Spatial distribution data set of wetlands in Baiyangdian Basin

白洋淀流域湿地连通性研究

模拟多情景下白洋淀流域土地利用变化及生态系统服务价值的空间响应

The physical foundation and environmental assurance provided by the regional habitat are crucial for the survival and sustainable development of organisms. Land use change, as a significant manifestation of human activity, is a crucial factor in habitat quality. An SD-PLUS coupled model was developed to simulate land use change in the Baiyangdian(BYD) Basin using data on land use, socio-economic factors, and the climatic environment from 2000 to 2020. The InVEST model was employed to assess the habitat quality of the basin from 2000 to 2050. The findings indicated the following: Between 2020 and 2050, the predominant land use changes across the three scenarios involve the conversion of farmland to construction land and grassland to woodland. The magnitude of these changes steadily declines over time. The magnitude of change in land use for all kinds was greater under SSP5 compared to SSP1 and SSP2. The movement of habitat quality grades primarily occurred from higher grades to lower grades. In 2050, the habitat quality is projected to improve compared to 2020 under three different scenarios. The highest improvement is expected in SSP5 with a 0.60% increase, followed by SSP2 with a 0.42% increase and SSP1 with the smallest increase of 0.23%.

Ancillary data are crucial in land use land cover (LULC) mapping process. This study goal is to investigate if adding Normalized Difference Vegetation Index (NDVI) and digital elevation model (DEM) data as ancillary data to the Landsat-8 spectral imagery (acquired on 14 April 2016) in the support vector machine (SVM ) classification process improves LULC mapping accuracy in GuaMusang, Malaysia. ENVI software was used to preprocess a single Landsat-8 image, convert it to reflectance, and calculate NDVI. ASTER-GDEM data were used to generate the DEM. The logical channel method was used to combine NDVI and DEM with Landsat-8 bands and limit the impact of shadows during SVM classification. The SVM accuracy was tested and evaluated on ancillary data and Landsat-8 spectral-based collection. The results revealed that the user's accuracy and producer's accuracy improved by 15.1% and 2.1%, for primary forest and by 17.93% and 28.86% for secondary forest, respectively. The classification reliability of the majority of LULC categories has increased significantly. Compared to SVM spectral-based set, the overall accuracy and kappa coefficient of the SVM ancillary-based set improved by 8.77% and 0.12, respectively. In conclusion, this article demonstrated that integrating DEM and NDVI data improves Landsat-8 image classification precision.

Due to the combined effects of the natural environment, climate change and human activities, profound changes have occurred in terms of the eco-environmental effects of land use/cover change (LUCC) in the Baiyangdian basin. Therefore, based on land remote sensing monitoring data from 2000 to 2020, the Eco-environmental Quality Index (EQI) was introduced in this study to measure the eco-environmental effects of land use change in the Baiyangdian basin. Subsequently, the GeoDetector model was applied to detect the formation mechanism of the eco-environmental effects in the Baiyangdian basin from 2000 to 2020. The results of the study showed that cropland, woodland and grassland were the most widely distributed land use types in the Baiyangdian basin. The area of cropland declined the most and was mostly converted to construction land. The EQI increased slightly during the study period. The eco-environment of the mountainous areas in the western part of the basin and in Baiyangdian Lake was better than that of other areas. Land use intensity had a significantly stronger influence on the quality of the eco-environment than other factors. The interaction between the influencing factors was mainly a non-linear enhancement and a two-factor enhancement, with non-linear enhancement dominating.

The analysis of variability of riverbed elevation recorded at five selected gauging cross-sections of Nida River, and at three gauging stations of Czarna Nida is presented in the paper. The studies concern the period of 60 – 80 years of observation. The trends of riverbed changes during the study period at the selected gauging stations were calculated based on the variability of observed minimal annual water stages. The reasons for the observed changes in the river course and channel geometry are given. These changes were caused by river regulation consisted of the shortening and narrowing of the river channel. Moreover, grain size distribution analysis in the selected gauging stations of Nida River and characteristic diameter variability of sediments along the river course examination are presented. These analyses were to evaluate the variability of characteristic diameters along the river course in connection with observed changes in cross-sections’ geometry. Additionally, to confirm the process of erosion or deposition recognized in the examined river channels, hydrodynamic equilibrium was determined. Three methods were proposed and used: the mean velocity and critical velocity in the main river channel comparison, the stream power value calculation which defines the character of the river channel, and the WWK (index of cutting or shallowing of the river channel) index.

The classification of land use in karst areas is mainly through the interpretation of satellite images to get. The traditional interpretation methods are supervised classification and unsupervised classification. But the classification polygons is trivial by supervised classification, and boundary is also complex. Different categories can be distincted by unsupervised classification, however, the property can't be determined by it. SVM(support vector machine) is a new type image classification technique, it has advantages of high accuracy, few errors and misclassifications. In this study, we use SPOT image data, topographic maps and administrative divisions data, employ the knowledge of support vector machine and land use classification, on the support of ENVI software, classify land use of the study area by SVM classification, supervised classification and unsupervised classification. The results showed that using the SVM to classify land use, the accuracy is high, while the supervised classification's and unsupervised classification's are low.

In a classification problem, where each input is associated to one output. Training data is used to create a model which predicts values to the true function. SVM is a popular method for binary classification due to their theoretical foundation and good generalization performance. However, when trained with noisy data, the decision hyperplane might deviate from optimal position because of the sum of misclassification errors in the objective function. In this paper, we introduce fuzzy in weighted learning approach for improving the accuracy of Support Vector Machine (SVM) classification. The main aim of this work is to determine appropriate weighted for SVM to adjust the parameters of learning method from a given set of noisy input to output data. The performance and customer rating in Quality Function Deployment (QFD) is used as our case study to determine implementing fuzzy SVM is highly scalable for very large data sets and generating high classification accuracy.

Archaeological surveys performed for the U.S. Army Corps of Engineers within the Lower Mississippi River and Red River Valleys have noted that archaeological deposits found on the natural levees of relict river channels consist only of surficial sites that postdate the abandonment of the associated river channel. From the results of these surveys, Richard Weinstein and David Kelley proposed the Channel in 1989. Their rule states that the archaeological deposits associated with the natural levees of an abandon river channel will consist only of surficial sites that postdate the abandonment of the river channel. The Relict Channel Rule has been explained as the result of preferences by prehistoric cultures to avoid the occupation of natural levees of active river channels. Archaeologists have suggested that the lack of rich biotic resources associated with an active channel and the hazards created by periodic flooding caused prehistoric cultures to avoid settling the natural levees of active river channels. Rather, it has been proposed that prehistoric cultures settled around oxbow lakes within abandoned channel segments. In addition, archaeological studies of the Red River within Arkansas have speculated that the danger posed by rapidly eroding cut banks was another factor that discouraged the settlement of the natural levees of active river channels. Sedimentological processes provide an alternative explanation for the Relict Channel Rule. While active, a typical meandering river channel rapidly migrates back and forth across its meander belt. During this time, its channel would rapidly migrate away from any archaeological deposits that formed adjacent to an active point bar. Simultaneously, overbank processes would quickly bury them. Also, an actively laterally migrating channel would consume the sites that form on the natural levee of a rapidly migrating cutbank. If a river cutbank was to migrate up to and stop at a preexisting site, that site would by that time be buried beneath natural levee deposits. Finally, archaeological sites formed during the initial establishment of a river course would eventually be either deeply buried by aggradation of natural levees or destroyed by lateral migration. As a result, only those archaeological deposits that date to a few tens of years prior to and postdate the abandonment of the channel will occur as surface sites. Therefore, regardless of whether the natural levees of a channel of an actively meandering river were used before or -after its abandonment, the rapid lateral migration of its channel while active will produce the distribution of surface sites noted by the Relict Channel Rule. An active segment of the Mississippi River between Donaldsonville and Port Allen, Louisiana is an exception to the Relict Channel Rule. Along this segment, numerous surface and scattered buried sites containing transitional Coles Creek and Plaquemine components have been recorded from the natural levees along both sides of the currently active Mississippi River. These sites, which include several mounds, occur most commonly on the cutbank side of a meander loop. Along one twenty mile segment, at least one prehistoric site is associated with each meander loop. Preexisting archaeological deposits are present along this active segment of the Mississippi River, because of the slow rate of lateral migration of its river channel. The slow rate of lateral migration has permitted the preservation of archaeological deposits that faster rates of lateral migration would have destroyed. Also, historic maps show that historic Native American villages heavily occupied the natural levees of this active segment of the Mississippi River. Thus, this study strongly indicates that the distribution of archaeological sites as expressed by the Relict Channel rule is a result of fluvial rather then cultural processes. It is concluded that the rapid lateral migration of a channel within a meander belt badly biases the temporal distribution of both surficial and buried archaeological deposits within it. First, the formation of a meander belt destroys any archaeological deposits that predate it. Second, rapid lateral migration of a river will destroy many of the archaeological deposits contemporaneous with its activity. A few archaeological deposits contemporaneous with an active river course might survive destruction along the outer edge of the meander belt as buried or surface sites associated with the natural levees of abandoned meander loops. Finally, any archaeological deposits that formed after the abandonment of a river course will occur as surface sites. Because of the extensive destruction and burial of sites by meander belt processes, reconstructing settlement patterns from the distribution of recorded sites can be difficult, if not impossible, for the archaeological deposits of many cultural groups. 140 Wylie Dr., Apt. 5, Baton Rouge, Louisiana 70808

Despite of good theoretic foundations and high classification accuracy of support vector machines (SVM), normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is very high. This paper presents a novel SVM classification approach for large data sets by considering models of classes distribution (MCD). A first stage uses SVM classification in order to gets a sketch of classes distribution. Then the algorithm obtain the support vectors (SVs) most close between each class and construct a ball using minimum enclosing ball from each pair of SVs with different label. The data points included in the balls constitute the MCD, which is the framework in the boundary of each class and represents the most important data points, these data points are used as training data for a posterior SVM classification. Experimental results show that our approach has good classification accuracy while the training is significantly faster than other SVM classifiers.

Human activities and river course change have a complex reciprocal interaction. The river channel is altered by human activity, and these alterations have an impact on the activities and settlements along the riverbank. Understanding the relationship between urbanization and changes in river morphology is crucial for effective river management, safeguarding the urban environment, and mitigating flood hazards. In this context, this study has been conducted to investigate the interrelationship between morphological dynamics, built-up growth, and urban flood risk along the Manohara River in Kathmandu Valley, Nepal. The Sinuosity Index was used to analyze variation in river courses and instability from 1996 to 2023. Built-up change analysis is carried out using supervised maximum likelihood classification method and rate of change is calculated for built-up area growth (2003–2023) and building construction between 2003 and 2021. Flood hazard risk manning was carried out using flood frequency estimation method integrating HEC-GeoRAS modeling. Linear regression and spatial overlay analysis was carried out to examine the interrelationship between river morphology, urban growth, and fold hazed risk. In recent years (2016–2023), the Manohara River has straightened, particularly after 2011. Before 2011, it had significant meandering with pronounced curves and bends, indicating a mature river system. However, the SI value of 1.45 in 2023 and 1.80 in 2003 indicates a significant straightening of high meandering over 20 years. A flood hazard modeling carried out within the active floodplain of the Manohara River shows that 26.4% of the area is under high flood risk and 21% is under moderate risk. Similarly, over 10 years from 2006 to 2016, the rate of built-up change was found to be 9.11, while it was 7.9 between 2011 and 2021. The calculated R2 value of 0.7918 at a significance level of 0.05 (with a p value of 0.0175, and a standard error value of 0.07877) indicates a strong positive relationship between decreasing sinuosity and increasing built-up, which demonstrates the effect of built-up expansion on river morphology, particularly the anthropogenic activities of encroachment and haphazard constructions, mining, dumping wastes, and squatter settlements along the active floodplain, causing instability on the river course and hence, lateral shift. The riverbank and active floodplain are not defined scientifically, which leads to the invasion of the river area. These activities, together with land use alteration in the floodplain, show an increased risk of flood hazards and other natural calamities. Therefore, sustainable protection measures must be prioritized in the active floodplain and flood risk areas, taking into account upstream–downstream linkages and chain effects caused by interaction between natural and adverse anthropogenic activities.

The action of the river is dynamic and exhibits morphological changes over time. River channel migration may take place because of sedimentation, geology, soil properties, geomorphic setup, precipitation, land use pattern, natural bank geometry (e.g., channel width, meander length, meander wavelength, amplitude, the radius of curvature, arc angle, and sinuosity), discharges of various frequencies (Brice 1982, MacDonald et al. 1991, Garcia et al. 1994), distribution of riparian vegetation, and vertical and horizontal heterogeneity of floodplain soils (Motta et al. 2012), etc. are some factors for channel migration. The present study is undertaken in the Dibru River Basin, the left-bank tributary of the Brahmaputra River. To identify the Spatio-temporal changes, satellite imagery is used in the GIS environment. The extraction of the river is done from the GIS software (Arc GIS 10.4) by digitizing process and tries to overlay the different time periods of shifting of the river and find out the rate of magnitude and nature of the river course changes. An interval of 10 years is taken to find the rate of magnitude and nature of changes in the river courses from satellite imagery. The time period is taken from 1977-2020 at 10 years intervals. Along with the rate of river course changes, channel avulsion is also shown with the help of satellite imagery. The Dibru Saikhowa National Park falls within the Dibru river basin, where numerous streams are found, within the national park. The Saikhoa river and Ajuka river flow within the national park. The Sursa river is a small channel linked with the Dangori river. With phases of time, the river made a headward erosion and confluence with the Ajuka river and formed a channel. The Saikhoa river flowed till 1987; due to deposition, the river abandoned its original course. In 1988, the Ajuka river and Sursa river merged and flowed northwest direction. The high discharges of the Lohit river diverted towards the Ajuka and Sursa Rivers and took a new channel named the Lower course of Lohit river within the study area. It can be called an avulsion channel because it changed its direction from its original to a new course in 1990. Since 1990, the course of the channel has been tremendously expanding its length and breadth, causing a flood, bank erosion, and deposition nearby human habitats and Dibru Saikhowa National Park. From the multi-temporal satellite imagery, the river courses were studied, and found the year of avulsion took place in the channel. Multi-temporal satellite imagery is used to identify the channel’s avulsion. An avulsion is the rapid separation of a river channel to form a new course, which is only possible due to flood, high discharge, soil properties or tectonic activity, etc. that creates instability and causes the channel avulsion.

River is a factor which determines environmental characteristics and scenery of an area; therefore, it is important to clarify the history of land use in old river channels in order to understand its local characteristics. In this study, the middle stream to downstream area of Arakawa River which is being vast floodplain is investigated. The objective of this study is investigating the correlation between Arakawa River’s topography and land use history in its old river channels. The land use history analysis was conducted by analyzing topographical map with scale 1/25,000, the old version of a topographical map, and aerial photographs. The GIS data was developed from topographical classification of the Arakawa River basin in order to clarify the relationship between topography and old river channels. Furthermore, a field research was conducted to obtain actual land use data. The result shows that the combinations of topography and old river channels can be classified into four types. From the study above, the land use of old river channels was changed caused by its land form and social factor in that area. It is also found that the history of land use in the old river channels from the Taisho Period to the present has been changed.

The relationship between ecosystem service supply and demand in plain areas undergoing urbanization: A case study of China's Baiyangdian Basin

Clarifying the complex relationships among ecosystem services (ESs) and their driving mechanisms is essential for effective ecosystem management and enhancing human welfare. Nonetheless, the current research on these issues still remains limited; therefore, further theoretical exploration is required. This study aims to quantitatively illustrate the trade-off strength of ESs and investigate the spatiotemporal heterogeneity connections between these relationships and various anthropogenic and natural factors in Baiyangdian basin, China, integrating InVEST, RMSE, geographical detector and MGWR methods. From 2000 to 2020, the total water yield (WY) and nutrient export (NE) increased, while the total carbon storage (CS) and habitat quality (HQ) decreased slightly. The trade-offs of ESs showed spatiotemporal heterogeneity. The most serious trade-off occurred between regulating services (CS and NE) and supporting services (HQ) in 2000, which was mainly distributed in the densely forested and grassed western and northern regions of the basin. The trade-off intensities of half of the pairwise ESs in 2020 increased, with the strengthened areas mainly located in the southeast of the watershed where built-up lands are concentrated. Various factors dominated the trade-offs among ESs, with the interactive effects of multiple drivers being more significant than those of individual factors. Land use type, vegetation cover and precipitation have the most pronounced effect on the trade-offs among ESs. The findings of this study may suggest and advocate for spatial ecological strategies to enhance the integrated and holistic advancement of various ESs and also serve as a reference for regional ecosystem governance and the attainment of sustainable growth.