Space remote sensing for spatial vegetation characterization

The study area, Madhav National Park (MP) represents northern tropical dry deciduous forest. The national park, due to its unique location (nearest to township), is under tremendous biotic pressure. In order to understand vegetation structure and dynamics, vegetation mapping at community level was considered important. Prolonged leafless period and background reflection due to open canopy poses challenge in interpretation of satellite data. The vegetation of Madhav National Park was mapped using Landsat TM data. The ground data collected from sample points were subjected to TWINSPAN analysis to cluster sample point data into six communities. The vegetation classification obtained by interpretation (visual and digital) of remote sensing data and TWINSPAN were compared to validate the vegetation classification at community level. The phytosociological data collected from sample points were analysed to characterize communities. The results indicate that structural variations in the communities modulate spectral signatures of vegetation and form basis to describe community structure subjectively and at spatial level.     

Applying remote sensing techniques to monitoring seasonal and interannual changes of aquatic vegetation in Taihu Lake,China

Knowledge of the composition and areal distribution of aquatic vegetation types, as well as their seasonal and interannual variations, is crucial for managing and maintaining the balance of lake ecosystems. In this study, a series of remotely sensed images with a resolution of 30 m (HJ-CCD and Landsat TM) were collected and used to map the distribution of aquatic vegetation types in Taihu Lake, China. Seasonal and interannual dynamics of aquatic vegetation types were explored and analyzed. The distribution areas of Type I (emergent, floating-leaved and floating vegetation) and Type II (submerged vegetation) were used to model their growing season phenology by double logistic functions. The resulting double logistic models showed, the area of Type I reached its peak in mid-August, and the maximum area for Type II occurred in mid-September. From 1984 to 2013, Type I area increased continuously from 59.75 km² to 148.00 km² (R² = 0.84), whereas the area covered by Type II first increased and then decreased, with a trend conforming to a significant quadratic curve (R² = 0.83). The eutrophication and stable state of Taihu Lake was assessed using a simple indicator which was expressed as a ratio of Type II area to Type I area. The results showed that the eutrophication in the lake might have been increasing in the area studied since 2000. Additionally, the results showed that air temperature had likely a direct effect on the growth of Type I (R² = 0.66) and a significant, but delayed, effect on the growth of Type II.     

应用遥感技术评价植被生化物质含量的研究进展

植物叶片中的各种生化物质 (包括叶绿素、叶黄素、类胡萝卜素等色素 ,N、P、K等营养物质 ,纤维素、半纤维素、木质素、蛋白质、淀粉、糖和油等 )都直接或间接地参与生物地球化学循环。为进一步理解生态系统功能 ,必须对不同时间、不同空间的这些参数进行调查。遥感技术为获取多时相、大范围数据提供了极大的方便 ,在地表植被生化特征测定方面发挥着重要的作用。 2 0世纪 80年代以来 ,世界各国相继推出了机载和星载高光谱传感器 ,高光谱遥感技术为植被生化物质的遥感开辟了新局面。本文从植被光谱特征出发 ,总结了目前生化参数遥感中的植被指数、导数光谱、红边位移分析和连续统去除等基本光谱处理方法 ,重点介绍了统计回归模型和光学 -几何模型在植被生化物质含量遥测中的应用。对现有利用遥感技术研究植被生化物质含量的研究进行了综合评述 ,并讨论了其局限性及未来的发展趋势     

Role of aquatic vegetation coverage on hypoxia and sunfish abundance in bays of a eutrophic reservoir

We studied the relation between aquatic vegetation coverage, summer dissolved oxygen and density of sunfishes (Lepomis spp.) in 10 shallow bays of a eutrophic reservoir. The bays ranged 5.2–15.7 ha in area, 0.6–1.3 m mean depth and 6–91% vegetation area coverage. Over the 10 bays mean dissolved oxygen concentration ranged 5.8–9.0 mg l^-1 in open water at least 20 m away from the vegetation, 0.8–8.1 mg l^-1 at the vegetation-water edge and 0.5–7.7 mg l^-1 in dense vegetation. Dissolved oxygen concentrations were inversely related to vegetation coverage. In open water, dissolved oxygen levels were consistently higher than 8 mg l^-1 when vegetation coverage was <20% of the bay and decreased to about 6 mg l^-1 at coverages near 80%. At the vegetation-water edge and within dense vegetation, dissolved oxygen levels dropped rapidly as vegetation coverage increased to 20% of the bay; when vegetation reached about 50% coverage, dissolved oxygen remained near 1.5 mg l^-1at the vegetation-water edge, but oxygen dropped below 1 mg l^-1in dense vegetation. Scarce vegetation harbored high Lepomis relative abundance (fish per m² of vegetation) whereas extensive vegetation harbored low relative abundance, both contributing little to absolute abundance (total fish in all vegetation); however, intermediate coverage offered a combination of mid-level fish relative abundance that together with mid-level plant coverage translated into high absolute fish abundance. We suggest this response is related to hypoxia, and where aquatic vegetation is extensive, the effect of vegetation on hypoxia and water quality in general may influence fish populations in a way similar to that often attributed to reduced foraging efficiency and increased competitive interactions.     

Mapping tropical forest fractional cover from coarse spatial resolution remote sensing imagery

At regional to global scales the only feasible approach to mapping and monitoring forests is through the use of coarse spatial resolution remotely sensed imagery. Significant errors in mapping may arise as such imagery may be dominated by pixels of mixed land cover composition which cannot be accommodated by conventional mapping approaches. This may lead to incorrect assessments of forest extent and thereby processes such as deforestation which may propagate into studies of environmental change. A method to unmix the class composition of image pixels is presented and used to map tropical forest cover in part of the Mato Grosso, Brazil. This method is based on an artificial neural network and has advantages over other techniques used in remote sensing. Fraction images depicting the proportional class coverage in each pixel were produced and shown to correspond closely to the actual land cover. The predicted and actual forest cover were, for instance, strongly correlated (up to r = 0.85, significant at the 99% level of confidence) and the predicted extent of forest over the test site much closer to the actual extent than that derived from a conventional approach to mapping from remotely sensed imagery.     

遥感技术支持下的植被生产力与生物量研究进展

目前广泛应用于植被生产力与生物量估算的遥感模型主要有经验模型、物理模型、半经验模型和综合模型 ,它们的应用受到诸如大气、背景、地形、植被覆盖率与结构等因素的影响。遥感技术的迅速发展及其它技术的应用 ,包括热红外、微波和激光遥感仪器以及多角度、高光谱和高分辨率技术等 ,正逐步消除或降低影响因素 ,进一步提高植被生产力与生物量估算的范围和精度     

基于GIS的浙江省水稻遥感估产最佳时相选择

水稻遥感估产最佳时相选择应包括水稻种植面积估算最佳时相和水稻产量预报最佳时相两部分。在水稻遥感估产最佳时相选择中,由于首次引入GIS技术提取水稻可能种植区域,缩小了研究范围,植被种类也较简单一,因此仅用农作物物候历即可确定水稻种植面积估算最佳时相,而不需要考虑所有的植被类型。利用盆栽试验和小区试验研究水稻产量与不同时期的农学参数、农学参数与植被指数及水稻产量与植被指数的关系,结果表明,水稻产量与农业参数、农学参数与光谱变量的关系均以孕穗以抽穗期最好,水稻产量与光谱变量的关系则从分蘖盛期到抽穗期的极显著。因此,以孕穗期到抽穗期作为建立水稻遥感估产模型的最佳时期。再利用1998年各地的水稻发育期观测资料,确定各区水稻产量遥感最佳时相。     

Broadscale patterns in the distribution of aquatic and terrestrial vegetation at three ice-free regions on Ross Island,Antarctica

Distribution patterns are presented for selected aquatic algae, and terrestrial algae, mosses and lichens, at three large, coastal ice-free regions on Ross Island. Each region is unique in certain aspects of its vegetation. The variation in areal and quantitative occurrence of different components of the vegetation in diverse ponds and streams, and over exposed ground surfaces, is related to the levels of marine salts in the environment, fertilisation by birds, water availability, substratum type and degree of exposure. A comparison is made with other antarctic, coastal, ice-free regions where similar broadscale patterns have been recognised.     

Assessing photosynthetic efficiency in an experimental mangrove canopy using remote sensing and chlorophyll fluorescence

This study examined the ability of the photochemical reflectance index (PRI) to track changes in effective quantum yield (Δ F/F _m ′), non-photochemical quenching (NPQ), and the xanthophyll cycle de-epoxidation (DPS) in an experimental mangrove canopy. PRI was correlated with (Δ F/F _m ′) and NPQ over the 4-week measurement period and over the diurnal cycle. The normalised difference vegetation index (NDVI) was not correlated with any aspect of photochemical efficiency measured using chlorophyll fluorescence or xanthophyll pigments. This study demonstrated that photochemical adjustments were responsible for controlling the flow of energy through the photosynthetic apparatus in this mangrove forest canopy rather than canopy structural or chlorophyll adjustments.     

Satellite remote sensing for ecological analysis of forested landscape

The spatial characterisation and vertical analysis are together considered important to evaluate structure of forested landscapes. In recent years, increased human impacts have resulted in changes in landscape and structure of the forest ecosystem. The present study is aimed to analyse impacts of disturbance on landscape structure using satellite remote sensing and a geographic information system (GIS) in Madhav National Park of India. The Landsat TM data have been used to identify vegetation types. The patch characteristics of the vegetation like size, shape, porosity and patch density have been studied. The physical and humanmade features have divided the national park in three zones. These zones are also utilised as management zones by the State Forest Department. The study indicates that the central zone is distinctly different from the south and north zones. The patch size and porosity have been found to be most important parameters to discriminate differences in the ecological status of three different zones of the park. The patchiness and shape provide supportive information and characterise the patches of the zones. The structural analysis of the vegetation revealed effect on species diversity and biomass distribution in the different disturbance regimes.     

An assessment of the aquatic and wetland vegetation of the Upper Mississippi River

Illinois, Iowa, Minnesota, Missouri, and Wisconsin have strong botanical traditions that have resulted in a macrophyte literature which documents the identity, taxonomy, floristics, and ecology of aquatic macrophytes and wetland vegetation of the Upper Mississippi River and its floodplain. These findings are reviewed with respect to floristics, vegetation dynamics (patterns, history, production and management), and environmental changes that impact vegetation. Aspects requiring future study are noted to direct subsequent investigations.     

Role of disturbed vegetation in mapping the boreal zone in northern Eurasia

Question: Is there a need for disturbance mapping integrated in the CircumBoreal Vegetation Mapping Program? Location: Eurasian boreal forest. Disturbance and mapping: The boreal zone is characterized by a multitude of natural and anthropogenic disturbance agents with importance over a wide range of spatial and temporal scales. Disturbance is a prime driver of succession in most of the boreal zone, producing landscape diversity characterized by a large‐scale vegetation mosaic of early to late succession states. When mapping the circumboreal vegetation, spatial extent, time involved from disturbance to recovered condition and likelihood of interacting disturbance types are crucial for how current vegetation is interpreted and subsequently included as map characteristics. In this paper we present examples from the boreal zone where natural and/or anthropogenic disturbance regimes dominate the state and distribution of vegetation, and possibilities for assessing the nature and extent of the disturbed regions using remotely sensed data. Conclusion: Disturbed vegetation occupies large areas in the boreal zone and related vegetation successions should be adequately represented when mapping the zone. In regions where the ‘potential natural vegetation’ is a hypothetical reconstruction from remnants of ‘natural’ vegetation it would be preferable to use the concept of ‘actual real vegetation’ for which remote sensing at coarse, medium and fine resolution is an efficient tool. The Land Cover Classification System (LCCS) may offer sufficient flexibility to incorporate information about the disturbance of circumboreal vegetation.     

Field-based remote sensing of intertidal epilithic chlorophyll: Techniques using specialized and conventional digital cameras

Information on the amount of chlorophyll (as an index of micro-algal abundance) on rock surfaces is essential for many reasons, including studies of grazing and its role in structuring intertidal assemblages. Many methods are destructive, error-prone and expensive. Remote sensing allows non-destructive, inexpensive and quantitative measurements to be made of chlorophyll in situ. One specialized and two inexpensive commercially-available digital cameras (Fuji IS1 and Sony DSC-V1) are evaluated for estimating amounts of chlorophyll on rock surfaces. To compare measurements from different images, they are calibrated, using reflectance standards of different brightness. To test the calibration, images of a natural rock platform were acquired under variable solar illumination and camera-exposure times. Analyses before and after calibration showed that the method was effective.A range of quantities of micro-algae was grown on sandstone disks in an aquarium over different intervals of time. Red and NIR reflectance images were obtained from the cores. For each core, the amount of chlorophyll was determined spectrophotometrically and estimated from the images using the Ratio Vegetation Index (RVI) and Normalised Difference Vegetation Index (NDVI). Each of these was linearly related to the measured chlorophyll, with r² ranging from 0.78 to 0.9. These techniques can be applied to the study of intertidal and freshwater benthic habitats.     

Satellite remote sensing of wetlands

To conserve and manage wetland resources, it is important to inventoryand monitor wetlands and their adjacent uplands. Satellite remote sensing hasseveral advantages for monitoring wetland resources, especially for largegeographic areas. This review summarizes the literature on satellite remotesensing of wetlands, including what classification techniques were mostsuccessful in identifying wetlands and separating them from other land covertypes. All types of wetlands have been studied with satellite remote sensing.Landsat MSS, Landsat TM, and SPOT are the major satellite systems that have beenused to study wetlands; other systems are NOAA AVHRR, IRS-1B LISS-II and radarsystems, including JERS-1, ERS-1 and RADARSAT. Early work with satellite imageryused visual interpretation for classification. The most commonly used computerclassification method to map wetlands is unsupervised classification orclustering. Maximum likelihood is the most common supervised classificationmethod. Wetland classification is difficult because of spectral confusion withother landcover classes and among different types of wetlands. However,multi-temporal data usually improves the classification of wetlands, as doesancillary data such as soil data, elevation or topography data. Classifiedsatellite imagery and maps derived from aerial photography have been comparedwith the conclusion that they offer different but complimentary information.Change detection studies have taken advantage of the repeat coverage andarchival data available with satellite remote sensing. Detailed wetland maps canbe updated using satellite imagery. Given the spatial resolution of satelliteremote sensing systems, fuzzy classification, subpixel classification, spectralmixture analysis, and mixtures estimation may provide more detailed informationon wetlands. A layered, hybrid or rule-based approach may give better resultsthan more traditional methods. The combination of radar and optical data providethe most promise for improving wetland classification.     

The epiphytic communities of various ecological types of aquatic vegetation of five pastoral ponds

Five small water bodies located within the agricultural region of Wielkopolska (west Poland) underwent investigation. Periphyton samples were collected from various macrophyte habitats representing rush vegetation (in five water bodies), submerged aquatic plants (in three) and nymphaeids (in one): Palędzie — Ceratophyllum demersum, Potamogeton crispus, Typha latifolia; Batorowo — Phragmites australis; Piotrowo — Potamogeton natans, Ceratophyllum submersum, Typha latifolia; Tarnowo Podgórne — Typha latifolia; Dąbrówka — Zannichellia palustris, Potamogeton pectinatus, Phragmites australis. The main goal of the study was to determine the composition and abundance of the periphytic communities inhabiting various types of rush and water vegetation of five water bodies located within a mid-field landscape area. Diatoms such as Achnanthidium minutissimum, Amphora ovalis, Cocconeis placentula orNavicula cincta revealed significantly higher densities in the zone of elodeids, while green algae prevailed among nymphaeids. As a result of this study it was found that the epiphytic algae were characterised by much lower diversity in respect to a specific water body, though much greater diversity was observed in its relation to the type of substratum. Two types of habitats were distinguished — the first of simple build (helophytes and nympheids) and the second containing the complicated architecture of plant stems (elodeids).     

Bathymetry,water optical properties,and benthic classification of coral reefs using hyperspectral remote sensing imagery

The complexity and heterogeneity of shallow coastal waters over small spatial scales provides a challenging environment for mapping and monitoring benthic habitats using remote sensing imagery. Additionally, changes in coral reef community structure are occurring on unprecedented temporal scales that require large-scale synoptic coverage and monitoring of coral reefs. A variety of sensors and analyses have been employed for monitoring coral reefs: this study applied a spectrum-matching and look-up-table methodology to the analysis of hyperspectral imagery of a shallow coral reef in the Bahamas. In unconstrained retrievals the retrieved bathymetry was on average within 5% of that measured acoustically, and 92% of pixels had retrieved depths within 25% of the acoustic depth. Retrieved absorption coefficients had less than 20% errors observed at blue wavelengths. The reef scale benthic classification derived by analysis of the imagery was consistent with the percent cover of specific coral reef habitat classes obtained by conventional line transects over the reef, and the inversions were robust as the results were similar when the benthic classification retrieval was constrained by measurements of bathymetry or water column optical properties. These results support the use of calibrated hyperspectral imagery for the rapid determination of bathymetry, water optical properties, and the classification of important habitat classes common to coral reefs.     

An integrated comparative approach to mangrove vegetation mapping using advanced remote sensing and GIS technologies: preliminary results

This study aims to develop an integrated methodology applying Remote Sensing and Geographic Information Systems (GIS) techniques for the assessment of the ecological status of mangrove forests. The study area is located at Phangnga Bay, Thailand. Various commonly available remote sensing data are evaluated for mangrove vegetation mapping. The satellite sensors used are covering the visible and infra-red (VIR) spectrum up to the microwave region of the electromagnetic spectrum. This study provides recommendations regarding the selection of a single sensor approach or sensor combination that fulfills a minimum requirement for practical mangrove mapping and inventory purposes (e.g. mangrove and non-mangrove areas, varying stocking density, dominant species composition and impact of human activities). Both their technical capabilities and their potentials are presented in correlation with the existing ground conditions.Asian Institute of Technology Bangkok, Thailand; National Research Council of Thailand Bangkok, Thailand; Royal Forestry Department Bangkok, Thailand     

Comparison of recent vegetation and diaspore banks along abiotic gradients in brackish coastal lagoons

Submerged vegetation and diaspore banks were investigated in three shallow brackish lagoons along the German southern Baltic Sea coast. The distribution of vegetation and diaspores was analysed at three depths (0.5, 1.0, 1.5 m) on three transects in each lagoon along salinity and nutrient gradients. Thirteen taxa of submerged vegetation were identified in three lagoons: 8 angiosperms and 5 charophytes. The diaspore analysis yielded 11 taxa of submerged diaspore types: 7 angiosperm taxa and 4 charophyte taxa groups.Salinity and nutrient gradients are the key factors governing the distribution of the vegetation and diaspore banks here. Statistical analysis (SIMPER) of vegetation and diaspore bank show differences in dissimilarities, i.e. Bray-Curtis similarities subtracted from 100, between the lagoon parts and between the lagoons. These differences increased with increasing intensity of the salinity and nutrient gradients. We argue that the diaspore bank reflects the former vegetation gradients shaped primarily by salinity gradients, whereas the present vegetation gradients are more affected by eutrophication. Vegetation surveys and diaspore bank analyses therefore supplement each other, and their combined use provides insight into former as well as recent gradients in the vegetation and the factors governing these gradients.     

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.     

The spectral responses of a submerged plant <Emphasis Type="Italic">Vallisneria spiralis</Emphasis> with varying biomass using spectroradiometer

The relationship between land features and their spectral characteristics is a key for the interpretation of remote sensing images. This study was designed to investigate the spectral responses of Vallisneria spiralis, a common submerged aquatic plant in Shanghai, with varying biomass both in the laboratory and in the Middle Lake section of a field-scale constructed wetland, using a FieldSpec™ Pro JR Field Portable Spectroradiometer. The results showed that the reflectance rate of V. spiralis increased with its increasing biomass, and this was exhibited both at the visible band (500–650 nm) and the near infrared band (700–900 nm). The water environment influenced the reflectance rate and the primary differences between the laboratory and field results mainly occurred at the near-infrared band (700–900 nm). A regression analysis was carried out between the biomass of V. spiralis and the reflectance rate at the wavelengths of QuickBird™ bands where the biomass responded most strongly. The results of this analysis showed a clear linear relationship by which the biomass of V. spiralis could be quantitatively deduced from the reflectance rate measured in situ. The implications of this observation, in terms of the ability of hyperspectral remote sensing to estimate and monitor the distribution and dynamics of submerged aquatic vegetation on a large scale, are discussed. Handling editor: S. M. Thomaz