Spatio-Temporal Land-Use Changes and the Response in Landscape Pattern to Hemeroby in a Resource-Based City

Tian, Yu; Liu, Bingxi; Hu, Yuandong; Xu, Qing; Qu, Ming; Xu, Dawei

doi:10.3390/ijgi9010020

Cited by 20 publications

(18 citation statements)

References 53 publications

(71 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the continuous advancement of RS and GIS, the application of RS and GIS to analyze the changing characteristics of landscape pattern and land use has become a research hotspot in geography, environmental science and other disciplines (Tekle and Hedlund, 2000;Groom et al, 2006;Shao and Wu, 2008;Du et al, 2012). The research includes the use of RS and machine learning methods to obtain long time series remote sensing to monitor the spatial and temporal evolution characteristics of land use and its driving factors (Gao et al, 2015;Thakkar et al, 2017), the use of Fragstats software and landscape pattern index to analyze landscape pattern changes (Huang et al, 2008;Liu et al, 2012) and the impact of land use and landscape pattern on the ecological environment (Singh et al, 2010;Jazouli et al, 2019;Tian et al, 2020). Tang et al (2020) linked land use, landscape pattern and ecosystem service values and used Pearson correlation coefficients to explore the extent to which changes in land use and landscape pattern are associated with ecosystem services, finding that high intensity land use leads to degradation of ecosystem services.…”

Section: Introductionmentioning

confidence: 99%

Research on temporal and spatial evolution of land use and landscape pattern in Anshan City based on GEE

Zhang

2022

Front. Environ. Sci.

View full text Add to dashboard Cite

Frequent mining activities can bring about problems such as soil erosion and environmental pollution, which are detrimental to the efficient use of land and the sustainable development of cities. Existing studies have paid little attention to mining areas and lack comparative analysis of landscape changes in multiple mining pits. In this paper, the main urban area of Anshan City, where the mining areas are concentrated, was used as the research area, and the Landsat TM/OLI surface reflectance (SR) data of the Google Earth Engine (GEE) platform and the random forest algorithm were used to map the land use in 2008, 2014, and 2020. On this basis, land use dynamics and landscape pattern indices were used to analyze the changes in land use and landscape patterns in the Anshan City area. In addition, a moving window method was combined to further analyze and compare the landscape changes between different pits. The results show that:1. From 2008 to 2020, the construction land in Anshan urban area continued to decline, the forest land continued to expand, and the construction land was shifted to the forest land and cultivated land. Mining land increased before 2014 and remained almost unchanged after 2014, which is in line with the actual situation. 2. During the study period, the landscape fragmentation degree and landscape heterogeneity in the urban area of Anshan kept increasing. The high value areas of landscape fragmentation were the urban-rural combination areas and the mining areas. Among them, the reclamation of Dagushan and Donganshan is better, while the reclamation of Anqian, Yanqianshan and Xiaolingzi mines needs to be strengthened. 3. The random forest algorithm based on GEE shows a high degree of accuracy for land use classification. The overall classification accuracy in 3 years exceeds 90% and the kappa coefficient exceeds 0.85. The study results can be used as an essential reference for optimizing the urban ecological environment and provide technical backing for the urbanization construction and rational use of land in Anshan City.

show abstract

Section: Introductionmentioning

confidence: 99%

Research on temporal and spatial evolution of land use and landscape pattern in Anshan City based on GEE

Zhang

2022

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…In Shendong Mining Area, the intensive mining activities will inevitably affect and occupy farmers' land, and interfere with the original land surface, vegetation, and water in the mining area, resulting in the aggravation of soil erosion. Soil and water conservation in Shendong Mining Area of the Loess Plateau is mainly based on the micro geomorphic landscape transformation of slope reduction [67], which can lead to terraces suitable for planting and the ridges suitable for trees and grass, optimize the original land structure type [66,77]; improve land use efficiency [78] and create degradable biomaterials for slope cover [79], help make the area more conducive to vegetation growth [39,80], and reduce water and soil loss [3,75,78,[81][82][83]. An increase in forest and grass coverage not only needs favorable terrain conditions, but also requires appropriate plant species to be used for vegetation rehabilitation, as well as workers with mastery of the corresponding technologies to engage in reclamation.…”

Section: The Research Conclusion Of the Evaluation System Is Consistementioning

confidence: 99%

Benefit Evaluation of Water and Soil Conservation Measures in Shendong Based on Particle Swarm Optimization and the Analytic Hierarchy Process

Guo

Chen

et al. 2020

Water

View full text Add to dashboard Cite

Soil erosion is the main threat to the stability of ecological environment and the harmonious development of society in Shendong Mining Area. The main causes of this threat include the strong interference of natural characteristics and land development. Scientific soil and water conservation measures can coordinate the contradictions among coal economic development, ecological protection, and residents’ prosperity. Based on particle swarm optimization and analytic hierarchy process, the benefit evaluation system of soil and water conservation measures in Shendong Mining Area is established. The weight ratio of three kinds of benefits in Shendong coal mine collapse area is: ecological benefit > social benefit > economic benefit. The conclusion shows that the implementation of the national policy and the effect of mining area management meet the expectation. Therefore, this study provides effective reference and reasonable suggestions for soil and water conservation in Shendong Mining Area. In terms of control measures, bioengineering measures, such as increased coverage of forest and grass as well as reasonable transformation of the landscape pattern of micro landform, can improve the degree of soil erosion control, optimize the land use structure, and improve the land use rate.

show abstract

“…Human activities have exerted considerable anthropogenic influences on the earth system since the Anthropocene (1)(2)(3). Indeed, the increase in human activities through the rapid growth of population and urbanization has gradually become an important driving factor affecting the ecological environment on a global scale (4)(5)(6)(7). According to previous studies, over 75 and 90% of the earth's land surface and riverine systems, respectively, have been altered as a result of human activities (8)(9)(10)(11)(12), resulting in a series of eco-environmental problems, such as global warming, water pollution, and land degradation (13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

A novel method for quantifying human disturbances: A case study of Huaihe River Basin, China

Wang

Zhang²,

Wang³

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

Human disturbances have become the main factors affecting the ecological environment. Therefore, evaluating the intensity of human disturbances is of great significance for ensuring effective regional conservation and ecosystem management. In this study, we constructed a novel method to quantify human disturbances based on three components of human disturbances into three types, namely naturalness transformation, natural resource consumption, and pollutant emissions. These components were quantified using the land use naturalness index (LNI), resource consumption index (RCI), and pollution emission index (PEI). Based on these three indicators, the human disturbances index (HDI) was calculated to reflect the intensity of human disturbances. In addition, remote sensing (RS), geographic information system (GIS), and multisource data were combined in the HDI method, taking into account the temporal variability of input parameters to achieve more convenient and comprehensive dynamic monitoring and evaluation of human disturbances. The applicability and effectiveness of the HDI method were assessed in the Huaihe River Basin, China. The obtained results revealed an increase and decrease in the intensities of human disturbances in the Huaihe River Basin from 1990 to 2005 and from 2010 to 2018, respectively. In addition, areas with a high level of human disturbances in the 1990–2005 period were mainly concentrated in the agricultural and industrial areas, while those in the 2010–2018 period were mainly observed in urban areas. This change was mainly due to a decrease in the pollutant emission amounts from agricultural and industrial lands and a marked increase in resource consumption in urban areas. This study provides theoretical guidance for regional conservation in the Huaihe River Basin and a new method for quantifying human disturbances.

show abstract

Spatio-Temporal Land-Use Changes and the Response in Landscape Pattern to Hemeroby in a Resource-Based City

Cited by 20 publications

References 53 publications

Research on temporal and spatial evolution of land use and landscape pattern in Anshan City based on GEE

Research on temporal and spatial evolution of land use and landscape pattern in Anshan City based on GEE

Benefit Evaluation of Water and Soil Conservation Measures in Shendong Based on Particle Swarm Optimization and the Analytic Hierarchy Process

A novel method for quantifying human disturbances: A case study of Huaihe River Basin, China

Contact Info

Product

Resources

About