Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province,Iran

The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not being scanned and has seriously limited the scientific applications of ETM+ data. A number of methods have been developed to fill the gaps in the incorrect images. Most of these methods have problems in heterogeneous landscapes. We applied and validated a simple and effective gap-fill algorithm developed by the US Geological Survey to a study area in the Golestan Province in the north of Iran. This algorithm operates under the assumption that the same-class neighboring pixels around the unscanned pixels have similar spectral characteristics, and that these neighboring and unscanned pixels share patterns of spectral differences between dates. For validation, unsupervised land use classification was performed on both gap-filled SLC-off data and the original “sound” data set. Classification results and accuracies were very comparable.     

Landsat8卫星数据在安徽黄山汤口-寨西地热资源调查中的应用

遥感大数据分析与应用正成为地球信息科学领域重要的研究内容。利用热红外遥感技术进行地热异常信息的提取可以为地热资源勘查评价提供重要的依据。Landsat系列卫星数据拥有长时间的数据积累和较高的空间分辨率,是地表热环境时空序列大数据分析的重要数据。最新一代的Landsat8 卫星热红外数据在延续了较高分辨率的同时,敏感性更强,更加适合于对地表热环境空间分布进行精确分析。本文以安徽黄山汤口-寨西工作区为研究区,分别选用2016年12月9日Landsat8 的热红外遥感数据和2009年12月6日Landsat5 TM 数据,采用大气校正方法进行地表温度的反演和对比分析,通过密度分割分析提取地热异常信息,并综合遥感地质解译信息、气象、地形等数据,对工作区地热资源有利区进行了预测。结果表明：两个时相地表温度反演结果的空间分布基本一致,利用Landsat8 热红外数据的地表温度反演结果可以有效地获取地热异常信息,所圈定的地热异常较为合理,与工作区内主要的断裂构造分布一致,且和物探勘查和钻孔实验结果相对应,可以为地热资源勘查大数据分析提供重要的数据源。     

Effects of land use change on landscape pattern of the Manas River watershed in Xinjiang, China

The mechanism of interaction between land use change and landscape pattern is pivotal in research concerning global environmental change. Quantitative evaluation of land use change that has resulted from excessive land development and its impact on landscape pattern are important for sustainable utilization of local land resources. The study area was the Manas River watershed, a typical watershed in an arid area. The present study evaluated the influence of long-term land use change on the landscape pattern; the findings are valuable for economic development and environmental protection. The processes for land use change and changes in landscape pattern were reconstructed and analyzed for data in topographic maps dated 1962 and in remote sensing images taken in 1976, 1989, 1999 and 2008 using mathematical models and landscape metrics. The results indicate significant changes in land use over the past 50 years, with increases in the areas of cultivated land and construction land, and a significant decrease in unused land and woodland areas; grassland and water resources first increased and then tended to decrease over this time. The comprehensive index of land use change is 0.55, indicating an unbalanced, one-way transition in the study area. Landscape fragmentation and diversity increased and landscape dominance decreased; in other words, differences between landscapes decreased. The changes resulted in a significant tendency toward diversity and fragmentation of the landscape. Therefore, large-scale intensive agricultural development can reduce the negative influence of land use change on the landscape pattern.     

基于面向对象分类技术的雅砻江流域地表信息提取与分析

雅砻江是川西最重要的河流之一,雅砻江流域内的土地利用情况与流域内的生态环境及河流水质密切相关。以Landsat 8 OLI遥感影像为数据源,采用面向对象的分类方法,建立分类规则,获取研究区的土地利用情况,利用Fragstats 4.2软件进行区域景观空间分布特征分析。结果表明:采用面向对象的分类方法的分类总体精度达到8711%,Kappa系数达到0.855。雅砻江流域内的区域整体景观连接性较好。草地和林地是研究区的主导类型,整体看分布较为集中。     

基于RS、GIS的人口空间分布研究

人口的空间分布问题涉及人口学、经济学、地理学等多个学科,统计型人口数据的空间化是"数字地球"的重要研究内容。阐述了人口地域分布的基本理论,回顾了人口空间分布的研究进展,结合研究实践,提出了在遥感、GIS技术支持下,统计型人口数据空间化的研究思路和技术流程,并对该方法的特点和应用前景做了展望。     

Groundwater vulnerability and risk mapping in a geologically complex area by using stable isotopes, remote sensing and GIS techniques

Groundwater vulnerability and risk mapping is a relatively new scientific approach for facilitating planning and decision making processes in order to protect this valuable resource. Pan European methodology for aquifers vulnerability has recently been developed by assessing all the existing relevant techniques and emphasizing on karstic environments. In the particular study, state-of-the-art methods and tools have been implemented such as remote sensing, isotopic investigations and GIS to map the groundwater vulnerability and pollution risk in a geologically complex area of W. Greece. The updated land use map has been developed from a Landsat 7+TM image elaborated with image analysis software, while the detailed hydrogeologic properties of the area have been recorded with an intensive isotopic study. The local groundwater vulnerability map has been produced following the aforementioned Pan European method, in a GIS environment while the risk map, which was the final product of the study, has been developed after combining the vulnerability and the land use maps. The results indicated that the areas comprised of highly tectonized calcareous formations represented high vulnerability and risk zones while forested areas away from the karstic aquifer illustrated moderate to low vulnerability. Moreover, human activities increase the pollution risk in lowland areas consisting of sedimentary deposits that have been classified as moderate vulnerability. The particular methodology operated efficiently in this study and due to its accuracy and relatively easy implementation can be used as a decision support tool for local authorities.     

Morphometric classification of the biosphere reserve “Eastern Carpathians” (Central Europe) with self-organizing map

In this paper, we propose a semiautomatic method for landscape analysis of biosphere reserve Eastern Carpathians with both spectral and morphometric constituents. The Shuttle Radar Topography Mission (SRTM) has provided digital elevation models for approximately 80 % of the earth’s land surface. SRTM data are used to calculate first derivatives (slope) and second derivatives of elevation (such as minimum curvature, maximum curvatures, and cross-sectional curvature) by fitting a bivariate quadratic surface with a window size of 9 by 9. Together with multispectral remote sensing data like Landsat 7 ETM+ with 28.5 m raster elements, these data provide comprehensive information for the analysis of the landscape in the study area. Unsupervised neural network algorithm—self-organizing map—divided all input vectors into inclusive and exhaustive classes on the basis of similarity between attribute vectors. An optimal self-organizing map with 21 classes using 1,000 iterations and a final neighborhood radius of 0.05 provided a low average quantization error of 0.3394 and was used for further analysis. Morphometric analysis, spectral signature analysis, and feature space analysis are used to assign semantic meaning to the classes as landscape elements according to form, cover, and slope, e.g., deciduous forest on ridge (convex landform) with steep slopes. The results revealed the efficiency of self-organizing map to integrate SRTM and Landsat data for landscape classification. This makes it possible to develop an alternative method for fast assessment and comparison of landscapes over large areas. This procedure is reproducible for the same applications with consistent results.     

遥感结合地面观测估算陆地生态系统蒸散发研究综述

地面观测和遥感模拟作为陆地生态系统蒸散发研究的2种基本手段,有着各自的优缺点且存在互补性。因此,有效地将遥感和地面观测站点资料相结合,探讨陆地生态系统蒸散发的时空分布规律及不同尺度转换理论与方法,实现蒸散耗水地面观测结果的尺度扩展和生态需水量估算成为普遍关注的焦点。从遥感与地面观测结合确定陆地生态系统蒸散发入手,论述目...     

黑河流域遥感—地面观测同步试验：科学目标与试验方案

介绍了黑河流域遥感-地面观测同步试验的科学背景、科学问题、研究目标以及观测试验方案和观测系统布置.总体目标是,开展航空-卫星遥感与地面观测同步试验,为发展流域科学积累基础数据;发展能够融合多源遥感观测的流域尺度陆面数据同化系统,为实现卫星遥感对流域的动态监测提供方法和范例.以具备鲜明的高寒与干旱区伴生为主要特征的黑河流域为试验区,以水循环为主要研究对象,利用航空遥感、卫星遥感、地面雷达、水文气象观测、通量观测、生态监测等相关设备,开展航空、卫星和地面配合的大型观测试验,精细观测干旱区内陆河流域高山冰雪和冻土带、山区水源涵养林带、中游人工绿洲及天然荒漠绿洲带的水循环和生态过程的各个分量;并且以航空遥感为桥梁,通过高精度的真实性验证,发展尺度转换方法,改善从卫星遥感资料反演和间接估计水循环各分量及与之密切联系的生态和其他地表过程分量的模型和算法.由寒区水文试验、森林水文试验和干旱区水文试验,以及一个集成研究--模拟平台和数据平台建设组成.拟观测的变量划分为5大类,分别是水文与生态变量、驱动数据、植被参数、土壤参数和空气动力参数.同步试验在流域尺度、重点试验区、加密观测区和观测小区4个尺度上展开.布置了加密的地面同步观测、通量和气象水文观测、降雨、径流及其他水文要素观测网络;使用了5类机载遥感传感器,分别是微波辐射计、激光雷达、高光谱成像仪、热红外成像仪和多光谱CCD相机;获取了丰富的可见光/近红外、热红外、主被动微波、激光雷达等卫星数据.     

The propagation mechanism of an oblique straight crack in a rock sample and the effect of osmotic pressure under in-plane biaxial compression

The objective of this paper is to analyze land use change on Daishan Island using a multi-temporal remote sensing imagery. Four Landsat optical remote sens     

A monitoring framework for land use around kaolin mining areas through Landsat TM images

Sustainable management of land requires regular acquisition of qualitative information regarding the status of its use. It is especially important to track the changes relating to the land’s competitive development needs such as mining. The field-based monitoring of a mine with a wide footprint is expensive and time-consuming. Remote sensing techniques have been developed and demonstrated as cost-effective alternatives for the conventional methods of land use/land cover (LULC) monitoring. In this study, the land cover changes that occurred between the year of 2000 and 2009 in a kaolin mining and processing area in the Kutch region of India are mapped using two Landsat-5 Thematic Mapper (TM) images. For this purpose, the spectral signature of the land covers including vegetation cover and kaolin were determined and matched filtering (MF) method was applied to classify the images. The overall accuracy of the classified 2009 image was estimated for the kaolin and the vegetation cover to 89.5 and 86.0 % respectively. The change in the land use which occurred from 2000 to 2009 were quantified and analysed for both classes. This study provided a practical framework for rapid mapping of the land cover changes around open-cut kaolin mining area using freely available Landsat data.     

Assessment of land-use change and its impact on the environment using GIS techniques: a case of Kolkata Municipal Corporation,West Bengal,India

It is axiomatically true that urbanization in India's metropolises and large cities has been exacerbated since the beginning of the millennium, consuming the natural and semi-natural ecosystem on the outskirts of the city, resulting in a zone with a distinct climate known as urban climate. Such a climate—the result of a built-up environment is distinctly different from the natural climate as the paved surface and concrete skyscrapers not only destroy the natural ecosystem, it peculiarly induce a different kind of insolation, cooling and air drainage were lacking in green space, water bodies and open space cannot accommodate with environmental rhythm properly, resulting into the accumulation of heat, ecological derangement of subsurface soil which can easily be predicted by GIS analysis. This paper is an attempt to measure urban growth and its impact on the environment in the metropolitan city Kolkata. The use of satellite data and GIS techniques to detect urban expansion is a highly scientific strategy. Using geospatial techniques, the current study attempts to examine major urban changes in Kolkata and its surroundings from 1988 to 2021. Landsat 5 TM and Landsat 8 OLI temporal data are used to identify land-use change through unsupervised classification; Spectral Radiance Model and Split Window Algorithm method are used for identifying land surface temperature change. SRTM DEM (30 m) has been used to identify flood risk zones and several spectral indices like Normalized Difference Vegetation Index and Modified Normalized Difference Water Index are a further extension for environmental assessment. By all such suitable methods, a clearer change in an urban environment is detected within the period of 33 years (1988–2021). The result shows that the population changes, vegetation cover and built-up area, and accessibility are at a rapid rate. These changes are causing major environmental degradation in the city. The classification result indicates that appropriate land use planning and environmental monitoring are required for the long-term exploitation of these resources.

     

Temporal merging of remote sensing data to enhance spectral regolith,lithological and alteration patterns for regional mineral exploration

Remote sensing has been widely used to map geological structure, regolith materials and hydrothermal alteration minerals in different regions of the world, based largely on the spectral characteristics of clay/carbonate and iron oxide minerals. Given that features related to minerals may form very subtle patterns in Landsat imagery, finding suitable methods for enhancing the spectral information due to alteration minerals has been the subject of much research since the satellites were launched. Although multispectral sensors such as Landsat do not have enough spectral resolution to distinguish between specific minerals, effective processing of the data does yield useful images for regional exploration and targeting when combined with a good understanding of the associated landforms. ASTER and various airborne systems can now provide useful, high-resolution mineral information. However, the cost and time taken to acquire and process good resolution spectral data should now be balanced against the enhanced spectral discrimination possible using temporal merging, or data stacking, from the existing Landsat data archive dating back to 1972. One critical characteristic of the spectra related to surface mineral composition is its persistence over time. This study proposes a further enhancement to the data using temporal merging to create images that are both easier to interpret, and more reliable indicators of lithology and alteration. The new approach is to select a large number of scenes, typically separated by two or more years, and to merge the data for each band to give a cumulative spectral signature. The technique of stacking Landsat data to create a new dataset with much greater spectral depth is termed Landsat TM3, or Landsat TM Temporal Merge for Terrain Mapping. This emphasises not only the process used to create the dataset, but also the dominant use to which these data are ideally suited, namely mapping geological and mineral-related terrains.     

Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island,Malaysia

Land surface temperature (LST) plays an important role in local, regional and global climate studies. LST controls the distribution of the budget for radiation heat between the atmosphere and the earth’s surface. Therefore, it is important to evaluate abrupt changes in land use/land cover (LULC). Penang Island, Malaysia has been experiencing a rapid and drastic change in urban expansion over the past two decades due to growth in industrial and residential areas. The aim of this study was to investigate and evaluate the impact of LST with respect to land use changes in Penang Island, Malaysia. Three supervised classification techniques known as maximum likelihood, minimum distance-to-mean and parallelepiped were applied to the images to extract thematic information from the acquired scene by using PCI Geomatica 10.1 image processing software. These remote sensing classification techniques help to examine land-use changes in Penang Island using multi-temporal Landsat data for the period of 1999–2007. Training sites were selected within each scene and seven land cover classes were assigned to each classifier. The relative performance of each technique was evaluated. The accuracy of each classification map was assessed using a reference data set consisting of a large number of samples collected per category. Two Landsat satellite images captured in 1999 and 2007 were chosen to classify the LULC types using the maximum likelihood classification method, determined from visible and near-infrared bands. The study revealed that the maximum likelihood classifier produced superior results and achieved a high degree of accuracy. The LST and normalised difference vegetation index (NDVI) were computed based on changes in LULC. The results showed that the urban (highly built-up) area increased dramatically, and grassland area increased moderately. Inversely, barren land decreased obviously, and forest area decreased moderately. While urban (minimally built-up) area decreased slightly. These changes in LULC caused at significant difference in LST between urban and rural areas. Strong correlation values were observed between LST and NDVI for all LULC classes. The remote sensing technique used in this study was found to be efficient; it reduced the time for the analysis of the urban expansion, and it was found to be a useful tool to evaluate the impact of urbanisation with LST.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.     

基于多尺度遥感数据估算地表通量的方法及其验证分析

地表水热通量(显热通量、潜热通量)的遥感估算在全球气候变化、水资源、生态环境等研究领域具有重要的应用价值.MODIS数据的空间分辨率较低(热红外波段星下点为1 km),而地球表面的几何物理属性又具有高度非均匀性,因而在实际应用中面临较严重的尺度问题.探讨了多源卫星数据(中高分辨率Landsat TM与中低分辨率MODIS)相结合佑算像元通量的2种方法,分别利用高分辫率的地表分类及植被指数信息在混合像元内部进行亚像元处理,以提高非均匀地表混合像元的通量估算精度.研究数据来自于2008年黑河流域综合实验获取的遥感数据和辅助数据,验证数据来自于实验期间获取的不同下垫面的地表通量数据,包括涡度相关(EC)数据,以及大孔径闪烁仪(LAS)数据.计算结果表明,2种方法皆可在下垫面不均匀或者地表类型较复杂的情况下得到比较明显的纠正效果,纠正后的通量与观测更加接近.相比之下,利用植被指数分解温度的方法适用性更广,纠正效果更好.在地面验证中,对比分析了EC和LAS数据在TM尺度和MO-DIS尺度通量验证的适用性.LAS数据测量尺度与MODIS卫星像元尺度相匹配,可以直接验证MODIS通量计算结果,EC数据虽然可以直接验证TM计算的通量,但与MODIS数据对比,还需要进行尺度转换,即先用EC验证TM通量,然后将TM通量降尺度,与MODIS进行对比.最后对利用LAS验证通量的不确定性进行了分析,发现图像中LAS测点的几何定位误差以及LAS测量路径中像元的选取都对验证结果有一定影响.     

中亚干旱区陆地水资源评估方法与挑战

集中回顾中亚干旱区陆地水资源评估手段进展.水资源评估手段主要可分为基于观测数据和水文模型模拟两大类.从数据获取手段来讲,站点实测、遥感、再分析数据是目前中亚水资源评估的主要数据来源.其中,遥感数据又可分为成像遥感数据以及非成像遥感数据(包括雷达高度计、重力卫星数据).由于干旱区站点资料缺乏,遥感与水文模型集成已经成为常...     

Analysis of urban growth using Landsat TM/ETM data and GIS—a case study of Hyderabad, India

Hyderabad is one of the fastest growing mega cities in India and it is facing many economic, social and environmental problems due to rapid urban growth. For the better planning of resources and to provide basic amenities to its residents, it is necessary to have sufficient knowledge about its urban growth activities. Also, it is necessary to monitor the changes in land use over time and to detect growth activities in different parts of the city. To accomplish these tasks with greater accuracy and easiest way, remote sensing and geographic information system (GIS) tools proved to be very advantageous. This study makes an attempt towards the mapping of land use classes for different time periods and analysis of apparent changes in land use using the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for the urban agglomeration of Hyderabad, India. In this study, three different time periods viz. 1989–2000, 2000–2005 and 2005–2011 are chosen for the analysis. The results have shown that high-density urban area had grown during 1989–2011 by encroaching into other land use classes. The urban growth has also affected water resources both, qualitatively and quantitatively in the region. The transformation of other land use types into urban area dynamically continued in the North-East and Southern parts of the city. In the North-East direction, the urban growth was mostly due to growth in industrial and residential area and in Southern part, mostly due to residential growth.     

Understanding land-use/cover change process for land and environmental resources use management policy in Ghana

Accurate information on land-use/cover change is a critical input for natural resource use management policy decisions. In Ghana, however, land-use/cover change is premised on the assumption that there has been a historically simple, linear, and uniform degradation of vegetation across all landscapes. The Kintampo and neighboring districts have become a subject of intense debate as to the real nature of prevailing land cover changes .It is commonly assumed that there is ubiquitously progressive irreversible woody vegetation loss across the area. The paper reports on the process and amount of land-use/cover changes that have prevailed in specific localities across the area within a 10-year period. It is hoped this will improve understanding and management of land-use/cover change in Ghana. Remote sensing and Geographic information systems technologies were used for the investigation. A multi-site satellite imagery approach was adopted to ensure that inductive inferences could be made. The outcome of the study indicated that, in space and time, there have been significant land-use/cover changes. Variability in change was a constant, rather than occasional feature across these human dominated landscapes. The conversion and transformation processes indicated that the traditional land-use strategies are self-sustaining. Any effective land-use/cover management strategy should be built upon the existing traditional farming system knowledge and practices.