Quantitative evaluation of human activity intensity on the regional ecological impact studies

Shiliang, 刘世梁 Liu; Lumeng, 刘芦萌 Liu; Xue, 武雪 Wu; Xiaoyun, 侯笑云 Hou; Shuang, 赵爽 Zhao; Guohua, 刘国华 Liu

doi:10.5846/stxb201711172048

Cited by 13 publications

(8 citation statements)

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“…The impact of human activity on the surrounding environment needs to be quantified (Yang et al, 2019). A multi-index superposition system was established based on weights to evaluate the human activity intensity (Liu et al, 2018). Trend analysis and residual analysis were used to calculate the human activity intensity based on MODIS-NDVI data, combining with remote sensing data and regional socioeconomic data (Wen & Yao, 2018).…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluation of human activity intensity in geological environment problems of Ji’nan City

Peng

Zhang²,

Gao

et al. 2020

European Journal of Remote Sensing

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Human activity intensity evaluation is the basis of analyzing the impact of human activity on the region. With increasing scale and quantity of human activity, the impact on the ecological environment is also more and more serious. The multifactor evaluation model of human activity intensity is established by determining the classification standard index. Firstly, population density, gross domestic product (GDP) per capita, mining points, construction land ratio and land utilization ratio are selected as quantitative indexes. Secondly, the weights of evaluation indexes are obtained by using objective valuation method. Further work, the quantitative evaluation model and systematic analysis of human a`ctivity intensity for Ji'nan city are established by multifactor method. The results show that the areas with the highest intensity of human activities are mainly distributed in Ji'nan urban area, the areas with higher intensity are mainly distributed in some towns of Licheng District and the urban areas of counties and cities, the areas with middle intensity are mainly distributed in the areas near Ji'nan urban area and counties, and the areas with lower intensity are mainly distributed in some areas far away from counties and cities. Quantitative evaluation of human activity intensity is helpful to investigate the changes of ecological environment.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Evaluation of human activity intensity in geological environment problems of Ji’nan City

Peng

Zhang²,

Gao

et al. 2020

European Journal of Remote Sensing

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show abstract

“…In order to maintain consistency in time scales, we processed the obtained data and used the Cell Statistics tool in ArcGIS10.8 to synthesize the monthly average temperature and daily temperature range into annual average raster data. [12,44,45] Extreme weather events and severe droughts have recently increased the frequency of wildfires worldwide, leading to more subsequent carbon emissions from fires [35]. According to several recent studies, it also has some surprising effects on notorious air pollution [20,34].…”

Section: Explanatory Variable Meteorological Variablesmentioning

confidence: 99%

“…For the YRD with complex ecosystems, general single indicators to explain the impact of human interference pose a challenge. Following Liu et al [44], we used the degree of human disturbance (DH) to quantify the extent of human damage to nature [20]. In alignment with the distribution standard proposed by Beyhan et al [45], we assigned intensity values to different land use types to quantify the degree of human disturbance to the ecosystem.…”

Section: Vegetation Variablesmentioning

confidence: 99%

Modeling the Effects of Drivers on PM2.5 in the Yangtze River Delta with Geographically Weighted Random Forest

Su¹,

Lin

Xu³

et al. 2023

Remote Sensing

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Establishing an efficient PM2.5 prediction model and in-depth knowledge of the relationship between the predictors and PM2.5 in the model are of great significance for preventing and controlling PM2.5 pollution and policy formulation in the Yangtze River Delta (YRD) where there is serious air pollution. In this study, the spatial pattern of PM2.5 concentration in the YRD during 2003–2019 was analyzed by Hot Spot Analysis. We employed five algorithms to train, verify, and test 17 years of data in the YRD, and we explored the drivers of PM2.5 exposure. Our key results demonstrated: (1) High PM2.5 pollution in the YRD was concentrated in the western and northwestern regions and remained stable for 17 years. Compared to 2003, PM2.5 increased by 10–20% in the southeast, southwest, and western regions in 2019. The hot spot for percentage change of PM2.5 was mostly located in the southwest and southeast regions in 2019, while the interannual change showed a changeable spatial distribution pattern. (2) Geographically Weighted Random Forest (GWRF) has great advantages in predicting the presence of PM2.5 in comparison with other models. GWRF not only improves the performance of RF, but also spatializes the interpretation of variables. (3) Climate and human activities are the most important drivers of PM2.5 concentration. Drought, temperature, and temperature difference are the most critical and potentially threatening climatic factors for the increase and expansion of PM2.5 in the YRD. With the warming and drying trend worldwide, this finding can help policymakers better consider these factors for PM2.5 prediction. Moreover, the effect of interference from humans on ecosystems will increase again after COVID-19, leading to a rise in PM2.5 concentration. The strong explanatory power of comprehensive ecological indicators for the distribution of PM2.5 will be a crucial indicator worthy of consideration by decision-making departments.

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“…(1) Ecological protection function. Human activities are the main factor that puts pressure on ecosystems, so human footprint is used as an indicator to reflect the degree of interfere- ence of human activities on the environment (Liu et al, 2018). National parks protect representative ecosystems and rare species, so the state of ecological protection is reflected by the level and number of state-protected species and the condition of vegetation (Chen et al, 2020c).…”

Section: Function Evaluation Indexmentioning

confidence: 99%

Evaluation and structural analysis of the functions of the Tibetan Plateau National Park Cluster

et al. 2022

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National parks are useful entities for looking at coordinated efforts to improve the Tibetan Plateau's function as an ecological safety barrier and the region's green development.Research on the characteristics of the function structures of the Tibetan Plateau's national parks is vital to promoting their systematic and coordinated development. This paper combines the pressure-state-response model, the rank-size rule and a coupling and coordination model to identify and evaluate the functions of national parks on the Tibetan Plateau and to analyze the categories, hierarchy and structures behind those functions. The results indicate the following: (1) The Tibetan Plateau National Park Cluster needs to maintain internal and external relations. Internally it needs to rationally allocate resources between ecological protection, recreation and community development, and externally it needs to promote its role as an ecological security barrier and promote regional green development by rationally ranking and organizing the individual national parks, so as to handle their co-evolution of functions at multiple scales. (2) Ecological protection, recreation and community development are the most prominent functions of the Tibetan Plateau National Park Cluster, but there is scope to develop their scientific research and education functions. The Zipf index shows that their multi-functional level conforms with the rank-size rule, indicating balanced development. Individual national parks need to strengthen their optimal functions according to their characteristic localization. (3) The degree of coupling between the functions of the Tibetan Plateau National Park Cluster is 0.7809, and the degree of coordination is 0.6227, which indicates a very strong coupling and moderate coordination. The coupling strength and degree of coordination between the multiple functions vary greatly among the individual national parks, which reflects their different function structures. There are four function structure types: fully coordinated, optimally developed, moderately developed and moderately underdeveloped.

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Quantitative evaluation of human activity intensity on the regional ecological impact studies

Cited by 13 publications

References 0 publications

RETRACTED ARTICLE: Evaluation of human activity intensity in geological environment problems of Ji’nan City

RETRACTED ARTICLE: Evaluation of human activity intensity in geological environment problems of Ji’nan City

Modeling the Effects of Drivers on PM2.5 in the Yangtze River Delta with Geographically Weighted Random Forest

Evaluation and structural analysis of the functions of the Tibetan Plateau National Park Cluster

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