American Apartheid: Segregation and the Making of the Underclass. Douglas S. Massey , Nancy A. Denton

Recent developments in the field of machine learning offer new ways of modelling complex socio-spatial processes, allowing us to make predictions about how and where they might manifest in the futu...

/pdf/understanding-urban-gentrification-through-machine-learning-3zmuso1lu3.pdf

Understanding urban gentrification through machine learning

https://doi.org/10.1016/j.cities.2022.103925

Unsupervised machine learning in urban studies: A systematic review of applications

Using DMSP/OLS nighttime light data and K–means method to identify urban–rural fringe of megacities

Revealing spatio-temporal evolution of urban visual environments with street view imagery

This article develops an integrated methodology to investigate dominant trajectories of neighborhood change that are often confronted in urban studies. Currently, researchers are using k-means clus...

A New Urban Typology Model Adapting Data Mining Analytics to Examine Dominant Trajectories of Neighborhood Change: A Case of Metro Detroit

Drought tolerance and quality stability are important indicators to evaluate the stress tolerance of tea germplasm resources. The traditional screening method of drought resistant germplasm is mainly to evaluate by detecting physiological and biochemical indicators of tea plants under drought stresses. However, the methods are not only time consuming but also destructive. In this study, hyperspectral images of tea drought phenotypes were obtained and modeled with related physiological indicators. The results showed that: (1) the information contents of malondialdehyde, soluble sugar and total polyphenol were 0.21, 0.209 and 0.227 respectively, and the drought tolerance coefficient (DTC) index of each tea variety was between 0.069 and 0.81; (2) the comprehensive drought tolerance of different varieties were (from strong to weak): QN36, SCZ, ZC108, JX, JGY, XY10, QN1, MS9, QN38, and QN21; (3) by using SVM, RF and PLSR to model DTC (drought tolerance coefficient) data, the best prediction model was selected as MSC-2D-UVE-SVM (R2 = 0.77, RMSE = 0.073, MAPE = 0.16) for drought tolerance of tea germplasm resources, named Tea-DTC model. Therefore, the Tea-DTC model based on hyperspectral machine-learning technology can be used as a new screening method for evaluating tea germplasm resources with drought tolerance.

/pdf/hyperspectral-machine-learning-model-for-screening-tea-23rmc4y9.pdf

Hyperspectral machine-learning model for screening tea germplasm resources with drought tolerance

Population growth, socioeconomic development, and rapid urbanization have exacerbated the deterioration of coastal ecosystems, particularly in the coastal region of southern China, which has experienced significant urbanization. A precise and timely insight into the ecological changes is indicative of economic and environmental harmonization in southern coast of China and other regions of the world. This study applied 731 Landsat images to assess quantitatively the spatial and temporal evolution of ecological environment quality in the coastal zone of South China during 1987─2020 based on the remote sensing ecological index (RSEI). The results show that 1) the correlation between the RSEI calculated using Landsat data and the parameters is more than 75%, and the results were significant when applied to assess the ecological environment of the coastal zone in South China. 2) The ecological quality of the coastal zone in South China as a whole showed a slight initial degradation during 1987─2020, followed by a gradual improvement trend and then a slight degradation; the area with good ecological quality decreased from 38.96 to 7.97%, and then gradually recovered to 56.61% in 2010. Subsequently, the regions with good ecological quality showed a significant decline, reducing to 1.72%, and then increasing to 38.46% until 2020. In addition, regional differences persisting during the study period are caused by the impact of human activities on the land use types of different landscapes. 3) Good and moderate ecological quality classes occupy most of the coastal zones in South China, but the pressure on the coastal zone is still not optimistic due to the sensitivity of the coastal zone and the accelerated urbanization in South China. As a large-scale, long time series of coastal zone ecological monitoring, this study can provide support for planning, ecological monitoring, environmental protection policy formulation, and integrated regional management of coastal zones and similar areas in South China.

The Eco-Environmental Changes in Typical Coastal Zones of Southern China From 1987 to 2020: A Case Study of Guangdong Coastal Counties

In this study, the surface of vermiculite-montmorillonite was modified by MnO2 loading. The modified vermiculite-montmorillonite was added to remediate the potentially toxic trace element (PTE) Hg present in soil containing coal gangue. Pot experiments were conducted to analyze and compare the pH values, Hg contents and Hg species present in coal gangue-containing soil, with and without the modified materials added, to determine whether the addition of modified materials had an effect on the growth of Brassica chinensis L. Results showed that with the addition of 35 g·kg−1 modified vermiculite-montmorillonite, the pH of soil increased by a value of 0.79, compared with that in the control group. When 15 g·kg−1 was added, the concentration of Hg in soil decreased by 98.2%. The addition of modified materials promoted the transformation of Hg in soil from a bioavailable form to an unavailable form; that is, the content of the residual form increased. The plant height and biomass of Brassica chinensis L. also increased, which indicated that the addition of modifiers can increase soil productivity, reduce the effects of PTEs on organisms in soil, and promote plant growth. Therefore, the addition of modified vermiculite-montmorillonite can achieve remediation of coal gangue-containing soil.

/pdf/remediation-of-soil-mercury-by-modified-vermiculite-2rpzbted.pdf

Remediation of Soil Mercury by Modified Vermiculite-Montmorillonite and Its Effect on the Growth of Brassica chinensis L.

As an important means of curbing soil degradation, afforestation has a profound impact on regional soil properties and quality. However, it is still unclear regarding how to conduct a systematic assessment of soil properties and soil quality and the impact of vegetation characteristics and plant functional traits in leguminous plantations with different afforestation years in drylands. Therefore, we investigated the vegetation characteristics and determined the functional traits of leaves and roots and the soil physicochemical properties of Caragana korshinskii plantations with 13, 35, and 55 years. The results showed that tree height; crown diameter (CD); root dry matter content; root water content; soil clay, silt, and sand contents; bulk density (BD); soil water content; soil organic carbon (SOC); total nitrogen (TN); available nitrogen; total phosphorus (TP); available phosphorus (AP); and soil quality index (SQI) changed significantly with an increase in afforestation years. Although the specific leaf area did not show a significant variation, it had a significant negative effect on soil properties and SQI, except for soil sand and BD. Soil sand and BD decreased with the afforestation succession, but the succession pattern of soil clay, silt, SOC, TN, TP, and AP was 13 years < 35 years < 55 years, and SQI increased from 0.20 (13 years) to 0.77 (55 years). This indicated that long-term legume afforestation led to the transformation of soil texture from silty loam to silt and significantly improved the soil properties and quality in the study area.

/pdf/effects-of-different-afforestation-years-on-soil-properties-2j6ct3eq.pdf

Effects of Different Afforestation Years on Soil Properties and Quality

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