时序InSAR技术在监测马村区地面沉降中的应用

本文利用Sentinel-1A SAR影像,通过小基线集(SBAS-InSAR)技术获取了马村区2016年10月26日至2019年3月9日地面沉降的年平均形变速率。监测结果表明,由于土地整治政策、人工开采以及矿区长期排水等因素的影响,马村区内存在多个沉降中心,其中最大沉降量达到-200 mm,最大形变速率达到-88 mm/a。通过建立剖面,提取并分析了张白河村、亮马村和新村附近沉降中心的沉降现状。     

南宁市地表形变InSAR监测及时空分析

基于Sentinel1-A数据,首先利用SBAS-InSAR(sat-ellite-based augmentation system-interferometric synthetic aperture radar)技术对南宁市区2017年12月至2019年1月的地表形变进行计算,获得研究区的地表形变速率图和累积形变量;其次,从Sentinel1-A卫星影像数据中选择6景影像进行差分干涉处理,提取5个时间段内的形变信息,并叠加分析得到总形变量;最后利用D-InSAR(differential-In-SAR)获得的形变结果对SBAS监测结果进行验证分析.结果表明:2017-2019年,南宁市地表形变极不均匀,其最大沉降速率约为23.52 mm/a,最大抬升速率约为17.77 mm/a;SBAS和D-InSAR所得监测结果总体上具有一致性,但局部存在一定差异.其中,SBAS方法提取的最大形变量约为31.55 mm,D-InSAR提取的最大形变量为39.93 mm.     

基于SBAS-INSAR技术的抚顺市矿区地表沉陷监测与分析

基于2019年1月13日至2019年6月6日期间获取的13景Sentinel-1SAR数据(VV极化),采用短基线集技术(SBAS)获取抚顺市矿区的地表形变信息.结果表明,抚顺市的矿区地面沉降较为严重,最大累计沉降量为138.929 mm,在老虎台煤矿和泰和煤矿.确定了抚顺市2019年1月至2019年6月内形变速率,最大形变速率为-199.961 mm/a,选择典型的4个位置绘制多时相形变速率变化图,采用常规四等水准控制点验证解算精度,结果表明SBAS-INSAR技术适用于矿区地表沉降监测和分析.     

黄土填方区地表沉降时序InSAR监测分析

“削山填沟造地”等岩土工程在湿陷性黄土沟壑地区屡见不鲜,掌握填方区沉降情况具有重要意义。本文收集了2017年11月—2020年12月获取的56景TerraSAR-X StripMap模式影像,利用时序InSAR技术监测了陕北某湿陷性黄土填方地基工程的沉降信息,并与2017年11月—2020年12月期间监测区3个水准点的沉降测量结果比对。结果表明,在填方区地表以沉降为主,在挖方区地表以抬升为主,研究区存在有1处较为明显的地表沉降情况,位于填挖边界线附近填方区内,形变速率范围为-40~-20 mm/a,最大形变速率达-49.9 mm/a,累计量为-151.6 mm,时序InSAR形变结果和实地水准结果吻合性较好,垂直方向形变速率中误差为1.8 mm/a,表明时序InSAR技术在湿陷性黄土填挖方区变形监测中具有较好的应用价值。     

基于PS-InSAR的深圳市地表形变监测研究

地面沉降具有区域性、累加性和不可逆性,会造成城市地面标高损失、城市内涝、建筑物受损等问题,In-SAR技术具有全天候、覆盖范围广、空间分辨率高等优点,可以进行长期的地表形变监测。本文利用PS-InSAR方法,结合2017年4月至2019年12月22景Sentinel-1A SAR数据,利用SARscape软件监测分析深圳市宝安区、南山区和福田区的地表形变情况,并根据形变速率的时间趋势进行地表形变分类。结果表明,研究区的年均形变最小值为-26.5 mm/a,形变平均值为-0.20 mm/a,沉降的时序结果可总结为持续抬升、持续沉降与先升后降3种形变类型,其中持续沉降区面积占比30.24%,主要分布在南山区,结合土地利用探讨了沉降类型的主要成因。     

利用SBAS时序技术识别地热资源开采引起的地表形变

本文以地热资源丰富的雄安新区为研究对象,利用SBAS技术对2015年7月至2019年2月的42幅Sentinel-1区域卫星影像和2016年8月至2018年12月的10幅ALOS-2区域卫星影像进行处理,以此获取雄安新区的时间序列地表形变。研究结果表明,雄安新区整体地表沉降严重,且沉降区主要集中在雄县和容城县,其中雄县沉降最为严重,沉降中心累计沉降量超过330 mm,容城县沉降中心累计下沉量超过120 mm。结合地热井位置和地热开采历史,由时间序列分析表明,大量开采地热资源会引起地表沉降现象。     

StaMPS技术在区域地表沉降形变监测中的应用

采用欧洲空间局环境监测卫星IW模式下Sentinel-1A VH极化影像数据,利用StaMPS技术,以惠东县为研究区域,选取区域内某个水准点(A)作为形变参考点,持续观测惠东县及城区重点区域2015-12～2018-02地表沉降形变,并对2019年解除的8个地质灾害点进行观测.实验表明惠东县东部山体部分有较明显沉降,最大形变速率达到-10 mm/y,城区部分及沿海部分有少量抬升,速率最大达到4 mm/y,累积最大沉降量达到-24 mm.城区重点区域地质情况较为稳定,部分区域形变基本在0～-2 mm/y,累积沉降量总体介于0～-4 mm,8个已解除的地质灾害点处于稳定状态.     

基于Landsat影像的北京市土地利用变化检测及驱动力研究

土地利用变化一直是城市化进展过程中的关键环节,有效检测城市土地利用变化,并对城市规划发展进行合理地统筹安排有着重要意义。本文利用1999年Landsat-7ETM影像和2017年Landsat-8OLI影像数据,结合遥感和GIS技术手段,采用最大似然监督分类方法,得到北京市1999-2017年间的土地利用变化数据。研究发现,近20年间北京市城市化进程明显,建筑用地面积由1999年1840.21km2增加到2017年3856.63km2;林地、农业用地等植被面积由1999年14013.18km2减少到2017年10701.22km2,土地利用变化转移明显,主要以植被覆盖区向建筑、裸地等城市用地转移为主,并且呈现明显的区域差异,以城区周边变化最为显著。最后,本文通过计算类型转移矩阵,对土地利用变化驱动因素进行了分析。     

基于不透水面的城市景观格局时空特征研究

土地利用/覆被变化是人类影响全球环境变化最直接的过程,城市作为人类文明的产物是该过程发生最剧烈的区域.客观、准确、及时的开展动态评估,有助于更好地认识城市的发展现状以及存在的问题.以哨兵影像为数据源,以西咸新区为研究区,通过转移矩阵和土地利用动态度等量化分析,研究了2016-2019年研究区景观格局的动态时空特征.主要研究结果为:①2019年新区各土地利用类型覆盖面积由大到小依次为植被、不透水面、裸地和水体,随着城市化的不断深入,植被面积在不断减少,不透水面面积在逐渐增加,2019年二者的面积占比分别为47.5％和42.6％;②以"绿色发展"为理念,以各新城地域特色和区位环境为基础,各新城的土地利用类型转移存在显著差异,2017年土地利用类型转移最剧烈,其中不透水面面积整体呈显著增加趋势,但沣东新城增加不显著,各新城的植被面积均有不同程度的减少,秦汉新城减少最显著但其植被总面积最大;③2016-2019年西咸新区的不透水面单一土地利用动态度为13.9％,面积显著扩张,其中以泾河新城和空港新城最为突出,分别为26.9％和37.2％;西咸新区的综合土地利用动态度为4.4％,各种土地利用类型转移频繁,综合利用度高,说明西咸新区正处于系统、全方位建设中.西咸新区的快速建设将成为陕西省经济社会发展的新增长点,为地区的人才引进、经济建设、社会进步提供动力,为陕西省丝绸之路的建设和影响辐射做出重要贡献.     

基于SBAS-InSAR技术和Sentinel-1A的城市地表沉降监测

基于SBAS-InSAR技术对覆盖研究区2017—2018年20景Sentinel-1A影像数据进行处理,得到研究区年沉降速率及时序形变信息,并与PS-InSAR结果进行对比验证,最后进一步分析了研究区沉降的成因.结果表明沉降主要发生在燕郊镇中部与西部区域,平均沉降速率超过20 mm/a,集中沉降区域平均沉降速率超过3...     

Environmental assessment and land change analysis in seminatural land covers applicable to land management

The present research is based on the hypertemporal analysis of a set of 212 images from the NDVI index from January 2003 to March 2012 provided by the medium-resolution sensor MODIS TERRA. The study area is located in the center of the Iberian Peninsula (Spain). The specific objectives of the study are to investigate the rhythms of the annual development of the NDVI of each of the classes, determine the classes that are most sensitive to climatic variability and define the interannual sequences of variation in NDVI with an associated trend analysis. The classes situated in lower-altitude areas are strongly dependent on autumn rainfall and present negative temporal tendencies, and those situated at mountaintops and on upper slopes are correlated with spring–summer temperatures and exhibit stable or positive tendencies.     

第三次国土调查的图斑自动综合方法

从第三次国土调查数据库快速缩编派生出多尺度数据库,是地图制图的重要任务。本文针对大量图斑,首先通过研究图斑栅格综合,减少碎图斑数量;然后构建图斑语义邻近度模型、空间几何拓扑模型,分析了顾及拓扑和地区地理特征约束下的地类图斑制图综合方法;最后形成了自动化图斑缩编生产工艺流程。基于上述方法,采用计算机编程技术研发国土三调缩编系统,并应用于四川省某县23万图斑量的三调数据并试验验证。试验结果表明,通过本文方法的成果符合专题制图要求,极大地提高了三调图斑的自动综合效率。     

Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes

Land surface temperature (LST), a key parameter in understanding thermal behavior of various terrestrial processes, changes rapidly and hence mapping and modeling its spatio-temporal evolution requires measurements at frequent intervals and finer resolutions. We designed a series of experiments for disaggregation of LST (DLST) derived from the Landsat ETM + thermal band using narrowband reflectance information derived from the EO1-Hyperion hyperspectral sensor and selected regression algorithms over three geographic locations with different climate and land use land cover (LULC) characteristics. The regression algorithms applied to this end were: partial least square regression (PLS), gradient boosting machine (GBM) and support vector machine (SVM). To understand the scale dependence of regression algorithms for predicting LST, we developed individual models (local models) at four spatial resolutions (480 m, 240 m, 120 m and 60 m) and tested the differences between these using RMSE derived from cross-validated samples. The sharpening capabilities of the models were assessed by predicting LST at finer resolutions using models developed at coarser spatial resolution. The results were also compared with LST produced by DisTrad sharpening model. It was found that scale dependence of the models is a function of the study area characteristics and regression algorithms. Considering the sharpening experiments, both GBM and SVM performed better than PLS which produced noisy LST at finer spatial resolutions. Based on the results, it can be concluded that GBM and SVM are more suitable algorithms for operational implementation of this application. These algorithms outperformed DisTrad model for heterogeneous landscapes with high variation in soil moisture content and photosynthetic activities. The variable importance measure derived from PLS and GBM provided insights about the characteristics of the relevant bands. The results indicate that wavelengths centered around 457, 671, 1488 and 2013–2083 nm are the most important in predicting LST. Nevertheless, further research is needed to improve the performance of regression algorithms when there is a large variability in LST and to examine the utility of narrowband vegetation indices to predict the LST. The benefits of this research may extend to applications such as monitoring urban heat island effect, volcanic activity and wildfire, estimating evapotranspiration and assessing drought severity.     

Spatial-temporal impacts of urban land use land cover on land surface temperature: Case studies of two Canadian urban areas

The surface fabric of urbanized areas, (i.e. its constituent land covers and land uses) plays an essential role in the generation of the urban/rural temperature differences, i.e. the Urban Heat Island (UHI) effect. Land surface information, derived from satellite imagery, and complementary information such as demographics can be used as the basis for an understanding of the atmospheric and surface thermal variations within cities. The results of comprehensive land surface characterizations of two major Canadian urban areas, the Greater Toronto Area and Ottawa-Gatineau, are described. Spatial information, including land cover fraction maps, land use and its historic changes, population density maps are compared with intra-urban surface temperature variations derived from satellite thermal imagery. Three aspects of the impacts of land cover and land use on urban land thermal characteristics are addressed, namely, (a) the relationships between surface temperature and subpixel land cover and population density (b) intra-city seasonal temperature variations and (c) the intensification of the urban heat island effect due to urban built-up land growth.     

GIS支持下土地生态环境敏感性评价——以金坛市为例

针对传统的生态环境敏感性评价指标体系差异较大,尚未形成统一体系,并且各个指标之间的关系及相互影响的情况并没有得到体现的问题,该文在地理信息系统的支持下,选取土地质量尺度的土地利用类型、土壤质地,及生态尺度的水环境、植被覆盖度、人口密度、坡度作为生态环境敏感性因子,同时建立了以水环境为主要因子的土地生态敏感性指数模型,对金坛市生态环境敏感性进行单因子评价和多因子综合评价。评价结果显示,金坛市生态高敏感区和中敏感区占到全市总面积的78%,低敏感区和不敏感区占到全市总面积的22%。针对不同土地生态敏感性分区因地制宜提出用地策略,为土地利用总体规划和城市生态保护提供参考。     

Application of remote sensing technology for land use/land cover change analysis

Land use/land cover changes over a period of 30 years were studied using remote sensing technology in a part of Gohparu block, Shahdol district of Madhya Pradesh. Land use/ land cover maps were prepared by visual interpretation of two period remotely sensed data. Post-classification comparison technique was adopted for this purpose. The loss of vegetation cover was estimated to be 22 percent and 14 percent of the land was found to have been tranformed into wasteland between 1967 and 1996. Overall rate of change was found to be 1.8 percent per year during this period.     

Remote sensing-derived national land cover land use maps: a comparison for Malawi

Reliable land cover land use (LCLU) information, and change over time, is important for Green House Gas (GHG) reporting for climate change documentation. Four different organizations have independently created LCLU maps from 2010 satellite imagery for Malawi for GHG reporting. This analysis compares the procedures and results for those four activities. Four different classification methods were employed; traditional visual interpretation, segmentation and visual labelling, digital clustering with visual identification and supervised signature extraction with application of a decision rule followed by analyst editing. One effort did not report classification accuracy and the other three had very similar and excellent overall thematic accuracies ranging from 85 to 89%. However, despite these high thematic accuracies there were very significant differences in results. National percentages for forest ranged from 18.2 to 28.7% and cropland from 40.5 to 53.7%. These significant differences are concerns for both remote-sensing scientists and decision-makers in Malawi.     

高精度建设用地变化自动提取技术在土地督察中的应用

为提高土地督察线索获取的快捷性和准确性,提出了一种基于稳定地物样本库的建设用地变化监测方法。首先,利用先验知识结合本底影像选取土地利用类型未发生变化的对象,形成稳定的地物样本库;然后,关联最新影像,动态筛选训练样本,实现建设用地变化自动监督分类;最后,基于先验知识对分类结果自动甄别,进行双重辅助变化信息提取,并利用相隔4个月的资源3号卫星数据开展对比试验。结果表明,该方法提取的建设用地变化位置准确率达72.82%(常规矢量监测法仅为33%),大大提高了违法用地位置信息发现的准确率,具有较高的可靠性和精度。     

Use of Landsat Thematic Mapper for urban land use/land cover mapping

Visual interpretation of Landsat Thematic Mapper data coupled with ground checking has been used to extract information for urban areas. The emphasis has been given on development of land use/land cover scheme and image interpretation keys for interpretation and delineation purposes using satellite remote sensing data. Lucknow city and its surroundings have been studied to evaluate the usefulness and potentiality of satellite data particularly Landsat Thematic Mapper for urban area studies. This study has demonstrated that remote sensing can provide a valuable tool for urban data acquisition.     

Effect of canal on land use/land cover using remote sensing and GIS

The monitoring of land use/land covers (LULCs) is an indispensable exercise for all those involved in executing policies to optimize the use of natural resources and minimize the ill impacts on the environment. The study here aims at analyzing the changes that occurred in LULC over a time span from 1990 to 2005 using multi date data of a part of Punjab. The digital data consisted of two sets of Landsat Thematic Mapper (TM) data and one set of IRS-1C data. Utilizing hybrid classification technique for interpretation and on field validation, it has been found that canal irrigation leads to changes in LULC as there is a change in cropping pattern as well as increase in water logged area.