基于Landsat影像的城市土地利用动态监测

土地是自然界不可或缺的资源,土地利用反映了人地关系。随着人口数量的持续增加和社会工业化、城市化的持续推进,如何科学地开发利用宝贵的土地资源越来越受到人们的重视。本文通过2013年和2023年的Landsat影像数据,结合遥感与GIS,对10年间合肥市土地资源进行监测与分析,结果表明,经过10年的城市发展,合肥市耕地面积减少了65707.92 hm 2,建设用地增长了39181.05 hm 2,林地减少了1728.27 hm 2,水域增加了28255.14 hm 2。

Spatiotemporal landscape pattern changes and their effects on land surface temperature in greenbelt with semi-arid climate:A case study of the Erbil City,Iraq

Urban expansion of cities has caused changes in land use and land cover(LULC)in addition to transformations in the spatial characteristics of landscape structure.These alterations have generated heat islands and rise of land surface temperature(LST),which consequently have caused a variety of environmental issues and threated the sustainable development of urban areas.Greenbelts are employed as an urban planning containment policy to regulate urban expansion,safeguard natural open spaces,and serve adaptation and mitigation functions.And they are regarded as a powerful measure for enhancing urban environmental sustainability.Despite the fact that,the relation between landscape structure change and variation of LST has been examined thoroughly in many studies,but there is a limitation concerning this relation in semi-arid climate and in greenbelts as well,with the lacking of comprehensive research combing both aspects.Accordingly,this study investigated the spatiotemporal changes of landscape pattern of LULC and their relationship with variation of LST within an inner greenbelt in the semi-arid Erbil City of northern Iraq.The study utilized remote sensing data to retrieve LST,classified LULC,and calculated landscape metrics for analyzing spatial changes during the study period.The results indicated that both composition and configuration of LULC had an impact on the variation of LST in the study area.The Pearson's correlation showed the significant effect of Vegetation 1 type(VH),cultivated land(CU),and bare soil(BS)on LST,as increase of LST was related to the decrease of VH and the increases of CU and BS,while,neither Vegetation 2 type(VL)nor built-up(BU)had any effects.Additionally,the spatial distribution of LULC also exhibited significant effects on LST,as LST was strongly correlated with landscape indices for VH,CU,and BS.However,for BU,only aggregation index metric affected LST,while none of VL metrics had a relation.The study provides insights for landscape planners and policymakers to not only develop more green spaces in greenbelt but also optimize the spatial landscape patterns to reduce the influence of LST on the urban environment,and further promote sustainable development and enhance well-being in the cities with semi-arid climate.

Assessing Spatio-Temporal Land Cover Changes in Dhund River Basin, Eastern Rajasthan (India), Using Multi-Temporal Landsat Data

Land cover is an impression of natural cover on surface of earth such as bare soil, river, grass etc. and utilization of these natural covers for various human needs and purposes by mankind is defined as land use. Land cover identification, delineation and mapping is important for planning activities, resource management and global monitoring studies while baseline mapping and subsequent monitoring is done by application of land use to get timely information about quantity of land that has been used. The present study has been carried out in Dhund river watershed of Jaipur, Rajasthan which covers an area of about 1828 sq∙km. The minimum and maximum elevation of the area is found to be 214 m and 603 m respectively. Land use and land cover changes of three decades from 1991 to 2021 have been interpreted by using remotes sensing and GIS techniques. ArcGIS software (Arc map 10.2), SOI topographic map, Cartosat-1 DEM and satellite data of Landsat 5 and Landsat 8 have been used for interpretation of eleven classes. The study shows an increase in cultivated land, settlement, waterbody, open forest, plantation and mining due to urbanization because of increasing demands of food, shelter and water while a decrease in dense forest, river, open scrub, wasteland and uncultivated land has also been marked due to destruction of aforementioned by anthropogenic activities such as industrialization resulting in environmental degradation that leads to air, soil and water pollution.

Landsat和GF数据面向对象土地覆盖分类研究

针对中分辨率遥感数据面向对象分类,以河北省北部山区和南部平原Landsat8 OLI,Landsat5 TM及高分一号(GF1)数据为研究对象,对支持向量机(support vector machine,SVM)、随机森林(random forest,RF)、决策树(decision tree,DT)及朴素贝叶斯(naive Bayes,NB)4种分类器的土地覆盖分类效果进行对比,并分析SVM,RF和DT中关键参数对分类结果的影响。结果表明:在2个研究区,各分类器结果略有差异,从整体上看其优劣排序为SVM,NB,RF和DT。其中SVM和DT分类精度随参数变化波动较大:对于SVM,当参数C取值不小于103且gamma不大于10^(-1)时,无论哪种情况其分类精度均优于90%;对于DT,当参数树深(Depth)大于3时,各情况下的分类精度相对较高且趋于稳定。RF分类精度随参数变化波动较小且没有明显的变化规律。研究结果可为中分辨率遥感数据面向对象土地覆盖分类研究提供参考。

Landscape ecological risk assessment and its driving factors in the Weihe River basin,China

Weihe River basin is of great significance to analyze the changes of land use pattern and landscape ecological risk and to improve the ecological basis of regional development.Based on land use data of the Weihe River basin in 2000,2010,and 2020,with the support of Aeronautical Reconnaissance Coverage Geographic Information System(ArcGIS),GeoDa,and other technologies,this study analyzed the spatial-temporal characteristics and driving factors of land use pattern and landscape ecological risk.Results showed that land use structure of the Weihe River basin has changed significantly,with the decrease of cropland and the increase of forest land and construction land.In the past 20 a,cropland has decreased by 7347.70 km2,and cropland was mainly converted into forest land,grassland,and construction land.The fragmentation and dispersion of ecological landscape pattern in the Weihe River basin were improved,and land use pattern became more concentrated.Meanwhile,landscape ecological risk of the Weihe River basin has been improved.Severe landscape ecological risk area decreased by 19,177.87 km2,high landscape ecological risk area decreased by 3904.35 km2,and moderate and low landscape ecological risk areas continued to increase.It is worth noting that landscape ecological risks in the upper reaches of the Weihe River basin are still relatively serious,especially in the contiguous areas of high ecological risk,such as Tianshui,Pingliang,Dingxi areas and some areas of Ningxia Hui Autonomous Region.Landscape ecological risk showed obvious spatial dependence,and high ecological risk area was concentrated.Among the driving factors,population density,precipitation,normalized difference vegetation index(NDVI),and their interactions are the most important factors affecting the landscape ecological risk of the Weihe River basin.The findings significantly contribute to our understanding of the ecological dynamics in the Weihe River basin,providing crucial insights for sustainable management in the region.

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.

Rainfall Dynamics and Landslides in Urban Areas of Gabon: The Case of Libreville-Est (Gabon)

Due to its abundant rainfall, the city of Libreville, which concentrates more than half of Gabon’s population, is frequently confronted with the impacts of natural disasters such as floods and landslides. This study attempts to identify the complex relationships between the dynamics of land use and the role of rainfall in the occurrence of landslides. On the one hand, it uses statistics on landslides compiled from information taken from general news bulletins and, on the other, daily rainfall data obtained from the National Meteorological Department. The study revealed that the Libreville East sector, dominated by Mount Nkol Ogoum, one of Libreville’s most prominent landforms, is affected by a land-use dynamic in which human settlement has been progressing for some thirty years, to the detriment of the original vegetation which, among other things, helped to stabilise the soil on the hillsides and the marshy areas at the foot of the slopes. The result is not only an uncontrolled occupation of the land, but also a major landslide every two years in this part of the city, causing significant loss of life and property. However, an analysis of the time series shows little rainfall variability, marked in particular by a predominance of negative anomalies, and the occurrence of a few exceptional daily rainfall peaks. Similarly, the period from 20 October to 20 November, which receives the most rainfall, also appears to be the most conducive to landslides.

基于Landsat8遥感影像的巢湖及周围地区土地利用变化研究

随着我国经济快速发展,人地矛盾日益突出,巢湖及周围地区作为安徽省中部的重要生态区和重要经济区,土地利用类型的变化影响着该区域的社会、政治、经济和生活。通过地理空间数据云官网获取Landsat8遥感影像数据,运用遥感技术(RS)和地理信息技术(GIS),针对研究区2017年、2019年和2021年三个时期的土地利用变化进行研究,分别从土地利用的变化幅度、土地利用的数量关系、土地利用动态度、土地利用程度分析研究区的土地利用类型的变化过程,分析该变化的驱动因子并提出对策,为今后该地区的经济建设和区域规划提供参考。

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

基于Landsat数据的衡阳市主城区热岛效应研究

由于城市化快速发展,致使城市热岛成为重要的城市生态环境问题之一。以衡阳市主城区为研究区,利用辐射传输方程法、均值-标准差、标准差椭圆分析和相关分析等方法,分析了2000年-2021年的地表温度和热岛效应的时空变化,并研究了NDVI指数与地表温度的相关性。结果表明:地表温度在2000年-2021年间高温集中分布在中心城区的湘江两岸,但随着时间的推移,逐渐向四周扩散;热岛分布存在三个时间段的规律性,以2004年、2009年为时间分割点;热岛的标准差椭圆的面积在扩大,且重心向西南方向移动;NDVI指数与地表温度呈现出明显的负相关关系。

基于Landsat8的凤永高速地表温度反演

在隧道建设过程中,高地温热害会影响机械设备效率和施工进度,还会恶化作业环境、对人员安全造成威胁,因此,精准识别地热异常区对隧道建设非常重要。热红外遥感是用遥感的方法探测地球表面的温度,以此为基础利用遥感技术反演地表温度愈发可靠。以云南省凤永高速凤庆-领岗地隧道为研究区域,采用Landsat8影像数据,运用大气校正法对研究区进行地表温度反演,再利用DEM数据制作地形坡向文件,按阳坡、阴坡分布提取地表温度,结合地质构造对地表温度异常进行分析,圈定地热异常区。

基于Landsat-8的湛江东海岛地物分类研究

“宝钢湛江项目”的实施对近十年湛江东海岛的地物分布产生剧烈影响,尤其是工业用地。本文基于2013年、2017年和2021年的陆地卫星8号(Landsat-8)数据对湛江东海岛进行地物分类,研究该区域近十年的用地变化趋势。以2013年数据为参照:采用归一化水体指数(Normalized Difference Water Index,NDWI)模型和谱间关系模型实现水陆分离,比对选择分离效果较优者以提取东海岛岸线;对比最大似然法、神经网络法和支持向量机法3种监督分类方法,选择提取地物效果最优者应用于其余数据。基于Google earth在线地图及无人机实测数据构建验证点集,使用混淆矩阵进行精度评价。结果表明:谱间关系模型的水陆分离效果较优,提取海岛岸线的精确度有明显提升;支持向量机法的分类总体精度和Kappa系数最高,分类结果能较好地反映研究区的真实地物分布;汇总三年数据的分类结果,发现用于发展工业的土地面积增长突出且处于持续增长趋势。谱间关系模型与支持向量机法分别实现了对东海岛岸线和地物类型的准确提取,得出近十年研究区的用地变化趋势,能为研究区的用地规划提供参考。

基于Landsat影像的雄安新区2013−2021年土地利用变化检测和生态政策评估

利用2013−2021年共9期Landsat8影像,采用面向对象的监督分类方法,得到新区逐年土地利用与覆盖分类结果,进行LUCC分析及生态品质评价.结论:1)分类结果总体精度>86.8%,K为0.81~0.88,优于同期FROM-GLC及GLC_FCS全球分类产品;2)雄安新区设立至今耕地面积减少,不透水面和林地面积增长,蓝绿空间面积占比由12%增加至30%,雄安3县(雄县、容城县和安新县)建设严格遵循了新区《规划纲要》中植树造林、城市发展、湿地涵养3项不同的建设任务,各县主要土地利用覆盖变化分别为耕地向林地的转变、耕地与不透水面的相互转变以及耕地向水体和水生植被的转变;3)不透水面扩张与城市建设对生态品质的负面影响正逐步被森林覆盖率、蓝绿空间面积增加带来的正面影响所抵消.总体看,雄安新区土地利用/覆盖变化遵循新区规划要求,体现了经济社会发展和生态建设的成果.

基于Landsat的环洞庭湖区湿地信息提取

大范围湿地信息的精细提取对湿地资源的管理和保护具有关键作用。基于GEE平台和ArcGIS软件,对Google云端提供的Landsat数据进行预处理后,分别采用最小距离、决策树、随机森林、迭代决策树4种不同类型的分类器提取环洞庭湖区域的湿地信息。主要研究结果如下:随机森林分类方法得出的分类结果的精度最高,总体精度(OA)为95.82%,Kappa系数为0.942;最终提取得到2015年环洞庭湖区湿地的各个地类中,水体(河流、湖泊、库塘)、苔草滩地、泥沙滩地、芦苇滩地的面积占比分别为6.385%、4.578%、0.418%、6.060%。研究结果可为大面积湿地的监测和分类工作提供更高效的技术支持和更可靠的数据保障。

Spatiotemporal detection of land use/land cover changes and land surface temperature using Landsat and MODIS data across the coastal Kanyakumari district, India

This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.

基于Landsat数据的城市热岛效应与LUCC关系研究

以Landsat-5和Landsat-8遥感影像数据为基础,通过地表温度反演和支持向量机分类法分别获得研究区城市热岛的空间分布和土地利用/覆盖变化数据,再利用ArcGIS对上述结果进行叠加分析。结果表明:城市热岛范围与强度随着时间变化呈上升趋势;土地利用/覆盖的变化在空间位置上会影响城市热岛效应;其中城市中建设用地与裸土地是导致热岛效应加剧的主要原因,而水系与植被对城市热岛效应有明显的抑制作用。

基于Landsat 8 TIRS地表温度数据反演的深圳城市热岛效应时空分布及土地利用的影响

基于2014~2021年Landsat 8 TIRS卫星遥感影像数据,分别采用劈窗算法(SWA)和大气校正法(ARC)反演了深圳市地表辐射温度,并利用地面站点监测数据对反演结果进行了验证,探讨了该期间深圳城市热岛效应的时空分布特征及其影响因素。研究结果表明,这两种算法反演的地表温度(TSWA、TARC)与地面站点监测气温(TM)都存在显著线性相关(TSWA=1.01×T_(M)+2.65,TARC=0.85×T_(M)+5.51,p<0.01),但劈窗算法更接近地面站点监测数据。在2014~2021年间深圳城市热岛面积(HI>0.01)未观察到显著增加的趋势(p=0.94)。深圳市城市热岛分布与城市发展格局关系密切,城市规划用地类型对城市热岛效应有显著影响。生态水域和生态绿地缓解了城市热岛效应,而交通道路和工业仓储等城市用地强化了城市热岛的形成,并且城市路网的分布和密度对城市热岛的形成有强显著性影响(p=0.003)。

基于Landsat影像的合肥市地表温度空间特征分析

文章以合肥市为例,选择2008—2020年内5期Landsat影像,对包河区、蜀山区、庐阳区、瑶海区4个行政区进行地物分类与地表温度反演;采用地理加权回归(geographically weighted regression,GWR)模型与标准差椭圆(standard deviational ellipse,SDE)分别分析不透水层对地表温度的影响程度及其空间分布演化特征。在500 m格网化划分尺度下,4个行政区不透水层与地表温度的GWR全局拟合系数R^(2)基本上大于0.8,其中包河区与庐阳区的R^(2)随时间变化相对稳定,而蜀山区与瑶海区的R^(2)增加,不透水层变化显著;2008—2020年,不透水层对应SDE演化趋势与对应城区扩张趋势基本一致,椭圆面积呈增长趋势,这与合肥市由以主城区为主的发展模式变为多地区共同发展模式相关。研究结果可为合肥市未来城市规划提供参考。

Landsat新型热红外地表温度产品与MODIS地表温度产品的交互对比

美国地质调查局(USGS)2020年12月正式发布了基于Landsat热红外光谱数据生产的2级地表温度产品(Landsat Collection 2 Level-2 surface temperature,LC2L2ST),但目前还鲜有该地表温度产品的相关研究报道。由于美国地质调查局已宣布自2022年开始将不提供除该产品之外的其他地表温度数据,因此有必要对该产品进行适时的评估。在同类遥感卫星产品中,MODIS地表温度产品的质量最被广大用户认可,应用也最为广泛,因此首次将Landsat新型热红外地表温度产品与MODIS地表温度产品进行交互对比,以评估新产品与MODIS地表温度产品的一致性。分别选取了我国的不同地区(福州、太湖、银川、敦煌)作为试验区,以20对同日过空的LC2L2ST与MODIS地表温度影像为数据源进行交互对比。影像涵盖植被、水体、建筑、荒漠等地物以及不同的季节。在试验区影像上选取一系列均质样区(ROI),通过各样区的地表温度均值散点进行拟合回归分析,研究二者地表温度间的差异及定量关系,并提出彼此转换的模型。结果表明,Landsat地表温度新产品与MODIS地表温度产品具有很高的相关性,4个试验区的决定系数(R^(2))皆大于0.98,集成4个试验区的总R^(2)也接近0.98;但LC2L2ST比MODIS的地表温度平均高0.90℃(RMSE=2.29℃)。分析发现,二者地表温度数据间的差异与其在空间分辨率、观测角度、地物类型和季节的不同有关。从不同地物和季节来看,LC2L2ST在晚秋和冬季略低于MODIS的地表温度,而在夏季极端高温的城镇、荒漠地区则明显高于MODIS的地表温度,且偏差可近7℃。总的看来,Landsat新型地表温度产品与MODIS同类产品的相关性显著,但在夏季的城市和沙漠地区的差异较大,因此,LC2L2ST新产品在夏季高温季节的适用性仍有待进一步基于地面实测温度的验证。鉴于两种地表温度数据产品仍存在着一定差距,因此二者如要协同使用,需要进行转换。本研究基于4个试验区的560个ROI样区构建了二者地表温度间的转换方程,并通过验证发现,经转换后的两数据差异性得到大幅缩小。因此,必要的数据转换有利于二者数据的协同使用,可为长时间序列的地表温度变化监测提供连续的遥感数据。

Understanding the Relationship Between Shrinking Cities and Land Prices:Spatial Pattern,Effectiveness,and Policy Implications

Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land,particularly in terms of land use and price.This study focuses on 2851 county-level cities in China in 2005–2018(excluding Hong Kong,Macao,Taiwan,and‘no data’areas in Qinhai-Tibet Plateau)as the fundamental units of analysis.By employing nighttime light(NTL)data to identify shrinking cities,the propensity score matching(PSM)model was used to quantitatively examine the impact of shrinking cities on land prices,and evaluate the magnitude of this influence.The findings demonstrate the following:1)there were 613 shrinking cities in China,with moderate shrinkage being the most prevalent and severe shrinkage being the least.2)Regional disparities are evident in the spatial distribution of shrinking cities,especially in areas with diverse terrain.3)The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels.4)Shrinking cities significantly negatively impact on the overall land price(ATT=–0.1241,P<0.05).However,the extent of the effect varies significantly among different spatial regions.This study contributes novel insights into the investigation of land prices and shrinking cities,ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.