2001~2018年我国热异常点时空分布特征研究

葛强; 沈文举; 李冉; 李莘莘; 蔡坤; 左宪禹; 乔保军; 张云舟

doi:10.11873/j.issn.1004-0323.2022.1.0073

閬ユ劅鎶�鏈笌搴旂敤鈥衡�� 2022, Vol. 37 鈥衡�� Issue (1): 73-84.DOI: 10.11873/j.issn.1004-0323.2022.1.0073

鈥� 闈掍績浼氬崄鍛ㄥ勾涓撴爮鈥� 涓婁竴绡� 涓嬩竴绡�

2001~2018骞存垜鍥界儹寮傚父鐐规椂绌哄垎甯冪壒寰佺爺绌�

钁涘己^1,³(),娌堟枃涓�^2,³,鏉庡唹⁴,鏉庤帢鑾�⁵(),钄″潳^1,³,宸﹀绂�^2,³,涔斾繚鍐�^1,³,寮犱簯鑸�⁶

^1.娌冲崡澶у 娌冲崡鐪佸ぇ鏁版嵁鍒嗘瀽涓庡鐞嗛噸鐐瑰疄楠屽锛屾渤鍗� 寮�灏� 475004
^2.娌冲崡澶у 娌冲崡鐪佺┖闂翠俊鎭鐞嗗伐绋嬪疄楠屽锛屾渤鍗� 寮�灏� 475004
^3.娌冲崡澶у 璁＄畻鏈轰笌淇℃伅宸ョ▼瀛﹂櫌锛屾渤鍗� 寮�灏� 475004
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^5.涓浗绉戝闄㈢┖澶╀俊鎭垱鏂扮爺绌堕櫌锛岄仴鎰熺瀛﹀浗瀹堕噸鐐瑰疄楠屽锛屽寳浜� 100101
^6.鍥藉鏂囩墿灞�锛屽寳浜� 100010

鏀剁鏃ユ湡:2020-09-13 淇洖鏃ユ湡:2021-12-21 鍑虹増鏃ユ湡:2022-02-20 鍙戝竷鏃ユ湡:2022-04-08
閫氳浣滆��: 鏉庤帢鑾�
浣滆�呯畝浠�:钁涘己(1977-)锛岀敺锛屾渤鍗楁硨闃充汉锛屾暀鎺堬紝涓昏浠庝簨绌洪棿淇℃伅澶勭悊銆佸ぇ鏁版嵁鍒嗘瀽鐮旂┒銆侲?mail锛�gq@henu.edu.cn
鍩洪噾璧勫姪:
鍥藉鑷劧绉戝鍩洪噾椤圭洰(U1704122)

Research on the Temporal and Spatial Cistribution Characteristics of Thermal Anomalies in China from 2001 to 2018

Qiang Ge^1,³(),Wenju Shen^2,³,Ran Li⁴,Shenshen Li⁵(),Kun Cai^1,³,Xianyu Zuo^2,³,Baojun Qiao^1,³,Yunzhou Zhang⁶

^1.Henan Key Laboratory of Big Data Analysis and Processing锛孠aifeng 475004锛孋hina
^2.Henan Engineering Laboratory of Spatial Information Processing锛孠aifeng 475004锛孋hina
^3.School of Computer and Information Engineering锛孒enan University锛孠aifeng 475004锛孋hina
^4.Earth Observation System and Data Center锛孋NSA锛孌epartment of Achievement Transformation锛孊eijing 100101锛孋hina
^5.State Key Laboratory of Remote Sensing Science锛孖nstitute of Remote Sensing and Digital Earth锛孋hinese Academy of Sciences锛孊eijing 100101锛孋hina
^6.State Administration of Cultural Heritage of China锛孊eijing 100010锛孋hina

Received:2020-09-13 Revised:2021-12-21 Online:2022-02-20 Published:2022-04-08
Contact: Shenshen Li

鎽樿/Abstract

鎽樿锛�

鍩轰簬2001~2018骞碝ODIS鏍囧噯浜у搧锛岀爺绌朵簡鎴戝浗鍙婁竷澶у尯鍩熺儹寮傚父鐐圭殑鏃剁┖鍒嗗竷鐗瑰緛銆傜粨鏋滆〃鏄庯細绌洪棿鍒嗗竷涓婏紝鐑紓甯哥偣涓昏鍒嗗竷鍦ㄩ櫎瑗垮寳銆佽タ鍗椾箣澶栫殑澶ч儴鍒嗗湴鍖猴紱骞撮檯瓒嬪娍涓婏紝2001~2014骞撮棿鐑紓甯哥偣鏁伴噺鎸佺画涓婂崌锛屽勾鍧囧闀跨巼涓�15.01%锛�2015骞村悗閫愬勾涓嬮檷锛屽勾鍧囦笅闄嶇巼涓�14.96%銆傛湀瀛ｅ昂搴︿笂锛岀儹寮傚父鐐瑰湪鏄ャ�佺瀛ｈ妭鍑虹幇鏈�涓洪绻侊紙鏄ワ細551 716涓紝绉嬶細416 698涓級锛屾槬銆佺瀛ｇ浉瀵瑰湪涓滃寳鍦板尯鍒嗗竷鏈�澶氾紙鏄ワ細164 898涓紝绉嬶細186 727涓級锛屼笢鍖楀湴鍖烘湀鍧囨暟閲�10鏈堟渶楂橈紙118 274涓級锛涘瀛ｇ儹寮傚父鐐规暟閲忔渶浣庯紙290 793涓級锛屽鍒嗗竷浜庡崕涓滃湴鍖猴紙120 455涓級锛屽崕涓滃湴鍖烘湀鍧囨暟閲�6鏈堟渶楂橈紙76 465涓級锛涘啲瀛ｆ暟閲忎负358 483涓紝涓斿湪鍗庡崡鍦板尯鍒嗗竷鏈�澶氾紙108 209涓級锛屽崕鍗楀湴鍖烘湀鍧囨暟閲�1鏈堟渶楂橈紙37 770涓級銆傜爺绌舵湁鍔╀簬鎺屾彙鎴戝浗鍏稿瀷鍖哄煙鐨勬．鏋椼�佽崏鍘熺伀鐏撅紝浠ュ強鐢变簬绉哥鐒氱儳銆佸伐涓氭帓鏀剧瓑寮曡捣鐑紓甯哥殑鍙樺寲鎯呭喌锛岃繘鑰屼负鍖哄煙鐏惧闃叉不鍜岀幆澧冪洃娴嬫彁渚涙妧鏈敮鎾戙��

鍏抽敭璇�: 鐑紓甯哥偣, 绉哥鐒氱儳, 鏃剁┖鍒嗗竷, MODIS

Abstract:

In recent years锛� environmental pollution problems caused by straw burning and industrial emissions have become more serious. The use of satellite thermal abnormal products to analyze the temporal and spatial distribution of thermal abnormalities plays an important role in environmental monitoring. Based on MODIS standard products from 2001 to 2018锛� the temporal and spatial distribution characteristics of thermal anomalies in China and seven major regions are studied. The results showed that锛� in terms of spatial distribution锛� thermal anomalies are mainly distributed in most areas except Northwest and East China. In terms of inter-annual trends锛� the number of thermal anomalies continued to increase from 2001 to 2014 years锛� with an average annual growth rate of 15.01%锛� 2015 years After that锛� it decreased year by year锛� with an average annual decline rate of 14.96%. On month and season scales锛� thermal anomalies occur most frequently in spring and autumn 锛坰pring锛� 551 716锛� autumn锛� 416 698锛夛紝 Spring and autumn are relatively most distributed in Northeast China 锛坰pring锛� 164 898锛� autumn锛� 186 727锛�. The highest in October 锛�118 274锛夛紱 the lowest number of hot anomalies in summer 锛�290 793锛夛紝 mostly distributed in East China 锛�120 455锛夛紝 the average monthly number in East China is the highest in June 锛�76 465锛夛紱 the number in winter is 358 483锛� South China has the most distribution 锛�108 209锛夛紝 and South China has the highest monthly average number in January 锛�37 770锛�. This research is helpful to master forest and grassland fires in typical regions of China锛� as well as changes in thermal abnormalities caused by straw burning and industrial emissions锛� and then provide technical support for regional disaster prevention and environmental monitoring.

Key words: Thermal anomaly, Straw burning, Temporal and distribution, MODIS

涓浘鍒嗙被鍙�:

钁涘己,娌堟枃涓�,鏉庡唹,鏉庤帢鑾�,钄″潳,宸﹀绂�,涔斾繚鍐�,寮犱簯鑸�. 2001~2018骞存垜鍥界儹寮傚父鐐规椂绌哄垎甯冪壒寰佺爺绌禰J]. 閬ユ劅鎶�鏈笌搴旂敤, 2022, 37(1): 73-84.

Qiang Ge,Wenju Shen,Ran Li,Shenshen Li,Kun Cai,Xianyu Zuo,Baojun Qiao,Yunzhou Zhang. Research on the Temporal and Spatial Cistribution Characteristics of Thermal Anomalies in China from 2001 to 2018[J]. Remote Sensing Technology and Application, 2022, 37(1): 73-84.

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[6]	閯繆娲�,鐬垮缓鍗�,琚侀福楦�,寮犺春. 鍩轰簬娣卞害瀛︿範鐨勯浜戝洓鍙峰崼鏄熺豢鍏夐�氶亾鏋勫缓鏂规硶[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2023, 38(1): 214-226.
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2001~2018骞存垜鍥界儹寮傚父鐐规椂绌哄垎甯冪壒寰佺爺绌�

Research on the Temporal and Spatial Cistribution Characteristics of Thermal Anomalies in China from 2001 to 2018

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寮曠敤鏈枃

浣跨敤鏈枃

鍙傝�冩枃鐚�

鐩稿叧鏂囩珷 15

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