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A Spatiotemporal image Fusion Method for Predicting High-Resolution Satellite images 35th

A Spatiotemporal Image Fusion Method for Predicting High-Res...

35th International conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE)

作者： Chhabra, Vipul Kiran, R. Uday Xiao, Juan Reddy, P. Krishna Avtar, Ram IIIT Hyderabad Hyderabad Telangana India Univ Tokyo Tokyo Japan Univ AIZU Fukushima Japan Hokkaido Univ Grad Sch Environm Sci Sapporo Hokkaido 0600810 Japan

ISBN: (纸本)9783031085307;9783031085291

Given a coarse satellite image and a fine satellite image of a particular location taken at the same time, the high-resolution spatiotemporal image fusion technique involves understanding the spatial correlation between the pixels of both images and using it to generate a finer image for a given coarse (or test) image taken at a later time. This technique is extensively used for monitoring agricultural land cover, forest cover, etc. The two key issues in this technique are: (i) handling missing pixel data and (ii) improving the prediction accuracy of the fine image generated from the given test coarse image. This paper tackles these two issues by proposing an efficient method consisting of the following three basic steps: (i) imputation of missing pixels using neighborhood information, (ii) cross-scale matching to adjust both the Point Spread Functions Effect (PSF) and geo-registration errors between the course and high-resolution images, and (iii) error-based modulation, which uses pixel-based multiplicative factors and residuals to fix the error caused due to modulation of temporal changes. The experimental results on the real-world satellite imagery datasets demonstrate that the proposed model outperforms the state-of-art by accurately producing the high-resolution satellite images closer to the ground truth.

关键词： Satellite images Monitoring Land cover image fusion

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DYNAMICS OF SPATIO-temporal URBAN EXPANSION IN SOUTH WEST DELHI REGION: A geo-spatial APPROACH FOR URBAN DISASTER MANAGEMENT

DYNAMICS OF SPATIO-TEMPORAL URBAN EXPANSION IN SOUTH WEST DE...

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conference on geo-information for Disaster Management (Gi4DM)

作者： Sharma, N. Kaur, A. Bose, P. Guru Gobind Singh Indraprastha Univ New Delhi India Govt NCT Delhi GeoSpatial Delhi Ltd New Delhi India

Constantly increasing population and up-scaling economic growth has certainly contributed to fast-paced urban expansion, but simultaneously, as a result, has developed immense pressure on our natural resources. Among other unfavorable consequences, this has led to significant changes in the land use and land cover patterns in megacities all across the globe. As the impact of uncontrolled and unplanned development continues to alter life patterns, it has become imperative to study severe problems resulting from rapid development and leading to environmental pollution, disruptions in ecological structures, ever increasing pressure on natural resources and recurring urban disasters This paper presents an approach to address these challenges using geospatial data to study the land use and land cover change and the patterns and processes of urban growth. Spatio-temporal changes in land-use/land-cover were assessed over the years using multi-date high resolution satellite data. The land use classification was conducted using visual image interpretation technique wherein, study area was categorized into five different classes based on NRSC classification system namely agricultural, built-up, urban green (forest), and fallow land and water bodies. Post-classification change detection technique was used for the assessment of land-cover change and transition matrices of urban expansion were developed to quantify the changes. The results show that the city has been expanding majorly in its borders, where land masses have been converted from agriculture based rural areas to urban structures. An increase in the built-up category was observed with the transformation of agricultural and marginal land with an approximate change of 8.62% in the peri-urban areas. Urban areas are becoming more densely populated and open barren lands are converted into urban areas due to over population and migration from the rural areas of Delhi and thus increasing threat towards urban disaster. Conse

关键词： Spatio-temporal Urban Expansion geo-spatial Land use/land cover Population Urban Disaster

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WILDFIRE DAMAGE ASSESSMENT USING MULTI-temporal SENTINEL-2 data

WILDFIRE DAMAGE ASSESSMENT USING MULTI-TEMPORAL SENTINEL-2 D...

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conference on geo-information for Disaster Management (Gi4DM)

作者： Chung, M. Jung, M. Kim, Y. Seoul Natl Univ Dept Civil & Environm Engn Seoul South Korea

Recently, the drastic climate changes have increased the importance of wildfire monitoring and damage assessment as well as the possibility of wildfire occurrence. Estimation of wildfire damage provides the information on wildfire-induced ecological changes and supports the decision-making process for post-fire treatment activities. For accurate wildfire damage assessment, the discrimination between disaster-induced and natural changes is crucial because they usually coupled together. In this study, Sentinel-2 images were employed to assess the damage from a wildfire, which occurred in the coniferous forest of Gangneung, Gangwon Province, South Korea on April 2019. The images were captured from both Sentinel-2A and -2B, shortening the temporal interval of available pre- and post-fire images. Multi-temporal image analysis was performed in both object and pixel-based with two commonly used spectral indices, NDVI and NBR. Additional image pair from the same period of 2018 was used to distinguish the fire-affected regions from the naturally changed area and compared with the results from using only one pair of images from 2019. The experimental results showed that the change detection performance could be affected by the number of image pairs and spectral indices used to discriminate burned region from unburned region. Thus it verified the significance of adequately employing annual multi-pair satellite images for wildfire damage assessment.

关键词： Wildfire damage assessment Multi-temporal image analysis OBIA Change detection Sentinel-2

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ASSESSMENT OF LANDSLIDE-INDUCED MORPHOLOGY CHANGES USING AN OBJECT-BASED image ANALYSIS APPROACH: A CASE STUDY OF HITARDALUR, ICELAND

ASSESSMENT OF LANDSLIDE-INDUCED MORPHOLOGY CHANGES USING AN ...

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conference on geo-information for Disaster Management (Gi4DM)

作者： Dabiri, Z. Hoelbling, D. Abad, L. Tiede, D. Univ Salzburg Dept Geoinformat Z GIS A-5020 Salzburg Austria

On July 7, 2018, a large landslide occurred at the eastern slope of the Fagraskogarfjall Mountain in Hitardalur valley in West Iceland. The landslide dammed the river, led to the formation of a lake and, consequently, to a change in the river course. The main focus of this research is to develop a knowledge-based expert system using an object-based image analysis (OBIA) approach for identifying morphology changes caused by the Hitardalur landslide. We use synthetic aperture radar (SAR) and optical remote sensing data, in particular from Sentinel-1/2 for detection of the landslide and its effects on the river system. We extracted and classified the landslide area, the landslide-dammed lake, other lakes and the river course using intensity information from S1 and spectral information from S2 in the object-based framework. Future research will focus on further developing this approach to support mapping and monitoring of the spatio-temporal dynamics of surface morphology in an object-based framework by combining SAR and optical data. The results can reveal details on the applicability of different remote sensing data for the spatio-temporal investigation of landslides, landslide-induced river course changes and lake formation and lead to a better understanding of the impact of large landslides on river systems.

关键词： Landslide Earth Observation (EO) River System Object-Based image Analysis (OBIA) Sentinel-1 Iceland

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THE USE OF MULTI-temporal SENTINEL SATELLITES IN THE ANALYSIS OF LAND COVER/LAND USE CHANGES CAUSED BY THE NUCLEAR POWER PLANT CONSTRUCTION

THE USE OF MULTI-TEMPORAL SENTINEL SATELLITES IN THE ANALYSI...

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conference on geo-information for Disaster Management (Gi4DM)

作者： Colak, E. Chandra, M. Sunar, F. ITU Geomat Engn Grad Program Civil Engn Fac TR-80626 Maslak Turkey Tech Univ Chemnitz Chemnitz Germany ITU Geomat Engn Dept Civil Engn Fac TR-80626 Maslak Turkey

Turkey, due to increased demand for energy has made plans for nuclear power generation since 1970. Sinop Nuclear Power Plant, which will be built on Sinop Inceburun peninsula at the Black Sea coast of Turkey, is one of the three different nuclear power plants planned to be built in Turkey. The Sinop Nuclear Power Plant consist of four different reactors. The construction of the first unit is expected to be completed by 2023, and the fourth unit is planned to be activated by 2028. On the other hand, the construction of the nuclear power plant will alter the land use at the actual plant site and its surroundings and hence may cause significant environmental changes. As an indicator, more than 650000 trees have been cut so far for the construction of nuclear power plant, and this can adversely affect the ecological balances of the region by endangering habitats and creating ecological damages. The aim of this study is to analyse the land use/land cover changes (LULC) in the forestry-dominated areas due to the construction of nuclear power plants using the multi-temporal Synthetic Aperture Radar (SAR) and optical satellite images. For this purpose, different change detection methods such as SAR intensity image differencing, supervised image classification method (Support Vector Machine algorithm) were applied to Sentinel 1 satellite image datasets (2016-2019) to evaluate the annual changes due to construction. In addition, a correlation analysis was performed between the canopy structure and vegetation biomass using Sentinel 2 NDVI dataset (2016-2019) and calibrated Sentinel 1 backscatter values. Furthermore, using the Google Earth Engine (GEE), the Landsat 8 NDVI time series of the affected forest area, generated at 8-day intervals, was used to validate changes in vegetation.

关键词： Multi-temporal data Change Detection Nuclear Power Plant Sentinel 1& 2

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MULTI-temporal HIGH-RESOLUTION LANDSLIDE MONITORING BASED ON UAS PHOTOGRAMMETRY AND UAS LIDAR geoINFORMATION

MULTI-TEMPORAL HIGH-RESOLUTION LANDSLIDE MONITORING BASED ON...

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conference on geo-information for Disaster Management (Gi4DM)

作者： Hung, C-L J. Tseng, C-W Huang, M-J Tseng, C-M Chang, K-J Taiwan Forestry Res Inst Div Watershed Management Taipei Taiwan Natl Taipei Univ Technol Dept Civil Engn Taipei Taiwan Chang Jung Christian Univ Dept Land Management & Dev Tainan Taiwan

Due to the high seismicity and high annual rainfall, numerous landslides occurred and caused severe impacts in Taiwan. Typhoon Morakot in 2009 brought extreme and long-time rainfall, and caused severe disasters. After 2009, numerous large scale deep-seated landslides may still creeping, however not necessary easily to inspect the activity. In recent years, the remote sensing technology improves rapidly, providing a wide range of image, essential and precious geoinformation. Accordingly, the Small unmanned aircraft system (sUAS) has been widely used in landslide monitoring and geomorphic change detection. This study used UAS to continuously monitor a landslide area in Baolai Village in southern Taiwan, which had a catastrophic landslide event triggered by heavy rainfall caused by Typhoon Morakot in 2009. In order to accesses the potential hazards, this study integrates UAS, field geomatic survey, terrestrial laser scanner (ground LiDAR), and UAS LiDAR for sequential data acquisition since 2015. Based on the methods we are able to construct multi-temporal and high resolution DTMs, so as to access the activity and to monitoring the creeping landslides. The data set are qualified from 21 ground control points (GCPs) and 11 check points (CPs) based on real-time kinematic-global positioning system (RTK- GPS) and VBS RTK-GPS (e-GNSS). More than 10 UAS flight missions for the study areas dated since 2015, for an area large than 5-40 Km(2) with 8-12 cm spatial resolution (GSD). Then, the datasets was compared with the airborne LiDAR data, to evaluate the quality and the interpretability of the dataset. Since early 2018, we integrate UAS LiDAR technology to scanning the sliding area. The density of the point cloud data sets are higher than 250 and 100 points/m(2) for the total and ground point, respectively. The spatial distributions of geomorphologic changes were quantified firstly with the GCPS and CPs. The potential disaster was evaluated at different times, and the result

关键词： UAS/UAV DEM of Difference (DoD) geomorphometry environment change detection accuracy assessment

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Multi-Modal and Multi-temporal data Fusion: Outcome of the 2012 GRSS data Fusion Contest

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2013年第3期6卷 1324-1340页

作者： Berger, Christian Voltersen, Michael Eckardt, Robert Eberle, Jonas Heyer, Thomas Salepci, Nesrin Hese, Soeren Schmullius, Christiane Tao, Junyi Auer, Stefan Bamler, Richard Ewald, Ken Gartley, Michael Jacobson, John Buswell, Alan Du, Qian Pacifici, Fabio Univ Jena Inst Geog Dept Earth Observat D-07743 Jena Germany German Aerosp Ctr DLR Remote Sensing Technol Inst IMF D-82234 Oberpfaffenhofen Germany Tech Univ Munich Chair Remote Sensing Technol D-80333 Munich Germany Ball Aerosp & Technol Fairborn OH 45324 USA Rochester Inst Technol Ctr Imaging Sci Rochester NY 14623 USA Natl Air & Space Intelligence Ctr Wright Patterson AFB OH 45433 USA Mississippi State Univ Dept Elect & Comp Engn Mississippi State MS 39762 USA DigitalGlobe Inc Longmont CO 80503 USA

The 2012 data Fusion Contest organized by the data Fusion Technical Committee (DFTC) of the IEEE geo-science and Remote Sensing Society (GRSS) aimed at investigating the potential use of very high spatial resolution (VHR) multi-modal/multi-temporal image fusion. Three different types of data sets, including spaceborne multi-spectral, spaceborne synthetic aperture radar (SAR), and airborne light detection and ranging (LiDAR) data collected over the downtown San Francisco area were distributed during the Contest. This paper highlights the three awarded research contributions which investigate (i) a new metric to assess urban density (UD) from multi-spectral and LiDAR data, (ii) simulation-based techniques to jointly use SAR and LiDAR data for image interpretation and change detection, and (iii) radiosity methods to improve surface reflectance retrievals of optical data in complex illumination environments. In particular, they demonstrate the usefulness of LiDAR data when fused with optical or SAR data. We believe these interesting investigations will stimulate further research in the related areas.

关键词： data fusion LiDAR multi-modal multi-temporal optical SAR urban VHR imagery

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Parallax Visualization of UAV FMV and WAMI imagery

Parallax Visualization of UAV FMV and WAMI Imagery

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conference on Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX

作者： Mayhew, Christopher A. Mayhew, Craig M. Vis III Imaging Inc Vienna VA USA

ISBN: (纸本)9780819490384

The US Military is increasingly relying on the use of unmanned aerial vehicles (UAV) for intelligence, surveillance, and reconnaissance (ISR) missions. Complex arrays of Full-Motion Video (FMV), Wide-Area Motion Imaging (WAMI) and Wide Area Airborne Surveillance (WAAS) technologies are being deployed on UAV platforms for ISR applications. Nevertheless, these systems are only as effective as the image Analyst's (IA) ability to extract relevant information from the data. A variety of tools assist in the analysis of imagery captured with UAV sensors. However, until now, none has been developed to extract and visualize parallax three-dimensional information.(1) Parallax Visualization (PV) is a technique that produces a near-three-dimensional visual response to standard UAV imagery. The overlapping nature of UAV imagery lends itself to parallax visualization. Parallax differences can be obtained by selecting frames that differ in time and, therefore, points of view of the area of interest. PV is accomplished using software tools to critically align a common point in two views while alternately displaying both views in a square-wave manner. Humans produce an autostereoscopic response to critically aligned parallax information presented alternately on a standard unaided display at frequencies between 3 and 6 Hz.(2) This simple technique allows for the exploitation of spatial and temporal differences in image sequences to enhance depth, size, and spatial relationships of objects in areas of interest. PV of UAV imagery has been successfully performed in several US Military exercises over the last two years.(3)

关键词： ISR PED UAV WAMI WAAS FMV DCGS parallax visualization autostereoscopic stereoscopic 3D three-dimensional square-wave switching alternating pairs critical alignment parallax-scanning

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Constrained Linear Spectral Unmixing Technique for Regional Land Cover Mapping Using MODIS data

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International conference on Systems, Computing Science and Software Engineering

作者： Kumar, Uttam Kerle, Norman Ramachandra, T., V Indian Inst Sci Ctr Ecol Sci Energy Res Grp Bangalore 560012 Karnataka India Indian Inst Sci Centre Sustainable Technol Bangalore 560012 Karnataka India Earth Observat ITC Internatl Inst Geo Informat Sci NL-7500 AA Enschede Netherlands

ISBN: (纸本)9781402087349

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up-to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat-TM/ETM+, IRS-ICID LISS-iii/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 in), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end-members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-iii classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications. Index Terms-Remote sensing, digital

关键词： Remote sensing digital image processing superspectral geographic Information System

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Proceedings of SPIE: geo-spatial and temporal image and data exploitation iii

Proceedings of SPIE: Geo-Spatial and Temporal Image and Data...

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PROCEEDINGS OF SPIE SPIE - The International Society for Optical Engineering: geo-spatial and temporal image and data exploitation iii

The proceedings contains 26 papers from the Proceedings of SPIE: geo-spatial and temporal image and data exploitation iii. Topics discussed include: efficient radiometrically accurate synthetic representation of IR scenes;imaging radiometer overlay model for infrared scene synthesis;virtual reality technology for lidar data analysis and prediction of thermal crossover based on imaging measurements over the diurnal cycle.

关键词： Infrared imaging

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