164 research outputs found

    Linking Flow Regime, Floodplain Lake Connectivity and Fish Catch in a Large River-Floodplain System, the Volga-Akhtuba Floodplain (Russian Federation)

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    River-floodplain systems are amongst the most productive—but often severely impacted—aquatic systems worldwide. We explored the ecological response of fish to flow regime in a large river-floodplain system by studying the relationships between (1) discharge and inundated floodplain area, with a focus on spatial and temporal patterns in floodplain lake connectivity, and (2) flood volume and fisheries catch. Our results demonstrate a non-linear relationship between discharge and floodplain inundation with considerable hysteresis due to differences in inundation and drainage rate. Inundation extent was mostly determined by flood volume, not peak discharge. We found that the more isolated lakes (that is, lakes with a shorter connection duration to the river) are located at higher local elevation and at larger hydrological distance from the main rivers: geographical distance to the river appears a poor predictor of lake isolation. Although year-to-year fish catches in the floodplain were significantly larger with larger flood volumes in the floodplain, they were not in the main river, suggesting that mechanisms that increase catch, such as increased floodplain access or increased somatic growth, are stimulated by flooding in the floodplain, but not in the river. Fish species that profit from flooding belong to different feeding guilds, suggesting that all trophic levels may benefit from flooding. We found indications that the ecological functioning of floodplains is not limited to its temporary availability as habitat. Refugia can be present within the floodplain itself, which should be considered in the management of large rivers and their floodplain

    Postmortem investigations on winter stranded sperm whales from the coasts of Belgium and the Netherlands

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    During winter 1994-95, four and three sperm whales (Physeter macrocephalus) were stranded along the Belgian and the Dutch coasts, respectively. Necropsies and tissue samplings were collected 24 hrs post mortem. Lesions on several whales included round and linear skin scars, ventral skin abrasions, acute skin ulcers, acute ulcerative stomatitides, acute to chronic external otitides, and passive visceral congestion. In addition, these sperm whales appeared to be debilitated with severe weight deficit, had blubber thickness reduction, the absence of abdominal fat, and the intestinal tracts were almost empty. Three categories of lesions and their possible relation with the stranding were evaluated. Cutaneous scars observed on the seven whales appeared to have no relation with the stranding. The poor body condition and acute integument ulcerative lesions were present before the stranding. Ventral skin abrasions and visceral passive congestion were caused by the strandings. Absence of food in the alimentary tracts, evidence of weight loss and blubber thickness reduction were compatible with an extended presence of the sperm whales in the North Sea, where adequate food is not available. This might lead to progressive weakness, predisposing the animals to secondary pathogens such as viral diseases. Finally, the coastal configuration of the southern North Sea makes it a trap for sperm whales which have entered the area during their wanderings

    Earth observation for sustainable urban planning in developing countries: needs, trends, and future directions

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    Abstract: Cities are constantly changing and authorities face immense challenges in obtaining accurate and timely data to effectively manage urban areas. This is particularly problematic in the developing world where municipal records are often unavailable or not updated. Spaceborne earth observation (EO) has great potential for providing up-to-date spatial information about urban areas. This article reviews the application of EO for supporting urban planning. In particular, the article overviews case studies where EO was used to derive products and indicators required by urban planners. The review concludes that EO has sufficiently matured in recent years but that a shift from the current focus on purely science-driven EO applications to the provision of useful information for day-to-day decision-making and urban sustainability monitoring is clearly needed

    Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

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    An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

    Change detection with remote sensing : relating NOAA-AVHRR to environmental impact of agriculture in Europe

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    Agricultural production in the European Union sharply rose during the second half of the 20 thcentury. As a side-effect environmental impact increased as well, and resulted in widespread environmental problems, which policymakers now seek to reduce. Therefore, up-to-date, standardised information on environmental impact of agriculture is required covering the entire area of the Union. NOAA-AVHRR images seem well suited to provide part of this information, because 1) one image covers a large area, 2) so significant time series are available, and 3) they contain two relevant spectral bands for vegetation and crop studies. The objective of this study is to develop a change detection method to locate changes in environmental impact using NOAA-AVHRR images.The required spatial observation units were defined such that they match both agriculture and NOAA-AVHRR. For this purpose a method was developed to determine the correspondence in geometry between two polygon sets. It was shown that polygons formed by bio-physical variables match patterns in AVHRR images better than those formed by socio-economic variables. The selected units were obtained from the soil map.Once the spatial units were defined, measures could be sought that characterise environmental impact in terms of land cover, so they might be observable in the AVHRR images. A suitable measure was found in change in agricultural area, which will result in changed environmental impact if other factors remain unchanged. For changes in agricultural intensity, which will lead to changed environmental impact as well, no suitable measures exist.Finally, three different change detection methods were proposed to detect changes in agricultural area using NOAA-AVHRR images. The methods aim at enhancing the information regarding agricultural change while minimising classification inaccuracy, spatial misregistration and radiometric effects. None of these methods proved successful in locating regions with changes in agricultural areas. The conclusion is that NOAA-AVHRR images seem not suited to detect changes in European agriculture.Besides these aspects related to a change detection method, methods to solve cloud contamination of NOAA-AVHRR images were studied. Clouds often reduce the useful area in AVHRR images. Seven procedures, including conventional and geostatistical methods, to replace small clouds by estimated land radiation values were compared. The estimates from the geostatistical methods led to the best estimates of reflection values from the landscape underlying the clouds.Next, the suitability of near-future remote-sensing systems was assessed for detecting changes in environmental impact of agriculture. MERIS is a sensor mounted on ENVISAT, a European satellite that will be launched in November 2001. Its announced specifications make it seem a promising information source for land applications at the continental scale. To estimate the value of its 300m pixel a new method is proposed, which is referred to as the Stained Glass Procedure. This method relates pixel size to discernible detail, and predicts the level of detail detectable in another (here non-existing yet) image. According to the Stained-Glass Procedure, MERIS images will show twice as much detail as NOAA-AVHRR images, which is a significant improvement. Unfortunately, it will take quite some years before time series useful for change detection have been collected
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