Combined Radar and Landsat data analysis for land use/cover studies over parts of the Punjab plains

L-band (HH) synthetic aperture radar imagery from Shuttle Imaging Radar-B (SIR-B) and Landsat multispectral scanner (MSS) images over parts of the Punjab plains were combined in order to utilize the complementary information contained in multispectral data sets. Among the various combination of Landsat MSS with SIR-B, the combination of Landsat MSS band 5 (0.6–0.7 μm) and band 7 (0.8–1.1 μm) with SIR-B data was found to be optimum in delineating landcover units. The integrated data was found to be superior in providing landcover information in comparison to SIR-B alone or a combination of landsat MSS band 4,5 and 7.     

Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India

Estimation and monitoring of crop evapotranspiration (ET_c) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ET_c by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ET_c was estimated 2.72 and 2.47 in mm day^?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ET_c.     

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.     

加入地物倾角分析的LiDAR回波强度校正

LiDAR回波强度数据的校正处理可以提升其在地物分类识别方面的利用价值。本文研究发现倾斜地物(如三角形、拱形房顶等)的自身倾角会改变激光反射角进而影响回波强度,而现有归一化校正模型缺乏对地物倾角的计算分析。随后结合LiDAR数据的采集方式和特点,以及倾斜地物的结构特征,提出了一种加入地物倾角计算的改进型归一化校正算法。首先,对激光点的回波强度值进行基于传输距离值的初步校正;然后,以平面距离值、高程、回波强度值差异为参考,判定激光点是否属于同一倾斜地物,若满足条件,则计算出激光点的趋势角,并依据制定的判定规则确定趋势角的正负;最后,将趋势角计算结果与扫描角数值结合计算出对应的反射角,并重新对回波强度值进行计算校正。实验表明,蓝铁皮材质的三角形、拱形房顶的回波强度值范围和均方差缩小,且采集的8种地物样本的回波强度均值的差异性与激光反射率测量结果基本一致,说明该算法能够有效识别具有一定面积且材质均一的倾斜人工地物并计算修正其自身倾角对回波强度带来的影响,从而进一步提高基于回波强度值的地物可分性。     

Change of river channel and bank erosion of the burhi dihing river (assam), assessed using remote sensing data and gis

The Burhi Dining river flows in a meandering course for about 220 km through alluvial plains of Assam including a short rocky and hilly tract in between. Sequential changes in the position of banklines of the river due to consistent bank erosion have been studied from Survey of India topographic maps of 1934 and 1972, and digital satellite data of 2001 and 2004 using GIS. Two broad kinds of changes have been observed, e.g. alteration of direction of flow due to neck cut-off and progressive gradual change of the meander bends that accounts for translational, lateral, rotational, extensional and other types of movement of the meander bends. Study of bankline shift due to the bank erosion has been carried out for the periods 1934–1972, 1972–2001, 2001–2004 and 1934–2004 at 13 segments spaced at 5′ longitude interval (average 15 km) as the river course trends nearly east to west. The amounts of the bank area lost due to erosion and gained due to sediment deposition are estimated separately. The total area eroded in both banks during 1934–1972 was more (26.796 km²) as compared to sediment deposition (19.273 km²), whereas total sediment deposition was more (34.61 km²) during 1972-2001 as compared to erosion (23.152 km²). Erosion was again more in 2001–2004 (7.568 km²) as compared to sediment deposition (2.493 km²). During the entire period (1934–2004) of study the overall erosion on the both banks was 31.169 km² and overall sediment deposition was 30.101 km². The highest annual rates of bank erosion as well as bank building of the river are 21055.47 m²/km in 2001–2004 and 9665.81 m²/km in 1972-2001, respectively. Similarly the highest average annual rates of erosion as well as sediment deposition in both banks are observed during 2001–2004 and 1972–2001, respectively. The hard rocks of the hilly tract situated in between result in development of entrenched meandering and this tract has suffered minimum bank erosion.     

Forest cover and landuse mapping in Karbi Anglong and North Cachar Hills districts of assam using landsat MSS data

Karbi Anglong and North Cachar Hills districts of Assam are endowed with rich and diverse vegetation resources. Increased human pressure due to shifting cultivation and raw material extraction for industrial purposes are heavily altering the forested landscape. The present study deals with mapping of forest types in the two districts using LANDSAT-MSS digital data. The maps thus generated provide spatial distribution of bioclimatic vegetation types. Supervised maximum likelihood classification has been performed using training sets collected during field work. The spectral behaviour of vegetation types have been studied for optimising classification scheme. The classification accuracy of classes mapped has been calculated.     

利用验潮站资料的中国近岸海潮模型精度评估

针对全球海潮模型在我国近海海域精度较差的问题,该文采用中国沿岸30个长期验潮站的调和常数,对比了3种全球海潮模型DTU10、TPXO7.2、NAO.99b和1个区域海潮模型NAO.99Jb在中国沿岸的准确度。通过海潮模型与验潮站分潮的振幅中误差、迟角中误差以及8个主要分潮的预报误差,对渤海、黄海、东海和南海北部进行了详细的分析。结果表明,NAO.99Jb在中国海域精度最高,NAO.99b次之。在渤海海域,DTU10在Q_1分潮精度最高,NAO.99b在K2分潮精度最高,其余分潮均是NAO.99Jb精度最高;在黄海海域,NAO.99b在Q_1分潮精度最高,其余分潮均是NAO.99Jb精度最高;在东海海域,DTU10在Q_1分潮精度最高,TPXO7.2在P1精度最高,NAO.99Jb在O1、M2分潮精度最高,其余分潮均是NAO.99b精度最高;在南海北部海域,DTU10在N2、S2分潮精度最高,其余分潮均是NAO.99Jb精度最高。     

基于夜光遥感数据的中原城市群建成区时空变化分析

本文基于“类NPP-VIIRS”夜光遥感数据集,采用改进的统计数据比较法提取中原城市群建成区,利用重心迁移指标和典型景观格局指标,分析中原城市群建成区2002—2020年的时空变化特征。研究表明:①中原城市群建成区扩张强度先快后慢,整体呈下降趋势;建成区重心在经历多次偏移后最终指向东南方向,但一直位于郑州大都市区范围内。②中原城市群发展迅速,建成区总面积在2002—2020年增加了1.429倍;在2011—2012年出现大量新兴城镇;2014年之后趋于稳定,城镇之间的联系越来越紧密。③中原城市群建成区空间格局复杂度逐年上升,破碎程度总体降低,郑州大都市区建成区扩张速度明显快于中原城市群整体建成区扩张速度。     

地面LiDAR点云数据先局部后整体配准方法

针对地面LiDAR获取的庞大点云数据,提出无人工标志的地面LiDAR点云先局部后整体的配准方法。分割出待配准的两测站重叠区域小块点云,采用基于KD-Tree遍历最近邻域点集的ICP算法计算三维坐标转换参数,实现地面LiDAR点云数据的快速配准。     

Relationship of local incidence angle with satellite radar backscatter for different surface conditions

This paper examines the relationship of C-band radar backscatter from the Advanced Synthetic Aperture Radar on board the ENVISAT satellite with the local angle of incidence, whose influence on the received signal is significant, particularly in the modes of sensor operation that use the full swath of the orbit track. Linear regression is carried out for each pixel throughout a large time series of radar data over the whole of the state of Queensland, Australia, and at Great Salt Lake, Utah, USA. In the first case, the resultant coefficients are analysed for correlation against various parameters, with regolith showing the highest correlation. Class separability analysis shows the potential to use the resultant coefficients as a supplement to absolute threshold values in order to distinguish between classes of vegetation and/or geology, where cloud cover may preclude the use of optical data. It is observed that the separability between water and land is greatly higher using the slope coefficient B than using backscatter σ⁰, which may be of great benefit in the remote sensing of water where cloud cover is present (from which radar is largely independent). This is especially the case when considering the observed overlapping of backscatter values from water, with values from aeolian sand and lacustrine and alluvial sediments, rendering the use of backscatter alone problematic. In order to test the potential use of B to map water extents, the study over the Great Salt Lake compares the classification accuracy of B against that of σ⁰. It is found that the σ₀ classification misrepresents desert, salt flat and dry lake basin areas, where the B classification differentiates these regions accurately. The resultant classification achieves a kappa statistic around 0.9, which shows very high conformance. An accurate and novel method to classify water is therefore demonstrated, which awaits the launch of anticipated improved synthetic aperture radar instruments on satellite missions in the coming few years.     

基于地理国情数据的PM_(2.5)因子多元回归分析

针对对PM2.5和与其相关的测绘成果进行的相关分析和回归模型分析相对不足的问题,该文以河北省石家庄市为研究对象,在相关因素分析的基础上,运用多元线性回归分析与多元非线性回归分析两种方法对石家庄市PM2.5浓度与扬尘地表、工业企业分布、地表覆盖以及道路等地理国情数据进行回归建模,并进行对比分析,根据判定系数R2得到最优建模方法及PM2.5重要影响因素及其影响关系。结果表明,该实验中多元非线性回归分析能获得较好的拟合效果,由模型可以看出扬尘地表、未利用地、人造覆盖面积与PM2.5呈正相关,是影响PM2.5的重要因素。该研究结果对于认识空气中PM2.5的来源与分布特征具有重要的参考价值。     

三大平原区县级地名演变研究

针对平原区县级地名密度演变、重心时空演变及语义演变特征问题,该文以东北平原、华北平原、长江中下游平原为例,利用GIS、核密度估计方法对其进行直观地展示与分析。结果表明:隋代至今,县级地名密度与地名重心均不同,平原区一直是地名密度较高的区域,地名重心呈现出先南移后北移的特征;县级地名的数量随时间变迁及政权更迭表现出波动变化,总体趋势是随时间推进数量逐渐增多,且地名密度基本高于全国平均水平,华北平原、长江中下游平原地名密度是全国均值的3倍以上;三大平原因山、水得名的县级地名数量均占总数的30%以上,因社会人文因素得名的比重呈上升趋势;东北平原县级地名形成时间比较集中,华北平原和长江中下游平原则较为分散。     

Urban aerosol mapping over Athens using the differential textural analysis (DTA) algorithm on MERIS-ENVISAT data

Low and moderate spatial resolution satellite sensors (such as TOMS, AVHRR, SeaWiFS) have already shown their capability in tracking aerosols at a global scale. Sensors with moderate to high spatial resolution (such as MODIS and MERIS) seem also to be appropriate for aerosol retrieval at a regional scale. We investigated in this study the potential of MERIS-ENVISAT data to resolve the horizontal spatial distribution of aerosols over urban areas, such as the Athens metropolitan area, by using the differential textural analysis (DTA) code. The code was applied to a set of geo-corrected images to retrieve and map aerosol optical thickness (AOT) values relative to a reference image assumed to be clean of pollution with a homogeneous atmosphere. The comparison of satellite retrieved AOT against PM₁₀ data measured at ground level showed a high positive correlation particularly for the AOT values calculated using the 5th MERIS’ spectral band (R²=0.83). These first results suggest that the application of the DTA code on cloud free areas of MERIS images can be used to provide AOT related to air quality in this urban region. The accuracy of retrieved AOT mainly depends on the overall quality, the pollution cleanness and the atmospheric homogeneity of the reference image.     

利用多源卫星数据研究青藏高原湖泊水储量变化及其影响因素

青藏高原分布着地球上海拔最高、数量最多的高原湖泊群,也是我国湖泊最集中的地区,有效掌握青藏高原湖泊水储量变化对于我国水资源有效利用具有重要意义。本文的研究核心是联合多源卫星数据研究青藏高原湖泊水储量变化,主要内容包括水陆交界处波形重跟踪算法研究、多源测高数据融合、利用测高和遥感数据计算湖泊水储量变化、结合GRACE数据进行湖泊水量平衡分析和青藏高原湖泊的气候变化响应研究等。     

顾及拓扑与尖角的分类矢量数据分组压缩算法

针对现有拆分重组法对存在复杂内环以及复杂相交岛屿多边形的分类矢量数据的压缩结果中包含裂缝、重叠及大量尖锐夹角的问题,提出了一种顾及拓扑一致性与尖角的分组压缩方法。依据分类矢量数据中多边形与多边形及其内环的相交关系对矢量矢量数据分组,以修正后拆分重组法结合直接分割法和间接分割法对分类矢量数据分组压缩,压缩结果中不存在裂缝与重叠现象,维护了分类矢量数据的拓扑一致性;通过取回尖角点前后被删除的点,解决了压缩结果中尖角过多的问题。以Landsat8遥感影像分类矢量数据实验验证了文章算法,并与直接分割法、间接分割法、拆分重组法进行了对比分析,验证了本文方法的有效性。     

Effect of data density,scan angle,and flying height on the accuracy of building extraction using LiDAR data

A Hough transform based approach for extraction of buildings using LiDAR data is presented. It is argued that LiDAR data should be smoothed and sparsed prior to Hough transform for better result. Algorithms to realize this are presented. Further, an algorithm which fits a vector model to extracted buildings is outlined. Simulated LiDAR data have been used to investigate the effect of three parameters (data density, flying height, and scan angle) on the quality of buildings extracted. A set of accuracy indices is proposed for this purpose. It is shown that the data density is the most significant parameter affecting the accuracy of building identification.     

目标颜色和入射角对Trimble GX扫描点云精度的影响

介绍三维激光扫描仪的误差分类及近年来国外在目标反射特性对点云精度影响方面的研究进展,大量实验表明点云精度与目标表面反射特性存在较强关系。通过对纸质贴片点云分析得出如下结论:Trimble GX三维激光扫描仪所测点云标准偏差与反射激光亮度符合乘幂函数关系;目标颜色对该扫描仪测量精度有较大影响,白、绿、黄、蓝等颜色对绿色激光反射率较好;纸质贴片旋转一个较小角度可使扫描点云质量最优;纸质贴片反射特性服从朗伯余弦定律。     

Statistical data fusion of multi-sensor AOD over the Continental United States

This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N³), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States.     

全极化SAR数据反演桥面高度

根据高分辨率SAR图像上建筑区的影像特征, 提出了基于灰度共生矩阵(gray-level cooccurrence Matrix, GLCM)纹理分析的建筑区提取方法, 该方法由初步定位和边界调整2个步骤组成, 均遵循特征计算、基于Bhattacharyya距离的特征选择和KNN分类流程, 所不同的是2个步骤中分别采用了逐块和逐点计算纹理特征的方式以兼顾纹理分析的效率和准确性。文中对不同SAR传感器获取的图像进行了实验。实验结果表明, 选用具有最大Bhattacharyya距离值的3或4个特征可以获得较好的初步定位结果, 建筑区的检测率超过80%, 虚警率低于10%;随着边界调整的进行, 检测到的建筑区边界逐渐接近于真实边界。实验结果验证了该算法的有效性。     

Lithological mapping from hyperspectral data by improved use of spectral angle mapper

The spectral angle mapper (SAM), as a spectral matching method, has been widely used in lithological type identification and mapping using hyperspectral data. The SAM quantifies the spectral similarity between an image pixel spectrum and a reference spectrum with known components. In most existing studies a mean reflectance spectrum has been used as the reference spectrum for a specific lithological class. However, this conventional use of SAM does not take into account the spectral variability, which is an inherent property of many rocks and is further magnified in remote sensing data acquisition process. In this study, two methods of determining reference spectra used in SAM are proposed for the improved lithological mapping. In first method the mean of spectral derivatives was combined with the mean of original spectra, i.e., the mean spectrum and the mean spectral derivative were jointly used in SAM classification, to improve the class separability. The second method is the use of multiple reference spectra in SAM to accommodate the spectral variability. The proposed methods were evaluated in lithological mapping using EO-1 Hyperion hyperspectral data of two arid areas. The spectral variability and separability of the rock types under investigation were also examined and compared using spectral data alone and using both spectral data and first derivatives. The experimental results indicated that spectral variability significantly affected the identification of lithological classes with the conventional SAM method using a mean reference spectrum. The proposed methods achieved significant improvement in the accuracy of lithological mapping, outperforming the conventional use of SAM with a mean spectrum as the reference spectrum, and the matching filtering, a widely used spectral mapping method.