Urban Land Use Change Research Articles

海口市生态用地变化与安全格局构建

PDF HTML阅读 XML下载 导出引用 引用提醒 海口市生态用地变化与安全格局构建 DOI: 10.5846/stxb201704120639 作者: 作者单位: 湖北大学,海南师范大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41361090） Ecological land use change and construction of ecological land security pattern in Haikou city Author: Affiliation: Hubei University,Hainan Normal University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:城市化过程中，城市生态用地变化与安全格局构建对于城市生态系统健康、城市居民生活质量和城市可持续发展有着重要意义，生态用地的变化直接影响生态安全格局变化，生态用地安全格局又对生态用地的规划有指导作用。基于GIS技术，对海口市1991年至2016年生态用地的时空变化过程进行研究，进而分析生态用地演变。选取高度、坡度、水资源安全作为生态安全影响单因子，并分级赋值，构建综合生态用地分布格局。以底线型生态用地为源，基于最小累计阻力模型（MCR），以阻力阈值作为分级边界，划分不同安全水平的生态用地区域，进而确定源间生态廊道、辐射道与战略点，构建生态用地安全格局。分析结果表明：1991年至2016年，海口市三类生态用地变化最大，其中林地减少13.33%，园地增加9.136%，坑塘水面增加3.71%。南渡江以西生态用地从以林地为主转为园地与建设用地为主，其余地区变化较少。生态用地安全变化区域集中在海口市西部与东部，其中西部高安全水平区减少，整体安全水平急剧恶化，东部高安全水平区略有提升。故需要制定和实施合理的生态用地保护政策，对生态用地格局进行优化调整，以期构建区域内生态环境协调发展的可行方案。 Abstract:In the process of urbanization, the change of urban ecological land use and the construction of a safety pattern are of great significance for the urban ecosystem health, the quality of life of urban residents, and the sustainable development of cities. Ecological land use change affects the ecological security pattern directly. The ecological land security pattern has a guiding role for the planning of ecological land. Based on the GIS technology, the temporal and spatial changes of ecological land in Haikou from 1991 to 2016 and the evolution of ecological land were studied. Selected height, slope and water resource security as single factor of ecological safety impact, give them graded amounts to build a comprehensive ecological land distribution pattern. Based on the minimum cumulative resistance (MCR) model, the resistance threshold was used as the hierarchical boundary, the ecological land area of different safety levels was divided, and then the ecological corridors, radiators, and strategic points were established to build a security pattern of the ecological land. The results showed that from 1991 to 2016, the three types of ecological land areas in Haikou City had the biggest changes, with the forest land decreasing by 13.33%, the garden area increasing by 9.136%, and the pond water surface increasing by 3.71%. The ecological land to the west of Nandu River mainly changed from forest land to garden land and construction land, and the rest of the area changed less. The high safety level area in 1991 was much larger than in 2016, but the low safety area was lower than in 2016. The overall trend gradually deteriorated. Over two years, the western and southern areas of the two "source" as the center, the high security area, the safety area, and the low security area formed a circular arrangement, while the Nandu River was the "source", with high, medium, and low areas localized along the river. In 2016, the corridors were arranged in three rings, distributed evenly throughout the city, but the relationship between the sources was weakened. The radiation path was still irregularly distributed, while the number of strategic points decreased significantly compared with those in 1991, indicating that the ecological impact and imbalance of each part become more and more serious, the stability of ecological safety in the region has been destroyed. The area where ecological land use change occurred is concentrated to the west and east of Haikou City, while the high safety area to the west of Haikou was reduced and the overall safety level deteriorated rapidly. The high safety level area to the east slightly improved. Therefore, it is necessary to formulate and implement a reasonable ecological protection policy and land use pattern to optimize the adjustment, with a view of building a coordinated environment for coordinated development of the ecological environment within the region. 参考文献 相似文献 引证文献

A Feature-Based Approach of Decision Tree Classification to Map Time Series Urban Land Use and Land Cover with Landsat 5 TM and Landsat 8 OLI in a Coastal City, China

Accurate mapping of temporal changes in urban land use and land cover (LULC) is important for monitoring urban expansion and changes in LULC, urban planning, environmental management, and environmental modeling. In this study, we present a feature-based approach of the decision tree classification (FBA-DTC) method for mapping LULC based on spectral and topographic information. Landsat 5 TM and Land 8 OLI images were employed, and the technique was applied to the coastal city of Xiamen, China. The method integrates multi-spectral features such as SAVI (soil adjustment vegetation index), NDWI (normalized water index), MNDBaI (modified normalized difference barren index), BI (brightness index), and WI (wetness index), with topographic features including DEM and slope. In addition, the new approach distinguishes between fallow land and cropland, and separates high-rise buildings from beaches and water bodies. Several of the FBA-DTC parameters (or rules) from 1997 to 2015 remained constant (i.e., DEM and slope), whereas others changed slightly. WI was negatively related to percent area of beach land, and BI was negatively related to percent area of arable land. The FBA-DTC method had an average user’s accuracy (UA) of 91.36% for built-up land, an average overall accuracy (OA) of 92.13%, and a Kappa coefficient (KC) of 0.90 for the period from 2003 to 2015, representing respective increases of 15.87%, 10.17%, and 0.13, compared with values calculated using maximum likelihood classification (MLC). Over the past 12 years, built-up land increased from 23.67% to 43.17% owing to occupation of coastal reclamation, arable land, and forest land. The FBA-DTC method presented here is a valuable technique for evaluating urban growth and changes in LULC classification for coastal cities.

Prices, policies, and place: What drives greenfield development?

While the recent global financial crisis heightened awareness of the linkages between global financial capital and urban spatial pattern, the timing of urban development – largely thought to be market driven – is not fully understood. Parcel-level studies of urban land-use change, which often use hazard models to investigate if and when development occurs, offer an opportunity to juxtapose the extent to which decisions to develop individual plots of farmland into housing are driven by market forces, the unique characteristics of the land and its intraurban location, or policies such as transportation infrastructure and municipal annexation. Using residential completion data in the Phoenix, Arizona region from 1992 to 2014, a period of dramatic commodity, fuel, and home price swings, and land cover imagery, we develop a parcel-level hazard model to gauge the relative impacts of market, policy, and place-based drivers of land change. We find limited evidence of induced development associated with freeway planning, that annexation and development are closely linked and moreso during economic booms, high fuel prices spur development in the region's core, and agricultural and urban land rents affect the timing of development. This study advances our understanding of development decision- making, policy impacts, and urban land-use change modeling and provides an empirical connection between local and global drivers of Greenfield development.

Simulating urban land-use changes at a large scale by integrating dynamic land parcel subdivision and vector-based cellular automata

ABSTRACTCellular automata (CA) have been widely used to simulate complex urban development processes. Previous studies indicated that vector-based cellular automata (VCA) could be applied to simulate urban land-use changes at a realistic land parcel level. Because of the complexity of VCA, these studies were conducted at small scales or did not adequately consider the highly fragmented processes of urban development. This study aims to build an effective framework called dynamic land parcel subdivision (DLPS)-VCA to accurately simulate urban land-use change processes at the land parcel level. We introduce this model in urban land-use change simulations to reasonably divide land parcels and introduce a random forest algorithm (RFA) model to explore the transition rules of urban land-use changes. Finally, we simulate the land-use changes in Shenzhen between 2009 and 2014 via the proposed DLPS-VCA model. Compared to the advanced Patch-CA and RFA-VCA models, the DLPS-VCA model achieves the highest simulation accuracy (Figure-of-Merit = 0.232), which is 32.57% and 18.97% higher respectively, and is most similar to the actual land-use scenario (similarity = 94.73%) at the pattern level. These results indicate that the DLPS-VCA model can both accurately split the land during urban land-use changes and significantly simulate urban expansion and urban land-use changes at a fine scale. Furthermore, the land-use change rules that are based on DPLS-VCA mining and the simulation results of several future urban development scenarios can act as guides for future urban planning policy formulation.

Urban Landuse Changes in Sri Lanka with Special Reference to Kaduwela Town from 1975 to 2016

The study of land use/land cover changes is very important to have proper planning and utilization of natural resources and their management. Traditional methods for gathering demographic, censuses data and analysis of environmental situation are not adequate for multi complex environmental studies since many problems often presented in environmental issues and great complexity of handling the multidisciplinary data set. Therefore, it does require new technologies like satellite remote sensing and Geographical Information Systems. The objective of the study is to identify the changing pattern of land use in Kaduwela Municipal Council from 1970’s to 2016. Primary and secondary data are to be used for the analysis. The secondary data from the UDA, Survey Department and land sat 5 images in 1975, 1980, 1997 and 2016. The primary data was collect using field checking and discussion held with offices and residence. The Land use of the urban sprawl in Kaduwela Municipal Council is change very fast. Specially most of the land uses are residential, commercial and service infrastructure facilities. The paddy, marshy or inland cultivation lands (Homestead) are the alternative land for use of residential, commercial and other urban activates. In addition, the land price of the area is increase very rapidly and fragmentation is increase and the size of the land plots is very small.

Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules

ABSTRACTA novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development.

Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules

A novel generalized pattern search GPS-based cellular automata GPS-CA model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that compu...

Investigation on the Expansion of Urban Construction Land Use Based on the CART-CA Model

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.

Change in Urban Landuse and its Effect on Natural Drainage System: A Geographical Micro Leveled Study of Bhosari Stream (PCMC)

Change in Urban Landuse and its Effect on Natural Drainage System: A Geographical Micro Leveled Study of Bhosari Stream (PCMC)

A modeling study on the effect of urban land surface forcing to regional meteorology and air quality over South China

The change of land-use from natural to artificial surface induced by urban expansion can deeply impact the city environment. In this paper, the model WRF/Chem is applied to explore the effect of this change on regional meteorology and air quality over South China, where people have witnessed a rapid rate of urbanization. Two sets of urban maps are adopted to stand for the pre-urbanization and the present urban land-use distributions. Month-long simulations are conducted for January and July, 2014. The results show that urban expansion can obviously change the weather conditions around the big cities of South China. Especially in the Pearl River Delta region (PRD), the urban land-use change can increase the sensible heat flux by 40 W/m2 in January and 80 W/m2 in July, while decrease the latent heat flux about −50 W/m2 in January and −120 W/m2 in July. In the consequent, 2-m air temperature (T2) increases as much as 1 °C and 2 °C (respective to January and July), planetary boundary layer height (PBLH) rises up by 100–150 m and 300 m, 10-m wind speed (WS10) decreases by −1.2 m/s and −0.3 m/s, and 2-m specific humidity is reduced by −0.8 g/kg and −1.5 g/kg. Also, the precipitation in July can be increased as much as 120 mm, with more heavy rains and rainstorms. These variations of meteorological factors can significantly impact the spatial and vertical distribution of air pollutants as well. In PRD, the enhanced updraft can reduce the surface concentrations of PM10 by −40 μg/m3 (30%) in January and −80 μg/m3 (50%) in July, but produce a correlating increase in the concentrations at higher atmospheric layers. However, according to the increase in T2 and the decrease in surface NO, the surface concentrations of O3 in PRD can increase by 2–6 ppb in January and 8–12 ppb in July. Meanwhile, there is a significant increase in the O3 concentrations at upper layers above PRD, which should be attributed to the increase in air temperature and the enhanced upward transport of O3 and its precursors. As for some relative small cities, such as Haikou, there is very little variation in surface PM10 and O3 in both months, implying less urbanization in these areas. Moreover, the depletion of O3 by NO may be the main cause of the reduction of O3 at upper layers in these small cities.

GIS-based simulation of land use change

This paper describes an application of ArcGIS to simulate land use changes in Lagos, Nigeria, using both Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR), over three epochs - 1963-1978, 1978-1984 and 1984-2000. Twelve salient, causal factors thought to be related to urban land use change in Lagos were used, such as distance to water, distance to residential structures, income potential and population potential. OLS was used to establish the regression coefficients, gauge the significance of each explanatory variable and estimate conformity with linear regression criteria. GWR was then used to simulate the urban form based on the results of the OLS model. For the three epochs the respective Kappa statistics for the simulated maps were 0.8858, 0.8366 and 0.8812, indicating an almost perfect agreement with the data of 1978, 1984 and 2000.

Spatio-temporal pattern of urban growth in Jos Metropolis, Nigeria

Rapid rates of urbanization being experienced in Nigeria have created serious environmental problems noticeable along the Jos metropolis. Evidence shows unguided and uncontrolled expansion in all directions, resulting in large scale urban growth and change in urban land use. This study examines the pattern, direction and nature of growth in Jos Metropolis for the time period: 1984–2014 (30 years). The combined approach using remotely sensed data, with change detection techniques and selected spatial metrics proved effective in understanding and representing the spatial-temporal dynamics of urban growth. The results revealed that built up area in the Metropolis had grown from 15km2 in 1984 to 62km2 in 2014 at an average growth rate of 6.7%. In total, 47km2 of non-built up has been converted to urban area. The rate of urban growth in Jos Metropolitan area can be divided into three key epochs: (1) slow and rapid growth rate (1984–1991), (2) consistent growth rate (1991–2003), (3) very rapid growth rate (2003–2014). The produced maps display a clear pattern of increased urban expansion. This extends from urban core to adjoining non-built up areas in all directions, largely towards the south direction and along major transportation corridors. The results of landscape analysis revealed that the city experienced fragmented urban growth process, mostly towards the outlying areas; while the urban core experienced relative compact growth.

Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China

Foshan is one of China's rapidly industrializing cities, and the municipality has undergone significant urbanization in the past 20 years. To investigate the urban development of Foshan municipality, we used an integrated modeling approach based on Markov chain (MC), logistic regression, and cellular automata (CA) to study dynamic changes in land use. An MC and neighborhood transfer matrix were used to determine the influence of the central cell and neighborhoods, while logistic regression was fitted by factors derived from a principle component analysis to produce probability maps of the driving forces. The accuracy of the Markov-logistic-CA model was sufficient for predicting processes of change in urban land use compared to other models. Then three scenarios were constructed through the setting of potential land use policies, land demands, and mapping future public transportation to reflect the possible urban patterns of Foshan in 2025. The simulation results indicated that a spread-out urban pattern will be dominant in Foshan in the future, while zoning development, with the preservation of ecological features in rural-urban areas, will relieve the environmental deterioration of the Foshan municipality.

Revitalization Efforts in San Francisco: An Urban History Case Study of San Francisco's Tenderloin District

San Francisco’s Tenderloin District has seen many changes over the last several decades. First a haven for gambling and prostitution, then a hot spot for music and pornography, to an current mixture of ghetto dynamics and urban revitalization. This research focuses on urban land-use changes in this district using geographic and ethnographic methods.

Impact of urban land-use change in eastern China on the East Asian subtropical monsoon: A numerical study

The effect of urban land-use change in eastern China on the East Asian subtropical monsoon (EASTM) is investigated by using the Community Atmosphere Model version 5.1. Comparison of the results between the urban expansion and reference experiments shows that with the urban expansion, the land surface energy balance alters: surface net radiation and sensible heat fluxes enhance while the latent heat fluxes reduce. As a result, a significant increase in surface air temperature over eastern China is detected. The urban land-use change contributes to a change in the zonal land-sea temperature difference (LSTD), leading to a delay in the time when LSTD changes from positive to negative, and vice versa. Additionally, the onset and retreat dates of the EASTM are also delayed. Meanwhile, the rise in surface air temperature leads to formation of abnormal northerly air flows, which may be the reason for the slower northward movement of the EASTM and a more southward location of its northern boundary.

A methodological approach to urban land-use change modeling using infill development pattern—a case study in Tabriz, Iran

In recent years, models of land-use change and urban growth have become important tools for city planners, economists, ecologists, and resource managers. In most models, future land-use changes are forecasted based on past development pattern and expansion to periphery. While today, metropolitan areas employ smart-growth strategies. The main objectives in this study are according to the smart-growth infill. In this approach, transmission of incompatible land uses to the outside of the city boundary, redevelopment, improvement, and renovation of urban old district and worn-out texture and reuse of abandoned land to new urban development are considered. In fact, the objective is the using of the infill development pattern to modeling approach for simulating urban future development using potentials inside the city. This paper presents a Land Transformation Model of urban land-use change based on an artificial neural network and a geographical information system. For developing this approach, future development of Tabriz city based on past development trend and infill development pattern is modeled. The modeling result based on past development pattern shows that the 31.26 % of green spaces and 60.93 % of agricultural land and wasteland will be destroyed and the built area will increase 89.75 % from 2005 to 2021. Development of infill development pattern model can regularize urban expansion in the coming decades. The result of infill development pattern, show that the built area will increase 40.32 percent and agricultural land and wasteland area decrease 32.67 percent until 2021. In fact, redevelopment of urban land uses in infill development pattern until 2021, not only preserve the green spaces and agricultural areas but also improve and rehabilitate old and worn-out textures.

The Research on Land-Use Change and Ecological Environment Effect of Urban Landscape in China

The rapid expansion of urban construction land has become the major characteristic of urban land-use change in China today. Meanwhile, the rapid urbanization process has led to the great changes of urban landscape in China, and it also has had certain impacts on environmental factors such as climate, soil, hydrology, biodiversity, etc., then it has made the overall ecological environment deteriorated. This study is based on the summary and analysis of research on land-use change and ecological environment effect of urban landscape in recent 20 years in China, and it aims at providing scientific bases and theoretical supports for the planning and construction of urban landscape, the sustainable land-use of city and the protection of ecological environment in China.

Effects of urban land-use change in East China on the East Asian summer monsoon based on the CAM5.1 model

The effects of urban land-use change in East China on the East Asian summer monsoon (EASM) are investigated using a Community Atmosphere Model Version 5.1. The results show that the urban land-use change in East China causes spatially-varying changes in surface net radiation and heat fluxes, atmospheric circulation, and water budgets. It results in significant surface warming (cooling) and precipitation decrease (increase) in a large region north (south) of 30°N. Urban expansion agglomerated in (29°–41°N, 110°–122°E) alters the surface energy budget and warms the surface, resulting in strengthened southwesterly airflow south of 25°N and increased convergence below the mid-troposphere between 20° and 30°N. A concomitant northward downdraft associated with the increased convection generates an anomalous high pressure north of 30°N. Meanwhile, the downdraft not only produces adiabatic warming but also inhibits the dynamic condition for precipitation formation. The anomalous high pressure formed in North China prevents the southwesterly airflow from advancing northward, leading to increase the convergence and precipitation in South China. These changes reduce the meridional temperature gradient in the mid-lower troposphere and weaken the westerly airflow near 30°N. In addition, horizontal transport of vorticity north of 35°N weakens significantly, which leads to an anomalous barotropic structure of anticyclonic there. As a result, the anomalous anticyclonic circulation and descent north of 30°N are strengthened. At the same time, the anomalous cyclonic circulation and ascent south of 30°N are enhanced. These process induced by the thermal state changes due to urbanization weakens the EASM.

Self-modifying CA model using dual ensemble Kalman filter for simulating urban land-use changes

There are many different methods to calibrate cellular automata (CA) models for better simulation results of urban land-use changes. However, few studies have been reported on combination of parameter update and error control using local data in CA calibration procedures. This paper presents a self-modifying CA model (SM-CA) that uses the dual ensemble Kalman filter (dual EnKF), which enables the CA model to simultaneously update model parameters and simulation results by merging observation data (local data). We applied the proposed model to simulate urban land-use changes in a 13-year period (1993–2005) in Dongguan City, a rapidly urbanizing region in south China. Simulation results indicate that this model yields better simulation results than the conventional logistic-regression CA and decision-tree CA models. For example, the validation is carried out using cross-tabulation matrix. The simulation results of SM-CA have allocation disagreement of 10.18%, 19.64%, and 30.03% in 1997, 2001, and 2005, respectively, which are 2.12%, 2.47%, and 6% lower than conventional logistic-regression CA models.

Urban agglomeration impact analysis using remote sensing and GIS techniques in Malegaon city, India

Abstract Malegaon district has witnessed rapid urban growth over the past three decades, which has resulted in vast ecological and environmental issues, both in urban and peri-urban areas. This study proposes a quantitative method of land use change studies in Malegaon district, focusing on the changes in urban agglomeration, population, land use and land cover; and its correlation with the population increase, migration and urbanization led problems related with water and environmental degradation. Digital image processing of satellite images has been used as a main tool and the morphological growth was based on the analysis of satellite image series (3 different dates, with time intervals between them). Images were preprocessed (atmospheric and geometric corrections) and classified according to the major land use like urban, agriculture, forest and water. The present study revealed an increase in settlement by 78% from 1989 to 2006 and an increase by 26% from 2006 to 2008, along with the increase in population, migration from rural areas owing to the economical growth and technological advantages associated with urbanization.