Application of remote sensing techniques in snow and ice hydrology

The contribution of snow and ice melt towards the water discharges of most of the Himalayan rivers is highly significant. It is, therefore, necessary to monitor the snow accumulation and depletion, and study the melting processes to help in efficient management of water resources. It is also important to compile a glacier inventory for the purpose. The snow bound areas in the Himalaya lie at high altitudes where the terrain is rugged and inaccessible. This renders the conventional methods of study not only difficult but hazardous as well. Remote sensing techniques, therefore, have a vital role to play in these studies for quick results with much less cost. Visual interpretation of Landsat imagery in Beas river basin and use of aerial photographs for glacier inventory in Baspa river basin have been cited as case studies. To perfect the methodology used in various remote sensing techniques, a pilot project approach has been suggested.     

中国西部喀喇昆仓明铁盖多金属矿化区的卫星遥感勘查

成矿环境的地质分析与遥感探测标志是矿产遥感定位的     

利用Landsat 8 OLI进行汉江下游水体浊度反演

综合比较Landsat 8 OLI遥感影像与地面同步水质监测结果,发现Landsat 8的近红外波段与其他波段的组合和水体浊度具有较高的相关性,以此为基础运用OLI的第1、3、5波段组合建立了汉江中下游浊度的遥感反演数学模型。根据该模型生成了2013年4~11月共3幅汉江中下游浊度分布图,并进行了空间分析。精度验证表明,模型相对误差在15%左右,R2=0.71,表明运用Landsat 8 OLI可有效地监测该区域水体浊度分布情况。     

热带森林植被的动态变化遥感监测

本文讨论了以热带森林植被为主体的再生资源的面积动态变化监测。研究中包括两个部分。首先,我们利用多时相遥感图像对大面积的西双版纳州进行地类判读,系统地分析了森林植被的动态变化。其次,利用Landsat MSS和TM数据对自然保护区的动态变化进行了包含无监督分类和归一化差值植被指数分析的数字图像处理,变化分类也相当符合实际。总的实验结果表明,这种监测方法是很有效的,可在再生资源监测中特别是在森林植被监测中加以推广应用。     

Use of remote sensing techniques for detailed hydrogeological investigations in parts of Narmada Sagar command area,MP

Of late, airphoto interpretation and Landsat imagery analysis play a vital role in geological mapping for detailed hydrogeological investigations for ground water prospecting. Certain obscure features like lineaments/fracture zones which are masked by surface soil and cultivated lands are easily visible. In hard rocks like granites and basalts the occurrence and movement of ground water are controlled by the fracture pattern. Delineation of potential zones of ground water for successful exploration is possible by the study and analysis of aerial photographs, visual interpretation of Landsat imagery and interactive data analysis system through computer techniques and applications. These techniques constitute for data integration with conventional methods of hydrogeological investigations and exploratory drilling. As a case study an area of 1500 sq km in part of the Narmada river basin of Madhya Pradesh and also forming a portion of Narmada Sagar area covered under topo sheets 46 N/12 and 46 N/16 was taken up. Aerial photographs pertaining to the area of study and Landsat imagery of band 5 and 7 in scale blown upto 1∶250,00 were scanned and analysed. It was observed that the successful artesian wells are located in pominent lineament/fractured zones in the study area. It is also recommended after through analysis different hyddromorphic zonations for future exploration of ground water.     

滇池周边典型城镇地表覆盖分类遥感分析研究

滇池作为滇中最大高原湖泊,其水环境保护及水污染治理工作至关重要. 针对滇池周边典型城镇地表覆盖变化,发挥遥感探测技术先进性,快速了解污染源,并实时监测滇池污染治理工程进展,为及时优化治理方案提供数据支撑具有重大意义. 选取滇池周边晋宁区典型城镇为研究区,基于Landsat8影像利用遥感提取地表覆盖分类信息,运用混淆矩阵对比了最大似然法和目视解译的分类提取精度. 可知Landsat8影像通过目视解译可以快速、高效地提取城镇地表覆盖分类信息,也适用于滇池流域昆明市区、呈贡区等城镇,为滇池流域治理保护的宏观动态监测提供技术支持,为滇池流域城镇的发展、规划和治理提供决策信息.      

Analyzing Change in Yellowstone's Terrestrial Emittance with Landsat Imagery

Yellowstone National Park (YNP) contains the world's largest concentration of geothermal features and is legally mandated to protect and monitor these natural features. Remote sensing is a component of the current geothermal monitoring plan. Landsat satellite data have a substantial historical archive and will continue to be collected into the future, making it the only available thermal imagery for historical analysis and long-term monitoring of geothermal areas in the entirety of YNP. Landsat imagery from Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors was used to examine change trajectories for terrestrial emittance among spatial groupings from 1986 to 2007. Trajectories of locations with known change events were also examined. Relationships between the spatial groupings and several change vectors (distance to geologic faults, distance to large water bodies, and distance to earthquake swarms) were explored. The analysis showed the strongest relationship between absolute difference in terrestrial emittance and earthquake swarms, with 34% of the variation explained. Certain known change events were reflected in the change trajectories, while the Landsat imagery was not able to detect other known events. This suggests that Landsat imagery might be a useful tool for monitoring geothermal responses in YNP, but cannot be expected to suffice as the sole monitoring tool.     

Age discrimination among eruptives of Menengai Caldera,Kenya, using vegetation parameters from satellite imagery

This paper reports an investigation to determine the degree to which digitally processed Landsat TM imagery can be used to discriminate among vegetated lava flows of different ages in the Menengai Caldera, Kenya. Since Landsat data display vegetation parameters well, and plant communities vary with type and depth of soil development, selective digital processing techniques were applied to take advantage of these characteristics for discriminating relative age differences of the underlying volcanics. A selective series of five images, consisting of a color‐coded Landsat 5 classification and four color composites, were compared with geologic maps. These included a color coded, modified, unsupervised classification and contrast enhanced, color composite images using TM bands 3–2–1, 4–3–2 and 7–5–3, and the first 3 Karhunen‐Loeve transformation axes that had been generated using 7 Landsat TM bands.

The most recent of more than 70 post‐caldera flows within the caldera are trachytes, which are variably covered by shrubs and subsidiary grasses. Soil development evolves as a function of time, and as such, supports a changing plant community. Progressively older flows exhibit the increasing dominance of grasses over bushes. It was found that the Landsat images correlated well with geologic maps, but that the two mapped age classes could be further subdivided on the basis of different vegetation communities. It is concluded that field maps can be modified, and in some cases corrected by use of such imagery, and that digitally enhanced Landsat imagery can be a useful aid to field mapping in similar terrains.     

Geology of the area around Katta,sindhudurg district,Maharashtra. Based on aerospace data

Geological studies of the area around Katta, in the southern part of the Ratnagiri District of Maharashtra, were carried out with the help of visual remote sensing techniques using LANDSAT imageries on 1:250,000 scale and aerial photographs on 1:60,000 scale. The major stratigraphic units represented in the area under study are the Archean Complex, Kaladgi Supergroup, Deccan Trap, Laterite and Alluvium. The Kaladgis unconformably overlie the Archean metasediments and also at places exhibit faulted contacts with the latter. The major part of the area is covered by a thick evergreen vegetation. The interpretation followed by field work and laboratory work revealed the following:

1. The different lithologic units could be delineated on the aerial photographs.
2. Different lineaments marked on the imagery were found to be due either to faults or fracture zones. Some of the older faults appear to have been rejuvenated after the formation of the laterites.
3. Some of the lithologic horizons can be identified on the Landsat imagery by virtue of their spatial signatures.

These studies indicate that even in the area covered with thick vegetation, aerospace imagery in appropriate band and data scale can provide significant geological information.     

PRACTICAL ASPECTS OF TOPOGRAPHIC MAPPING FROM SPOT IMAGERY

SPOT-1, launched on 22nd February, 1986, has provided the first opportunity to produce topographic maps from space on an operational basis. The use of SPOT imagery can be justified because of reduced costs and reduced lead times for map production. However SPOT imagery cannot be handled in the same way as conventional photography and it requires new procedures to be adopted, The two main reasons for this are the large area covered by each image and the dynamic form of sensing. The procedures discussed in this paper have been implemented in a working system for map compilation.     

我国土地资源遥感调查与监测技术体系建设构想

本文在全面分析总结我国土地资源遥感调查与监测历程的基础上,提出了我国土地资源遥感调查与监测的技术框架与体系以及主要问题和关键技术。研究结果表明我国土地资源遥感调查与监测体系建立已经极为迫切,其目标在于建立土地资源遥感调查与监测本底库和动态库,形成多系统组成的技术体系框架。     

Exploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area

Remote sensing data utilize valuable information via various satellite sensors that have different specifications. Image fusion allows the user to combine different spatial and spectral resolutions to improve the information for purposes such as forest monitoring and land cover mapping. In this study, I assessed the contribution of dual-polarized Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar data to multispectral Landsat imagery. The research investigated the separability of forested areas using different image fusion techniques. Quality analysis of the fused images was conducted using qualitative and quantitative analyses. I applied the support vector machine image classification method for land cover mapping. Among all methods examined, the à trous wavelet transform method best differentiated the forested area with an overall accuracy (OA) of 94.316%, while Landsat had an OA of 92.626%. The findings of this study indicated that optical-SAR-fused images improve land cover classification, which results in higher quality forest inventory data and mapping.     

Monitoring mangrove forests: Are we taking full advantage of technology?

Mangrove forests grow in the estuaries of 124 tropical countries around the world. Because in-situ monitoring of mangroves is difficult and time-consuming, remote sensing technologies are commonly used to monitor these ecosystems. Landsat satellites have provided regular and systematic images of mangrove ecosystems for over 30 years, yet researchers often cite budget and infrastructure constraints to justify the underuse this resource. Since 2001, over 50 studies have used Landsat or ASTER imagery for mangrove monitoring, and most focus on the spatial extent of mangroves, rarely using more than five images. Even after the Landsat archive was made free for public use, few studies used more than five images, despite the clear advantages of using more images (e.g. lower signal-to-noise ratios). The main argument of this paper is that, with freely available imagery and high performance computing facilities around the world, it is up to researchers to acquire the necessary programming skills to use these resources. Programming skills allow researchers to automate repetitive and time-consuming tasks, such as image acquisition and processing, consequently reducing up to 60% of the time dedicated to these activities. These skills also help scientists to review and re-use algorithms, hence making mangrove research more agile. This paper contributes to the debate on why scientists need to learn to program, not only to challenge prevailing approaches to mangrove research, but also to expand the temporal and spatial extents that are commonly used for mangrove research.     

Forest cover trends from time series Landsat data for the Australian continent

In perennial and natural vegetation systems, monitoring changes in vegetation over time is of fundamental interest for identifying and quantifying impacts of management and natural processes. Subtle changes in vegetation cover can be identified by calculating the trends of a vegetation density index over time. In this paper, we apply such an index-trends approach, which has been developed and applied to time series Landsat imagery in rangeland and woodland environments, to continental-scale monitoring of disturbances within forested regions of Australia. This paper describes the operational methods used for the generation of National Forest Trend (NFT) information, which is a time-series summary providing visual indication of within-forest vegetation changes (disturbance and recovery) over time at 25 m resolution. This result is based on a national archive of calibrated Landsat TM/ETM+ data from 1989 to 2006 produced for Australia's National Carbon Accounting System (NCAS). The NCAS was designed in 1999 initially to provide consistent fine-scale classifications for monitoring forest cover extent and changes (i.e. land use change) over the Australian continent using time series Landsat imagery. NFT information identifies more subtle changes within forested areas and provides a capacity to identify processes affecting forests which are of primary interest to ecologists and land managers. The NFT product relies on the identification of an appropriate Landsat-based vegetation cover index (defined as a linear combination of spectral image bands) that is sensitive to changes in forest density. The time series of index values at a location, derived from calibrated imagery, represents a consistent surrogate to track density changes. To produce the trends summary information, statistical summaries of the index response over time (such as slope and quadratic curvature) are calculated. These calculated index responses of woody vegetation cover are then displayed as maps where the different colours indicate the approximate timing, direction (decline or increase), magnitude and spatial extent of the changes in vegetation cover. These trend images provide a self-contained and easily interpretable summary of vegetation change at scales that are relevant for natural resource management (NRM) and environmental reporting.     

长时间序列多源遥感数据的森林干扰监测算法研究进展

时空意义明确的森林干扰和恢复信息是评价森林生态系统碳动态的关键因素之一。然而由于诸多的现实困难,多尺度的森林干扰定量化时空信息相对缺乏。Landsat数据具备光谱、时间和空间分辨率上的优势,以及可以免费获取的特点,使其成为主要的长时间序列动态监测的遥感数据源之一,为长时间周期内提供具有合适的空间细节和时间频率的森林干扰信息成为可能。特别是基于Landsat时间序列堆栈(LTSS)的森林干扰自动分析算法的出现,更为森林生态系统的近实时监测提供强有力的工具。本文全面评述了长时间序列遥感数据准备和预处理技术以及国内外基于遥感数据源的多时相森林干扰监测方法,重点分析了基于Landsat的多种指数监测和自动化方法的优缺点,并总结了其与多源数据结合的扩展应用,最后就现有方法与国内外新的数据、技术手段的关联进行了展望,以期为推广中国本土卫星影像应用于森林干扰监测提供理论借鉴。     

On stereo pair decomposition on landsat imagery

In interpretation of Landsat imagery that are obtained in different spectral bands, it is often desirable to superimpose some sort of ‘z’ information like terrain height, gravity or magnetic field of the Earth over these imagery. This can be achieved by decomposition of Landsat imagery into synthetic stereo pair by using known ‘z’ information. This enhances interpretation capabilities and such stareo decomposition is quite useful in many practical applications. Here, a method of stereo decomposition of Landsat image when ‘z’ information is available has been developed and implemented. As an illustrative example, a method has been applied for a Landsat scene and the results of the same are shown in the plates.     

GNSS-MR技术用于雪深探测的初步研究

积雪是全球水循环中的重要组成部分,积雪深度与雪水当量的精确监测对全球气候变化研究极其重要。随着GNSS研究与应用的不断深入,基于多路径效应的GNSS-MR（GNSS multipath reflectometry）技术用于地表环境监测（植被、土壤湿度、雪深、海平面等）已成为一种新兴的遥感手段。分析了SNR（signal-to-noise ratio）信噪比值的变化特性,详细给出了基于SNR观测值的GNSS-MR技术探测雪深的基本原理及其计算流程图。为了验证算法的有效性,利用科罗拉多州17 d连续跟踪站NWOT的GPS数据反演了降雪厚度,其结果与实测的雪深记录数据吻合较好,误差均值为0.07 m。初步研究结果验证了GNSS-MR技术用于积雪深度探测的可行性,并为后续充分利用现有的全球密集GNSS跟踪站数据开展地表环境监测提供重要参考。     

高光谱遥感影像管理系统的设计与实现

由于高光谱数据的海量高维特征,使得传统的信息系统难以有效地对这些数据进行高效地存储、处理、分析,表现等管理操作。因此如何采用新的技术来开发一个能有效管理高光谱遥感影像数据的影像管理系统,是当前高光谱快速发展和深入应用的一个瓶颈之一。本文在研究的过程中,对当前影像管理系统的发展作了大量的分析,利用成熟的关系数据库和程序设计语言,开发了一个方便实用的高光谱遥感影像管理系统以管理高光遥感影像和其他遥感信息,提高影像管理效率。系统已初步实现了多景高光谱遥感影像检索,可以任意加载、导入高光谱遥感影像,运行效果良好。     

济南市土地利用变化监测分析

济南作为山东省省会城市,在城市发展与土地利用变化方面应做到合理监测。本文以山东省济南市为研究对象,对济南市的土地遥感影像图进行分类。利用2005年和2016年济南市区Landsat遥感影像为基础数据,结合济南市矢量边界文件,对济南市的遥感影像图进行处理,通过目视解译,建立合理的训练样本,再结合野外调查的结果,制作济南市的土地利用分类图,根据分类结果对济南市土地利用变化进行分析与评价,为今后的济南市土地利用提供科学的依据和合理的建议[1]。     

Vegetation recovery monitoring over the waste dump in Haizhou opencast coalmine area,China, during 1975–2000 using NDVI and VF index

Vegetation condition monitoring has been done from 1975 to 2000 in the waste dump of Haizhou opencast coalmine area, China, using remote sensing techniques with the objective of improving our understanding of the temporal and spatial variation of vegetation recovery in the mining dump. Four historical vegetation indexes (NDVI, VF, soil brightness and vegetation greenness) from two Landsat 2 MSS images and two Landsat 5 TM images are extracted and analyzed. For the purpose of comparison and analysis two improved techniques such as normalization grading of change slope and image segmentation were used in this study. Based on the results obtained through the above analysis two conclusions are derived: (1) vegetation recovery in the study area is in an improved condition, (2) two remote sensing based vegetation indexes such as VF and NDVI are the optimal parameters to monitor vegetation condition, which could be used as the indicators of land reclamation progress in the mining area.