Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.  

Mapping Invasive Aquatic Vegetation in the Sacramento-San Joaquin Delta using Hyperspectral Imagery

The ecological and economic impacts associated with invasive species are of critical concern to land managers. The ability to map the extent and severity of invasions would be a valuable contribution to management decisions relating to control and monitoring efforts. We investigated the use of hyperspectral imagery for mapping invasive aquatic plant species in the Sacramento-San Joaquin Delta in the Central Valley of California, at two spatial scales. Sixty-four flightlines of HyMap hyperspectral imagery were acquired over the study region covering an area of 2,139 km² and field work was conducted to acquire GPS locations of target invasive species. We used spectral mixture analysis to classify two target invasive species; Brazilian waterweed (Egeria densa), a submerged invasive, and water hyacinth (Eichhornia crassipes), a floating emergent invasive. At the relatively fine spatial scale for five sites within the Delta (average size 51 ha) average classification accuracies were 93% for Brazilian waterweed and 73% for water hyacinth. However, at the coarser, Delta-wide scale (177,000 ha) these accuracy results were 29% for Brazilian waterweed and 65% for water hyacinth. The difference in accuracy is likely accounted for by the broad range in water turbidity and tide heights encountered across the Delta. These findings illustrate that hyperspectral imagery is a promising tool for discriminating target invasive species within the Sacramento-San Joaquin Delta waterways although more work is needed to develop classification tools that function under changing environmental conditions.  

Remote sensing of aquatic vegetation: theory and applications

Aquatic vegetation is an important component of wetland and coastal ecosystems, playing a key role in the ecological functions of these environments. Surveys of macrophyte communities are commonly hindered by logistic problems, and remote sensing represents a powerful alternative, allowing comprehensive assessment and monitoring. Also, many vegetation characteristics can be estimated from reflectance measurements, such as species composition, vegetation structure, biomass, and plant physiological parameters. However, proper use of these methods requires an understanding of the physical processes behind the interaction between electromagnetic radiation and vegetation, and remote sensing of aquatic plants have some particular difficulties that have to be properly addressed in order to obtain successful results. The present paper reviews the theoretical background and possible applications of remote sensing techniques to the study of aquatic vegetation.  

基于NDVI指数的骆马湖水生植被分级研究

基于典型时段骆马湖LandsatTM遥感影像,利用归一化植被指数（NDVI）法对骆马湖水生植被进行分级研究.采用标准差分级方法,将骆马湖水生植被分为5个等级.研究结果表明,利用这种分级方法处理的图像能够较准确地反映骆马湖水生植被区域分布和等级分区,能够更准确地给出采砂区和生态保护区域的位置,增强湖区水生态环境保护工作的有效性和针对性.  

Macrobenthic Monitoring in the Lower St. Johns River, Florida

The macrobenthos in the oligohaline 132 km reach of the Lower St. Johns River, Florida, is an unusual blend of freshwater and marine organisms within the annelid, mollusk, aquatic insect, and crustacean groups. During 1993–1994, the community composition was freshwater-oriented in the 47 km (seg I) and estuarine-dominated in the lower 85 km (seg II). Of the total 146 taxa collected, 89% were euryecious 'eutrophic' and 'pollution-tolerant' organisms. Densities ranged between 5000 and 20 000 individuals/m² ann av and maximum densities (85 000 individuals/m²) occurred in the muck substrate at the confluence of major tributaries and embayments. Throughout the lake-like seg II, benthic hypoxia existed during much of summer through fall. Biotic index values for grab, artificial substrate, and sled trawl samples reflected greatest stresses to the macrobenthos then. Both low taxonomic diversity and densities of organisms at the most downriver stations nearest the port of Jacksonville indicated that toxic substances also adversely affected the macrobenthos. Maintenance of the narrow band of littoral submerged aquatic vegetation (SAV) and adjacent shoreline riparian vegetation is important to sustain macrobenthic communities and other kinds of aquatic life in the river.  

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。