Remote sensing and geophysical survey applications for delineating near-surface palaeochannels and shallow aquifer in the United Arab Emirates

This study integrates remote sensing data and geoelectrical dipole–dipole resistivity to delineate near-surface palaeochannels and shallow aquifer in the northern part of Abu Dhabi Emirate, United Arab Emirates. The shuttle imaging radar images and shuttle radar topographic mission DEM were used to delineate near-surface palaeochannels visually based on the contrast between bright and dark tone and automatically using the eight-direction flow model. The delineated palaeochannels were validated by comparing the textural features evident from advanced land observing satellite-phased array type L-band synthetic aperture radar images and determining whether these patterns were different. Field observation and geoelectrical dipole–dipole resistivity method was used to define the depth of palaeochannels and lithology of the shallow aquifer. The remote sensing and geophysical investigations in the UAE, including the study area, indicate the presence of buried palaeochannels with south-west and north-west flow directions from Oman Mountain. The study area can be of economic importance to the local population.     

利用一种模糊神经网络对遥感影像进行分类的研究

结合遥感影像的特点,提出一种模糊逻辑系统和神经网络中的BP算法相结合的模糊神经网络,利用其进行整个遥感图像的分类,并和典型的BP神经网络进行对比,发现其优点以及存在的问题。     

基于高分二号数据的湖南省十大水库网箱围栏养殖分布遥感调查

水库尤其是饮用水水源型水库的网箱围栏养殖对水域环境影响较大,利用高分辨率遥感具有丰富空间信息和纹理信息的特点,可以有效提取网箱养殖的分布信息。本文以高分二号卫星遥感影像为数据源,利用人机交互目视解译的方法提取湖南省十大水库等内陆水域网箱养殖信息,研究了网箱养殖空间分布情况,并估算了网箱养殖的氮、磷年排放量,为水产行业部门监管提供了有力的技术支撑。     

Remote sensing of alpine lake water environment changes on the Tibetan Plateau and surroundings: A review

Alpine lakes on the Tibetan Plateau (TP) are key indicators of climate change and climate variability. The increasing availability of remote sensing techniques with appropriate spatiotemporal resolutions, broad coverage and low costs allows for effective monitoring lake changes on the TP and surroundings and understanding climate change impacts, particularly in remote and inaccessible areas where there are lack of in situ observations. This paper firstly introduces characteristics of Tibetan lakes, and outlines available satellite observation platforms and different remote sensing water-body extraction algorithms. Then, this paper reviews advances in applying remote sensing methods for various lake environment monitoring, including lake surface extent and water level, glacial lake and potential outburst floods, lake ice phenology, geological or geomorphologic evidences of lake basins, with a focus on the trends and magnitudes of lake area and water-level change and their spatially and temporally heterogeneous patterns. Finally we discuss current uncertainties or accuracy of detecting lake area and water-level changes from multi-source satellite data and on-going challenges in mapping characteristics of glacial lakes using remote sensing. Based on previous studies on the relationship between lake variation and climate change, it is inferred that the climate-driven mechanisms of lake variations on the TP still remain unclear and require further research.     

高分光学遥感影像在铁路勘察中的应用及展望

为促进我国铁路勘察设计领域高分光学遥感影像的应用,结合当前铁路勘察设计工作的特点,系统总结了高分光学影像的发展及其在地理信息产品生产、地质勘察和环境影响评价分析等方面的应用现状,指出面向铁路勘察设计的高分影像应用存在的问题,提出未来的研究重点是建立适应于铁路勘察设计特点的遥感影像高精度的处理和智能信息提取与解译、业务应用等方面,以期形成高效的光学遥感卫星铁路勘察设计应用体系。     

龙门山南段(芦山段)旅游资源遥感调查与评价

芦山县地处龙门山南段,是成都平原向龙门山山地过渡的地带,特殊的地质、地貌条件和人类活动造就了区内山体、峡谷、岩溶、瀑布、湖泊、河流、森林和花卉等一大批自然景观,同时孕育了大批极具旅游价值的人文景观。这些旅游景观多以点状方式散布在全县范围内,人们对于全县的旅游资源,尤其是自然景观的分布范围和规模没有一个全面的认识,为此必须对芦山县的旅游资源进行大范围的调查。但是逐一调查每个景观难度较大,也难以从宏观和微观两个层次上去把握资源的分布和特征,本文利用ETM遥感图像,按照先解译自然景观,再结合其他资料间接判定人文景观的方法,实现了对区内旅游资源的调查和评价。     

青海省聚乎更煤矿区矿山地质环境遥感监测及质量评价

以2011年和2012年获取的2期IKONOS2数据为信息源,在波段组合、数据融合和正射纠正等图像预处理基础上,针对矿山地质环境问题进行人机交互解译,对青海省木里煤田聚乎更煤矿区因煤矿开发而引发的矿山地质环境问题及矿山环境恢复治理情况进行了遥感调查与监测;并将矿山环境调查结果与矿区基础地理及地质资料相结合,根据矿区环境的实际状况,合理选择矿山地质环境评价因子及权重指标,对该矿区的矿山地质环境质量进行了动态评价。结果表明:聚乎更煤矿区的矿山地质环境质量呈明显下降的趋势,2012年采矿活动对矿山地质环境有影响的面积较2011年增加了近10 km2,主要是地表植被直接或间接地受到破坏,且矿山环境恢复治理工作进程远远跟不上矿山环境恶化速度。     

Carbon sinks and tropical forest biomass estimation: a review on role of remote sensing in aboveground-biomass modelling

Tropical forest embraces a large stock of carbon and contributes to the enormous amount of above- and below-ground biomass and the global carbon cycle. The carbon kept in the above-ground living biomass of trees is typically the largest pool and the most directly impacted by deforestation and degradation. Hence, quantifying carbon stock and fluxes from tropical forests by estimating the above-ground forest biomass is the critical step that will be investigated further in this paper. Remote sensing technology can provide many advantages in quantifying and mapping forest structure and monitoring and mapping above-ground biomass, and is both temporally and spatially accurate. Therefore, a good data-set of biomass which comprises canopy height and canopy structure can provide carbon sequestration potential for forest reserves. This paper reviews a thorough research of biomass estimation using remote sensing and geospatial technologies.     

Remote sensing and information value (IV) model for regional mapping of fluvial channels and topographic wetness in the Saudi Arabia

This study aims to map regions of near surface fluvial channels, mega-basins and topographic wetness in Saudi Arabia using remote sensing data and an information value (IV) model, which is a modified approach of weight of evidence. We used the new version of the Shuttle Radar Topographic Mission (SRTM) to delineate the fluvial channels, mega-basin, and slope. These hydrological parameters were used to index the topographic wetness of each mega-basin in the region based on IV in a Geographic Information System. We validated our method using the Space Imaging Radar-C and Landsat 8 images and compared the textural features (fluvial channels) evident from SRTM digital elevation model and to determine whether these patterns were different. Our results revealed that the region is drained by nine tributaries and that the Err Rub Al Khali and Sahba mega-basins have the highest value of the IV and topographic wetness values; the Arran and coastal mega-basins have the lowest value of the IV and topographic wetness values. An integrated approach is timely and economically effective and can be applied throughout the arid and semi-arid regions to help hydrologists and urban developers.     

Functional relation of land surface albedo with climatological variables: a review on remote sensing techniques and recent research developments

Surface albedo has been documented as one of the Essential Climate Variables (ECV) of the Global Climate Observing System (GCOS) that governs the Earth's Radiation Budget. The availability of surface albedo data is necessary for a comprehensive environmental modelling study. Thus, both temporal and spatial scale issues need to be rectified. This study reports about the availability of surface albedo data through in-situ and remote sensing satellite observations. In this paper, we reviewed the existing models for surface albedo derivation and various initiatives taken by related environmental agencies in order to understand the issues of climate with respect to surface albedo. This investigation evaluated the major activities on albedo-related research specifically for the retrieval methods used to derive the albedo values. Two main existing albedo measurement methods are derived through in-situ measurement and remotely sensed observations. In-situ measurement supported with number of instruments and techniques such aspyrheliometers, pyranometers and Baseline Surface Radiation Network (BSRN) and remotely sensed observations using angularly integrated Bi-directional Reflectance Distribution Function (BRDF) by both geostationary and polar orbit satellites. The investigation results reveals that the temporal and spatial scaling is the major issues when the albedo values are needed for microclimatic study, i.e. high-resolution time-series analyses and at heterogeneity and impervious surface. Thus, an improved technique of albedo retrieval at better spatial and temporal scale is required to fulfil the need for such kind of studies. Amongst many others, there are two downscaling methods that have been identified to be used in resolving the spatial scaling biased issues: Smoothing Filter-based Intensity Modulation (SFIM) and Pixel Block Intensity Modulation (PBIM). The temporal issues can be resolved using the multiple regression techniques of land surface temperature, selected air quality parameters, aerosol and daily skylight.     

Remote sensing of Red Mediterranean soils: a case study in the viticultural southern Rhone Valley using SPOT satellite imagery

The aim of this work was to map Red Mediterranean soils, for which no previous mapping approach exists, using optical multispectral satellite remote sensing data. This case study explores the use of SPOT XS images over the viticultural Southern Rhone Valley, France, to map exposed vineyard soils. Field spectral measurements were used to distinguish Red Mediterranean soil surfaces during Spring 1999. A supervised maximum likelihood classification was applied to sparsely vegetated and unvegetated surfaces of two spring images from 1995 and 1997, drawing on the field training set and available soil data. Similar global spatial segmentation was obtained despite different soil surface states on these dates. Classification performances were higher than 84% in both images. Mean classification accuracies of Red Mediterranean soils at seven reference surfaces were 60% in 1995 and 70% in 1997. This suggests that the direct use of optical remote sensing data at medium resolution can be useful for mapping bare Red Mediterranean soils.     

近30年云贵高原水蚀荒漠化遥感监测及影响因子时空分异规律

云贵高原属于典型季节性干旱生态脆弱区,其中因流水造成的水蚀荒漠化已成为限制该区域持续发展的重大生态环境问题之一。本文采用长时间序列Landsat卫星数据监测云贵高原核心区云贵两省近30年水蚀荒漠化的现状与时空变化,并分析该区域荒漠化关键影响因子的时空分异规律,提出一种多指标规则分类算法用于云贵高原水蚀荒漠化遥感监测,并选用植被面积、GDP及降水3个关键影响因子,采用地理加权回归模型,分析该区域水蚀荒漠化影响因子的空间分异规律。试验结果表明：①云贵高原荒漠化的主要分布区为滇桂黔区、川滇交界地区、滇西边境区及蒙自地区。②近30年研究区水蚀荒漠化变化趋势可分为1989—2010年、2010—2013年及2013—2016年3个阶段,1989—2010年该区域的荒漠化呈现波动增长状态;2010—2013年荒漠化面积快速扩展;2013—2016年荒漠化快速扩展的趋势得到了有效遏制。③3个关键影响因子与水蚀荒漠化关系呈现数值大小不同、正负效应和因子组合效应的空间分布差异,局部地区的经济发展和气候变化加剧了其水蚀荒漠化。本文研究成果将为云贵高原水蚀荒漠化的精细化防控和治理提供一定的理论依据和技术支撑。     

Fusion of RADARSAT-2 and multispectral optical remote sensing data for LULC extraction in a tropical agricultural area

In this study, we investigated the performance of different fusion and classification techniques for land cover mapping in Hilir Perak, Peninsula Malaysia using RADAR and Landsat-8 images in a predominantly agricultural area. The fusion methods used are Brovey Transform, Wavelet Transform, Ehlers and Layer Stacking and their results classified into seven different land cover classes which include (1) pixel-based classifiers (spectral angle mapper (SAM), maximum likelihood (ML), support vector machine (SVM)) and (2) Object-based (rule-based and standard nearest neighbour (NN)) classifiers. The result shows that pixel-based classification achieved maximum accuracy of the optical data classification using SVM in Landsat-8 with 74.96% accuracy compared to SAM and ML. For multisource data classification, the highest overall accuracy recorded for layer stacking (SVM) was 79.78%, Ehlers fusion (SVM) with 45.57%, Brovey fusion (SVM) with 63.70% and Wavelet fusion (SVM) 61.16%. And for object-based classifiers, the overall classification accuracy is 95.35% for rule-based and 76.33% for NN classifier, respectively. Based on the analysis of their performances, object-based and the rule-based classifiers produced the best classification accuracy from the fused images.     

Urban growth monitoring and projection using remote sensing and geographic information systems: a case study in the Twin Cities Metropolitan Area,Minnesota

This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary.     

An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach

An assessment of gully erosion along road drainage-release sites is critical for understanding the contribution of roads to soil loss and for informed land management practices. Considering that road-related gully erosion has traditionally been measured using field methods that are expensive, tedious and limited spatially as well as temporally, it is important to identify affordable, timely and robust methods that can be used to effectively map and estimate the volume of gullies along the road networks. In this study, gullies along major roads were identified from remotely sensed data sets and their volumes were estimated in a Geographic Information Systems environment. Also, the biophysical and climatic factors such as vegetation cover, the road contributing surface area, the gradient of the discharge hillslope and rainfall were derived from remotely sensed data sets using Geographic Information Systems techniques to find out whether they could explain the morphology of gullies that existed in this area. The results of this study indicate that hillslope gradient (R²?=?0.69, α = 0.00) and road contributing surface area (R²?=?0.63, α = 0.00) have a strong influence on the volume of gullies along the major roads in the south-eastern region of South Africa, as might have been expected. However, other factors such as vegetation cover (R² = 0.52, α = 0.00) and rainfall (R² = 0.41 and α = 0.58) have a moderately weaker influence on the overall volume of gullies. Overall, the findings of this study highlight the importance of using remote sensing and Geographic Information Systems technologies in investigating gully erosion occurrence along major roads where detailed field work remains a challenge.     

基于多源多时相遥感数据的秋季菜田监测与分析——以北京市大兴区为例

根据北方蔬菜种植生育期特点,选择7~8月份的高分1号(GF1)融合影像、10月份的16 m宽覆盖的GF1影像以及8月份Rapid Eye融合影像,结合耕地本底数据开展提取秋季菜田信息的技术流程研究,并对2013年和2014年大兴区秋季菜田进行了动态监测,同时结合气象等数据分析其时空分布规律和变化原因。     

Geospatial technologies for detection and monitoring of Ganoderma basal stem rot infection in oil palm plantations: a review on sensors and techniques

Basal stem rot (BSR) is a type of disease that induces oil palm death within a short span of the appearance of symptoms. BSR early detection would facilitate to curb this by adopting appropriate strategies. In this paper, a systematic review was undertaken to demonstrate the need for authentic health condition monitoring of oil palm plantations. The currently used remotely sensed (RS) techniques for BSR detection and classification were reviewed. Several kinds of RS techniques were exerted for BSR detection and its severity classification up to four levels. It was identified that applied geospatial technologies, including multispectral and hyperspectral remote sensing, terrestrial laser scanning, spatial maps, tomography images, intelligent e-nose and Microfocus X-ray fluorescence, were capable of distinguishing infected oil palms from the non-infected ones. Furthermore, some of them are able to categorize BSR severity level up to four levels as well as of its early detection.     

Remote sensing and avian influenza: A review of image processing methods for extracting key variables affecting avian influenza virus survival in water from Earth Observation satellites

Recent studies have highlighted the potential role of water in the transmission of avian influenza (AI) viruses and the existence of often interacting variables that determine the survival rate of these viruses in water; the two main variables are temperature and salinity.