scholarly journals Extracting Frequent Sequential Patterns of Forest Landscape Dynamics in Fenhe River Basin, Northern China, from Landsat Time Series to Evaluate Landscape Stability

2021 ◽  
Vol 13 (19) ◽  
pp. 3963
Author(s):  
Yue Zhang ◽  
Xiangnan Liu ◽  
Qin Yang ◽  
Zhaolun Liu ◽  
Yu Li
Keyword(s):  
Time Series ◽  
River Basin ◽  
Landscape Pattern ◽  
Pattern Mining ◽  
Northern China ◽  
Shape Index ◽  
Landscape Patterns ◽  
Forest Landscape ◽  
Distribution Law ◽  
Scientific Support

The forest landscape pattern evolution can reveal the intensity and mode of action of human–land relationships at different times and in different spaces, providing scientific support for regional ecological security, human settlement health, and sustainable development. In this study, we proposed a novel method for analyzing the dynamics of landscape patterns. First, patch density (PD), largest patch index (LPI), landscape shape index (LSI), and contiguity index (CI) were used to identify the types of forest spatial patterns. The frequent sequential pattern mining method was used to detect the frequent subsequences from the time series of landscape pattern types from 1991 to 2020 and further evaluate the forest landscape stability of the Fenhe River Basin in China. The results show that different frequent sequence patterns have conspicuous spatial and temporal differences, which describe the evolution processes and stability changes during a certain period of forest evolution and play an important role in the analysis of forest dynamics. The proportion of the disturbed regions to the total forest area exhibited a downward trend. The long-term evolution pattern indicates that there are many evolution processes and trends in the forest at the same time, showing an aggregation distribution law. Compared with 2016, the forest landscape has become complete in 2020, and the overall stability of the Fenhe River Basin has improved. This study can provide scientific support to land managers and policy implementers and offer a new perspective for studying forest landscape pattern changes and evaluating landscape stability.

scholarly journals A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 990
Author(s):  
Yongfen Zhang ◽  
Nong Wang ◽  
Chongjun Tang ◽  
Shiqiang Zhang ◽  
Yuejun Song ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
River Basin ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Sediment Yield ◽  
River Basins ◽  
Landscape Patterns ◽  
Soil Erodibility ◽  
Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

scholarly journals Study of the Spatiotemporal Variation Characteristics of Forest Landscape Patterns in Shanghai from 2004 to 2014 Based on Multisource Remote Sensing Data

2018 ◽  
Vol 10 (12) ◽  
pp. 4397 ◽  
Author(s):  
Yang Li ◽  
Chunyan Xue ◽  
Hua Shao ◽  
Ge Shi ◽  
Nan Jiang
Keyword(s):  
Spatial Distribution ◽  
Landscape Pattern ◽  
Urban Forest ◽  
Urban Forests ◽  
Urban Ecosystem ◽  
Landscape Patterns ◽  
Forest Landscape ◽  
Forest Patches ◽  
Forest Coverage ◽  
High Degree

The landscape patterns of urban forests not only reflect the influence of urbanization on urban forests, but also determines its function in urban ecosystem services. In the case of mastering the overall forest landscape pattern of a city, a study of the structure of urban forest landscapes at different scales and in urbanized regions is beneficial to a comprehensive understanding of the forest characteristics of a city. In the present study, an attempt was made to map and monitor the spatio-temporal dynamics of an urban forest in Shanghai from 2004 to 2014 using remote sensing techniques. Methods of landscape ecology analysis are followed to quantify the spatiotemporal patterns of an urban forest landscape by urban and rural gradient regionalization. The results show that the spatial structure of an urban forest landscape is essentially consistent with an urban landscape pattern. Due to strong interference from human activities, the ecological quality of forest landscapes is low. At the landscape level, the urban forest coverage rate increased from 11.43% in 2004 to 16.02% in 2014, however, the number of large patches decreased, there was a high degree of urban forest landscape fragmentation, landscape connectivity was poor, landscape patch boundaries were uniform, and weak links were present between ecological processes. Different urban and rural gradient division methods exhibit obvious gradient characteristics along the urban–rural gradient in Shanghai. The regional differences in the urban forest landscape ecological characteristics have further increased as a result of urban planning and zoning. The total amount of urban forest is located closer to the urban center, which has the smallest total amount of forest; however, in terms of urban forest coverage, the suburbs have more coverage than do the outer suburbs and the central urban areas. The urban forest landscape’s spatial distribution area is evidently different. Urbanization affects the areas closest to urban residential areas, which are markedly disturbed by humans, and the urban forest landscape has a high degree of fragmentation. The forest patches have become divided and unconnected, and the degree of natural connectivity has gradually decreased over the past 10 years. At the landscape class level, broadleaf forests are dominant in Shanghai, and their area exhibits an increasing trend; shrublands and needleleaf forests, however, show a decreasing trend. Compared with other forest types, the spatial distribution of broadleaf forest is concentrated in the suburbs, and the aggregation effect is relatively apparent. From the perspective of urban forest landscape pattern aggregation characteristics in Shanghai, the spatial distribution of urban forest landscape point patterns in the study area exhibit extremely uneven characteristics. The point density of urban forest patches larger than 1 ha in Shanghai increased from 2004 to 2014. However, the total number of patches with areas larger than 5 ha decreased, and this decrease plays an important role in the ecological environment. In the past 10 years, the concentration characteristics of urban forests with large patches has gradually decreased. In 2014, the urban forest landscapes decreased by 5 km compared to the intensity of aggregates in 2004, which also indicates that urban forests in Shanghai tend to be fragmented. The results of this study can be useful to help improve urban residents’ living environments and the sustainable development of the urban ecosystem, and they will also be vital to future management.

scholarly journals Study of the Landscape Pattern of Shuiyu Village in Beijing, China: A Comprehensive Analysis of Adaptation to Local Microclimate

2021 ◽  
Vol 14 (1) ◽  
pp. 375
Author(s):  
Ling Qi ◽  
Ranqian Liu ◽  
Yuechen Cui ◽  
Mo Zhou ◽  
Wojciech Bonenberg ◽  
...  
Keyword(s):  
Landscape Pattern ◽  
Rural Areas ◽  
Optimization Design ◽  
Adaptive Design ◽  
Northern China ◽  
Comprehensive Analysis ◽  
Landscape Patterns ◽  
Climate Index ◽  
Technical Parameters ◽  
Computer Numerical Simulation

The paper used technical parameters to investigate optimized solutions to protect the ecological environment and improve the microclimate adaptability among the traditional villages in Beijing. Shuiyu Village was used as a case study to analyze the coupling relationship between landscape patterns and the microclimate of traditional villages, with a focus on the ecological relationship between residents and the microclimate. This study also developed a climate index system, which includes computer numerical simulation and microclimate comprehensive analysis methods. The distinct types of landscape patterns were studied using the system. In addition, this paper studied the adaptive design mechanism in-depth, the form parameters of comfort evaluation controllability, and map expression technology of morphological parameters. The findings of this study include the optimized value of the environment based on landscape pattern and the map through the Rhino modeling platform. An interactive platform was developed, and a parametric-assisted optimization design process for traditional villages in the northern part of China was proposed. Moreover, this study concluded optimized strategies and technical guidelines for future planning of the rural areas in northern China with a goal to protect traditional villages and transform them into smart villages with microclimate adaptability.

Forest landscape patterns dynamics of Yihe-Luohe river basin

2003 ◽  
Vol 13 (2) ◽  
pp. 153-162
Author(s):  
Ding Shengyan ◽  
Shang Fude ◽  
Qian Lexiang ◽  
Cao Xinxiang ◽  
Li Shuang ◽  
...  
Keyword(s):  
River Basin ◽  
Landscape Patterns ◽  
Forest Landscape

scholarly journals Spatiotemporal Mining of Time-Series Remote Sensing Images Based on Sequential Pattern Mining

2015 ◽  
Vol II-4/W2 ◽  
pp. 111-118
Author(s):  
H. C. Liu ◽  
G. J. He ◽  
X. M. Zhang ◽  
W. Jiang ◽  
S. G. Ling
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Land Cover ◽  
Land Cover Change ◽  
Pattern Mining ◽  
Sequential Pattern Mining ◽  
Sequential Pattern ◽  
Landscape Patterns ◽  
Mining Method ◽  
Study Region

With the continuous development of satellite techniques, it is now possible to acquire a regular series of images concerning a given geographical zone with both high accuracy and low cost. Research on how best to effectively process huge volumes of observational data obtained on different dates for a specific geographical zone, and to exploit the valuable information regarding land cover contained in these images has received increasing interest from the remote sensing community. In contrast to traditional land cover change measures using pair-wise comparisons that emphasize the compositional or configurational changes between dates, this research focuses on the analysis of the temporal sequence of land cover dynamics, which refers to the succession of land cover types for a given area over more than two observational periods. Using a time series of classified Landsat images, ranging from 2006 to 2011, a sequential pattern mining method was extended to this spatiotemporal context to extract sets of connected pixels sharing similar temporal evolutions. The resultant sequential patterns could be selected (or not) based on the range of support values. These selected patterns were used to explore the spatial compositions and temporal evolutions of land cover change within the study region. Experimental results showed that continuous patterns that represent consistent land cover over time appeared as quite homogeneous zones, which agreed with our domain knowledge. Discontinuous patterns that represent land cover change trajectories were dominated by the transition from vegetation to bare land, especially during 2009–2010. This approach quantified land cover changes in terms of the percentage area affected and mapped the spatial distribution of these changes. Sequential pattern mining has been used for string mining or itemset mining in transactions analysis. The expected novel significance of this study is the generalization of the application of the sequential pattern mining method for capturing the spatial variability of landscape patterns, and their trajectories of change, to reveal information regarding process regularities with satellite imagery.

River-Basin Planning for Control of Nitrate Pollution

1982 ◽  
Vol 14 (4-5) ◽  
pp. 245-252 ◽  
Author(s):  
C S Sinnott ◽  
D G Jamieson
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
River Basin ◽  
Water Resource ◽  
Potable Water ◽  
Potential Problem ◽  
Nitrate Pollution ◽  
Optimal Mix ◽  
Regional Basis ◽  
The Impact

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.

scholarly journals Superiority of Hybrid Soft Computing Models in Daily Suspended Sediment Estimation in Highly Dynamic Rivers

2021 ◽  
Vol 13 (2) ◽  
pp. 542
Author(s):  
Tarate Suryakant Bajirao ◽  
Pravendra Kumar ◽  
Manish Kumar ◽  
Ahmed Elbeltagi ◽  
Alban Kuriqi
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Suspended Sediment ◽  
River Basin ◽  
Time Series Data ◽  
Series Data ◽  
Discrete Wavelet ◽  
Original Time Series ◽  
Inference System ◽  
Original Time

Estimating sediment flow rate from a drainage area plays an essential role in better watershed planning and management. In this study, the validity of simple and wavelet-coupled Artificial Intelligence (AI) models was analyzed for daily Suspended Sediment (SSC) estimation of highly dynamic Koyna River basin of India. Simple AI models such as the Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were developed by supplying the original time series data as an input without pre-processing through a Wavelet (W) transform. The hybrid wavelet-coupled W-ANN and W-ANFIS models were developed by supplying the decomposed time series sub-signals using Discrete Wavelet Transform (DWT). In total, three mother wavelets, namely Haar, Daubechies, and Coiflets were employed to decompose original time series data into different multi-frequency sub-signals at an appropriate decomposition level. Quantitative and qualitative performance evaluation criteria were used to select the best model for daily SSC estimation. The reliability of the developed models was also assessed using uncertainty analysis. Finally, it was revealed that the data pre-processing using wavelet transform improves the model’s predictive efficiency and reliability significantly. In this study, it was observed that the performance of the Coiflet wavelet-coupled ANFIS model is superior to other models and can be applied for daily SSC estimation of the highly dynamic rivers. As per sensitivity analysis, previous one-day SSC (St-1) is the most crucial input variable for daily SSC estimation of the Koyna River basin.

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