Margins, Edges, Borders and Botany

The Greater Mekong Subregion (GMS) has experienced rapid economic growth and urbanization. However, few studies have paid attention to urban land use dynamics, especially spatiotemporal patterns of urban expansion and land use change, in this region. This research aimed to conduct a comprehensive study of urban land use change in Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City, from 1990 to 2015. The analysis was based on land use maps derived from Landsat satellite products and employed urban expansion intensity, sector analysis, gradient-direction analysis, and landscape metrics. The results show Xishuangbanna, Yangon, Vientiane, Phnom Penh, Bangkok, and Ho Chi Minh City all experienced dramatic urban expansion and land use change since 1990, with urban expansion intensities of 15.01, 5.26, 9.15, 1.56, 11.88 and 11.91, respectively. The landscape metrics analysis indicated that urban areas were always aggregated and self-connected, while other land use types showed trends of disaggregation and fragmentation. In the process of urban expansion, paddy and natural land use types were commonly transformed to built up area. The results further reveal several common issues in urban land use, e.g., land fragmentation and loss of natural land use types. Finally, the discussion on the relationship between government policy and land use change for these cities shows land reform and attitude toward foreign direct investments played important roles in urban land use change in GMS.

Urban growth is regarded as a necessary transitional stage for a sustainable economy, but uncontrolled or arbitrary urban growth rapidly consumes rural resources and causes environmental pollution, ecological deterioration. In this paper, we developed a remote sensing and GIS-based integrated approach to monitor and analyze agricultural and urban spatial land use and ecological landscape change characteristics. In the proposed approach, multi-temporal satellite images from 1995 to 2010 were selected and classified to obtain land cover and use spatial changes. And GIS was used to analyze variation tendency for land use and ecological landscape indices. Experiments were performed in the Changping County, north of Beijing to analyze rapid urbanization effects in the past two decades, especially during the Beijing 2008 Olympic Games. The results indicate that there has been a notable urban growth and a visible loss about 38.8% in cropland, meanwhile dominated landscape structures and patterns have greatly changed from agriculture to urban in the study area.

The aim of this study is to determine the role of geomorphological factors in land use and plant cover organization. For this purpose, the relationship between geomorphological factors such as geomorphological unit, elevation, slope, aspect, and curvature with land use and plant cover was analyzed using GIS (Geographical Information Systems) techniques and statistical methods (zonal analysis, correlation analysis, regression analysis). Using zonal analysis, the boundaries of both land use patterns and plant species are clearly drawn according to geomorphological factors. Using correlation analysis, the direction and intensity of the relationship between each geomorphological factor with land use patterns and plant species were determined. Finally, regression analysis method was used to determine the impact rate of geomorphological factors on land use patterns and plant cover. Thus, the effects of geomorphological factors on the distribution of both land use patterns and the each plant species were explained in detail. When the results of all three analyses are evaluated in general, the elevation is very strong, the slope strong, the aspect medium, the geomorphological unit weak, and the curvature has a very weak effect on the distribution of land use patterns and the plant species in the research area. The data obtained from the study will contribute to the planning and implementation of activities such as forest, agriculture, land use, water management to be carried out by local administrations and decision-makers. In addition, it will form a scientific basis for the sustainability of forest existence in harmony with the ecological conditions of Göksun Plain and its surroundings.

The extent of anthropogenic land use in watersheds determines the amount of pollutants discharged to streams. This indirectly and directly affects stream water quality and biological health. Most studies have therefore focused on ways to reduce non-point pollution sources to streams from the surrounding land use in watersheds. However, the mechanistic pathways between land use and the deterioration of stream water quality and biological assemblages remain unclear. This study estimated a structural equation model (SEM) representing the impact of agricultural and urban land use on water quality and the benthic macroinvertebrate index (BMI) using IBM AMOS in the Nam-Han river systems, South Korea. The estimated SEM showed that the percent of urban and agricultural land in the watersheds significantly affected both the water quality and the BMI of the streams. Specifically, a higher percent of urban land use had directly increased the biochemical oxygen demand (BOD) and total phosphorus (TP), and deteriorated the BMI of streams. Similarly, higher proportions of agricultural land use had also directly increased the BOD, total nitrogen (TN), and total phosphorus (TP) concentrations, and lowered the BMI of streams. In addition, it was observed that the percent of urban and agricultural land use had indirectly deteriorated the BMI through increased BOD. However, we were not able to observe any significant indirect effect of the percent of urban and agricultural land use through increased nutrients including TN and TP. These results indicate that increased urban and agricultural land use in the watersheds had directly and indirectly affected the physicochemical characteristics and benthic macroinvertebrate communities in streams. Our findings emphasize the need to develop more elaborate environmental management and restoration strategies to improve the water quality and biological status of streams.

China’s urban land use has shifted from incremental expansion to inventory eradication. The traditional extensive management mode is difficult to maintain, and the fundamental solution is to improve land use efficiency. Xi’an, the largest central city in Western China, was selected as the research area. The super-efficiency data envelopment analysis (DEA) model and Malmquist index method were used to measure the land use efficiency of each district and county in the city from the micro perspective, and the spatial-temporal change characteristics and main influencing factors of land use efficiency were analyzed, which not only made up for the research content of urban land use efficiency in China’s underdeveloped areas, but also pointed out the emphasis and direction for the improvement of urban land use efficiency. The results showed that: (1) The land use efficiency of Xi’an reflected the land use intensive level of the underdeveloped areas in Western China, that is, the overall intensive level was not high, the gap between the urban internal land use efficiency was large, the land use efficiency of the old urban area and the mature built-up area was relatively high, and the land use efficiency of the emerging expansion area and the edge area was relatively low. (2) Like the eastern economically developed areas, the land use efficiency of western economically underdeveloped areas was generally on the rise, while Xi’an showed the U-shaped upward evolution characteristics, and there were four types of changes in the city, that is, highly intensive, medium intensive, high–medium–low-intensive, and intensive–extensive. (3) Various cities should configure resources and optimize mechanism to improve their land use efficiency based on economic and social development. During the study period, Xi’an showed the law of evolution from the south edge area and the emerging expansion area to the main urban area. (4) The improvement of technological progress was the main contribution factor of the land use efficiency in underdeveloped areas of China, and the low-scale efficiency was the main influence factor that caused low land use efficiency. In future urban land use, efforts should be made to optimize and upgrade technology and strictly control the extensive use of land.

Spatial pattern of urban functional landscapes along an urban–rural gradient: A case study in Xiamen City, China

Based on the theories of the information entropy of urban land use structure, co-integration and error correction model, this thesis analyses the relationship between economic growth, urbanization level and the information entropy of urban land use structure. The information entropy values of China's urban land use structure from 1981 to 2004 have been calculated in this paper. The relationship between China's GDP and the information entropy of urban land use structure is investigated in details. The results indicate a co-integration relationship between GDP and the information entropy of urban land use structure. However, there is no co-integration relationship between urbanization and the information entropy of urban land use structure. On the basis of the above analyses, the error correction model on GDP and the information entropy of urban land use structure is instituted. The application of the model shows that every 1% decrease in the information entropy value of urban land use structure demands a 59.53% growth in GDP. Because of the existing co-integration relationship between the economic growth and the information entropy of urban land use structure, the order degree of China's urban land use structure has relied heavily on the economic growth for a long time. The economic growth will significantly affect the optimal regulation of urban land use structure in the future. Further investigation also shows that economic growth and urbanization act as the direct driving force of the optimization of urban land use structure, but the optimization of urban land use structure can't promote the economic growth and the urbanization. Therefore, it becomes a very pressing strategic issue to adjust the economic structure and industrial distribution to optimize the distribution of urban land use and to optimize the structure of urban land use to improve the efficiency and promote the socio-economic development.

Impact of land use compactness on the habitat services from green infrastructure in Wuhan, China

Urbanization and agricultural land use can increase the transport of nutrients to fluvial ecosystems; yet, the overall impact of urban and nonpoint agricultural inputs on the composition, bio-lability, and the fate of fluvial dissolved organic matter (DOM) remains poorly understood. We investigated the optical and molecular composition and bio-lability of DOM in 76 streams and rivers with varying sizes of catchment area (1 ~ 4850 km2) along large gradients of urban and agricultural land use. Optical spectroscopy and Fourier transform ion cyclotron mass spectrometry (FT-ICR MS) were used to determine the chemical composition of DOM, and laboratory bio-incubations were used to assess DOM bio-lability. We found that urban and agricultural land use intensification was associated with the reduced relative contribution of DOM from pristine soils, enriched dissolved organic carbon (DOC), and higher contributions of aliphatic and peptide-like DOM, as well as enrichment of N- and S-containing molecular formulae. Specifically, FT-ICR MS revealed that the relative abundance of CHO-containing formulae decreased while that of CHOS-containing formulae increased with increasing urban land use. DOM bio-availability was higher in rivers draining urbanized and agricultural landscapes and was related to decreased DOM aromaticity and increased proportions of energy-rich aliphatic formulae. Our results suggested that DOM from urbanized and agricultural catchments significantly altered the chemical composition and bio-availability of DOM with potential effects on ecosystem metabolism and the fate of organic carbon in the downstream-linked streams and rivers. Anthropogenic disturbances may thus boost the microbial processing of organic carbon, including uptake, retention, and outgassing in the impacted ecosystems. Graphical Abstract

Headwater streams constitute the majority of stream length of river systems, and have important roles in terms of landscape processes and as habitat for organisms. These bodies of water are also tightly coupled with the local terrestrial landscape, making them ideal for studying linkages between land use and stream condition. Despite the ubiquity and importance of these streams, they are often overlooked and damaged. Previous research has shown that both urban and agricultural land use negatively impact stream condition, and that the magnitude of anthropogenic effects is generally greater in urban landscapes. Understanding of agricultural and urban land use impacts on streams depends on identifying cause and effect linkages between human system (demographic) features, terrestrial landscape features, and biophysical characteristics of streams. Using correlation analysis, path analysis, and non-metric multidimensional scaling, I simultaneously investigated these relationships in 29 central Iowa watersheds that collectively represented a strong urban-rural gradient. These analyses enabled me to quantify the impact of human land use on headwater streams, and identify direct and indirect mechanisms for human impacts on benthic macroinvertebrate communities. Aquatic macroinvertebrates were a primary focus of this study because they have well-established utility as indicators of stream condition due to their diverse environmental requirements, and importance in food webs. Results suggested that urban land use had a greater negative impact than agricultural land use on stream condition, as indicated by spatial variation in total invertebrate taxon richness and the percentage of the total number of invertebrates that were mayflies (Ephemeroptera), stoneflies (Plecoptera), and caddisflies (Trichoptera). Urban impacts appeared to be caused by pollutants delivered to streams by impervious surfaces, while agricultural effects were the result of nitrogen enrichment from croplands. Regardless of land

We explored land use, fish assemblage structure, and stream habitat associations in 20 catchments in Opequon Creek watershed, West Virginia. The purpose was to determine the relative importance of urban and agriculture land use on stream biotic integrity, and to evaluate the spatial scale (i.e., whole-catchment vs riparian buffer) at which land use effects were most pronounced. We found that index of biological integrity (IBI) scores were strongly associated with extent of urban land use in individual catchments. Sites that received ratings of poor or very poor based on IBI scores had > 7% of urban land use in their respective catchments. Habitat correlations suggested that urban land use disrupted flow regime, reduced water quality, and altered stream channels. In contrast, we found no meaningful relationship between agricultural land use and IBI at either whole-catchment or riparian scales despite strong correlations between percent agriculture and several important stream habitat measures, including nitrate concentrations, proportion of fine sediments in riffles, and the abundance of fish cover. We also found that variation in gradient (channel slope) influenced responses of fish assemblages to land use. Urban land use was more disruptive to biological integrity in catchments with steeper channel slopes. Based on comparisons of our results in the topographically diverse Opequon Creek watershed with results from watersheds in flatter terrains, we hypothesize that the potential for riparian forests to mitigate effects of deleterious land uses in upland portions of the watershed is inversely related to gradient.

Analysis on coupling relationship of urban scale and intensive use of land in China

The accessibility provided by the transportation system plays an essential role in driving urban growth and urban functional land use changes. Conventional studies on land use simulation usually simplified the accessibility as proximities and adopted the grid-based simulation strategy, leading to the insufficiencies of characterizing spatial geometry of land parcels and simulating subtle land use changes among urban functional types. To overcome these limitations, an Accessibility-interacted Vector-based Cellular Automata (A-VCA) model was proposed for the better simulation of realistic land use change among different urban functional types. The accessibility at both local and zonal scales derived from actual travel time data was considered as a key driver of fine-scale urban land use changes and was integrated into the vector-based CA simulation process. The proposed A-VCA model was tested through the simulation of urban land use changes in the City of Toronto, Canada, during 2012–2016. A vector-based CA without considering the driving factor of accessibility (VCA) and a popular grid-based CA model (Future Land Use Simulation, FLUS) were also implemented for comparisons. The simulation results reveal that the proposed A-VCA model is capable of simulating fine-scale urban land use changes with satisfactory accuracy and good morphological feature (kappa = 0.907, figure of merit = 0.283, and cumulative producer’s accuracy = 72.83% ± 1.535%). The comparison also shows significant outperformance of the A-VCA model against the VCA and FLUS models, suggesting the effectiveness of the accessibility-interactive mechanism and vector-based simulation strategy. The proposed model provides new tools for a better simulation of fine-scale land use changes and can be used in assisting the formulation of urban and transportation planning.

Revealing the spatial–temporal pattern and convergence characteristics of urban land use efficiency has important guiding significance for adjusting and optimizing the regional urban land use structure. Taking the provincial units in China as the research object, the urban land use efficiency evaluation system considering the unexpected output was constructed, and the slack-based measure (SBA) model was used to quantitatively measure the provincial urban land use efficiency from 2000 to 2020. The exploratory spatial data analysis (ESDA) model and spatial convergence index were combined to reveal the spatial–temporal pattern and convergence characteristics of provincial urban land use efficiency. The results showed that the provincial urban land use efficiency has been continuously improving, with regional differences as shown in eastern region > northeast region > central region > western region. Moran’s I of provincial urban land use efficiency was greater than 0, there was a positive spatial correlation, and the clustering feature became increasingly significant. The spatial form of LISA was characterized by “small agglomeration and large dispersion”; the H(High)-H(High) type was clustered in the Yangtze River Delta and Beijing–Tianjin–Hebei, while the L(Low)-L(Low) type was clustered in Xizang, Xinjiang and Qinghai. There was a σ convergence in provincial urban land use efficiency, and there was significant absolute β convergence and conditional β convergence of provincial urban land use efficiency. The results showed that the differences in provincial urban land use efficiency were shrinking, showing a “catch-up effect”, and converging to their respective stable states over time. Based on the analysis of the spatial–temporal pattern and convergence characteristics of provincial urban land use efficiency in China, we could provide a direction for the optimization of the urban land use structure and efficiency improvement in China, in order to narrow the differences in urban land use efficiency in China’s four major regions.

Change in urban construction land use is an important factor when studying urban expansion. Many scholars have combined cellular automata (CA) with data mining algorithms to perform relevant simulation studies. However, the parameters for rule extraction are difficult to determine and the rules are simplex, and together, these factors tend to introduce excessive fitting problems and low modeling accuracy. In this paper, we propose a method to extract the transformation rules for a CA model based on the Classification and Regression Tree (CART). In this method, CART is used to extract the transformation rules for the CA. This method first adopts the CART decision tree using the bootstrap algorithm to mine the rules from the urban land use while considering the factors that impact the geographic spatial variables in the CART regression procedure. The weights of individual impact factors are calculated to generate a logistic regression function that reflects the change in urban construction land use. Finally, a CA model is constructed to simulate and predict urban construction land expansion. The urban area of Xinyang City in China is used as an example for this experimental research. After removing the spatial invariant region, the overall simulation accuracy is 81.38% and the kappa coefficient is 0.73. The results indicate that by using the CART decision tree to train the impact factor weights and extract the rules, it can effectively increase the simulation accuracy of the CA model. From convenience and accuracy perspectives for rule extraction, the structure of the CART decision tree is clear, and it is very suitable for obtaining the cellular rules. The CART-CA model has a relatively high simulation accuracy in modeling urban construction land use expansion, it provides reliable results, and is suitable for use as a scientific reference for urban construction land use expansion.