Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China

Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified framework.Thus,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification agreement.The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,respectively.The FROMGLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification,respectively.High consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,China.In contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern China.Field size was the most important factor for mapping cropland.For area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and GlobCover2009.The cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products.Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction,which is essential for food security and crop management,so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.

滇中城市群碳储量时空演变及其对LULC变化的响应

[目的]通过分析滇中城市群碳储量的时空演变特征及其对土地利用/覆被(land use/land cover,LULC)变化的响应,以深化对该区域碳循环的理解,从而有效地指导碳管理和生态恢复策略的制定。[方法]利用InVEST和PLUS模型模拟并预测1990—2030年滇中城市群碳储量的时空演变规律,结合土地覆被变化数据,定量分析碳储量与LULC变化之间的响应关系。[结果](1)1990—2020年滇中城市群的土地类型主要以林地、耕地和草地为主,林地、耕地和建设用地呈增长趋势,其中建设用地增幅最大;(2)滇中城市群碳储量呈现出“先增后减,逐渐趋于平稳”的变化特征,2000年达到最高值,为1.46×10^(9)t,到2020年下降到1.45×10^(9)t,空间上呈“西高东低”的分布特征;(3)未来不同发展情景下的碳储量预测显示,与2020年相比,4个情景到2030年碳储量均呈下降趋势,其中生态发展情景下降最少,相比2020年下降0.43×10^(7)t,而耕地发展情景下降最为显著,相比2020年下降1.05×10^(7)t;(4)耕地和林地间的转变是影响碳储量的主要因素,其中耕地向林地的转换对滇中城市群碳储量增加尤为关键,林地增加可显著提升区域碳储量,而草地减少则对碳储量产生负面影响。[结论]林地和耕地转换对增加或降低滇中城市群碳储量具有显著影响。

基于GEE平台1995—2022年云南省LULC变化及驱动因素分析

快速准确地获取土地利用信息,可为城市发展和生态环境保护提供参考依据。基于谷歌地球引擎(Google Earth Engine,GEE)平台的多时相Landsat图像密集时间叠加和随机森林算法对云南省的土地利用类型进行分类,分析云南省土地利用和土地覆盖(Land use and Land cover,LULC)时空变化趋势,并使用地理探测器定量评估关键的驱动因素。结果表明,1)LULC分类平均总体精度和Kappa系数分别为88.64%、86.01%,精度较高,满足数据使用要求。2)云南省土地类型以林地、耕地、草地及稀疏灌草混交地为主,占比97.91%~98.38%,土地利用转移以林地和耕地互相转换、草地及稀疏灌草混交地转为耕地为主。3)云南省滇中和滇东部的土地利用强度总体高于其他地区,滇西北和滇西南地区的土地利用强度较低。4)不同驱动因素对LULC影响程度存在显著差异,植被类型、年均气温和土壤类型对LULC变化的影响程度相对较小,高程、坡度、坡向、年均降水、人口密度、GDP和人口城镇化率等对LULC变化的影响程度普遍较高,其中GDP、人口密度和人口城镇化率对LULC变化程度影响较高。研究结果可为云南省后续生态环境保护政策制定和区域可持续发展提供数据基础与支撑。

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.

Spatiotemporal dynamics of land use/land cover(LULC)changes and its impact on land surface temperature:A case study in New Town Kolkata,eastern India

Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.

挠力河融水径流氮分布特征及其对流域LULC的响应

春季融水是中国东北地区河流的重要水文特征,然而对其研究却不多见。以东北三江平原挠力河为研究对象,进行春季融水径流氮分布特征的研究,并利用GIS技术获取各流域土地利用/土地覆被(Land Use/LandCover,LULC)类型面积百分比。将各流域出口氮浓度值与流域LULC类型面积百分比进行Spearman非参数相关分析,结果表明,挠力河中下游融水径流氮分布对流域LULC具有重要响应。其中,农田和居民点对径流氮分布具有正效应,林地具有负效应,湿地的正负效应有待进一步研究。并推断,农田和居民点是挠力河中下游融水径流的氮源,林地是氮汇。从理论上分析,湿地在流域中处于相对较低的位置,应该是接收氮的汇,具有吸收、蓄存和转化氮的功能,且湿地的氮吸收存在一个随面积大小不同而变化的阈值;当氮的输入量低于这一阈值时,湿地为氮汇,而当氮的输入量高于这一阈值时,湿地便成为向下游径流输出氮的源。尽管如此,湿地作为水陆之间的过渡带,独特的位置使其成为农田与径流之间的缓冲带,是氮从农田向径流迁移的最后一道屏障。因此,建议以流域为单元进行LULC规划与管理,加强河岸缓冲带保护与建设,恢复和重建河流中下游河岸湿地,构造宽度适宜、结构完整和高度连通的河岸植被缓冲带。

时空过程对象的LULC时空演变分析算法

地理时空变化是地理学研究的重要内容之一,如何用计算机技术来表达空间数据的时空变化独具前瞻性。从揭示LULC时空演变过程和挖掘时空演变规律出发,讨论了基于地类图斑的时空演变过程类型与判定方法,并构建了一种基于地类图斑的时空变化分析算法。通过对抚仙湖流域近40年来LULC时空演变分析,验证了算法的可靠性与有效性。表明该方法可用于地表覆盖等地理要素的时空变化过程分析,能较好地揭示地理要素及其属性在时间轴上的改变过程。

近26年和田绿洲人口对LULC时空变化分析及其生态响应

研究人口对于绿洲地区土地利用与覆盖(LULC)变化的驱动作用对研究全球环境变化具有重要意义。对1992年和2017年的人口数据及影像文件进行处理,采用相关性分析、支持向量机等方法研究人口对研究区LULC变化的影响。结果表明:(1)26年间,和田绿洲的人口明显增加。(2)和田绿洲LULC变化明显,建设用地扩张明显,沙地面积增加,水体、未利用地、裸地面积均呈现减少趋势。(3)人口变化对和田绿洲LULC变化的驱动作用包括直接驱动和间接驱动2种。直接驱动表现为建设用地向南扩张的趋势。间接驱动表现为草地、沙地、水体面积等的变化。(4)26年间,和田绿洲生态服务价值降低,其生态环境有一定恶化的趋势,当地相关部门需加以治理。

Spatial Patterns of LULC and Driving Forces in the Transnational Area of Tumen River:A Comparative Analysis of the Sub-regions of China,the DPRK,and Russia

Understanding the spatial patterns of land-use and land-cover(LULC)and their driving forces in transnational areas is important for the sustainable development of these regions.However,the spatial patterns of LULC and their driving forces across multiple scales are poorly understood in transnational areas.In this study,we analyzed the spatial patterns of LULC and driving forces in the transnational area of Tumen River(TATR)in 2016 across two scales:the entire region and the sub-regions of China,the Democratic People’s Republic of Korea(DPRK),and Russia.Results showed that the LULC was dominated by broadleaf forest and dry farmland in the TATR in 2016,which accounted for 66.86%and 13.60%of the entire region,respectively.Meanwhile,the LULC in the three sub-regions exhibited noticeable differences.In the Chinese and the DPRK’s sub-regions,the area of broadleaf forest was greater than those for the other LULC types,while the Russian sub-region was dominated by broadleaf forest and grassland.The spatial patterns of LULC were mainly influenced by topography,climate,soil properties,and human activities.In addition,the driving forces of the spatial patterns of LULC in the TATR had an obvious scaling effect.Therefore,we suggest that effective policies and regulations with cooperation among China,the DPRK,and Russia are needed to plan the spatial patterns of LULC and improve the sustainable development of the TATR.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

滇中城市群地表温度时空演变及其与LULC的响应

[目的]探讨滇中城市群的地表温度(land surface temperature,LST)时空变化及其与土地利用/覆盖(land use/land cover,LULC)类型的关系。[方法]基于Google Earth Engine(GEE)平台,利用1990—2020年滇中城市群区域的Landsat卫星影像数据反演LST,并采用Sen-MK趋势分析、均值-标准差法、城市热方差指数(urban thermal field variance index,UTFVI)和相关性分析等定量分析1990—2020年滇中城市群的LST时空变化及其与LULC类型的响应关系。[结果](1)滇中城市群的年际温度等级存在显著时空差异,中温区始终占据绝对主导地位(40%),但其面积占比逐年下降。(2)1990—2020年,UTFVI<0的区域呈逐年增加趋势,UTFVI>0.02的区域呈下降趋势,生态热环境逐渐改善。(3)不同LULC类型的LST存在响应差异。其中,LST与建筑用地的面积占比呈显著正相关(r>0.70)。1990—2020年水域的LST始终最低,多年平均温度为17.38℃,而建筑用地和耕地覆盖的地区温度最高,多年平均温度均高于21℃。(4)1990—2020年,滇中城市群城市迅速扩张,LULC变化显著,建筑用地面积增长100.29%,城市的快速发展使LST升高。[结论]LULC是影响LST的重要因素,合理配置LULC结构,能够改善城市群热环境。研究结果可为滇中城市群的合理开发规划及改善生态条件提供重要见解。

Impacts of climate change and LULC change on runoff in the Jinsha River Basin

The climate change and Land Use/Land Cover(LULC)change both have an important impact on the rainfall-runoff processes.How to quantitatively distinguish and predict the impacts of the above two factors has been a hot spot and frontier issue in the field of hydrology and water resources.In this research,the SWAT(Soil and Water Assessment Tool)model was established for the Jinsha River Basin,and the method of scenarios simulation was used to study the runoff response to climate change and LULC change.Furthermore,the climate variables exported from 7 typical General Circulation Models(GCMs)under RCP4.5 and RCP8.5 emission scenarios were bias corrected and input into the SWAT model to predict runoff in 2017-2050.Results showed that:(1)During the past 57 years,the annual average precipitation and temperature in the Jinsha River Basin both increased significantly while the rising trend of runoff was far from obvious.(2)Compared with the significant increase of temperature in the Jinsha River Basin,the LULC change was very small.(3)During the historical period,the LULC change had little effect on the hydrological processes in the basin,and climate change was one of the main factors affecting runoff.(4)In the context of global climate change,the precipitation,temperature and runoff in the Jinsha River Basin will rise in 2017-2050 compared with the historical period.This study provides significant references to the planning and management of large-scale hydroelectric bases at the source of the Yangtze River.

Effects of atmospheric correction and pansharpening on LULC classification accuracy using WorldView-2 imagery

Changes of Land Use and Land Cover(LULC)affect atmospheric,climatic,and biological spheres of the earth.Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate global warming and biodiversity reduction.This paper examined effects of pansharpening and atmospheric correction on LULC classification.Object-Based Support Vector Machine(OB-SVM)and Pixel-Based Maximum Likelihood Classifier(PB-MLC)were applied for LULC classification.Results showed that atmospheric correction is not necessary for LULC classification if it is conducted in the original multispectral image.Nevertheless,pansharpening plays much more important roles on the classification accuracy than the atmospheric correction.It can help to increase classification accuracy by 12%on average compared to the ones without pansharpening.PB-MLC and OB-SVM achieved similar classification rate.This study indicated that the LULC classification accuracy using PB-MLC and OB-SVM is 82%and 89%respectively.A combination of atmospheric correction,pansharpening,and OB-SVM could offer promising LULC maps from WorldView-2 multispectral and panchromatic images.

基于趋势分析法的输电线路施工区植被动态变化分析

近年来,大量输变电线路工程的建设投入对生态环境产生了潜在威胁,了解相关建设施工对当地的生态环境的扰动至关重要。采用趋势分析和变异系数法等研究方法,基于MODIS NDVI和土地利用等多源遥感数据,分析了2008—2022年间1000 kV特高压交流输变电工程(南昌段)施工的建设前后对区域植被生长环境以及土地利用变化的影响。研究结果发现,输变电路10 km范围的植被NDVI呈略微下降的趋势,由2008年的0.745下降至2022年的0.724;研究区土地利用转化特征主要表现为耕地向其他地类流转,其主要影响集中在施工期。总体上,输电线路工程的建设对研究区内生态环境影响不明显。研究可为该区同类项目输变电工程以及生态环境保护提供一定的理论依据和数据支撑。

Establishing the relationship between land use land cover,normalized difference vegetation index and land surface temperature:A case of Lower Son River Basin,India

The study explores the intricate interplay between land use land cover(LULC),normalized difference vegetation index(NDVI),and land surface temperature(LST)within the Lower Son River Basin in India from 1991 to 2020.The region’s ecological balance has been increasingly strained due to rapid urbanization and changing land use patterns.Through a combination of Landsat TM&OLI/TIRS satellite imageries and geospatial analysis techniques,this study unveils the intricate connection between land use and land cover changes,vegetation,and land surface temperature variations.The study area is classified into three altitudinal zones(Zone Ⅰ:39–300 m,Zone Ⅱ:301–600 m and Zone Ⅲ:601–1,247 m)to examine the changes in depth.The area has seen significant changes in LULC,vegetation and LST in all the three altitudinal zones.The findings hold significant implications for sustainable land management and environmental conservation strategies in the Lower Son River Basin.As per the result,103,438 ha of vegetation was converted into agriculture land and 82,572 ha of agricultural land was transformed into settlements from 1991 to 2020.This trend shows human pressure on the land resource in the study area.Minor increase in water body is seen which is attributed to commissioning of Bansagar dam.Zone Ⅰ has seen highest settlement growth while Zone Ⅲ experienced severe deforestation of around 15%.Zone Ⅱ and Ⅲ needs attention for holistic sustenance.Analysis of LST shows that it has increased by 0.82℃ from 1991 to 2020 which is a red flag.The study underscores the critical importance of balanced land use practices to preserve ecological integrity and mitigate the adverse effects of urbanization and climate change.

Spatiotemporal evolution and future simulation of land use/land cover in the Turpan-Hami Basin,China

The Turpan-Hami(Tuha)Basin in Xinjiang Uygur Autonomous Region of China,holds significant strategic importance as a key economic artery of the ancient Silk Road and the Belt and Road Initiative,necessitating a holistic understanding of the spatiotemporal evolution of land use/land cover(LULC)to foster sustainable planning that is tailored to the region's unique resource endowments.However,existing LULC classification methods demonstrate inadequate accuracy,hindering effective regional planning.In this study,we established a two-level LULC classification system(8 primary types and 22 secondary types)for the Tuha Basin.By employing Landsat 5/7/8 imagery at 5-a intervals,we developed the LULC dataset of the Tuha Basin from 1990 to 2020,conducted the accuracy assessment and spatiotemporal evolution analysis,and simulated the future LULC under various scenarios via the Markov-Future Land Use Simulation(Markov-FLUS)model.The results revealed that the average overall accuracy values of our LULC dataset were 0.917 and 0.864 for the primary types and secondary types,respectively.Compared with the seven mainstream LULC products(GlobeLand30,Global 30-meter Land Cover with Fine Classification System(GLC_FCS30),Finer Resolution Observation and Monitoring of Global Land Cover PLUS(FROM_GLC PLUS),ESA Global Land Cover(ESA_LC),Esri Land Cover(ESRI_LC),China Multi-Period Land Use Land Cover Change Remote Sensing Monitoring Dataset(CNLUCC),and China Annual Land Cover Dataset(CLCD))in 2020,our LULC data exhibited dramatically elevated overall accuracy and provided more precise delineations for land features,thereby yielding high-quality data backups for land resource analyses within the basin.In 2020,unused land(78.0%of the study area)and grassland(18.6%)were the dominant LULC types of the basin;although cropland and construction land constituted less than 1.0%of the total area,they played a vital role in arid land development and primarily situated within oases that form the urban cores of the cities of Turpan and Hami.Between 1990 and 2020,cropland and construction land exhibited a rapid expansion,and the total area of water body decreased yet resurging after 2015 due to an increase in areas of reservoir and pond.In future scenario simulations,significant increases in areas of construction land and cropland are anticipated under the business-as-usual scenario,whereas the wetland area will decrease,suggesting the need for ecological attention under this development pathway.In contrast,the economic development scenario underscores the fast-paced expansion of construction land,primarily from the conversion of unused land,highlighting the significant developmental potential of unused land with a slowing increase in cropland.Special attention should thus be directed toward ecological and cropland protection during development.This study provides data supports and policy recommendations for the sustainable development goals of Tuha Basin and other similar arid areas.

Assessment of vegetation cover changes and the contributing factors in the Al-Ahsa Oasis using Normalized Difference Vegetation Index(NDVI)

The abandonment of date palm grove of the former Al-Ahsa Oasis in the eastern region of Saudi Arabia has resulted in the conversion of delicate agricultural area into urban area.The current state of the oasis is influenced by both expansion and degradation factors.Therefore,it is important to study the spatiotemporal variation of vegetation cover for the sustainable management of oasis resources.This study used Landsat satellite images in 1987,2002,and 2021 to monitor the spatiotemporal variation of vegetation cover in the Al-Ahsa Oasis,applied multi-temporal Normalized Difference Vegetation Index(NDVI)data spanning from 1987 to 2021 to assess environmental and spatiotemporal variations that have occurred in the Al-Ahsa Oasis,and investigated the factors influencing these variation.This study reveals that there is a significant improvement in the ecological environment of the oasis during 1987–2021,with increase of NDVI values being higher than 0.10.In 2021,the highest NDVI value is generally above 0.70,while the lowest value remains largely unchanged.However,there is a remarkable increase in NDVI values between 0.20 and 0.30.The area of low NDVI values(0.00–0.20)has remained almost stable,but the region with high NDVI values(above 0.70)expands during 1987–2021.Furthermore,this study finds that in 1987–2002,the increase of vegetation cover is most notable in the northern region of the study area,whereas from 2002 to 2021,the increase of vegetation cover is mainly concentrated in the northern and southern regions of the study area.From 1987 to 2021,NDVI values exhibit the most pronounced variation,with a significant increase in the“green”zone(characterized by NDVI values exceeding 0.40),indicating a substantial enhancement in the ecological environment of the oasis.The NDVI classification is validated through 50 ground validation points in the study area,demonstrating a mean accuracy of 92.00%in the detection of vegetation cover.In general,both the user’s and producer’s accuracies of NDVI classification are extremely high in 1987,2002,and 2021.Finally,this study suggests that environmental authorities should strengthen their overall forestry project arrangements to combat sand encroachment and enhance the ecological environment of the Al-Ahsa Oasis.

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×10^(8)people,providing important ecosystem services for human survival and development.However,dryland ecosystems are extremely fragile and sensitive to external environmental changes.Land use and land cover(LULC)changes significantly impact soil structure and function,thus affecting the soil multifunctionality(SMF).However,the effect of LULC changes on the SMF in the drylands of China has rarely been reported.In this study,we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center.We explored the drivers of the SMF changes under different LULC types(including forest,grassland,shrubland,and desert)and used structural equation modeling to explore the main driver of the SMF changes.The results showed that the SMF under the four LULC types decreased in the following descending order:forest,grassland,shrubland,and desert.The main driver of the SMF changes under different LULC types was mean annual temperature(MAT).In addition to MAT,pH in forest,soil moisture(SM)and soil biodiversity index in grassland,SM in shrubland,and aridity index in desert are crucial factors for the SMF changes.Therefore,the SMF in the drylands of China is regulated mainly by MAT and pH,and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes.The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

Application of Cellular Automata and Markov Chain model for urban green infrastructure in Kuala Lumpur,Malaysia

Kuala Lumpur of Malaysia,as a tropical city,has experienced a notable decline in its critical urban green infrastructure(UGI)due to rapid urbanization and haphazard development.The decrease of UGI,especially natural forest and artificial forest,may reduce the diversity of ecosystem services and the ability of Kuala Lumpur to build resilience in the future.This study analyzed land use and land cover(LULC)and UGI changes in Kuala Lumpur based on Landsat satellite images in 1990,2005,and 2021and employed the overall accuracy and Kappa coefficient to assess classification accuracy.LULC was categorized into six main types:natural forest,artificial forest,grassland,water body,bare ground,and built-up area.Satellite images in 1990,2005,and 2021 showed the remarkable overall accuracy values of 91.06%,96.67%,and 98.28%,respectively,along with the significant Kappa coefficient values of 0.8997,0.9626,and 0.9512,respectively.Then,this study utilized Cellular Automata and Markov Chain model to analyze the transition of different LULC types during 1990-2005 and 1990-2021 and predict LULC types in 2050.The results showed that natural forest decreased from 15.22%to 8.20%and artificial forest reduced from 18.51%to 15.16%during 1990-2021.Reductions in natural forest and artificial forest led to alterations in urban surface water dynamics,increasing the risk of urban floods.However,grassland showed a significant increase from 7.80%to 24.30%during 1990-2021.Meanwhile,bare ground increased from 27.16%to 31.56%and built-up area increased from 30.45%to 39.90%during 1990-2005.In 2021,built-up area decreased to 35.10%and bare ground decreased to 13.08%,indicating a consistent dominance of built-up area in the central parts of Kuala Lumpur.This study highlights the importance of integrating past,current,and future LULC changes to improve urban ecosystem services in the city.

基于GEE的昆明市生态系统服务价值与生态风险变化

[目的]研究区域生态系统服务价值和生态风险变化及影响,为土地资源合理利用及国土空间生态修复提供决策支持。[方法]以Landsat遥感影像为数据源,使用GEE(Google Earth Engine)平台随机森林分类方法对云南省昆明市1990—2020年的土地利用变化信息进行提取,基于解译结果进行空间动态变化分析,采用当量因子法估算生态系统服务价值,运用生态风险模型揭示生态风险变化趋势,并借助双变量空间自相关模型计算二者的相关性。[结果]①1990—2020年,昆明市土地利用类型中林地和草地占地面积最大,建设用地面积明显增加,耕地、草地和林地面积减少。②昆明市生态系统服务价值总体呈逐年上升趋势,共上升3.08×108元,生态保护政策的有效实施对生态系统服务价值的提升有积极作用;研究期间生态风险以中、低风险为主,占总面积的79%,生态风险总体均值下降了0.12,城市经济发展与环境保护向良性态势发展。③生态风险对生态系统服务价值变化具有一定的影响。随着时间的推移,高价值—高风险区面积逐渐减少,低价值—低风险区面积逐渐增加,无明显极值。[结论]将区域生态系统服务价值和生态风险结合,能够较好地刻画昆明市人类活动所引起的生态环境状况的改变,为环境保护和高质量的可持续发展提供决策管理参考,有效防范生态风险,使昆明市经济发展与环境保护向良性态势发展。