基于馬爾科夫分割的單極化SAR數(shù)據(jù)洪澇水體檢測方法
doi: 10.11999/JEIT180420 cstr: 32379.14.JEIT180420
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1.
中國科學院大學 ??北京 ??100049
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2.
中國科學院電子學研究所 ??北京 ??100190
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3.
中國科學院空間信息處理與應用系統(tǒng)技術重點實驗室 ??北京 ??100190
Single-polarization SAR Data Flood Water Detection Method Based on Markov Segmentation
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1.
University of Chinese Academy of Sciences, Beijing 100049, China
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2.
Insititute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
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3.
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China
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摘要:
我國是個洪澇災害多發(fā)的國家,每年7月、8月份洪澇災害時常發(fā)生。因此,實現(xiàn)洪澇受災區(qū)域的水體快速檢測對災害救援和評估具有重要的意義。高分3號SAR衛(wèi)星數(shù)據(jù)采用主動式對地觀測技術,全天時、全天候成像的特點在洪澇減災應用中具有明顯的優(yōu)勢。以湖南省洪澇災害區(qū)域快速檢測為目的,該文提出基于高分3號單極化SAR數(shù)據(jù)的洪澇區(qū)域水體快速檢測方法,包括SAR預處理,顧及SAR分布特性且保邊緣的馬爾科夫模型洪澇水體提取,基于SAR幾何構象模型的陰影虛警干擾去除等步驟,并利用人工檢測結果進行相對精度評價。測試結果表明,所提方法可以實現(xiàn)洪澇受災區(qū)域的快速、精確提取。
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關鍵詞:
- SAR /
- 高分3號衛(wèi)星 /
- 馬爾科夫隨機場 /
- 洪澇 /
- 減災
Abstract:China is a flood disaster-prone country, where floods occur frequently every year, from July to August. Therefore, rapid disaster detection and assessment of floods affected areas is of great significance. GF-3 SAR satellite data has obvious advantages of all-day, all-weather imaging characteristics in flood disaster reduction applications because of its active observation technology. For the purpose of rapid water detection in flooding area, a rapid detection method of flood area based on GF-3 single-polarized SAR data is proposed, including SAR preprocessing, flood extraction based on Markov random fields, shadow false alarm removal. Its detecting accuracy is evaluated with manual detection result. The test results show that this method can realize the rapid and accurate extraction of waters in flood disaster area.
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Key words:
- SAR /
- GF-3 /
- Markov Random Field (MRF) /
- Flood disaster /
- Disaster reduction
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表 2 災區(qū)水體自動提取效率分析(s)
計算
硬件生成
1B轉換
8位一致性
濾波受災區(qū)域
提取去除
陰影地理
編碼總時間 4核CPU 1 1 713 2 43 2 762 8核CPU 1 1 218 1 15 1 237 36核CPU 1 1 55 1 8 1 67 64核CPU 1 1 27 1 5 1 36 下載: 導出CSV
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