International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.最新文献

{"title":"Seasonal variability of aerosol optical depth over indian subcontinent","authors":"A. Prasad, R.P. Singh, A. Singh, M. Kafatos","doi":"10.1109/AMTRSI.2005.1469835","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469835","url":null,"abstract":"Ganga basin extends 2000 km E-W and about 400 km N-S and is bounded by Himalayas in the north. This basin is unequivocally found to be affected by high aerosols optical depth (AOD) (>0.6) throughout the year. Himalayas restricts movement of aerosols toward north and as a result dynamic nature of aerosol is seen over the Ganga basin. High AOD in this region has detrimental effects on health of more than 460 million people living in this part of India besides adversely affecting clouds formation, monsoonal rainfall pattern and Normalized Difference Vegetation Index (NDVI). Severe drought events (year 2002) in Ganga basin and unexpected failure of monsoon several times, occurred in different parts of Indian subcontinent. Significant rise in AOD (18.7%) over the central part of basin (Kanpur region) have been found to cause substantial decrease in NDVI (8.1%) since 2000. A negative relationship is observed between AOD and NDVI, magnitude of which differs from region to region. Efforts have been made to determine general distribution of AOD and its dominant departure in recent years spatially using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The seasonal changes in aerosol optical depth over the Indo-Gangetic basin is found to very significant as a result of the increasing dust storm events in recent years.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133351771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving automated detection of land cover change for large areas using Landsat data","authors":"Kuan Song, J. Townshend, Sunghee Kim, P. Davis, R. Clay, O. Rodas","doi":"10.1109/AMTRSI.2005.1469836","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469836","url":null,"abstract":"Detection of land cover change using multi- temporal data is crucial for many Earth Science issues. We examine the potential of several alternative approaches for automated detection of land cover change using Landsat data. Specifically we test their efficacy in consistently detecting change for large areas by examining their performance for Eastern Paraguay. We used Landsat imagery with limited training data solely from 10 km squares located at one degree intersections. Traditional classifiers showed a substantial decrease in accuracy when extrapolating from one scene to multiple other scenes, whereas decision tree and support vector machine classifiers maintained accuracy.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122847402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi temporal approach to fire detection using MSG data","authors":"F. V. D. Bergh, P. Frost","doi":"10.1109/AMTRSI.2005.1469861","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469861","url":null,"abstract":"The timely detection of fires is an important service that earth observation satellites can offer. Some very successful contextual fire detection algorithms have been developed for moderate to high resolution sensors. This paper presents a new algorithm that exploits the high update rate of the Meteosat Second Generation (MSG) satellite to derive a multi temporal fire detection algorithm. This is achieved by using a Kalman filter to predict the expected temperature, which can then be used to identify pixels that deviate significantly from their expected values.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128225605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multitemporal remote sensing of the outburst of three aquatic weeds in the Fuquene Lagoon, Colombia","authors":"J. Yague","doi":"10.1109/AMTRSI.2005.1469837","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469837","url":null,"abstract":"Looking into the subject matter, the analysis relates to two societal benefits identified by the GEOSS, namely those of improving the management and protection of terrestrial ecosystems and understanding, monitoring and conserving biodiversity. This multitemporal study presents the deterioration of a Colombian highland lagoon, Fuquene, due to bad land use practices that have fostered the outburst of three aquatic weeds: reed, buchon and elodea.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using multi-temporal MODIS 250 m data to calibrate and validate a sediment transport model for environmental monitoring of coastal waters","authors":"R.L. Miller, C. D. Del Castillo, C. Chilmakuri, J. McCorquodale, I. Georgiou, B. McKee, E. D’Sa","doi":"10.1109/AMTRSI.2005.1469872","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469872","url":null,"abstract":"Abstract — Muti-temporal images of total suspended matter (TSM) derived from MODIS (Moderate Resolution Imaging Spectrometer) Terra 250 m red-band reflectance data were used to set the initial conditions and validate output of a hydrodynamic and sediment transport model ( ECOMSED) developed for Lake Pontchartrain, LA USA. During this initial study, the moderately high spatial resolution of the 250 m images provided a significant improvement in model definition when compared to model runs calibrated using 1 km data available from most ocean viewing instruments (e.g., AVHRR and SeaWiFS). The combination of daily MODIS imagery and model simulations offer a more robust monitoring and prediction system of suspended sediments than available from either system alone. The additional use of Aqua MODIS imagery should afford greater refinement in model paramerization and accuracy. Keywords-suspended sediments; sediment transport; MODIS; ECOMSED; water quality; monitoring. I. I NTRODUCTION Coastal waters, especially bays and estuaries, are often characterized by high concentrations of suspended materials derived from freshwater inflow and/or by the resuspension of bottom sediments. High concentrations of suspended sediments can govern many important water column parameters and processes including total water quality, benthic and phytoplankton productivity, and the redistribution and transport of water-borne pathogens, pollutants, and other materials. For example, several investigators [1, 2] have reported that the distribution and concentration of fecal coliform are directly associated with sediment resuspension and suspended sediment transport. These findings establish a direct link between sediment dynamics and public health. Hence, there is considerable interest in monitoring the transport and fate of suspended sediments from a broad range of investigators, environmental managers, and policy makers. Unfortunately, in many coastal aquatic systems, the use of traditional field measurements is inadequate to effectively monitor suspended sediments at the desired spatial and temporal scales due to the presence of dynamic physical processes (e.g., wind driven resuspension, river flow) or the large size of the system. In contrast, observations from remote sensing instruments and numerical models can provide unique information regarding the distribution and transport of suspended sediments that cannot be obtained using traditional field sampling techniques. Remote sensing from airborne and space-based instruments provide a large-scale synoptic view; numerical models provide a better understanding of the underlying system processes as 0-7803-9119-5/05/$20.00 (C) 2005 IEEE","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115360106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of indicators of burning efficiency based on time series of SPOT VEGETATION data","authors":"S. Lhermitte, J. V. van Aardt, P. Coppin","doi":"10.1109/AMTRSI.2005.1469854","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469854","url":null,"abstract":"Accurate estimates of the aerial extent and burning efficiency are essential parameters for understanding and monitoring the impact of fires on the atmospheric and terrestrial ecosystems. Such inputs are important for global and regional carbon cycle models and provide a more comprehensive and accurate basis for understanding and monitoring vegetation recovery. Time series of satellite imagery offer the potential to quantify these parameters with spatial and temporal accuracy. Several studies (GLOBSCAR project of European Space Agency (ESA), GBA2000 project of Joint Research Centre (JRC, Italy)) have been developed to detect burned areas from satellite imagery, using the evolution of the spectral characteristics of a burn through time. The resulting data sets are available for the globe for the year 2000. Current research investigates the potential of time series of SPOT Vegetation (SPOT-VGT) S10 data (1998-2004) to quantify burning efficiency of the burns detected in the framework of GLOBSCAR and GBA2000. Burning efficiency is defined as the percentage biomass of a pixel that is burned. General constants have up to now been assigned per biome to define burning efficiency. The objective of this study was to provide quantitative estimates of the spatio-temporal variation of burning efficiency based on remote sensing indicators. Two different techniques were tested to quantify the burning efficiency of every detected fire pixel by means of consistent indicators. Southern Africa was used as a pilot study area due to the availability of both ground and satellite data. Firstly, a technique based on time series analysis of sub-pixel fractions was developed. A linear spectral mixture analysis (SMA) technique was applied to assess the fraction vegetation and non-vegetation components for every pixel through time. Endmember analysis was performed to extract appropriate pure endmembers for the SMA. Detailed vegetation geo-datasets and fire scar records were used to validate the endmembers. The results of the SMA provided a fractional variable for every pixel. These fractional variables were subsequently subjected to an image differencing change detection algorithm to quantify the changes in the vegetation component as a measure of burning efficiency. Secondly, a technique based on temporal variations of vegetation indices was developed. The temporal difference of several vegetation indices (Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Global Environment Monitoring Index (GEMI), and Normalized Burn Ratio (NBR)) was used to quantify the changes in the time trajectory. This difference is hypothesized to represent the changes in vegetation content and burned area and to provide a scaled index of the magnitude of change caused by fire, hence the burning efficiency. The results of both techniques were compared and validated with field data containing burn severity and severity indices based on Landsat imagery with high","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114841348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trend analysis of time-series phenology derived from satellite data","authors":"B. Reed, J.F. Brown","doi":"10.1109/AMTRSI.2005.1469863","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469863","url":null,"abstract":"Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface for the past 15 years. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land surface processes over large areas. Repeat observations from satellite-borne multispectral sensors provide a mechanism to move from plant-specific to regional scale studies of phenology. In addition, we now have sufficient time-series (since 1982 at 8-km resolution covering the globe and since 1989 at 1-km resolution over the conterminous US) to study seasonal and interannual trends from satellite data. Phenology metrics including start of season, end of season, duration of season, and seasonally integrated greenness were derived from 8 km AVHRR data over North America spanning the years 1982-2003. Trend analysis was performed on the annual summaries of the metrics to determine areas with increasing or decreasing trends for the time period under study. Results show only small areas of changing start of season, but the end of season is coming later over well defined areas of New England and SE Canada, principally as a result of land use changes. The total greenness metric is most striking at the shrub/tundra boundary of North America, indicating increasing vegetation vigor or possible vegetation conversion as a result of warming.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"390 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126931491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mountain pine beetle detection and monitoring: replication trials for early detection","authors":"A. Roberts, J. Northrup, R. Reich","doi":"10.1109/AMTRSI.2005.1469832","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469832","url":null,"abstract":"This paper reports replication results from a two year study to acquire, process and evaluate digitally converted aerial photographic imagery for the detection and monitoring of mountain pine beetle (MPB) infestations. In 2002/03 we demonstrated that it was possible to reliably detect a spreading MPB infestation at six different sites by late May early June. These results were supported by detailed ground truth and high resolution imagery that permitted the identification of individual trees at a crown resolution of up to 10cm pixels (>2000 pixels/crown). Our 2002 initial results were fully confirmed by our 2003 multispectral and colour negative imagery and hybrid supervised classification procedures. It is our opinion that this procedure should be taken to the operational trial phase to evaluate the performance of these imaging and classification procedures in a working context.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124815939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Denoising and wavelet-based feature extraction of MODIS multi-temporal vegetation signatures","authors":"L. Bruce, A. Mathur","doi":"10.2747/1548-1603.43.1.67","DOIUrl":"https://doi.org/10.2747/1548-1603.43.1.67","url":null,"abstract":"Temporal vegetation signatures (i.e., vegetation indices as functions of time) generated using the MODIS imagery poses many challenges, primarily due to signal-to-noise-related issues. This article describes the use of MODIS time-series data for the detection of specific tropical invasive species vegetation types. Due to challenges with the MODIS quality assurance data, a significant level of noise was present in the temporal signatures. This study investigated methods for denoising the vegetation temporal signatures, followed by a comparative analysis of three denoising methods to generate signatures for vegetation target detection. The analytical approach focused on the use of wavelet-based versus Fourier-based feature extraction methods. Methods included the development of a novel wavelet-based feature extraction method that quantifies the fundamental shape of the temporal signatures.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124452783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of multi-temporal remotely sensed data for monitoring land reclamation in Sudbury, Ontario (Canada)","authors":"A. Abuelgasim, C. Chung, C. Champagne, K. Staenz, S. Monet, K. Fung","doi":"10.1109/AMTRSI.2005.1469879","DOIUrl":"https://doi.org/10.1109/AMTRSI.2005.1469879","url":null,"abstract":"The industrial mining activities, conducted in the Sudbury area (Ontario, Canada) over the last 100 years, have had a significant environmental impact on the local ecosystems in the region. These impacts include habitat disturbance due to mine development, the impact of acid-generating tailings, and the effects of airborne pollution from smelting activities. The natural vegetation in the region was seriously affected, resulting in the loss of a significant portion of the vegetated cover and leading to soil erosion. As most mining regions, the city of greater Sudbury was faced with the challenges of restoration for the areas with significant ecological damage. Towards the end of the seventies, an ambitious Regional Reclamation Program was initiated for re-vegetating affected regions. Areas with significant disturbance and barren regions were limed to reduce soil acidity and immobilize metal contaminants. The planting of mixed grasses, trees and shrubs followed this process. The major species of interest were pines (Pinus resinosa, P. strobus, P. banksinana), birch (Betula papyrifera) and trembling aspen (Populus tremuloides). Planning ecological restoration activities and monitoring the results of these activities can be time consuming and expensive relying on field measurements alone. Multi-temporal remotely sensed imagery provides extensive repetitive coverage over large areas, with valuable geospatial and biological information. In this study, a multi-temporal data set of six Landsat TM images spanning a period of 20 years, was used to monitor the status of the vegetation cover, evaluate the success of the restoration program, and provide a base of information for the long-term monitoring of restored sites.","PeriodicalId":302923,"journal":{"name":"International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005.","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128279704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}