- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Fusion of Multi-Temporal Interferometric Coherence and Optical Image Data for the 2016 Kumamoto Earthquake Damage Assessment
摘要： Earthquakes are one of the most devastating types of natural disasters, and happen with little to no warning. This study combined Landsat-8 and interferometric ALOS-2 coherence data without training area techniques by classifying the remote sensing ratios of specific features for damage assessment. Waterbodies and highly vegetated areas were extracted by the modified normalized difference water index (MNDWI) and normalized difference vegetation index (NDVI), respectively, from after-earthquake images in order to improve the accuracy of damage maps. Urban areas were classified from pre-event interferometric coherence data. The affected areas from the earthquake were detected with the normalized difference (ND) between the pre- and co-event interferometric coherence. The results presented three damage types; namely, damage to buildings caused by ground motion, liquefaction, and landslides. The overall accuracy (94%) of the confusion matrix was excellent. Results for urban areas were divided into three damage levels (e.g., none–slight, slight–heavy, heavy–destructive) at a high (90%) overall accuracy level. Moreover, data on buildings damaged by liquefaction and landslides were in good agreement with field survey information. Overall, this study illustrates an effective damage assessment mapping approach that can support post-earthquake management activities for future events, especially in areas where geographical data are sparse.
关键词： damage assessment,Landsat-8,ALOS-2 interferometric coherence,urban damage area,liquefaction,landslides,Kumamoto earthquake
更新于2025-09-23 15:23:52
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Enhancing multispectral remote sensing data interpretation for historical gold mines in Egypt: a case study from Madari gold mine
摘要： In the last decade, most of the outcrops around the historic gold mines in Egypt had been damaged by the local miners, a situation that complicated remote sensing-based exploration research activities. Madari gold mine area was no more fortunate than other mines in the region. This study identifies a new integrated remote sensing workflow that emphasizes the spectral variations related to differences in chemical and mineralogical compositions of the investigated rock units and deemphasizes the spectral variations introduced by the local miners. All combinations of ratio images are first generated from Landsat 8 Operational Land Imager (OLI) data, then a suite of ratio images that best differentiates between the investigated units is selected, and finally the selected ratio images were stacked to substitute the original image bands in the further processing techniques. The PCA was then applied to the selected ratio images within the stack. Subsequently, a statistical analysis of the eigenvector matrix for each of the PC bands was conducted to select the optimum PC bands and a Principal Component False Color Composite image (PC-FCC) was created from the three selected PC bands. The PC-FCC image (PC3, PC11, PC4 in RGB) was chosen as a result of subtracting the average PC eigenvector negative weights from the average positive eigenvectors weights. Not only was the PC-FCC image used to distinguish the main rock units in the damaged area, but also, to identify the areas with intense alteration zones.
关键词： Eastern Desert,Principal component analysis (PCA),Landsat 8 (OLI),Madari gold mine,Egypt,Ratio images
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Investigating the Relationship Between Shallow Groundwater, Soil Moisture and Land Surface Temperature Using Remotely Sensed Data
摘要： Shallow groundwater has a decisive impact on land surface temperature (LST) and soil moisture (SM). In the present paper relationship between shallow groundwater, SM and LST was studied. For this purpose, the groundwater level and soil moisture were measured in 59 and 39 locations respectively in the southwest of Iran, during June 2016, Simultaneous with the overpass of a Landsat 8 satellite from the study site. After necessary image processing the LST was retrieved from the Landsat image using the split window algorithm. Then relationship between retrieved LST and different field observation were studied. Results show that there is a significant relationship between the groundwater depth and SM with LST. These results indicate that shallow groundwater depth and soil moisture content could be estimated and mapped using the retrieved LST from the satellite imagery.
关键词： Remote Sensing,LST,Landsat 8,Shallow Groundwater,Soil moisture
更新于2025-09-23 15:23:52
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Synergistic Use of Optical and Dual-Polarized SAR Data With Multiple Kernel Learning for Urban Impervious Surface Mapping
摘要： Accurate mapping of impervious surface distribution is important but challenging. Integrating optical and SAR data to improve urban impervious surface estimation has recently shown promising performance. Further investigation and development on this multisensory approach are conducted in this study. A novel multiple kernel learning (MKL) framework is proposed to integrate heterogeneous features from Landsat-8 and Sentinel-1A data effectively. A linearly weighted combination of basic kernels built using each group of features is learned as the optimal kernel, while the hyperparameters and the weight of each basic kernel are determined simultaneously by using the differential evolution algorithm. Then, the optimal kernel is embedded into the support vector regression algorithm, and the impervious surface abundance of the study area is estimated by applying the developed multiple kernel support vector regression (MKSVR) model. The impervious surface ground truth at a subpixel level is derived from a high-resolution image by means of object-oriented classification. The experimental results indicate that the synergistic use of optical and dual-pol SAR data by employing MKSVR achieves a noteworthy improvement for impervious surface estimation compared to that using optical image alone, the root mean square error is decreased by 4.30%, and the coefficient of determination (R2) is increased by 9.47%, and that the incorporation of optical and SAR does not guarantee the improved performance, simply stacking all features of multisource data into a vector is not a good choice, and the MKL is a powerful tool to apply as demonstrated by the experiments conducted in this study.
关键词： Landsat-8,Heterogeneous features,Sentinel-1A,multiple kernel support vector regression (MKSVR),impervious surface abundance
更新于2025-09-23 15:23:52
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Geometric accuracy of remote sensing images over oceans: The use of global offshore platforms
摘要： The geometric accuracy of tens of millions of scenes of medium-resolution remote sensing (RS) images collected in the past 45 years has been systematically evaluated for land scenes, but the accuracy of ocean scenes is poorly known due to the lack of ground control points (GCPs). In this study, the locations of offshore platforms are first derived from time-series of Landsat-8 OLI images, and are then used as offshore reference points to systematically assess the geometric performance of RS images covering offshore oil/gas development areas. An inventory of 16,131 offshore platforms at the global scale is established, and then a novel method using the position-invariant characteristic of offshore platforms and the coherent characteristic of the geometric shift among tie-points (i.e. between sensed points from to-be-assessed images and the corresponding OLI-derived reference points) is developed for assessing the geometric accuracy of Landsat and other RS images. The method has been applied to 112,935 Landsat scenes (~1.87% of the entire archive) over oceans. The results indicate an optimal performance of Landsat OLI images (both pre-collection and Collection-1) but a less reliable performance of Landsat TM/ETM+ L1TP images. Approximately 50% of TM L1GS and ETM+ L1GT images have at least 2 pixels of geometric error. The new reference points inventory and the developed method were also applied to many other low-resolution and finer-resolution imagery (e.g. VIIRS Night-fire product, Terra/Aqua MODIS active fire product, ENVISAT ASAR, ALOS-1 PALSAR, Sentinel-1 SAR, Sentinel-2 MSI, the National Agriculture Imagery Program (NAIP) aerial images, and images from several Chinese satellites), and a quantitative description of the geometric accuracy of these sensors is also presented. The findings suggest that the new offshore reference point inventory is probably useful to help establish more robust offshore GCPs for U.S. Geological Survey (USGS) GCP library and further improve the ongoing USGS Global GCP improvement plan and European Space Agency Global Reference Image plan.
关键词： Offshore platforms,Remote sensing images,Landsat,Geometric accuracy,Ground control points
更新于2025-09-23 15:23:52
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Large-Area Gap Filling of Landsat Reflectance Time Series by Spectral-Angle-Mapper Based Spatio-Temporal Similarity (SAMSTS)
摘要： Landsat time series commonly contain missing observations, i.e., gaps, due to the orbit and sensing geometry, data acquisition strategy, and cloud contamination. A spectral-angle-mapper (SAM) based spatio-temporal similarity (SAMSTS) gap-filling algorithm is presented that is designed to fill small and large area gaps in Landsat data, using one year or less of data and without using other satellite data. Each gap pixel is filled by an alternative similar pixel that is located in a non-missing region of the image. The alternative similar pixel locations are identified by comparison of reflectance time series using a SAM metric revised to be adaptive to missing observations. A time series segmentation-and-clustering approach is used to increase the search efficiency. The SAMSTS algorithm is demonstrated using six months of Landsat 8 Operational Land Imager (OLI) reflectance time series over three 150 × 150 km (5000 × 5000 30 m pixels) areas in California, Minnesota and Kansas. The three areas contain different land cover types, especially crops that have different phenology and abrupt changes due to agricultural harvesting, which make gap filling challenging. Fillings on simulated gaps, which are equivalent to 36% of 5000 × 5000 images in each test area, are presented. The gap filling accuracy is assessed quantitatively, and the SAMSTS algorithm is shown to perform better than the simple closest temporal pixel substitution gap filling approach and the sinusoidal harmonic model-based gap filling approach. The SAMSTS algorithm provides gap-filled data with five-band reflective-wavelength root-mean-square differences less the 0.02, which is comparable to the OLI reflectance calibration accuracy.
关键词： Landsat,reflectance,time series,spectral angle mapper,gap filling
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Towards Joint Land Cover and Crop Type Mapping with Numerous Classes
摘要： The detailed, accurate and frequent land cover and crop-type mapping emerge as essential for several scientific communities and geospatial applications. This paper presents a methodology for the semi-automatic production of land cover and crop type maps using a highly analytic nomenclature of more than 40 classes. An intensive manual annotation procedure was carried out for the production of reference data. A class nomenclature based on CORINE land cover Level-3 was employed along with several additional crop-type classes. Multitemporal surface reflectance Landsat-8 data for the year of 2016 were used for all classification experiments with a linear SVM classifier. Quantitative and qualitative evaluation highlighted the efficiency of the proposed approach achieving high accuracy rates. Further analysis on individual classes’ performance highlighted the challenges in the proposed classification scheme as well as important outcomes regarding the spectral behavior of the considered categories.
关键词： support vector machines,CORINE Land Cover,Landsat-8,classification
更新于2025-09-23 15:23:52
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[IEEE 2018 14th International Conference on Emerging Technologies (ICET) - Islamabad, Pakistan (2018.11.21-2018.11.22)] 2018 14th International Conference on Emerging Technologies (ICET) - Identification and mapping of coral reefs using Landsat 8 OLI in Astola Island, Pakistan coastal ocean
摘要： Recent field surveys have reported the presence of corals in many places in the Pakistan coastal ocean; Astola Island especially has been a subject of interest with regards to corals and overall marine biodiversity, and has in fact recently been declared Pakistan’s first Marine Protected Area. This study presents an analysis of coral reefs identification and their spatial distribution through optical satellite remote sensing in the surrounding area of Astola Island. Besides remote sensing data, the study considers sea survey data collected by divers in recent years. A benthic map of ocean ecosystem habitats is generated, through processing of Landsat 8 OLI (Operational Land Imager) imagery. The satellite data was selected at low-tide time to get maximum sunlight penetration in shallow water. Water-column correction was used to generate the depth-invariant index on multiple band-pairs. Water column corrected depth-invariant index bands were then segmented and classified through object-based classification. The results from the remote sensing data processing over Astola Island show good agreement with the field survey data, with nearly all the field survey points of coral reefs falling within the coral reefs class. Use of remote sensing imagery such as Landsat 8, and application of the water column correction method can allow for regular monitoring and management of coral reefs and other benthic ecosystems in the coastal ocean of Pakistan and coastal Arabian Sea.
关键词： Pan-sharpening,Landsat 8,Coral reefs,Object Base Image Analysis,Depth Invariant Index
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Landsat 9 Thermal Infrared Sensor 2 Characterization Plan Overview
摘要： Landsat 9 will continue the Landsat data record into its fifth decade with a near-copy build of Landsat 8 with launch scheduled for December 2020. The two instruments on Landsat 9 are Thermal Infrared Sensor-2 (TIRS-2) and Operational Land Imager-2 (OLI-2). TIRS-2 is a two-channel pushbroom imager with a 15-degree field of view that will have a 16-day measurement cadence from its nominal 705-km orbit altitude. Its carefully developed instrument performance requirements and associated characterization plan will result in stable and well-understood science-quality imagery that will be used for environmental, economic and legal applications. This paper will present a summary of the plan for TIRS-2 prelaunch characterization at the component, subsystem, and instrument level.
关键词： prelaunch characterization,calibration,Landsat 9,thermal infrared remote sensing,TIRS-2
更新于2025-09-23 15:22:29
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Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA
摘要： Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011–2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.
关键词： Wildfire,burned area,Landsat,Worldview-3,GeoEye-1,severity,Worldview-2,QuickBird-2,revegetation
更新于2025-09-23 15:22:29