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LANDSAT-5 TM Data Radiometric Correction and Geospatial Positioning Accuracy
LANDSAT-5 TM数据的辐射校正与几何定位精度

CHEN Jun,WANG Wen,LI Zi-yang,LI An,

中国图象图形学报 , 2008,
Abstract: Radiometric correction and geospatial correction ,which are two key steps for quantitative remote sensing information,are crucial to reveal the target and background character and the actual geographical position.In this paper,a method of radiometric correction and the geospatial positioning accuracy of Landsat-5 TM data processed with precise ephemeris parameters is introduced.Test with the Landsat-5 TM data verified that the method used in China Remote Sensing Satellite Ground Station is effective to eliminate the system errors produced during the imaging process.
Cloud and shadow removal from Landsat TM data
Landsat TM遥感影像中厚云和阴影去除

RI Pyongsop,MA Zhangbao,QI Qingwen,LIU Gaohuan,

遥感学报 , 2010,
Abstract: Cloud removal is an important step in remote sensing image process. In this paper, the author proposed a new algorithm for cloud removal using multi-temporal Landsat TM image data based on spectral characteristics analysis. Through the spectral characteristics analysis of the thick cloud region and its shadow region, the thick cloud and its shadow identification models were designed. Using image regression, unsupervised classification and pixel replacing techniques as well as these models, the influence of thick clouds and its shadows can be eliminated or reduced in the Landsat TM images. The result shows that the algorithm can eliminate or significantly reduce the cloud influence from Landsat TM image data.
Remote Monitoring of Wheat Streak Mosaic Progression Using Sub-Pixel Classification of Landsat 5 TM Imagery for Site Specific Disease Management in Winter Wheat  [PDF]
Mustafa Mirik, R. James Ansley, Jacob A. Price, Fekede Workneh, Charles M. Rush
Advances in Remote Sensing (ARS) , 2013, DOI: 10.4236/ars.2013.21003
Abstract: Wheat streak mosaic (WSM), caused by Wheat streak mosaic virus is a viral disease that affects wheat (Triticum aestivum L.), other grains, and numerous grasses over large geographical areas around the world. To improve disease management and crop production, it is essential to have adequate methods for monitoring disease epidemics at various scales and multiple times. Remote sensing has become an essential tool for monitoring and quantifying crop stress due to biotic and abiotic factors. The objective of our study was to explore the utility of Landsat 5 TM imagery for detecting, quantifying, and mapping the occurrence of WSM in irrigated commercial wheat fields. The infection and progression of WSM was biweekly assessed in the Texas Panhandle during the 2007-2008 crop years. Diseased-wheat was separated from uninfected wheat on the images using a sub-pixel classifier. The overall classification accuracies were >91% with kappa coefficient between 0.80 and 0.94 for disease detection were achieved. Omission errors varied between 2% and 14%, while commission errors ranged from 1% to 21%. These results indicate that the TM image can be used to accurately detect and quantify disease for site-specific WSM management. Remote detection of WSM using geospatial imagery may substantially improve monitoring, planning, and management practices by overcoming some of the shortcomings of the ground-based surveys such as observer bias and inaccessibility. Remote sensing techniques for accurate disease mapping offer a unique set of advantages including repeatability, large area coverage, and cost-effectiveness over the ground-based methods. Hence, remote detection is particularly and practically critical for repeated disease mo- nitoring and mapping over time and space during the course of a growing season.

Study of Correspondence Analysis on Landsat TM

Liu qingsheng,Lin qizhong,Wang zhigang,

中国图象图形学报 , 1999,
Abstract: Landsat TM image is one of the primary sources of remote sensing geological information at present. It provides a lot of information for mapping and recognizing unaltered and altered rocks and vegetation and other things in the region of visible and near infrared and short-wave infrared and thermal infrared bands. Because its thermal infrared band(TM7) has a low spatial resolution, generally, it isn't used. This paper uses Correspondence Analysis (CA) to process the TM image at the Seerteng Mountain, Inner Mongolia Autonomous Region, and acquired good results and shows the useful information that CA provides.
Application of Landsat TM and JERS-1 SAR Data to Gold Exploration
Landsat TM及JERS-1 SAR数据在金矿探测中的应用研究

Zhang Manlang,Zheng Lanfen,

遥感学报 , 1996,
Abstract: The key point for gold exploration using remote sensing technology is the information extraction of ore-forming structures and the spectral character of the ferroxides and alterated hydrous dinerals. JERS-1 SAR is of great potential in structural extraction, which can be achieved by suppressing the speckled noise and edge enhancement using spatial filters. With the help of principal component analysis of the band or ratio imagery of the landsat TM, the spectral character of alterated minerals can be extracted, while the influnce of the vegetation can be suppressed. Both alteration and structural information can be extracted by the integration of the two above remote sensing data.
Automatically Extracting Information Form Maize Fields based on TM Remote Sensing Images

YANG Guang,ZHANG Bai,WANG Zong-ming,WAN G Zh-qiang,BIAN Hong-feng,

资源科学 , 2006,
Abstract: Many researches have focused on the automatic extraction of information from Landsat/TM remote sensing images.However,many of them seemed to be low effective,and the application of remote sensing technology is limited.Firstly,this paper analysed the current situation about how to extract arable land information from remote sensing images,and middle Jilin province and northeast Liaoning Province were selected as study area.The supervised classification method was adopted in the Landsat/TM image classification and maize land in the study area was extracted from the Landsat/TM images with the precision of up to 85.5%.Secondly,the method of automatic information extraction based on the multi-characters space in remote-sensing images was put forward.According to the method,maize fields information space was divided into several sub-spaces including spectral feature space,shape feature space,interference feature space and local geoscience-based feature space.Automatic classification of thematic information about maize land was carried out based on TM images and use of the method above.An expertise database was created for the automatic extraction of maize land from Landsat/TM images on the basis of multi-characters space with the use of knowledge engineer module from the ERDAS 8.5 software.The extraction of maize fields in the study area from the images was performed again on the basis of the expertise database.It was found that the interpretation was notably improved with the precision of 92.9%.Comparing this classification result with the traditional visual interpretation,it was concluded that the new method adopted in the paper could improve efficiency of thematic information extraction from the remote sensing images.At the same time,the method appears to have wide application perspective and have a great potential to be used in other areas.The method was also theoretically significant for automatic interpretation of remote-sensing images in the future.
Detection of Usefullness of Integrating Remotely Sensed Data (Landsat TM) with GIS  [PDF]
H. Abdul Halim,H.A. Jumaat,M.A. Juhari,A.R. Sahibin
Information Technology Journal , 2006,
Abstract: A study integrating remote sensing and Geographical Information System (GIS) was carried out in the Kuala Terengganu district, Terengganu, Malaysia to map and determine the land use change as a result of development pressure in the area. Two sets of Landsat Thematic Mapper (TM) dated 31 July 1988 and 14 July 2002, at scale 1: 150 000 were acquired. Land use classes were interpreted from these images and the resultant maps were checked in the field to determine ground truth and mapping accuracy. The land use map data were transferred directly into the computer via ILWIS (Integrated Land Water and Water Information System) version 3.1 software. It shown that in this study seven categories of land use changes were detected namely forest (-9.93%), agricultural (-1.46%), swamp (-36.92%), urban (190.29%), cleared land (-21.43%), water bodies (-7.48%) and bush/shrub (6.34%). The accuracy assessment undertaken showed that the total accuracy for produced the map is 77.89%. This study showed that Landsat TM is a useful data for study in land use change.
Multi-temporal Remote Sensing Change Detection Using Dynamic Bayesian Networks

Ouyang Yun,Ma Jian-wen,Dai Qin,

电子与信息学报 , 2007,
Abstract: Utilizing Dynamic Bayesian Networks (DBNs) to deal with multi-temporal remote sensing data, the multi-temporal data of different time can be input simultaneously, and the classification and the acquirement of relationships between the output types can be finished simultaneously. Using the Landsat TM remote sensing data of Beijing eastern area acquired in May of 1994, 2001 and 2003 for the experiment, the experimental results indicate that the DBN-based change detection method is a new effective method of remote sensing change detection, and show its great potential for the research on the analysis of the dynamic changes of remote sensing time-series data.
The Preliminary Study on the Super-scale Rockslide in the Western Mountains of Shijiazhuang Using the Landsat-5 TM Image

QIAO Yanxiao,ZHANG Shaocai,

遥感技术与应用 , 1999,
Abstract: A super scale rockslide was discovered in the landsat 5 TM image proccessed by computer by Hebei remote sensing center, and was confirmed by geological specia lists recently. This paper introduce the Preliminary study result with respect t o the development conditions, features, cause and stability of the slide, and in dicates the next work direction and its theoretical meaning for the slide.

Zhang Lei Wang Xinmin,

遥感学报 , 1989,
Abstract: Landsat Thematic Mapper (TM) image is rich in spectral information, while SPOT panchromatic data is fine in its spatial resolution. Complementary and effective use of these data has shown in its increasing importance in the field of remote sensing application.In this paper, methods of digital merging of SPOT and TM data are investigated. Resultant of enhancement both in spectral and in spatial resolution is illustrated by an example.
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