Showing papers on "Wetland classification published in 2010"

Spatial and Temporal Variation in Wet Area of Wetlands in the Prairie Pothole Region of North Dakota and South Dakota

Abstract: Because of their sensitivity to temperature and precipitation, wetlands in the Prairie Pothole Region (PPR) are predicted to undergo changes in number, wet area, and hydroperiod as a result of climate change. However, existing PPR wetland monitoring programs are insufficient to accurately describe broad-scale variation in hydrology that might obscure signals of climate change. We assessed spatial and temporal patterns in wet area of ~40,000 wetland basins sampled each May from 1988–2007 in the U.S. PPR. The percentage of basins containing water, the wet area of basins relative to a baseline, the coefficient of variation of wet area of basins, and correlations of wet area values with values from previous years all varied temporally, spatially, and among water regimes that characterized annual duration of surface inundation. High variability in wetness suggests that monitoring programs designed to detect changes in PPR wetlands due to climate change must be implemented over broad spatiotemporal scales and consider natural and anthropogenic factors that influence water levels to be able to distinguish directional change from natural variation. Ancillary information such as annual indices of water conditions can greatly enhance the value of wetland classification schemes such as that used in the National Wetlands Inventory.

Modeling Methane Emission from Wetlands in North-Eastern New South Wales, Australia Using Landsat ETM+

Abstract: Natural wetlands constitute a major source of methane emission to the atmosphere, accounting for approximately 32 ± 9.4% of the total methane emission. Estimation of methane emission from wetlands at both local and national scale using process-based models would improve our understanding of their contribution to global methane emission. The aim of the study is to estimate the amount of methane emission from the coastal wetlands in north-eastern New South Wales (NSW), Australia, using Landsat ETM+ and to estimate emission with a temperature increase. Supervised wetland classification was performed using the Maximum Likelihood Standard algorithm. The temperature dependent factor was obtained through land surface temperature (LST) estimation algorithms. Measurements of methane fluxes from the wetlands were performed using static chamber techniques and gas chromatography. A process-based methane emission model, which included productivity factor, wetland area, methane flux, precipitation and evaporation ratio, was used to estimate the amount of methane emission from the wetlands. Geographic information system (GIS) provided the framework for analysis. The variability of methane emission from the wetlands was high, with forested wetlands found to produce the highest amount of methane, i.e., 0.0016 ± 0.00009 teragrams (Tg) in the month of June, 2001. This would increase to 0.0022 ± 0.0001 Tg in the month of June with a 1 ° C rise in mean annual temperature by the year 2030 in north-eastern NSW, Australia.

Wetland Use and Selection by Breeding Waterbirds in the Boreal Forest of Quebec, Canada

Abstract: Wetlands of remote forested landscapes of Quebec support numerous species of breeding waterbirds yet species-habitat associations remain poorly quantified. From 1990 to 2005, we conducted systematic helicopter surveys of breeding waterfowl and common loons (Gavia immer) across a 540,000-km2 forested region of Quebec. Data from this survey were used to investigate local habitat use and selection by waterbirds, based on a wetland classification system derived from digital forestry maps. Detailed indicated-breeding-pair (IBP) distributions were developed for broad aquatic, wetland, and shoreline habitat types. We also estimated selection ratios within groups of similar habitat types. Small (≤8 ha), connected ponds were highly used and selected by five dabbling duck species and by wood duck (Aix sponsa), Canada goose (Branta canadensis), ring-necked duck (Aythya collaris), hooded merganser (Lophodytes cucullatus), common goldeneye (Bucephala clangula), and Barrow’s goldeneye (B. islandica). Dabbling duck species, wood duck, and Canada goose made extensive use of streams (25–41% of all IBP). Community organization was mainly driven by openness of aquatic habitat and water movement, i.e., from lentic to lotic habitats. Failure to include streams in waterfowl surveys and habitat mapping could produce biased estimates of wetland habitat use and selection in the boreal forest.

Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA

Abstract: Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that “biological integrity” is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland’s position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA

Abstract: Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

Inferring ecological relationships from occupancy patterns for California Black Rails in the Sierra Nevada foothills

Abstract: Occupancy models provide a useful tool for examining relationships between species' occurrences and environmental or ecological covariates when detection probability is less than one. This research is focused on the secretive and rare California Black Rail ( Laterallus jamaicensis coturniculus ) and its wetland habitats in a newly discovered part of its range in the Sierra Nevada foothills of California, USA. In order to examine the Black Rail's distribution, residency, density, relationship to a larger conspecific, the Virginia Rail ( Laterallus limicola ), and relationship to livestock grazing, three classes of occupancy models were utilized: single-species/single-season models, single season/two-species models, and multi-season/single-species models. In order to develop a wetland classification procedure for identifying potential Black Rail habitats, we evaluated the utility of combining topographic features with spectral and geometric features using high-resolution satellite imagery and a digital elevation model (DEM). The secretive California Black Rail has a disjunct and poorly understood distribution. After a new population was discovered in Yuba County in 1994, we conducted call playback surveys from 1994-2006 in the Sierra foothills and Sacramento Valley region to determine the distribution and residency of Black Rails, estimate densities, and obtain estimates of site occupancy and detection probability. We found Black Rails at 164 small, widely scattered marshes distributed along the lower western slopes of the Sierra Nevada foothills, from just northeast of Chico (Butte County) to Rocklin (Placer County). Marshes were surrounded by a matrix of unsuitable habitat, creating a patchy or metapopulation structure. We observed Black Rails nesting and present evidence that they are year-round residents. Assuming perfect detectability we estimated a lower-bound mean Black Rail density of 1.78 rails ha -1 , and assuming a detection probability of 0.5 we estimated a mean density of 3.55 rails ha -1 . The probability of detecting occupancy from a single call playback survey at a marsh was high (mean = 0.84), and the estimated proportion of marshes occupied (across all years) was 0.58. The proportion of sites occupied by Black Rails in the foothills remained relatively stable from 2002-2006 despite turnover from year to year of specific sites. Irrigation ditches were the primary water source at 75% of the marshes that had Black Rails. Approximately two-thirds of marshes with Black Rails were on private land. Black Rails are more widespread in the Sierra foothills than was previously known, and the foothills distribution appears to be discontinuous with populations in the San Francisco Bay-Delta Estuary. Occupancy surveys may be an improved method for monitoring population trends of this secretive marsh bird where habitat patches are highly fragmented. Two-species occupancy models that account for false absences provide a robust method for testing for evidence of competitive exclusion, but previous model parameterizations were inadequate for incorporating covariates. We present a new parameterization that is stable when covariates are included, the conditional two-species occupancy model, that can be used to examine alternative hypotheses for species' distribution patterns. This new model estimates the probability of occupancy for a subordinate species conditional upon the presence of a dominant species. It can also be used to test if the detection of either species differs when one or both species are present, and if detection of the subordinate species depends on the detection of the dominant species when both are present. We apply the model to test if the presence of the larger Virginia Rail affects probabilities of detection or occupancy of the smaller California Black Rail in small freshwater marshes that range in size from 0.013-13.99 ha. We hypothesized that Black Rail occupancy should be lower in small marshes when Virginia Rails are present than when they are absent, because resources are presumably more limited and interference competition should increase. We found that Black Rail detection probability was unaffected by the detection of Virginia Rails, while, surprisingly, Black and Virginia Rail occupancy were positively associated even in small marshes. The average probability of Black Rail occupancy was higher when Virginia Rails were present (0.74 p however, spring cover was not well predicted by RDM. Accurate, transferable and efficient mapping procedures are needed for wetland inventory, assessment and monitoring. Wetland mapping is typically carried out using two types of inputs: (1) spectral reflectance data from imagery and (2) topographic/hydrologic data derived from digital elevation models (DEMs). Hybrid approaches that integrate remotely-sensed imagery with topographic data have shown improved wetland mapping accuracy in several studies. Here we evaluate the performance of nine topographic features (aspect, downslope flow distance to streams, elevation, horizontal distance to sinks, horizontal distance to streams, plan curvature, profile curvature, slope and topographic wetness index) on freshwater wetland classification accuracy in the Sierra foothills of California. To evaluate object-based classification accuracy we test both within-image and between-image predictions using six different classification schemes (naive Bayes, the C4.5 decision tree classifier, k-nearest neighbors, boosted logistic regression, random forest, and a support vector machine classifier) in the classification software package Weka 3.6.2. Adding topographic features had mostly positive effects on classification accuracy for within-image tests, but mostly negative effects on accuracy for between-image tests. The topographic wetness index was the most beneficial topographic feature in both the within-image and between-image tests for distinguishing wetland objects from other green objects (irrigated pasture and woodland) and shadows. Our results suggest that there is a benefit to using a more complex index of topography than simple measures such as elevation for the goal of mapping small palustrine emergent wetlands, but this benefit, for the most part, has poor transferability when applied between image sections. Occupancy models provide a robust method for examining species-environment relationships when detection probability is imperfect. The Black Rail study system in the Sierra foothills provides a unique and valuable opportunity for examining the effects of interspecific competition and grazing on a threatened subspecies at a regional scale. Further development of wetland mapping procedures will allow for a more complete description of the distribution of this rare and enigmatic marsh bird.

Analysis of Landscape Characteristics of the Wetland Systems in the Lhasa River Basin

Abstract: Alpine wetlands are unique natural ecosystems,showing a variety of functions like conserving water and regulating climate.In terms of domestic and foreign studies regarding wetland classification and wetland characteristics of the Lhasa River,the wetland system there is divided into six landscape types and 13 ecosystem types.On the basis of geography,ecology and spatial analysis in conjunction with data collected from field observations and China-Brazil Earth Resources Satellite(CBERS)images acquired in 2006,the wetland database for the study site was constructed.Then wetland landscape indexes,like patch size/density,patch shape,aggregation/ dispersion and diversity were calculated.Wetland landscape characteristics at three scales, landscape,ecosystem and geomorphologic region,were analyzed by means of ArcGIS.Results indicate that landscape characteristics differ greatly at the three scales.The total wetland area was estimated to be 209 000 hm2,accounting for 6.37%of the total land area.At the landscape scale, alpine meadow landscape is landscape matrices of alpine wetland,accounting for roughly 77.74% of the total wetland area.The contribution rate of open water wetland landscape was found to be 15.56%.Grass marsh and shrub wetland areas are relatively smaller,showing a discrete distribution.The contribution rates of beach and forest wetlands are generally lower.At the ecosystem scale,Kobresia littledalei meadow community is the core plant community type of alpine wetland,accounting for around 65.45%.Its landscape indexes such as patches area,patches number,patches density,patches shape indexes and patches contact indexes show the biggest values.At the region scale,it was found that there are different landscape characteristics in the three regions.Over the river source areas,wetland types are simple,showing that Kobresia littledalei swamped meadow is a major wetland landscape,and patch fragmentation is high.In the river valley,wetland type is the richest,showing the largest landscape diversity index of 1.841.Wet meadow and river wetlands are dominant wetland landscapes with a mosaic distribution.The region is affected by human activities and agricultural/pasture production,thereby resulting in a weak stability of ecosystems.In the Damshung basin,there are 5 wetland types with the biggest dominance index and evenness index.Kobresia littledalei swamped meadow is still a major wetland type with a stronger stability of ecosystems.

Using MRF approach to wetland classification of high spatial resolution remote sensing imagery: A case study in Xixi Westland National Park, Hangzhou, China

Abstract: The accurate discrimination of distinct thematic classes using classification techniques developed for medium/low resolution images is not effective when apply to very high spatial resolution (HR) data (e.g. Quickbird, IKONOS) due to the spatial heterogeneity issue. In this paper, Markov random field (MRF) models, which are useful tools for integrating contextual (considering spatial dependence within and between pixels) information into classification process is used to model spatial heterogeneity for improving the classification accuracy. Two novel MRF approaches are evaluated using a Quickbird HR image covers Xixi National Wetland Park, Hangzhou, China. The experimental results show this method is effective to exact segmentation of land boundaries and suppress classification noises. In addition, the improved MRF models outperform than conventional method in terms of classification accuracy and time-efficiency.

Wetland Definitions:Creation,Evolution and Application

Abstract: In this paper,we review the creation,evolution and application of wetland definitionsVarying wetlands are found from the tundra to the tropics and on every continent except Antarctica in the planetWetlands have many distinguishing features,the most notable of which are water presence,unique soil conditions,and biota that are adapted to or tolerant of saturated soilsMany wetland definitions have been developed by scientists,USfederal agencies,and the Ramsar Convention for both scientific and regulatory purposesWetlands are not easily defined but a well-conceived,science-based definition of wetlands is important for scientists and resource managers to understand the nature of wetlands and/or to use and protect wetlandsA scientific definition is the basis for wetland classificationDeveloping an effective wetland classification system requires a well-conceived,science-based definition and clearly explicit guidance on the appropriate use of various wetland indicators to verify the presence of wetlands on the groundBased on a well-accepted wetland definition,both wetland classification and inventory further provide needed information and a working frame for wise use and management of wetlands

Wetland characterization and classification using polarimetric RADARSAT-2 data

Abstract: Wetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, the hydrological and carbon cycles, and wildlife habitat and biodiversity. Mapping wetlands and monitoring their change are a long-term task. Remote Sensing characters with macrocosm, dynamics, quantity, and comparability will largely favor wetland research, especially radar remote sensing, which is not limited by climate conditions, has been proved an effective tool in wetland monitoring. In this paper, the unique polarimetric data of RADARSAT-2 is investigated for wetland classification. The target decomposition is used for optimum characterization of wetland target scattering. In this study, it is shown that the polarimetric information provided by RADARSAT-2 permits discriminating eight classes of land surface, and leads to an effective unsupervised and supervised Wishart classification of Poyang Lake wetland. Hence, the combination of RADARSAT-2's polarimetric and all-weather capabilities should provide unique information for operational mapping and monitoring of wetlands.

Classification of Remote Sensing Image for Lake and Marsh in the Area of Three River Sources Based on Decision Tree Using MODIS Data

Abstract: Wetland is one of the typical ecosystems which can be found in the interaction area between water and landIt is not only our important living environment,but also one of the landscapes which have the richest biodiversitySince it has many functions such as stabilizing the environment,protecting species gene and providing the resources for the humans,so it plays a very important role in maintaining the region and the global ecological equilibriumUnfortunately,the wetland was opened up,its area reduces day by day,and the biodiversity encounters the serious disturbance and the destruction since 20th century,because of the contradictory between the population booming and the land resource reducingThe research area in this paper is the Three River Sources area in Qinghai ProvinceIt lies on the west part of China,the center of Qinghai-Tibet Plain,and south of the Qinghai ProvinceAs implied by its name,the Three River Sources area is the source catchments area of Yangtze River,Yellow River and the Lancang RiverThis area has rich wetland resources for it is covered density rivers,lakes and marshes25% water of Yangtze River,49% water of Yellow River and 15% o water of Lancang River is coming from this areaIn order to better understand the wetland distribution of the Three River Sources area,MOD13Q1 product data and decision tree method for wetland classification were used in this paperAs the dataset have much noises which are called salt and pepper noises,after many experiments,it is found that using the median filter and the principal component(PC) transform methods in the data pre-processing can efficiently revise these MODIS dataIn the processing of the decision tree building,the digital elevation model(DEM) is good for separating the lakes and othersTo control the curve shape and the threshold of the turning point of the curve in order could make useful of the curve of marshes' NDVI time series and finally finished the construction of the decision treeThrough the accuracy testing,the classification accuracy of lakes reached 965%,the overall classification accuracy reached 842%,and the kappa coefficient was 078The results showed that the time series of MOD13Q1 data and decision tree method could meet requirements of lakes and marshes classification in a vast scale,but how to use them to classify the river needs more studies in future

Constructing a Classification System of Wetlands in Huang-Huai-Hai Plain

Abstract: There are complicated and various wetland systems in Huang-Huai-Hai Plain,which is resulted from the evolution of three rivers(Yellow River,Huaihe River and Haihe River) in time and space.The natural evolution characteristics gradually disappear and is restricted by the hydrological regime under artificial adjustment in these wetland systems,whose integrity is broken and landscape is fragmented seriously,due to the influence of human activities.In order to protect,manage and rationally utilize wetlands,it is important to construct an appropriate classification system that is coincident with the current pattern and benefcial to the future management.The ecological services of constructed wetlands are highlighted and a new type named as Ditch Wetland is added to the wetland classification system for facilitating the classification of constructed wetlands.

Wetland Information Extraction from RS Image Based on Wavelet Packet and the Active Learning Support Vector Machine

Abstract: Wetlands which are the planet’s most important ecosystem have high scientific research -value and will bring us both social and economic benefits. However, duing to various natural and man made factors, more and more wetlands have converted to agricultural land and urban land. Now, the changes in wetlands’ area and quantity have caused public’s widespread concern. And wetland’s management and protection will benefit from the improvement of the wetland information abstraction’s precision. Improving the classification precision of the RS image is a difficult problem because of the small scale of remote sensing images. This paper which is about the wetland remote sensing images extraction is based on the LANDSAT ETM remote sensing data, and the result of the Wavelet Packet reconstruction will be used as the sample set of the Active Support Vector Machine .At the end of this paper, a comparative analysis of the experimental results will show between the single classification (SVM, BPNN) method and the solution which is proposed in this article. This method can be proved to obtain very good classification results through many experiments on remote sensing image classification I’ve done. Experimental results show that this algorithm’s classification accuracy is better than the single classification’s. Moreover, in the active learning process, the bad influence of the image’s isolated and intersection points on the classification is avoided, and the number of training samples are reduced greatly.

Wetland Information Extraction Based on Remote Sensing Technology

Abstract: The wetland classification of medium-resolution remote sensing images is a difficult problem because the mixed pixel phenomenon is serious. In this study, visual interpretation was used to extract water. Then the traditional and improved linear spectral mixture analysis models were selected to extract other wetland types. Although errors and confusion exist, this method shows satisfying results with an overall accuracy of 86.2% and a KAPPA coefficient of 0.79. The method in this paper can achieve a more precise information extraction of the wetland and could provide a reference of wetland extraction for other regions.

Evaluation on wetland classification in Yancheng natural reserve, China using HJ-1 data

Abstract: Remote sensing of wetlands is one of important aspect in application and research of remote sensing. This paper studied the HJ-1 CCD data (30m/pixel) applied to wetland resource analysis of the Yancheng national natural reserve. And we gave evaluation on ability of the HJ-1 CCD data in wetland classification. Firstly, we gave the spectral analysis of the typical wetland types. The extraction experiments were carried out by supervised and unsupervised classification methods. Finally, we compared the classification results with those gained from Landsat-5 TM data (June 2007). It indicates that the HJ-1 CCD data have good recognition performance.