Changes In Land Use Types Research Articles

Effects of land use change type on soil microbial attributes and their controls: Data synthesis

Land use change (LUC) significantly affects climatic, edaphic conditions and soil microbial attributes in terrestrial ecosystems. However, the overall impacts of LUC type on soil microbial attributes remain limited. Here we synthesized data of soil microbial attributes under different types (i.e. type Ⅰ: conversions from other lands to cropland, with human disturbance land degradation; type Ⅱ: conversions from forestland to grassland, shrubland to grassland, and forestland to shrubland, with natural land degradation) of land use from 90 published studies to quantify the effects of LUC types on soil microbial attributes and their controls. Total phospholipid fatty acids (PLFAs), fungi, bacteria and Actinobacteria (ACT) biomass were largely decreased under the type Ⅰ of LUC, whereas these attributes were generally increased under the type Ⅱ of LUC. The soil organic C (SOC), total N, and C:N ratio were the predominant controllers under the type Ⅰ, and the total N, phosphorus and C:N ratio were the main controllers under the type Ⅱ over soil microbial attributes. Additionally, the basal microbial respiration was decreased under the type Ⅰ due to lower SOC content, but the microbial metabolic quotient was increased under the type Ⅱ due to higher C:N ratio. Overall, our results revealed that the microbial attributes and their controls were highly dependent on the type of LUC, which could provide new insight for land use management under expanded LUC worldwide.

Impact of land-use changes on ant communities and the retention of ecosystem services in Rashad District, Southern Kordofan, Sudan

The ecological consequences of biodiversity loss are usually the reduction of ecosystem functions. These responses, however, differ depending on the type of land-use change and the ecological setting. We investigated the impact of land-use type and ecosystem functions on the ant assemblage of Rashad District, Sudan. We analysed the effects of three different land uses (soy monoculture, pasture and organic production of vegetables) on the ant community by assessing ant composition in 176 different locations. The collection sites were conventional soy monoculture, pastures, organic agriculture, and native vegetation such as Campo, Kubos, and forests. We recorded 264 ant species on the soil surface of the Rashad District, where 342 to 354 species were thought to exist. Pastures and organic agriculture areas have 61% and 56% of the native myrmecofauna, respectively, while conventional soy monoculture areas are home to only 17% of native ant species. Forest areas present a unique community, and soy monoculture areas have the strongest pattern of biotic homogenisation. We also detected that rare species (of low frequency) were the chief promoters of richness in the Rashad District, and the most threatened with local extinction, due to their low density and low occurrence in agrosystems. Overall, we found that agricultural expansion reduces ant diversity, particularly in soybean crops, and can affect ecosystem functions. To mitigate the reduction in the ant assemblage, we recommend the conservation of multiple natural habitats. Significance: Agricultural land conversion and climate change play a major role in shaping tropical landscapes, but the direct and indirect links to biodiversity and species community composition remain poorly understood. Ant richness is correlated with biomass, demonstrating that the effects on ecosystem function are dependent on the particularities of each assessed function (such as resource type), the types of land uses, and the abundance of ants in the region. Land-use effects on ant diversity were strongly scale dependent. The highest ant diversity occurred in soy monoculture areas.

Application of swat hydrological model to assess the impacts of land use change on sediment loads

Controlling and reducing the watershed's erosion and sedimentation is essential to ensure the continuity of projects implemented to develop land and water resources and improve sustainability, performance, and longevity. Sediment control is also critical in managing the river basin in limiting the transport of solids, improving water quality, sustaining aquatic life, and preventing damage to downstream aquatic environments and ecosystems. Estimating the potential effects of land-use changes on surface runoff and soil erosion requires distributed hydrological modeling methods. In addition to naturally occurring sediments, changes in land-use types for different applications can be a primary cause for the increase in sediment rates in the watershed. This study used the Soil and Water Assessment Tool (SWAT), a rainfall-runoff model, to evaluate land use/cover changes (i.e., deforestation) and their impact on sediment load under different scenarios. For the baseline (no changes) scenario, the watershed is calibrated using the flow and sediment data measured from the rain gauge station during the time step to estimate the post-deforestation changes at the sub-catchment scale of the study area. The study results indicated that the total surface runoff and sediment yield for the selected sub-catchment in the deforestation scenario with the highest spatial distribution, due to the high erosivity (24% increase) of excessive surface runoff after deforestation, sediment yield increased 3.5-fold. In contrast, due to the removal of trees and vegetation's canopy, the evapotranspiration, leaf area index, and dissolved oxygen transported into reach showed the inverse ratios, and the values decreased by 5%, 24, and 17%, respectively, in compared with the baseline scenario. In terms of watershed management, therefore, the application of hydrological models such as SWAT rainfall-runoff and erosion models can be a helpful method for decision-makers to apply for the protection of forests from intensive impacts such as deforestation and limiting their socio-environmental effects.

Analysis of Ecological Environment Changes and Driving Forces in Boao town of Hainan Province

Based on the three phases of remote sensing imageries in 2000, 2010 and 2020, taking Boao town as the study area, this paper analyzed the changes in the ecological environment and the driving forces of ecological environment. The results showed that: (1) The main land use type of Boao town was forest, followed by cultivated land. The main change of land use types in Boao town from 2000 to 2020 is from forest to other land types. (2) The average vegetation coverage of Boao town was 70.68% in 2000, 62.49% in 2010 and 71.65% in 2020, which indicated a trend of first decreasing and then increasing. (3) The changes of landscape pattern index of type level from 2000 to 2020 were as follows: the landscape shape index and landscape fragmentation of cultivated land decreased gradually, while the landscape shape index and landscape fragmentation of construction land and forest land increased. The trend of landscape pattern index of landscape level from 2000 to 2020 was as follows: landscape fragmentation continued to increase, landscape spread continued to decline, landscape separation continued to rise, and landscape diversity and evenness continued to increase. (4) In the driving force analysis of ecological environment changes in Boao Town, the results of principal component analysis showed that human factors were the leading factors of ecological environment changes in Boao Town, and economic factors such as GDP, output value of the third industry and per capita disposable income of farmers were the main driving forces of landscape pattern changes in Boao town.

Impact of Land Use on Atmospheric Particulate Matter Concentrations: A Case Study of the Beijing–Tianjin–Hebei Region, China

The increasing frequency of human activities has accelerated changes in land use types and consequently affected the atmospheric environment. In this manuscript, we analyze the relationships between the particulate matter concentration and land use changes in the Beijing–Tianjin–Hebei (BTH) region, China, from 2015 to 2018. The experimental results indicate that (1) an improved sine function model can suitably fit the periodic changes in the particulate matter concentration, with the average R2 value increasing to 0.65 from the traditional model value of 0.49, while each model coefficient effectively estimates the change characteristics of each stage. (2) Among all land use types, the particulate matter concentrations in construction land and farmland are high, with a large annual difference between high and low values. The concentration decreases slowly in spring and summer but increases rapidly in autumn and winter. The concentrations in forestland and grassland are the lowest; the difference between high and low values is small for these land use types, and the concentration fluctuation pattern is relatively uniform. Natural sources greatly influence the concentration fluctuations, among which frequent dusty weather conditions in spring impose a greater influence on forestland and grassland than on the other land use types. (3) The landscape pattern of land use exerts a significant influence on the particulate matter concentration. Generally, the lower the aggregation degree of patches is, the higher the fragmentation degree is, the more complex the shape is, the higher the landscape abundance is, and the lower the particulate matter concentration is. The higher the construction land concentration is, the more easily emission sources can be aggregated to increase the particulate matter concentration. However, when forestland areas are suitably connected, this land use type can play a notable role in inhibiting particulate matter concentration aggravation. This conclusion is of great relevance to urban land use planning and sustainable development.

Distribution, ecological risk assessment and source identification of pollutants in soils of different land-use types in degraded wetlands.

BackgroundUrbanization and global warming are generating ecological degradation and land pattern alteration problems in natural wetlands. These changes are greatly affecting the ecological services of wetlands. Therefore, there is an urgent need to explore the relationship between pollutants and land-use type for wetland restoration purposes. Zaozhadian Lake is a freshwater wetland in the North China Plain, which is facing degradation and land-use types changes. An experiment for analyzing soil pollutants was conducted in three land-use types of farmland, lake, and ditch in the Zaozhadian Lake. The aims of this study were to identify the distribution, pollution degree, and sources of pollutants in different land-use types, and to explore the influence of land-use type changes on contamination.MethodsIn this study, surface sediments (0–10 cm) of three land types (farmland, lake, and ditch) in Zaozhadian Lake were collected, and heavy metals (Cu, Ni, Zn, Pb, Cd, Cr, Hg), As, total nitrogen (TN), total phosphorus (TP) and organic matter (OM) were determined. Kriging interpolation was used to visualize the pollutants distribution. The pollution degree of TN and TP was evaluated by the Nemerow pollution index. The pollution of heavy metals and As was evaluated by the geological accumulation index (Igeo) and the potential ecological risk index (RI). Then, dual hierarchical clustering analysis and the principal component analysis were performed to further analyze the impact of land type changes on pollutants.ResultsThe heavy metal contents in the farmland were higher than other areas, while the TN (3.71 ± 1.03 g kg-1) and OM (57.17 ± 15.16 g kg−1) in lake sediments were higher than that in other regions. Farmland, lake, and ditches had low ecological risks, with RI values of 84.21, 71.34, and 50.78, respectively. The primary heavy metal pollutants are Pb, Cu, and Ni. Furthermore, Cu, As, Ni, Pb, and Zn were primarily derived from agriculture pollution, the source of Cd was the industrial pollution, and Cr mainly originated from natural sources. Nutrients primarily came from the decomposition of aquatic animals, plants, and human-related activities. When the lake area was converted into farmland, the heavy metal concentrations in the soils increased and the TN and OM decreased. Based on the results, this study put forward key strategies including the adjustment of the land-use type and restriction of the entry of pollutants into the wetland ecosystems in the Zaozhadian Lake. More attention should be paid to the impact of land-use type change on pollutants in wetlands.

Extracting Land Use Change Patterns of Rural Town Settlements with Sequence Alignment Method

Understanding land use change patterns of rural town settlements (RTSs) is crucial for rural and small-town planning; however, few studies have explored pattern mining approaches to RTS trajectory analysis. In this study, we adopted a novel method by building sequence alignment method (SAM) to detect representative trajectory clusters of land use change of 1158 RTSs in seven waves from 1980 to 2015 in Guangdong, China. The results suggest that there are 10 clusters of RTSs with varying trajectories of land use change, implying their differences in the development processes and underlying socioeconomic, demographical, and institutional factors. A spatial distribution map of RTSs shows that stable cultivated ecological and stable ecologically dominant RTSs are distributed in the northern, eastern, and western parts of Guangdong, whereas stable rural construction and stable mixed construction RTSs are mostly located around the provincial boundary. Notably, 73% of the RTSs that have undergone changes in land use types are located in the Pearl River Delta (PRD), including urbanized and agricultural upgraded RTSs. The analysis presented here summarizes the driving forces of the spatial evolution of RTSs, including the location, landforms, industries, and policy factors. This study provides dynamic policy implications to understand longitudinal and sequential spatial restructuring and regional coordinated development in the fast-growing PRD area.

Deciphering the influence of multiple anthropogenic inputs on taxonomic and functional profiles of the microbial communities in Yitong River, Northeast China.

We conducted the analysis of physicochemical parameters, 16S rRNA amplicon sequencing and real-time quantitative polymerase chain reaction to explore the impact of human inputs on the bacterioplankton communities within a tributary of the largest river flowing through a megacity in northeast China. Agriculture largely accounted for the alteration of diversity and functions of the microbial communities. Furthermore, nitrate and total phosphorus declined at the reservoir outlet. The WWTP effluent discharge caused a decrease of the relative abundance of Actinobacteria and Cyanobacteria, while the impact on the variation of alpha diversity of river microbial community was slight. Carbon fixation and nitrogen cycle varied with the change of land use type. The rare taxa contributed with a predominant role in the response to environmental variables and NH3-N as well as NO3--N were the main environmental factors that drove the shift in the bacterial community. The occurrence of the human-specific fecal indicator was mostly derived from agriculture, and its increase in relative abundance was observed in the WWTP effluent. Thus, our study provides guidance for ecological assessment and management of rivers by revealing the response pattern of river bacterioplankton to multiple types of anthropogenic stressors.

Empirical study on comparative analysis of dynamic degree differences of land use based on the optimization model

The land use dynamic degree model is constantly improved with the in-depth development of land use change research to optimize research results. On the basis of the analysis and summary of existing land use dynamic degree models, this study proposes an optimization model. We take the analysis of land use change in Jining City as an example for empirical research. Results show that the simulation effect of the optimized land use dynamic degree model is more reliable. The optimized single land use dynamic degree model can more truly reflect the intensity of changes in various land use types. The optimized comprehensive land use dynamic degree model can better reflect the intensity of regional land use changes; thus, hot spots of land use changes are easier to identify.

基于土地利用及植被覆盖变化的黄河源区生境质量时空变化特征

PDF HTML阅读 XML下载 导出引用 引用提醒 基于土地利用及植被覆盖变化的黄河源区生境质量时空变化特征 DOI: 10.5846/stxb202105131254 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 第二次青藏高原综合科学考察研究项目（2019QZKK0403）；中国科学院战略性先导科技专项（A类）（XDA20020202，XDA19040304） Spatiotemporal variation of habitat quality in the Source Region of the Yellow River based on land use and vegetation cover changes Author: Affiliation: 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:位于青藏高原腹地的黄河源地区生态环境脆弱，面临生物多样性锐减、生态系统退化等问题，黄河源区生态系统保护及其高质量发展已成为国家的重点战略之一。土地利用与植被覆盖是影响生境质量的重要因素，定量化土地利用方式、强度及格局和植被覆盖格局对生态质量影响的研究越来越受到关注，但其对黄河源区生态质量的耦合效应尚不明确。基于2000年和2015年黄河源区土地利用类型及生长季归一化植被指数（NDVI），采用InVEST模型探究了不同时期黄河源区生境质量时空变化，并采用地理加权回归（GWR）模型揭示了生境质量对土地利用和植被覆盖变化的空间响应特征。结果表明，2000年与2015年土地利用类型变化主要为未利用土地向草地的转移。植被覆盖变化方面，源区生长季NDVI整体上升。从生境质量的空间分布来看，黄河源区生境质量总体呈现南高北低的空间格局，高值分布在南部及中部地区，低值分布在北部布青山、东北部高海拔区及黄河乡的黄河沿岸。相较于2000年，2015年黄河源区生境质量平均提高11.47%。草地面积和NDVI与生境质量均呈显著正相关关系，其中NDVI是提高黄河源区生境质量的重要驱动因子。研究结果突出了NDVI对提高黄河源区生境质量的主导作用，可为未来源区生态保护提供借鉴。 Abstract:The Source Region of the Yellow River is situated in the hinterland of Qing-Tibetan Plateau, with very fragile ecosystem. The Source Region of the Yellow River is facing problems such as biodiversity and ecosystem degradation. Ecological protection and high-quality development of the Source Region of the Yellow River has been risen to be one of the key concerns of the national strategy. Land use and vegetation cover are important factors affecting habitat quality. More and more attention has been paid to quantitative evaluation of the impact of the change of land use types, intensity and patterns to habitat quality and the change of the spatiotemporal pattern of vegetation cover to habitat quality. However, the coupling effects of land use and vegetation cover on the habitat quality of the Source Region of the Yellow River are still unclear. Based on the data of land use and the normalized difference vegetation index (NDVI) of vegetation growing season in the Source Region of the Yellow River in 2000 and 2015, this study used the InVEST model to explore the temporal and spatial changes of the habitat quality in the source area of the Yellow River in different periods, and used the geographical weighted regression (GWR) model to quantitatively analyze the coupling effect of land use and NDVI on the evolution of habitat quality. The results showed that land-use types had mainly changed from unused land to grassland in 2000 and 2015 in the Source Region of the Yellow. Overall NDVI in the Source Region of the Yellow River increased during the growing season in 2000 and 2015. From the perspective of spatial distribution, the habitat quality generally presented a spatial pattern of low in the north and high in the south. The high values were distributed in the southern and central regions, and the low values were distributed in the Buqing Mountain in the north, the high-altitude areas in the northeast and along the Yellow River in Yellow River Township. Compared with 2000, the habitat quality in the Source Region of the Yellow River in 2015 increased by 11.47% on average. Both the grassland and NDVI had a significantly positive correlation with the habitat quality, and NDVI dominated the change of habitat quality. The results of this study highlight the leading role of NDVI in improving the habitat quality in the Source Region of the Yellow River and can provide a reference for future ecological protection of the source region. 参考文献 相似文献 引证文献

Study of urbanization trend prediction in Nanchang based on CA-Markov model

In order to promote the healthy development of Nanchang city in the future and maintain the virtuous cycle of urban ecosystem, this paper uses CA-Markov model to simulate and forecast the land use of Nanchang city in 2030 and explore the urbanization process of Nanchang city. Firstly, the land use changes in Nanchang from 2000 to 2020 are described, followed by land use simulations for Nanchang in 2020 as a verification of accuracy, and land use projections for Nanchang in 2030 based on accuracy requirements. The results show that: (1) the rate of urban expansion will continue to be maintained or even gradually increase from 2020 to 2030 under the expansion model based on the period 2000-2020. (2) The main factor in the change of land use types in the built-up area of Nanchang over the past two decades is socio-economic factors, with natural factors taking second place. (3) The area of land development intensity in Nanchang will reach its peak in 2030, and the expansion of the municipal districts will gradually slowdown in favour of Nanchang and Xinjian counties, which have a more extensive land area and are close to the central urban area.

Monitoring the Spatio-Temporal Changes of Non-Cultivated Land via Long-Time Series Remote Sensing Images in Xinghua

The amount of cultivated land per capita in China is relatively low, and the phenomenon of non-agricultural cultivated land (NACL) in recent years has negatively impacted the stability of grain production in China. In this study, long-time series images obtained via satellite remote sensing were used to monitor spatio-temporal changes in NACL at the county scale. Seven-phase images were acquired from 1990 to 2020 (every five years) using medium-resolution Landsat MSS, TM, ETM+, and Sentinel MSI. Vegetation indices and texture features were extracted for all images. Terrain features such as slope, aspect and elevation were extracted from the DEM data. Combining vegetation index features, texture features, terrain features and multispectral bands, the image classification was performed using the random forest (RF) algorithm. The indices of classification accuracy assessment indices included overall accuracy (OA) and multiclass F-scores (F_m). Zonal statistics were used to calculate the area of cultivated land in towns for 1990 and 2020, and to create grades for the reduction of cultivated land. Finally, indicators including land use dynamic degree (LUDD), land use type change (LUTC) and land use change rate (LUCR) were adopted to reflect the spatio-temporal of NACL in the study area. The results show that RF classification algorithm achieves accurate and efficient land use extraction. The OA were greater than 86%, and the F_m were over 0.88. The cultivated land area in the study area showed decreasing trend. From 1990 to 2020, the ratio of cultivated land decreased from 59.75% to 50.21%. Meanwhile, the dynamic degree of cultivated land increased annually. The conversion of cultivated land into construction land was dominant, accounting for 31.84% of the total change in cultivated land over the past 30 years. This study also reveals that NACL is highly related to local economic and land-use policies. Multi-source remote sensing data have been used to quantitatively analyse the spatio-temporal changes in cultivated land conversion, providing a reference for relevant land management departments to master cultivated land use changes and adjust land management policies.

北京市景观格局演变及其对多种生态系统服务的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 北京市景观格局演变及其对多种生态系统服务的影响 DOI: 10.5846/stxb202107272042 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 城市与区域生态国家重点实验室开放基金项目（SKLURE2020-2-1）；国家自然科学基金青年科学基金项目（41901227） Changes of landscape pattern and its impacts on multiple ecosystem services in Beijing Author: Affiliation: 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:景观格局是人与自然共同作用的结果，深刻影响着区域的生态系统服务及可持续发展。以高度城市化地区——北京市为案例，选取了粮食生产、水质净化、空气净化、气体调节、生境质量以及休闲娱乐6项重要生态系统服务，采用InVEST （Integrated Valuation of Ecosystem Services and Tradeoffs）、ROS （Recreation Opportunity Spectrum）等模型定量评估了1980-2018年生态系统服务时空分布。通过对北京市景观组成与景观配置指数进行定量分析，进一步探索了景观格局演变对生态系统服务的影响。结果表明：（1）北京市1980-2018年建设用地扩张了120%，建设用地扩张是耕地面积减少的主要原因。景观格局总体上趋于破碎化，斑块形状复杂化，斑块异质性增加；（2）时间上，北京市1980-2018年粮食生产、水质净化、气体调节、生境质量、休闲娱乐5项生态系统服务均呈现下降趋势；空间上，粮食生产呈现东南部较高，西北部较低的分布特征，其余生态系统服务均呈现西北部较高，东南部较低，市中心最低的分布特征；（3）景观水平上，林地、建设用地等景观组成变化对生态系统服务影响最为显著。破碎化指数、多样性指数等景观配置指数对生态系统服务影响最为显著；类型水平上，平均斑块面积、斑块聚集度对生态系统服务影响相对最为显著。总体来讲，通过分析景观格局演变如何影响生态系统服务，为如何通过设计和优化景观格局来提升生态系统服务提供了定量依据，从而为促进区域的景观可持续规划提供理论依据和案例参考。 Abstract:Landscape pattern is the result of the interaction between human and nature. During the urbanization process, the landscape pattern had changed significantly, which affected the ecological process and thus threatened ecosystem services. The assessment of the impacts of landscape pattern on ecosystem services is crucial for regional sustainable development. Taking Beijing as a case study, we quantified the spatiotemporal changes of six selected ecosystem services, including food production, water purification, air quality regulation, carbon storage, habitat quality, and recreation opportunity from 1980 to 2018 by using the InVEST and Recreation Opportunity Spectrum (ROS) models. In addition, we analyzed changes of landscape patterns in Beijing, and explored the impacts of landscape patterns on ecosystem services. The results showed that:1) the landscape pattern in Beijing experienced dramatically changes from 1980 to 2018. The build-up land expanded by 120%, which mainly resulted in the reduction of cropland. The overall landscape pattern tended to be fragmented, the patch shape index became more complicated and the heterogeneity of the patches also increased. 2) Food production, water purification, carbon storage, habitat quality, and recreation opportunity showed a decreasing trend from 1980 to 2018. Spatially, food production was higher in the southeast and lower in the northwest. For the other ecosystem services, they were higher in the northwest, lower in the southeast, and the lowest in the central downtown area. During the past 38 years, the food production decreased the most in the central region of Beijing, while the air quality regulation, carbon storage, habitat quality, and recreational opportunity decreased the most in the eastern and southern regions. 3) At the landscape level, changes in land-use types, such as woodland, grassland, and build-up land had the most significant impacts on ecosystem services. Landscape metrics, such as the fragmentation index and diversity index influenced ecosystem services more obviously. At the class level, the mean patch area and the patch aggregation index had the most significant impacts on ecosystem services. Among them, the mean patch area and aggregation index of woodland showed positive effects on air quality and carbon storage. However, the aggregation index of built-up land showed a negative effect on habitat quality. In general, this study focused on analyzing the impacts of landscape pattern changes on ecosystem services, which can help decision makers to improve the ecosystem services by optimizing landscape patterns. The results of this study also can provide theoretical and practical basis for promoting regional landscape sustainable planning. 参考文献 相似文献 引证文献

福建省安溪县土地利用时空演变规律及其关键驱动因素

以福建省安溪县为研究边界, 选取了1999—2019年该县及所属乡镇的耕地、林地、草地、园地、水域、建设用地和未利用地等7个土地利用类型作为物种变量, 与其相关性较大的社会经济指标为环境变量, 采用典范对应分析和空间自相关等方法进行分析, 以明确安溪县和所属乡镇的土地利用时空演变特征及其关键驱动因素。研究结果表明：安溪县1999—2019年间土地利用类型变化总体上呈“三减四增”态势, 并在全局空间分布格局上呈明显的聚焦状态。全县耕地、草地和水域面积分别减少36.82%、22.91%和8.18%, 而林地、园地(主要是茶园)、建设用地和未利用地面积则分别增加了10.37%、56.39%、206.08%和90.14%。就林地面积而言, 近10年来安溪县24个乡镇中有1/3的乡镇林地呈下降趋势。其中, 祥华、大坪、虎邱、参内、福田和城厢6个乡镇林地面积减少明显。研究表明：在县域水平上, 主要土地利用类型变化, 除了受地理因素的制约外, 主要受社会经济指标和宏观政策的驱动因素调控。排位最大的前3个因素分别是社会消费品零售总额、地区生产总值和茶叶产量。在镇域水平上, 不同乡镇由于地理条件, 特别是城镇化水平和经济发展状况不同, 其土地利用策略和发展驱动力也不同, 但茶产业发展驱动仍是关键因素。根据土地利用现状与存在问题, 提出应强化土地利用科学规划与有效整治, 方可保证区域生态经济协调可持续发展。;In this study, Anxi County of Fujian Province was taken as the research boundary, 7 types of land use including the cultivated land, forest land, grassland, garden land, water bodies, and construction land as well as unutilized land in the County and its townships from 1999 to 2019 were selected as the species variables, and the socioeconomic indicators with a relatively high correlation with them were the environmental variables for this study. The spatial and temporal evolution characteristics of land use and its key driving factors in Anxi County and its townships were analyzed by means of canonical correspondence analysis (CCA) and spatial autocorrelation. The results showed that the change of land-use type in Anxi County from 1999 to 2019 generally performed a trend of three decreases and four increases, indicating a significant pattern of agglomeration in globally spatial distribution. The area of cultivated land, grassland and water bodies decreased by 36.82%, 22.91% and 8.18%, respectively, while forest land, garden land (mainly tea plantation), construction land and unutilized land increased by 10.37%, 56.39%, 206.08% and 90.14%, respectively. Forest land areas have been increased as a whole within 20a, but the changes varied from township to township. In the past decades, 1/3 of the 24 townships of Anxi County, such as Xianghua, Daping, Huqiu, Cannei, Futian and Chengxiang, showed a significant declining trend in forest land area. Further analysis showed that the changes in main types of land-use were mainly controlled by the driving factors of socioeconomic indicators and macro policies except for restriction by geographical factors in county scale. The top three factors were the total retail sales of consumer goods, the gross regional product and tea production. In township scale, different townships had different land use strategies and development drivers due to different geographical conditions, especially the level of urbanization and economic development, but the development driver of tea industry was still a key factor. Therefore, the authors suggest that it is important to strengthen the scientific planning and effective renovation of land use based on status and problems of land use, so as to ensure the coordinated and sustainable development of regional ecological economy.

城市化背景下小微湿地景观动态变化及其驱动因素

PDF HTML阅读 XML下载 导出引用 引用提醒 城市化背景下小微湿地景观动态变化及其驱动因素 DOI: 10.5846/stxb202107061800 作者: 作者单位: 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（32171530,31472020） Dynamic changes in small wetland landscapes and their driving factors under the background of urbanization Author: Affiliation: Fund Project: The National Natural Science Foundation of China (32171530, 31472020) 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:小微湿地是指自然界在长期演变过程中形成的小型湿地。城市发展导致小微湿地大量消失，了解小微湿地景观动态变化特征及驱动因素是保护与管理小微湿地的重要基础。以合肥市包河区为研究区域，选取2006-2018年4期遥感影像，利用空间分析方法确定2006-2010年、2010-2014年、2014-2018年、2006-2018年4个时期小微湿地景观动态变化，基于300m×300m的网格单元，结合增强回归树和地理加权逻辑回归模型，分析13个预测变量与小微湿地损失之间的关系。结果表明：2006-2018年，小微湿地在整个研究区大范围减少，总面积下降了60.8%，斑块数量减少了60.5%，同时，小微湿地边缘复杂度降低，小微湿地间的空间距离增加，聚集程度降低。增强回归树模型显示，城市发展初期(2006-2010年)，周边用地类型(建设用地、旱地、林地和草地)变化是导致小微湿地损失的主要因素，中后期(2010-2018年)各类型土地利用变化的相对影响有不同程度的下降，斑块面积和坡度对小微湿地损失的驱动作用逐渐凸显。2006-2018年，建设用地变化(14.4%)、斑块面积(13.5%)、旱地变化(11.1%)、坡度(10.1%)、林地变化(8.5%)、草地变化(7.0%)是导致小微湿地损失的高重要性变量。地理加权逻辑回归模型揭示了高重要性变量对小微湿地损失影响的空间非平稳性特征，结果显示，除斑块面积系数的空间可视化无解释意义，其余高重要性变量对小微湿地损失的影响随地点的变化，贡献的大小和方向也有所不同。研究方法和结果可以为城市快速发展地区小微湿地的保护与管理提供理论支持。 Abstract:The term "small wetland" refers to wetlands of small scale, which can stabilize ecological systems in the process of long-term development. Against the backdrop of rapid urbanization, many small wetlands have been disappearing, often in groups in cities. Understanding the dynamic changes and their driving factors in small wetlands provides an important basis for the effective protection and management of small wetlands. In this study, we took Baohe District in Hefei City as the research area and analyzed the landscape pattern characteristics by interpreting remote sensing data through time (2006, 2010, 2014, and 2018). The spatial analysis method was used to determine the dynamic changes in small wetland landscapes over four study periods of 2006-2010, 2010-2014, 2014-2018, and 2006-2018. Based on a 300 m×300 m grid unit, boosted regression tree and geographically weighted logistic regression models were employed to identify the relationships between 13 predictive variables and the loss of small wetlands. The results showed that the total area of small wetlands decreased by 60.8% and the number of patches decreased by 60.5% during the period from 2006 to 2018. At the same time, the extent and complexity of the perimeter of the small wetlands decreased, the spatial distance between the small wetlands increased, and the distribution tended towards more discrete. The boosted regression tree model quantified the relative influences of the predictive variables and determined high-importance variables to further analyze the nonlinear relationships between the variables and the decline in small wetlands. In the early stage of urbanization, changes in the surrounding land-use type were the major driving factors in the loss of small wetlands. In the middle and late stages of urbanization, both the trend in large-scale urban sprawl slowed down, and the relative importance of other land-use type changes also declined to varying extents. The driving factors of patch area and slope on the loss of small wetlands gradually increased in importance. Construction land changes (14.4%), patch area of small wetlands (13.5%), dryland changes (11.1%), slope (10.1%), forestland changes (8.5%), and grassland changes (7.0%) were high-importance variables of small wetland losses from 2006 to 2018. The local and spatial influences of these high-importance variables were analyzed further by geographically weighted logistic regression using coefficients determined at each sample point. With the exception that the spatial visualization of the small wetland patch areas had no explanatory significance, the influences of the remaining variables varied with location, and their contributions also differed in magnitude and direction. This study provides a reference for the protection and management of small wetlands in rapidly developing urban areas. 参考文献 相似文献 引证文献

Mapping of non-submerged aquatic vegetation by using UAV for clarifying the status of <i>Eichhornia crassipes</i> (Mart.) Solms in the Nong Bong Khai Non-hunting Area, Thailand

Eichhornia crassipes (Mart.) Solms.is listed as one of the worst invasive alien plants that can be introduced to the new environment primarily by human activities. They have very high reproduction rates in favorable conditions, especially concentrated nutrients. Native plants' habitats can be encroached by the density of Eichhornia crassipes mat and disappear in their environment. This study aims to study causes of the increase of Eichhornia crassipes by analyzing land use/land cover and water quality in Nong Bong Khai Non-hunting Area, Chiang Rai, Thailand. Then we used unmanned aerial vehicles (UAV) with 2 flight altitude levels (30m, 90m) for non-submerged aquatic vegetation mapping to study the distribution. The results showed that increases in Eichhornia crassipes resulted from high concentrations of nutrients in water. From 2009 to 2018, The land use/land cover reports indicated changes in land use type which area of field crop highly increased. The distribution map that was generated by applying a 90-m orthophoto from the UAV showed high covering area of Eichhornia crassipes by 13.82% of the lake area. Also, the vegetation map generated from a 30-m orthophoto showed the distribution and proportion of Eichhornia crassipes were more than those of other native plant species. This study showed that changes in land use/land cover around the lake affected water quality changes, which was a main cause of highly increasing rates of Eichhornia crassipes. Moreover, the orthophoto from the UAV at different altitude levels was suitable and useful for monitoring the distribution of Eichhornia crassipes and also other plant species.

Spatial Analysis Of Land Use Changes Towards Banjarbaru City's Regional Spatial Plan

Banjarbaru City is one of the cities in South Kalimantan Province which is developing quite rapidly from year to year. Hence, it is necessary to research and study changes in land use and their suitability with the city development plan. The purpose of this study is to examine changes in the area and types of land use changes in Banjarbaru City within a period of 8 years, from 2013 to 2021, determine the rate of land use change, and assess the suitability of land use changes to the applicable Banjarbaru City spatial plan. This research method is an overlay to see changes in land use and the suitability of changes in land use with the direction of spatial functions in the Regional Spatial Plan. The result of this research is that in an area of ​​16,414.00 ha (53.7%) there is a change in land use in Banjarbaru City in the period 2013-2021. The biggest land use changes are dry land agriculture, vacant land, wetland agriculture, housing, and villages. The use of dry land and agricultural land has the largest decrease in area, which is 15,090.71 ha or a decrease of 365.5%. The use of vacant land increased in an area of ​​14,715.684 hectares or an increase of almost 4 times. Wetland agriculture has decreased in an area which is reduced by 986.55 ha or decreased by 65.8%. The use of land for housing/residential in the form of housing or villages has also undergone considerable changes. The use of residential land has increased by 528.105 hectares (44.626%) and the village area to 444.32 ha (21.2%). The suitability of land use with the RTRW in Banjarbaru City is 16,742.86 ha (54.8%) categorized as appropriate, while an area of ​​13,779.69 ha (45.2%) is categorized as not in accordance with the applicable RTRW.

Spatio-Temporal Changes and Driving Force Analysis of Wetlands in Jiaozhou Bay

Tian, Y.; Li, J.; Wang, S.; Ai, B.; Cai, H., and Wen, Z., 2022. Spatio-temporal changes and driving force analysis of wetlands in Jiaozhou Bay. Journal of Coastal Research, 38(2), 328–344. Coconut Creek (Florida), ISSN 0749-0208. Jiaozhou Bay is the largest bay-type coastal wetland with high biodiversity in Shandong Peninsula. In recent years, the wetland of Jiaozhou Bay has been reduced dramatically due to urban expansion. It is significant to study the characteristics and causes of the wetland changes in the past 40 years for the rational exploitation and sustainable development of coastal wetland resources. The types, spatial distribution, and area information of the wetland from 1983 to 2019 are obtained by artificial visual interpretation and supervised classification using ten Landsat remote sensing images, assisted by Google images. The research analyzes the conversion of land use types and the change rule of landscape pattern in the wetland, as well as the driving forces of the wetland evolution and the uncertainty factors affecting the analysis results. The results indicate that the wetland area shows an overall decreasing trend from 1983 to 2019, 77% of which are converted into nonwetland. The wetland area increases initially, followed by a decrease from 1990 to 2000, but then continues to decrease slowly from 2000 to 2019. There are many types of land use changes from coastal tidal flats to other land use types such as construction land or pond, and the landscape pattern has been gradually fragmented. The continuous increase in temperature is the main natural cause for the degradation of the wetland. Population factor is the most important driving force for the change of the wetland. The main uncertain factors affecting the analysis results are the capture time of remote sensing image, tidal level correction, wetland classification system, and method. The results provide a basis for the decision-making of wetland protection. The quantitative data will provide a reference for the construction of a multiyear wetland dataset in Jiaozhou Bay.

Quantifying the Contribution of LUCC to Surface Energy Budget: A Case Study of Four Typical Cities in the Yellow River Basin in China

With social changes and economic development, human activities inevitably lead to significant changes in land use types. Land use and land cover change (LUCC) leads to a series of changes in energy balance and surface temperature, which has an impact on the regional climate. In this study, MODIS remote sensing data were used to quantify the results of the biological and geophysical effects caused by LUCC in four typical cities in the Yellow River Basin of China: Jinan, Zhengzhou, Lanzhou and Xining. The results showed the following: (1) The latent heat flux and the net radiation of the four cities were both increasing on the whole. The latent heat flux of water and forest was higher, which played a key role in energy consumption on the ground. The net radiation value of the old urban and urban expansion areas was higher, while that of the forest was lower, which indicated that human activities increased the input of surface energy. (2) The differences between latent heat flux and net radiation in areas greatly affected by human activities were much smaller than those in natural areas such as forest and grassland. This indicted that human activities increased the warming trend. In addition, most of the differences between latent heat flux and net radiation in the four cities showed a downward trend. (3) Different cities have different regulating factors for land surface temperature (LST). In Jinan and Zhengzhou, the regulation of LST by net radiation was more obvious, while in Lanzhou and Xining, the regulation of LST by latent heat flux was more pronounced. By comparing LUCC and the forced balance between energy intake and consumption in four typical cities along the Yellow River Basin, this study emphasizes the difference of energy budgets under different land use types, which has important reference value for judging the spatial difference of urban thermal environments.

Contributions of Human Activities and Climatic Variability to Changes in River Rwizi Flows in Uganda, East Africa

This study employed Soil and Water Assessment Tool (SWAT) to analyze the impacts of climate variability and human activities on River Rwizi flows. Changes in land use and land cover (LULC) types from 1997 to 2019 were characterized using remotely sensed images retrieved from Landsat ETM/TM satellites. SWAT was calibrated and validated over the periods 2002–2008 and 2009–2013, respectively. Correlation between rainfall and river flow was analyzed. By keeping the optimal values of model parameters fixed while varying the LULC maps, differences in the modeled flows were taken to reflect the impacts of LULC changes on rainfall–runoff generation. Impacts due to human activities included contributions from changes in LULC types and the rates of water abstracted from the river as a percentage of the observed flow. Climate variability was considered in terms of changes in climatic variables such as rainfall and evapotranspiration, among others. Variability of rainfall was analyzed with respect to changes in large-scale ocean-atmosphere conditions. From 2000 to 2014, the portion of River Rwizi catchment area covered by cropland increased from 23.0% to 51.6%, grassland reduced from 63.3% to 37.8%, and wetland decreased from 8.1% to 4.7%. Nash–Sutcliffe Efficiency values for calibration and validation were 0.60 and 0.71, respectively. Contributions of human activities to monthly river flow changes varied from 2.3% to 23.5%. Impacts of human activities on the river flow were on average found to be larger during the dry (14.7%) than wet (5.8%) season. Using rainfall, 20.9% of the total river flow variance was explained. However, climate variability contributed 73% of the river flow changes. Rainfall was positively and negatively correlated with Indian Ocean Dipole (IOD) and Niño 3, respectively. The largest percentages of the total rainfall variance explained by IOD and Niño 3 were 12.7% and 9.8%, respectively. The magnitude of the correlation between rainfall and IOD decreased with increasing lag in time. These findings are relevant for developing River Rwizi catchment management plans.