve this insufficient situation, some soil parameters such as chemical properties should be collaborated with this model. In this case, moderate land quality level of the study area decreased from 28.7 to 12.3%, whereas 4.0% of low quality land of the study area increased to 20.8%. In addition, this research was also carried out to provide guidance for planner or decision makers about specially protected area of the Salt Lake.     

基于Landsat TM/ETM+/OLI遥感大数据分析南京市1984—2015年大气能见度变化趋势

对南京市1984—2015年Landsat 4／5／7／8卫星TM／ETM＋／OLI传感器获取的遥感数据，利用ENVI遥感软件的FLAASH大气校正模块，进行了区域大气能见度（ VIS）遥感反演。结果表明，时间跨度达30余年的Landsat卫星遥感数据影像序列反演的VIS呈明显的下降趋势，20世纪80年代数值较高，“差”能见度（＜10 km）的观测率不到6％，21世纪以来VIS下降明显，“差”能见度的观测率为20％～25％。与2010—2015年南京市PM10、PM2．5监测数据进行了对比，在城市空气清洁及污染较轻时，星地监测结果有较好的一致性，但中到重污染天气时FLAASH算法反演VIS偏高，侧重于代表离主城区距离远的偏远乡野山林地区的能见度状况。     

高分一、二号卫星遥感数据在生态环境监测中的应用

从水环境质量监测、水体信息提取、植被资源监测、城市土地覆盖识别、大气环境监测5个方面综述了高分一号(GF-1)、高分二号(GF-2)卫星遥感数据在区域生态环境监测领域的应用,分析了相关研究的应用方向和重点,表明GF-1、GF-2卫星遥感数据在该领域具有良好的适用性和较大的应用潜力。     

水质参数的遥感反演和遥感监测

遥感技术由于具有快速、宏观、低成本和周期性的优点,便于探测水质的时空变化,已成为水质参数监测的重要手段。目前能够直接进行遥感反演的水质参数主要是悬浮物浓度、叶绿素a浓度、可溶解性有机物等光学活性物质,并已经建立了许多反演模型。但是这些模型直接用于水质的遥感监测仍存在一些问题。今后,利用3S技术将地面观测和遥感观测结合起来,可望推动水色遥感的实际应用。     

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.     

Mapping Turbidity in the Charles River, Boston Using a High-resolution Satellite

The usability of high-resolution satellite imagery for estimating spatial water quality patterns in urban water bodies is evaluated using turbidity in the lower Charles River, Boston as a case study. Water turbidity was surveyed using a boat-mounted optical sensor (YSI) at 5 m spatial resolution, resulting in about 4,000 data points. The ground data were collected coincidently with a satellite imagery acquisition (IKONOS), which consists of multispectral (R, G, B) reflectance at 1 m resolution. The original correlation between the raw ground and satellite data was poor (R2 = 0.05). Ground data were processed by removing points affected by contamination (e.g., sensor encounters a particle floc), which were identified visually. Also, the ground data were corrected for the memory effect introduced by the sensor's protective casing using an analytical model. Satellite data were processed to remove pixels affected by permanent non-water features (e.g., shoreline). In addition, water pixels within a certain buffer distance from permanent non-water features were removed due to contamination by the adjacency effect. To determine the appropriate buffer distance, a procedure that explicitly considers the distance of pixels to the permanent non-water features was applied. Two automatic methods for removing the effect of temporary non-water features (e.g., boats) were investigated, including (1) creating a water-only mask based on an unsupervised classification and (2) removing (filling) all local maxima in reflectance. After the various processing steps, the correlation between the ground and satellite data was significantly better (R2 = 0.70). The correlation was applied to the satellite image to develop a map of turbidity in the lower Charles River, which reveals large-scale patterns in water clarity. However, the adjacency effect prevented the application of this method to near-shore areas, where high-resolution patterns were expected (e.g., outfall plumes).     

湖南省生态环境遥感监测平台建设思考

简述了国内外遥感监测平台的发展现状,基于湖南省生态环境遥感监测现状进行了分析,指出遥感监测平台存在遥感监测与评估技术缺乏、监测能力薄弱以及监测网络建设不完善等问题。从平台建设架构出发,构建了数据平台,对卫星遥感数据、地面调查/监测资料、无人机航测数据进行管理、存储、分析等;业务平台,主要围绕水、气、土壤等整个生态环境监测体系开展相应的监测和管理,还可针对重点区域,环境督察等业务进行拓展;展示平台,主要是通过各种终端设备和硬件对各类业务进行可视化。提出发射独立高分遥感卫星、深化遥感监测应用研究、加强各部门协同合作等建议,以期为湖南省生态环境遥感监测平台建设与发展提供参考。     

基于国产“风云三号”卫星MERSI的太湖蓝藻水华监测业务化应用

使用无锡市环境监测中心站环境遥感综合处理系统,对2017年7—11月FY-3/MERSI影像数据进行蓝藻水华提取分析,并通过当日与国外MODIS、VIIRS影像数据的蓝藻水华提取结果进行协同比对,验证FY-3/MERSI影像在蓝藻水华预警监测业务化应用的前景。结果表明,3种数据源均能实现蓝藻水华空间分布的业务化运行;由于卫星过境时间的不同,可综合利用这3种数据源观测太湖蓝藻水华在一天中的动态变化,分析蓝藻水华的发生规律。     

近岸海域水色异常遥感监测方法研究

水体颜色是判断水体质量的重要依据，利用遥感技术检测水色异常是进行水质评估和水体污染监测的重要技术手法。基于盐城市废黄河入海口处的GF1-WFV影像数据，利用遥感影像自身光谱特征来构建水色异常判断函数，对研究区域的水色异常进行快速提取和定位，并比较分析了基于单景影像特征和多景影像特征设置判断阈值的提取结果。研究结果表明：该方法完全基于遥感影像光谱特征，可有效提取出未知类型的水色异常信息；与基于单景影像设置的判断阈值相比，基于双景影像设置的判断阈值更合理、更适用，提取速度更快，提取范围更精确，Kappa系数为0.80;另外，采用合适窗口大小进行均值滤波处理能有效防止提取结果细碎和斑块化。     

湖库水生植被光学遥感监测研究进展和展望

水生植被在湖库生态系统中发挥稳定沉积物、净化水质、平衡水生生态系统等作用,监测水生植被变化对湖库生态环境的监测具有重要意义。梳理了国内外利用高光谱、多光谱光学卫星遥感数据提取湖库水生植被的方法,尤其是针对其中涉及的阈值确定问题进行总结分析,介绍了典型研究区水生植被时空分布和变化以及与水质的关系,最后给出一些水生植被遥感监测的展望。     

遥感技术在环境监测中的应用进展与思考

随着卫星、航空技术及其业务化应用的快速发展,遥感监测已成为天空地一体化环境监测预警体系的重要组成部分。简述了环境遥感业务化的发展及特点,以江苏省为例,详细介绍了水环境、大气环境及生态环境遥感监测的省级具体应用情况。针对新时代生态环境保护工作的管理需求,尝试从同质处理、调查验证、硬件建设、热点挖掘、人才发展等5个方面提出相关建议,以期为省域生态环境遥感监测工作的后续发展提供参考。     

基于遥感影像的木兰溪水质参数反演

水质监测对水环境评价及污染预防至关重要，但地面监测成本高、监测面积有限等，难以满足实时、大范围监测的要求。为了更好地解决该问题，基于遥感影像的空中监测技术越来越得到研究人员的青睐。以木兰溪为研究区，利用和地面监测数据同步的Landsat-8卫星遥感影像数据，对木兰溪的典型水质参数总磷、总氮、溶解氧、高锰酸盐指数的反演问题进行研究。首先，根据Landsat-8的水体敏感波段，分别选取总磷、总氮、溶解氧、高锰酸盐指数的反演特征波段组合为(b1-b2)/(b2+b3),(b1-b2)/(b3-b4),b2/(b1+b4),b1/b2;其次，利用反演特征波段组合分别构建总磷、总氮、溶解氧、高锰酸盐指数浓度的SVR(Support Vector Regression)反演模型，通过IPSO算法对SVR模型的参数进行优选；然后，将IPSO-SVR反演模型和统计回归反演模型、广义回归神经网络(GRNN)反演模型在验证集上进行评估，以平均绝对误差和均方根误差作为评价指标进行对比分析，结果表明IPSO-SVR反演模型的平均绝对误差和均方根误差最小，说明IPSO-SVR反演模型具有较高的精度和较好的实用性...