Automatic Cloud Detection of GF4 Multispectral Imagery Supported by the Priori Terminal Pixel Library

Meiyan Shu; Xiaohe Gu; Lin Sun; Jinshan Zhu; Tingting Chen; Kai Wang; Quan Wang; Guijun Yang

doi:10.11873/j.issn.1004-0323.2020.1.0194

Remote Sensing Technology and Application 鈥衡�� 2020, Vol. 35 鈥衡�� Issue (1): 194-201.DOI: 10.11873/j.issn.1004-0323.2020.1.0194

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Automatic Cloud Detection of GF4 Multispectral Imagery Supported by the Priori Terminal Pixel Library

Meiyan Shu^1,^2,^3,⁴(),Xiaohe Gu^2,^3,⁴,Lin Sun¹(),Jinshan Zhu¹,Tingting Chen¹,Kai Wang¹,Quan Wang¹,Guijun Yang^1,^2,^3,⁴

^1. College of Surveying Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
^2. Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
^3. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
^4. Beijing Engineering Research Center for Agriculture Internet of Things, Beijing 100097, China

Received:2018-11-01 Revised:2019-10-21 Online:2020-04-01 Published:2020-02-20
Contact: Lin Sun

鍏堥獙缁堢鍍忓厓搴撴敮鎸佷笅鐨凣F-4澶氬厜璋卞奖鍍忚嚜鍔ㄤ簯妫�娴�

鏉熺編鑹�^1,^2,^3,⁴(),椤炬檽楣�^2,^3,⁴,瀛欐灄¹(),鏈遍噾灞�¹,闄堝┓濠�¹,鐜嬪嚡¹,鐜嬫潈¹,鏉ㄨ吹鍐�^1,^2,^3,⁴

^1. 灞变笢绉戞妧澶у娴嬬粯绉戝涓庡伐绋嬪闄� 灞变笢闈掑矝 266590
^2. 鍐滀笟閮ㄥ啘涓氶仴鎰熸満鐞嗕笌瀹氶噺閬ユ劅閲嶇偣瀹為獙瀹わ紝鍖椾含鍐滀笟淇℃伅鎶�鏈爺绌朵腑蹇冿紝鍖椾含 100097
^3. 鍥藉鍐滀笟淇℃伅鍖栧伐绋嬫妧鏈爺绌朵腑蹇冿紝鍖椾含 100097
^4. 鍖椾含甯傚啘涓氱墿鑱旂綉宸ョ▼鎶�鏈爺绌朵腑蹇冿紝鍖椾含 100097

閫氳浣滆��: 瀛欐灄
浣滆�呯畝浠�:鏉熺編鑹筹紙1993-锛夛紝濂筹紝娌冲崡鍛ㄥ彛浜猴紝纭曞＋鐮旂┒鐢�,涓昏浠庝簨瀹氶噺閬ユ劅鏂归潰鐨勭爺绌躲�侲?mail:2448858578@qq.com銆�
鍩洪噾璧勫姪:
鍥藉鑷劧绉戝鍩洪噾椤圭洰(41571323);灞变笢鐪佽嚜鐒剁瀛﹀熀閲戦」鐩�(ZR201702210379);鍖椾含甯傝嚜鐒剁瀛﹀熀閲戦」鐩�(6172011);鍖椾含甯傚啘鏋楃瀛﹂櫌鍒涙柊鑳藉姏寤鸿涓撻」(KJCX20170705)

Abstract

Abstract:

The GaoFen4 (GF4) satellite is China鈥檚 first geo-synchronous orbit remote sensing satellite. With the advantages of high frequency and wide width, it can provide fast and stable optical remote sensing images for agricultural, forestry, disaster reduction, meteorology, environmental protection, water conservancy and other applications in China. Efficient image automatic cloud detection helps to further improve the utilization efficiency of GaoFen4 images. CDAG锛圕loud Detection Algorihtm-Generating锛塁loud detection is an automatic cloud detection algorithm based on spectral analysis of pixel components, which can effectively reduce the influence of mixed pixels, complex surface structure and atmosphere. This paper aims to explore the application of CDAG algorithm in cloud detection of GaoFen4 multispectral imagery (GF4-PMS). Firstly, different cloud types and surface cover types were selected from hyperspectral images (AVIRIS) to establish cloud pixel library and clear sky pixel library. Next, the pixel library of multispectral images was simulated based on Hyperspectral pixel library and spectral response function of GF4-PMS sensor. Then, according to the spectral difference analysis of broken cloud, thin cloud, thick cloud and non-cloud pixel, the similarity probability analysis was performed on the to-be-detected pixel of the GF4-PMS image and the terminal pixel, and the GF4-PMS image cloud detection based on the optimal threshold automatic iteration was realized. Finally, cloud detection accuracy verification was carried out from multiple indicators such as cloud pixel correct rate, clear sky pixel correct rate, false positive rate and missed rate. The results show that AVIRIS images can effectively extract terminal pixel libraries for GF4-PMS image cloud detection. Clouds of Various types on GF4-PMS images can be better identified based on the CDAG algorithm. The accuracy of detection results for broken clouds, thin clouds and thick clouds with different time phases and different underlying surfaces can reach more than 90%. Therefore, the cloud detection method based on the priori terminal pixel library has a good application value for improving the utilization efficiency of GF4-PMS images.

Key words: CDAG algorithm, GF4-PMS, Cloud detection, Pixel library, Data simulation

鎽樿锛�

楂樺垎鍥涘彿鍗槦鏄垜鍥界涓�棰楀湴鐞冨悓姝ヨ建閬撻仴鎰熷崼鏄燂紝浠ュ叾楂橀銆佸骞呯殑鐗圭偣锛屽彲涓烘垜鍥藉啘涓氥�佹灄涓氥�佸噺鐏俱�佹皵璞°�佺幆淇濆拰姘村埄绛夊簲鐢ㄦ彁渚涘揩閫熴�佺ǔ瀹氱殑鍏夊閬ユ劅褰卞儚锛岄珮鏁堢殑褰卞儚鑷姩浜戞娴嬫湁鍔╀簬杩涗竴姝ユ彁楂橀珮鍒嗗洓鍙峰奖鍍忕殑鍒╃敤鏁堢巼銆侰DAG锛圕loud Detection Algorithm-Generating锛夋槸涓�绉嶅熀浜庡儚鍏冪粍鍒嗗厜璋卞垎鏋愮殑鑷姩浜戞娴嬬畻娉曪紝鑳芥湁鏁堥檷浣庢贩鍚堝儚鍏冦�佸鏉傝〃闈㈢粨鏋勫拰澶ф皵绛夊洜绱犵殑褰卞搷銆備负浜嗘帰绱DAG绠楁硶瀵逛簬楂樺垎4鍙峰鍏夎氨褰卞儚锛圙F4-PMS锛夌殑浜戞娴嬪簲鐢ㄨ兘鍔涳紝棣栧厛锛屼粠楂樺厜璋卞奖鍍忥紙AVIRIS锛変笂閫夊彇涓嶅悓鐨勪簯绫诲瀷鍜屽悇绉嶅湴琛ㄨ鐩栫被鍨嬶紝寤虹珛浜戝儚鍏冨簱鍜屽湴鐗╁儚鍏冨簱锛涘叾娆★紝鍩轰簬楂樺厜璋卞儚鍏冨簱鍜孏F4-PMS浼犳劅鍣ㄥ厜璋卞搷搴斿嚱鏁版ā鎷熷嚭澶氬厜璋卞奖鍍忓儚鍏冨簱锛涚劧鍚庯紝鏍规嵁纰庝簯銆佽杽浜戙�佸帤浜戝強闈炰簯鍍忓厓鐨勫厜璋卞樊寮傛�у垎鏋愶紝灏咷F4-PMS褰卞儚鐨勫緟妫�娴嬪儚鍏冧笌缁堢鍍忓厓杩涜鐩镐技姒傜巼鍒嗘瀽锛屽疄鐜板熀浜庢渶浣抽槇鍊艰嚜鍔ㄨ凯浠ｇ殑GF4-PMS褰卞儚浜戞娴嬶紱鏈�鍚庯紝浠庝簯鍍忓厓姝ｇ‘鐜囥�佹櫞绌哄儚鍏冩纭巼銆佽鍒ょ巼銆佹紡鍒ょ巼绛夊涓寚鏍囪繘琛屼簯妫�娴嬬簿搴﹂獙璇併�傜粨鏋滆〃鏄庯細AVIRIS褰卞儚鍙互鏈夋晥鎻愬彇閫傜敤浜嶨F4-PMS褰卞儚浜戞娴嬬殑缁堢鍍忓厓搴擄紝鍩轰簬CDAG绠楁硶鑳借緝濂藉湴璇嗗埆GF4-PMS褰卞儚涓婂悇绉嶇被鍨嬬殑浜戯紝瀵逛簬涓嶅悓鏃剁浉銆佷笉鍚屼笅鍨潰鐨勭浜戙�佽杽浜戙�佸帤浜戠殑妫�娴嬬簿搴﹀彲杈�90%浠ヤ笂銆傚洜姝わ紝鍩轰簬鍏堥獙缁堢鍍忓厓搴撶殑浜戞娴嬫硶瀵逛簬鎻愬崌GF4-PMS褰卞儚鐨勫埄鐢ㄦ晥鐜囧叿鏈夎緝濂界殑搴旂敤浠峰�笺��

鍏抽敭璇�: CDAG绠楁硶, GF4-PMS, 浜戞娴�, 鍍忓厓搴�, 鏁版嵁妯℃嫙

CLC Number:

TP701

Meiyan Shu,Xiaohe Gu,Lin Sun,Jinshan Zhu,Tingting Chen,Kai Wang,Quan Wang,Guijun Yang. Automatic Cloud Detection of GF4 Multispectral Imagery Supported by the Priori Terminal Pixel Library[J]. Remote Sensing Technology and Application, 2020, 35(1): 194-201.

鏉熺編鑹�,椤炬檽楣�,瀛欐灄,鏈遍噾灞�,闄堝┓濠�,鐜嬪嚡,鐜嬫潈,鏉ㄨ吹鍐�. 鍏堥獙缁堢鍍忓厓搴撴敮鎸佷笅鐨凣F-4澶氬厜璋卞奖鍍忚嚜鍔ㄤ簯妫�娴媅J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(1): 194-201.

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Automatic Cloud Detection of GF4 Multispectral Imagery Supported by the Priori Terminal Pixel Library

鍏堥獙缁堢鍍忓厓搴撴敮鎸佷笅鐨凣F-4澶氬厜璋卞奖鍍忚嚜鍔ㄤ簯妫�娴�

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