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- 摘要
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- 实验方案
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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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Novel Gap Filling BARC with High Chemical Resistance
摘要： In the recent of the semiconductor manufacturing process, variety of properties (narrow gap-filling and planarity etc.) are required to organic BARC in addition to the conventional requirements. Moreover, SC-1 resistance is also needed because BARC is often used as a wet etching mask when TiN processing. But conventional BARC which include crosslinker does not have enough SC-1 resistance, and we found that it is also difficult to obtain good gap-filling and good planarity because of outgassing and film shrinkage derived from the crosslinker. In this study, we have developed the new self-crosslinking BARC. The new crosslinking system shows low outgassing and film shrinkage because of not including crosslinker. So, novel BARC has better gap filling property and planarity and over 3 times higher SC-1 resistance than that of conventional BARC. Moreover, by adding the low molecular weight additive which has high adhesive unit to TiN surface, the novel BARC has over 10 times higher SC-1 resistance than that of conventional BARC. And this novel BARC can be applied both ArF & KrF lithography process because of broad absorbance, high etching rate, chemical resistance (SC-1, SC-2, DHF, and others) and good film thickness uniformity. In this paper, we will discuss the detail of new self-crosslinking BARC in excellent total performance and our approach to achieve high chemical resistance.
关键词： KrF,ArF,Self-crosslinking,Gap filling,Planarity,Chemical resistance,BARC
更新于2025-09-23 15:22:29