Urban heat islands (UHIs) has been proven firmly related to the land use structure. Identifying interactions between UHIs and multiple land use components is a crucial step to obtain human heat welfare information. However, few studies have predicted sub cell scale land use structure dynamics on UHIs due to the lack of subpixel simulation methods. Herein, we present an integrated framework coupling subpixel unmixing and mixed-cell simulation methods to predict fine-scale land-use structural changes. A widely used XGBoost was used to determine the optimal scale for future UHIs prediction. This framework explores how multiscale changes in land use structure will affect future UHIs intensity, taking Wuhan, China as a study area. The results reveal that most influence comes from the scale below the 330-m grid, while the fine-scale land use components of a given position show limited impact on the UHI intensity. Impervious surfaces contribute more than 55% of the importance, while bare soil and water components within the 270-m grid also significantly affect UHIs. We also find that optimizing the structure of land use components can potentially release approximately 599,000 people from high-UHI regions in the study area.
The stimulated grazing method was used to study the vegetation variation,intake variation and plant response of mountain meadow in Xiahe County,Gansu Province.The result indicated that the vegetation biomass showed a single-peak curve with or without grazing stress.The total average intake showed an inverse exponential model.The stimulated values were significantly correlated with the real values.
Rapid urban extension, accompanied by intensive landscape changes, significantly affects the habitats. Promoting sustainable urban development such as compact city policy is essential for ecosystem trade-offs. Previous studies tended to investigate how urbanization influences the ecosystem considering future climate and population projection. Few studies examined the impact of urban patterns on habitat quality at a fine resolution. This study builds a framework to demonstrate future urban evolution using a bottom-up Cellular Automata (CA) model and a top-down Markov model, and then incorporated the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess corresponding habitat quality. Three compact city scenarios in 2040 and 2060 are proposed in the Guangzhou-Hong Kong-Macao Greater Bay Area (GBA). The results show that the highly compact scenario presents the most severe habitat quality degradation from 2020 to 2040 due to the remarkable urbanization of surrounding farmland. By 2060, new urban clusters will easily form by intensifying medium-compact scenarios, causing massive vegetation loss. The GBA has significant spatial heterogeneity in habitat quality variation because of the uneven development between the central and surrounding cities. Our results can provide insights for developing long-term land use strategies considering regional differences to balance ecological conservation and urbanization requirements.
Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the ability to simulate the detailed patch evolution of multiple land use types. This study introduces a patch-generating land use simulation (PLUS) model that integrates a land expansion analysis strategy and a CA model based on multi-type random patch seeds. These were used to understand the drivers of land expansion and to investigate the landscape dynamics in Wuhan, China. The proposed model achieved a higher simulation accuracy and more similar landscape pattern metrics to the true landscape than other CA models tested. The land expansion analysis strategy also uncovered some underlying transition rules, such as that grassland is most likely to be found where it is not strongly impacted by human activities, and that deciduous forest areas tend to grow adjacent to arterial roads. We also projected the structure of land use under different optimizing scenarios for 2035 by combining the proposed model with multi-objective programming. The results indicate that the proposed model can help policymakers to manage future land use dynamics and so to realize more sustainable land use patterns for future development. Software for PLUS has been made available at https://github.com/HPSCIL/Patch-generating_Land_Use_Simulation_Model
Abstract. Inland river basins in arid to semi-arid regions are widely distributed in Northwest China, Central Asia, Central Australia, and North Africa, and are often subject to significant human activities. The most distinctive natural feature of such basins is the shortage of water resources, and the pivotal reasons involve less precipitation and heavy evapotranspiration (ET). In recent years, intensive human activities also damage the natural environment of the basins. They result in many problems especially the deterioration of ecological environment which will lead to severe consequences such as desertification, sandstorm, the disappearance of wetlands, reduction of forest and grassland degradation. They prevent us from achieving the goal of sustainable development. How to balance economic development and ecosystem conservation and to realize the sense of sustainability in inland river basins will be vitally important.The Heihe River is the second largest inland river in the Northwest of China with a long history development by human (Figure 1). Water resources from the river are crucial not only for the ecosystem but also for local human societies. The Heihe River Basin (HRB) is divided into three zones with different landscapes and natural environments. The upstream of HRB is the headstream which generates water resources mainly from glaciers and snow in Qilian Mountain. A large population of nomadic national minorities inhabits here and keeps animal husbandry as the primary production activity. In the early times, the Chinese government encouraged production activities to stimulate economic growth, and significant over-grazing and resultant severe grassland degradation occurred. Grassland is crucial for maintaining water resources especially in arid regions, without grasses most water will quickly evaporate into the air. Therefore, land resource management about grassland and the impact of human activities on the natural environment are of high research value in the HRB.This research aims to investigate the impact of over-grazing on grassland degradation in the inland ecosystem of the HRB. The changes of grassland distribution were simulated under different over-grazing scenarios to provide a reference for resource management and the related decision-making process and to contribute to the sustainable development of the region.
Globally, natural landscapes and their recreational ecosystem services (RES) are both under threat from anthropogenic activities and environmental changes. But the demand for RES increases with the development of human living standards. Therefore, mapping and assessing the supply–demand relationships of RES is crucial for landscape planning, management, and human well-being. This study aimed to study the relationships between supply and demand of RES in Shandong province, China, quantify the supply, demand, and supporting capacity of RES, analyze the degree of matching and coupling between the supply and demand of RES, and explore the effect of terrain gradient to RES. The results indicated that the average value of coupling coordination (CCD) between supply–demand of RES in Shandong province was 0.45, which is a mild balance. According to the supply–demand matching types, areas with low supply-high demand accounted for 6.62%, indicating a serious shortage matching of supply and demand. Using hotel quantity and roads as indicators of the supporting capacity of RES, the overall coordination between landscape aesthetic quality (LAQ) and regional hotel quantity shows a mild imbalance (0.38), while that with the regional road density shows a good balance (0.60). Furthermore, the scenery spots density, RES supply, RES supply–demand CCD and support capacity CCD shows an upward trend with the increase of elevation and slope, an "increased-decreased-increased" trend with the increase of terrain niche index. This study provides spatial matching of RES supply and demand in Shandong province. Optimizing land-use structures and improving natural resource allocation were proposed to boost coordination of RES supply and demand.
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