scholarly journals Assessment and Estimation of the Spatial and Temporal Evolution of Landscape Patterns and Their Impact on Habitat Quality in Nanchang, China

Land ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1073
Author(s):  
Yanan Li ◽  
Linghua Duo ◽  
Ming Zhang ◽  
Zhenhua Wu ◽  
Yanjun Guan
Keyword(s):  
Land Use ◽  
Habitat Quality ◽  
Landscape Pattern ◽  
Prediction Models ◽  
Landscape Patterns ◽  
Assessment Model ◽  
Planning System ◽  
Distribution Data ◽  
Ecological Planning ◽  
The Impact

Assessing and predicting the evolution of habitat quality based on land use change under the process of urbanization is important for establishing a comprehensive ecological planning system and addressing the major challenges of global sustainable development. Here, two different prediction models were used to simulate the land use changes in 2025 based on the land use distribution data of Nanchang city in three periods and integrated into the habitat quality assessment model to specifically evaluate the trends and characteristics of future habitat quality changes, explore the impact of landscape pattern evolution on habitat, and analyze the differences and advantages of the two prediction models. The results show that the overall habitat quality in Nanchang declined significantly during the period 1995–2015. Habitat degradation near cities and in various watersheds is relatively significant. During the period 2015–2025, the landscape pattern and habitat quality of Nanchang will continue to maintain the trend of changes observed between 1995 and 2015, i.e., increasing construction land and decreasing habitat quality, with high pressure on ecological restoration. This study also identified that CA-Markov simulates the quantity of land use better, while FLUS simulates the spatial pattern of land use better. Overall, this study provides a reference for exploring the complex dynamic evolution mechanism of habitats.

scholarly journals Assessing Habitat Vulnerability and Loss of Naturalness: Applying the GLOBIO3 Model in the Czech Republic

2021 ◽  
Vol 13 (10) ◽  
pp. 5355
Author(s):  
Vilém Pechanec ◽  
Ondřej Cudlín ◽  
Miloš Zapletal ◽  
Jan Purkyt ◽  
Lenka Štěrbová ◽  
...  
Keyword(s):  
Land Use ◽  
Czech Republic ◽  
Habitat Quality ◽  
Species Abundance ◽  
Biodiversity Loss ◽  
Infrastructure Development ◽  
Natural Habitats ◽  
The Czech Republic ◽  
New Equation ◽  
The Impact

Global and regional biodiversity loss is caused by several drivers including urban development, land use intensification, overexploitation of natural resources, environmental pollution, and climate change. The main aim of our study was to adapt the GLOBIO3 model to the conditions of the Czech Republic (CR) to assess loss of naturalness and biodiversity vulnerability at the habitat level on a detailed scale across the entire CR. An additional aim was to assess the main drivers affecting the biodiversity of habitat types. The GLOBIO3 model was adapted to CZ-GLOBIO by adapting global to local scales and using habitat quality and naturalness data instead of species occurrence data. The total mean species abundance (MSA) index of habitat quality, calculated from the spatial overlay of the four MSA indicators by our new equation, reached the value 0.62. The total value of MSA for natural and near-natural habitats was found to be affected mainly by infrastructure development and fragmentation. Simultaneously, intensity of land use change and atmospheric nitrogen deposition contributed primarily to the low total value of MSA for distant natural habitats. The CZ-GLOBIO model can be an important tool in political decision making to reduce the impact of the main drivers on habitat biodiversity in the CR.

scholarly journals Investigation of Climate and Land Use Change Impacts on Stream Flow of Guder Catchment, Ethiopia

2021 ◽  
Author(s):  
Bekam Bekele Gulti ◽  
Boja Mokonnen Manyazew ◽  
Abdulkerim Bedewi Serur
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Stream Flow ◽  
Open Space ◽  
Smart Growth ◽  
Assessment Model ◽  
Study Region ◽  
Climate Conditions ◽  
Change Impact ◽  
The Impact

Abstract Climate change (CC) and land use/cover change (LUCC) are the main drivers of streamflow change. In this paper, we investigate the impact of climate and LULC change impact on stream flow of Guder catchment by using Soil and Water Assessment model (SWAT). The scenarios were designed in a way that LULC was changed while climate conditions remain constant; LULC was then held constant under a changing climate and combined effect of both. The result shows that, the combined impacts of climate change and LULC dynamics can be rather different from the effects that follow-on from LULC or climate change alone. Streamflow would be more sensitive to climate change than to the LULC changes scenario, even though changes in LULC have far-reaching influences on streamflow in the study region. A comprehensive strategy of low impact developments, smart growth, and open space is critical to handle future changes to streamflow systems.

scholarly journals Relating Land Use/Cover and Landscape Pattern to the Water Quality under the Simulation of SWAT in a Reservoir Basin, Southeast China

2021 ◽  
Vol 13 (19) ◽  
pp. 11067
Author(s):  
Kaige Lei ◽  
Yifan Wu ◽  
Feng Li ◽  
Jiayu Yang ◽  
Mingtao Xiang ◽  
...  
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Google Earth ◽  
Landscape Patterns ◽  
Buffer Size ◽  
Construction Land ◽  
Drinking Water Standard ◽  
Reservoir Basin ◽  
The Impact ◽  
Cover Pattern

Understanding the relationship between land use/cover pattern and water quality could provide guidelines for non-point source pollution and facilitate sustainable development. The previous studies mainly relate the land use/cover of the entire region to the water quality at the monitoring sites, but the water quality at monitoring sites did not totally reflect the water environment of the entire basin. In this study, the land use/cover was monitored on Google Earth Engine in Tang-Pu Reservoir basin, China. In order to reflect the water quality of the whole study area, the spatial distribution of the determinants for water quality there, i.e., the total nitrogen and total phosphorus (TN&TP), were simulated by the Soil and Water Assessment Tool (SWAT). The redundancy analysis explored the correlations between land use/cover pattern and simulated TN&TP. The results showed that: (1) From 2009 to 2019, forest was the dominant land cover, and there was little land use/cover change. The landscape fragmentation increased, and the connectivity decreased. (2) About 25% TP concentrations and nearly all the TN concentrations at the monitoring points did not reach drinking water standard, which means nitrogen and phosphorus pollution were the most serious problems. The highest output per unit TN&TP simulated by SWAT were 44.50 kg/hm2 and 9.51 kg/hm2 and occurred in areas with highly fragile landscape patterns. (3) TN&TP correlated positively with cultivated and construction land but negatively with forest. The correlation between forest and TN&TP summited at 500–700-m buffer and construction land at 100-m buffer. As the buffer size increased, the correlation between the cultivated land, and the TN weakened, while the correlation with the TP increased. TN&TP correlated positively with the Shannon’s Diversity Index and negatively with the Contagion Index. This study provides a new perspective for exporting the impact of land use/cover pattern on water quality.

scholarly journals Spatio-Temporal Variation Analysis of Landscape Pattern Response to Land Use Change from 1985 to 2015 in Xuzhou City, China

2018 ◽  
Vol 10 (11) ◽  
pp. 4287 ◽  
Author(s):  
Yantao Xi ◽  
Nguyen Thinh ◽  
Cheng Li
Keyword(s):  
Land Use ◽  
Landscape Pattern ◽  
Urban Areas ◽  
Vegetation Index ◽  
Agricultural Land ◽  
Local Level ◽  
Land Use Changes ◽  
Landscape Patterns ◽  
Rapid Urbanization ◽  
Barren Land

Rapid urbanization has dramatically spurred economic development since the 1980s, especially in China, but has had negative impacts on natural resources since it is an irreversible process. Thus, timely monitoring and quantitative analysis of the changes in land use over time and identification of landscape pattern variation related to growth modes in different periods are essential. This study aimed to inspect spatiotemporal characteristics of landscape pattern responses to land use changes in Xuzhou, China durfing the period of 1985–2015. In this context, we propose a new spectral index, called the Normalized Difference Enhanced Urban Index (NDEUI), which combines Nighttime light from the Defense Meteorological Satellite Program/Operational Linescan System with annual maximum Enhanced Vegetation Index to reduce the detection confusion between urban areas and barren land. The NDEUI-assisted random forests algorithm was implemented to obtain the land use/land cover maps of Xuzhou in 1985, 1995, 2005, and 2015, respectively. Four different periods (1985–1995, 1995–2005, 2005–2015, and 1985–2015) were chosen for the change analysis of land use and landscape patterns. The results indicate that the urban area has increased by about 30.65%, 10.54%, 68.77%, and 143.75% during the four periods at the main expense of agricultural land, respectively. The spatial trend maps revealed that continuous transition from other land use types into urban land has occurred in a dual-core development mode throughout the urbanization process. We quantified the patch complexity, aggregation, connectivity, and diversity of the landscape, employing a number of landscape metrics to represent the changes in landscape patterns at both the class and landscape levels. The results show that with respect to the four aspects of landscape patterns, there were considerable differences among the four years, mainly owing to the increasing dominance of urbanized land. Spatiotemporal variation in landscape patterns was examined based on 900 × 900 m sub-grids. Combined with the land use changes and spatiotemporal variations in landscape patterns, urban growth mainly occurred in a leapfrog mode along both sides of the roads during the period of 1985 to 1995, and then shifted into edge-expansion mode during the period of 1995 to 2005, and the edge-expansion and leapfrog modes coexisted in the period from 2005 to 2015. The high value spatiotemporal information generated using remote sensing and geographic information system in this study could assist urban planners and policymakers to better understand urban dynamics and evaluate their spatiotemporal and environmental impacts at the local level to enable sustainable urban planning in the future.

ECONOMIC AND PHYSICAL MODELING OF LAND USE IN GCAM 3.0 AND AN APPLICATION TO AGRICULTURAL PRODUCTIVITY, LAND, AND TERRESTRIAL CARBON

2014 ◽  
Vol 05 (02) ◽  
pp. 1450003 ◽  
Author(s):  
MARSHALL WISE ◽  
KATE CALVIN ◽  
PAGE KYLE ◽  
PATRICK LUCKOW ◽  
JAE EDMONDS
Keyword(s):  
Land Use ◽  
Crop Yield ◽  
Carbon Emissions ◽  
Crop Yields ◽  
Assessment Model ◽  
Agricultural Crop ◽  
Terrestrial Carbon ◽  
Global Change Assessment Model ◽  
The Impact

The release of the Global Change Assessment Model (GCAM) version 3.0 represents a major revision in the treatment of agriculture and land-use activities in a model of long-term, global human and physical Earth systems. GCAM 3.0 incorporates greater spatial and temporal resolution compared to GCAM 2.0. In this paper, we document the methods embodied in the new release, describe the motivation for the changes, compare GCAM 3.0 methods to those of other long-term, global agriculture-economy models and apply GCAM 3.0 to explore the impact of changes in agricultural crop yields on global land use and terrestrial carbon. In the absence of continued crop yield improvements throughout the century, not only are cumulative carbon emissions a major source of CO 2 emissions to the atmosphere, but bioenergy production remains trivial — land is needed for food. In contrast, the high crop yield improvement scenario cuts terrestrial carbon emissions dramatically and facilitates both food and energy production.

Evaluating the Impact of Socioeconomics, Land Use, Built Environment, and Road Facility on Cyclist Safety

2017 ◽  
Vol 2659 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Ahmed Osama ◽  
Tarek Sayed
Keyword(s):  
Land Use ◽  
Built Environment ◽  
Prediction Models ◽  
Spatial Effects ◽  
Severe Injuries ◽  
Bayesian Techniques ◽  
The Road ◽  
Safety Models ◽  
Light Pole ◽  
The Impact

With the increasing demand for sustainability, the use of cycling as an efficient active mode of transportation is being encouraged. However, the vulnerability of cyclists to severe injuries in crashes can discourage road users from cycling. Therefore, the study of the factors that affect the safety of cyclists is important. This paper describes an investigation of the relationship between cyclist–motorist crashes and various traffic zone characteristics in Vancouver, British Columbia, Canada. The goal was to assess the impacts of socioeconomics, land use, the built environment, and the road facility on cyclist safety through the use of macrolevel collision prediction models. The models were developed by generalized linear regression and full Bayesian techniques. An actual bike exposure indicator (the number of bike kilometers traveled) and the number of vehicle kilometers traveled were used as exposure variables in the models. The safety models showed that cyclist–motorist crashes were nonlinearly associated with an increase in bike, vehicle, and transit traffic as well as socioeconomic variables (i.e., population, employment, and household densities), variables related to the built environment (transit stop, traffic signal, and light pole densities), commercial area density, and the proportion if arterial–collector roads. The models revealed, however, a decline in cyclist–motorist crashes in association with an increase in the proportions of local roads and off-street bike links and an increase in recreational and residential area densities. The spatial effects were accounted for in the full Bayes models and were found to be significant; such a finding implies the importance of consideration of the spatial correlation in the development of macrolevel cyclist safety models.

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 Density of Biogas Power Plants as An Indicator of Bioenergy Generated Transformation of Agricultural Landscapes

2019 ◽  
Vol 11 (9) ◽  
pp. 2500 ◽  
Author(s):  
Nandor Csikos ◽  
Malte Schwanebeck ◽  
Michael Kuhwald ◽  
Peter Szilassi ◽  
Rainer Duttmann
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landscape Pattern ◽  
Power Plants ◽  
Biogas Production ◽  
Kernel Density ◽  
Shape Index ◽  
Agricultural Landscapes ◽  
The Impact ◽  
Impact Zones

The increasing use of biogas, produced from energy crops like silage maize, is supposed to noticeably change the structures and patterns of agricultural landscapes in Europe. The main objective of our study is to quantify this assumed impact of intensive biogas production with the example of an agrarian landscape in Northern Germany. Therefore, we used three different datasets; Corine Land Cover (CLC), local agricultural statistics (Agrar-Struktur-Erhebung, ASE), and data on biogas power plants. Via kernel density analysis, we delineated impact zones which represent different levels of bioenergy-generated transformations of agrarian landscapes. We cross-checked the results by the analyses of the land cover and landscape pattern changes from 2000 to 2012 inside the impact zones. We found significant correlations between the installed electrical capacity (IC) and land cover changes. According to our findings, the landscape pattern of cropland—expressed via landscape metrics (mean patch size (MPS), total edge (TE), mean shape index (MSI), mean fractal dimension index (MFRACT)—increased and that of pastures decreased since the beginning of biogas production. Moreover, our study indicates that the increasing number of biogas power plants in certain areas is accompanied with a continuous reduction in crop diversity and a homogenization of land use in the same areas. We found maximum degrees of land use homogenisation in areas with highest IC. Our results show that a Kernel density map of the IC of biogas power plants might offer a suitable first indicator for monitoring and quantifying landscape change induced by biogas production.

scholarly journals Spatiotemporal analysis of landscape patterns and its effect on soil loss in the Rmel river basin, Tunisia

2020 ◽  
Vol 16 (No. 1) ◽  
pp. 39-49
Author(s):  
Sana Bouguerra ◽  
Sihem Jebari ◽  
Jamila Tarhouni
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Soil Loss ◽  
Water Resource Management ◽  
Landscape Patterns ◽  
Delivery Ratio ◽  
Trade Offs ◽  
Sediment Export ◽  
The Impact

Changes in land use and land cover (LULC) are generally associated with environment pollution and the degradation of natural resources. Detecting LULC changes is essential to assess the impact on ecosystem services. The current research studies the impact of the LULC change on the soil loss and sediment export in a period of 43 years from 1972 to 2015. Landsat imageries were classified into five classes using a supervised classification method and the maximum likelihood Algorithm. Then, the sediment retention service for avoiding reservoir sedimentation was assessed using the InVEST SDR (integrated valuation of ecosystem services and trade-offs sediment delivery ratio) model. The results showed that the changes are very important in this study period (1972–2015). Forests were reduced by 18.72% and croplands were increased by approximately 54%. The InVEST SDR model simulation results reveal an increase in the sediment export and soil loss, respectively, from 1.68 to 5.57 t/ha/year and from 15.22 to 43.61 t/ha/year from the year 1972 to 2015. These results highlight the need for targeted policies on integrated land and water resource management. Then, it is important to improve the common understanding of land use and land cover dynamics to the different stakeholders. All these can help in projecting future changes in the LULC and to investigate more appropriate policy interventions for achieving better land and water management.

Sign in / Sign up

Export Citation Format

Share Document