全球典型植被叶片光谱特征及其对LAI反演的影响分析

doi:10.11873/j.issn.1004-0323.2019.1.0155

鎽樿/Abstract

鎽樿锛� 鍦ㄥ叏鐞冭寖鍥撮暱鏃堕棿搴忓垪LAI閬ユ劅浜у搧鍙嶆紨绠楁硶涓紝妞嶈鍐犲眰鍙嶅皠鐜囨ā鍨嬩粎浣跨敤灏戦噺鍙剁墖鍏夎氨鐗瑰緛浠ｈ〃鍏ㄧ悆妞嶈鍏ㄥ勾鐨勫吀鍨嬫琚厜璋辩壒寰侊紝鍙剁墖鍏夎氨鐨勪笉纭畾鎬у鑷碙AI閬ユ劅浜у搧瀛樺湪涓�瀹氱殑璇樊銆傜洰鍓嶅叏鐞冨凡缁忔瀯寤轰簡澶氫釜鍏稿瀷妞嶈鍙剁墖娉㈣氨鏁版嵁闆嗭紝杩欎簺鏁版嵁闆嗗寘鍚涓琚墿绉嶃�佷笉鍚岀┖闂村湴鍩熷強澶氭椂鐩稿彾鐗囧厜璋辨暟鎹紝涓哄畾閲忓垎鏋愬彾鐗囧厜璋辩壒寰佹彁渚涗簡鏁版嵁鏀寔銆備富瑕佸埄鐢↙OPEX鈥�93銆丄NGERS鈥�03銆佷腑鍥藉吀鍨嬪湴鐗╂尝璋辨暟鎹簱鍜岄噹澶栧疄娴嬬殑鍙剁墖鍏夎氨鏁版嵁锛屼互榛勮竟鍙傛暟銆佺孩杈瑰弬鏁板拰鍙剁墖鍏夎氨鎸囨暟浣滀负鍒嗘瀽鎸囨爣锛屾帰璁ㄤ笉鍚屾琚墿绉嶃�佷笉鍚屾皵鍊欏尯鍜屼笉鍚岀墿鍊欐湡鐨勫彾鐗囧厜璋辩壒寰佸樊寮傦紝鍙婂叾瀵规琚啝灞傚弽灏勭巼銆丩AI鍙嶆紨鐨勫奖鍝嶏紝涓哄彂灞曡�冭檻鐜板疄鍙剁墖鍏夎氨宸紓鐨凩AI鍙嶆紨绠楁硶鎻愪緵鐮旂┒鍩虹銆傜粨鏋滆〃鏄庯細妞嶈鍙剁墖鍏夎氨瀛樺湪澶氭牱鎬э紝鍙剁墖鍏夎氨鐗瑰緛宸紓涓昏褰卞搷MODIS浼犳劅鍣ㄨ繎绾㈠娉㈡鍜岀豢娉㈡鍙嶅皠鐜囧�硷紝鍏朵腑锛岀豢娉㈡鍙嶅皠鐜囧�煎鍙剁墖鍏夎氨鍙樺寲鏈�涓烘晱鎰燂紱鍦↙AI鍙嶆紨绠楁硶涓紝濡傛灉鍙�冭檻妞嶈绫诲瀷鑰屼笉鑰冭檻鐗╃鍙剁墖鍏夎氨宸紓锛屽彲鑳戒細缁橪AI鍙嶆紨甯︽潵澶т簬3鐨勮宸��

鍏抽敭璇�: 鍙剁墖鍏夎氨鐗瑰緛, LOPEX鈥�93, ANGERS鈥�03, 涓浗鍏稿瀷鍦扮墿娉㈣氨搴�, 鍙堕潰绉寚鏁�

Abstract: Long time series LAI remote sensing inversion algorithms use only a few leaves spectra to represent the global leaf spectral characteristics throughout the year.while due to the variation of leaf spectra锛宨t may introduce uncertainties to LAI remote sensing products.An amount of spectrum databases containing leaf spectrum of different vegetation species锛実eographical locations and time phase and corresponding biochemical parameters have been constructed to provide support for the analysis of spectral characteristics of leaves.This paper mainly uses the leaf spectral database LOPEX鈥�93锛孉NGERS鈥�03锛孲pectral library of typical ground objects in China and field experimental data to analyze the effects of spectral characteristics of different plant species and different climate zones on MODIS reflectance of specific channels and further to provide prior information for the development of LAI inversion algorithms with consideration of leaf spetra differences.The result suggests that锛歍here exists diversity in vegetation leaf spectra.The spectral differences mainly affect the reflectance in red and green band (green band is most sensitive to leaf spectra variation).Only considering vegetation types without taking leaf spectral variation into account may induce error over 3 in remote sensing LAI inversion algorithms.

Key words: Leaf optical characteristics, LOPEX鈥�93, ANGERS鈥�03, Spectral library of typical ground objects in China, Leaf area index

涓浘鍒嗙被鍙�:

TP237

鍒樻磥, 鏉庨潤, 鏌抽挦鐏�, 浣曞浆褰�, 浜庢枃娑�. 鍏ㄧ悆鍏稿瀷妞嶈鍙剁墖鍏夎氨鐗瑰緛鍙婂叾瀵筁AI鍙嶆紨鐨勫奖鍝嶅垎鏋怺J]. 閬ユ劅鎶�鏈笌搴旂敤, 2019, 34(1): 155-165.

Liu Jie, Li Jing, Liu Qinhuo, He Bingbing, Yu Wentao. GlobalLeaf Spectral Characteristics of Typical Vegetation and It鈥檚 Impacts on LAI Inversion[J]. Remote Sensing Technology and Application, 2019, 34(1): 155-165.

鍙傝�冩枃鐚�

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[10]	閮埄褰�,鍒樻棣�,杩愬悜鍐�,寮犲媷,瀛欎笘璐�. 鍩轰簬鏁版嵁鏈虹悊鐨勬琚彾闈㈢Н鎸囨暟閬ユ劅鍙嶆紨鐮旂┒[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(5): 1047-1056.
[11]	钖涘崕鏌�,鐜嬫樁鏅�,鍛ㄧ孩鏁�,鐜嬮敠鍦�,涓囧崕浼�. 鍩轰簬妯℃嫙閫�鐏畻娉曠殑BP绁炵粡缃戠粶妯″瀷浼扮畻楂樺垎杈ㄧ巼鍙堕潰绉寚鏁�[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(5): 1057-1069.
[12]	鑳℃湀绔�,姝︾埥,鍐櫓宄�,鍒樻磱. 闈㈠悜閬ユ劅鍙堕潰绉寚鏁颁骇鍝佺殑鍦板舰鏍℃鐮旂┒[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(5): 1070-1078.
[13]	鏂圭孩浜�. 鎴戝浗鍙堕潰绉寚鏁板崼鏄熼仴鎰熶骇鍝佺敓浜у強楠岃瘉[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(5): 990-1003.
[14]	鍒樹繆,瀛熷簡宀�,钁涘皬涓�,鍒橀『鍠�,闄堟棴,瀛欎簯鏅�. 鍩轰簬BP绁炵粡缃戠粶鐨勫鐜夌背澶氱敓鑲叉湡鍙堕潰绉寚鏁板弽婕旂爺绌�[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2020, 35(1): 174-184.
[15]	寰愬崼鏄�,钖涘崕鏌�,闈冲崕瀹�,鏉庣埍鍐�. 铻嶅悎閬ユ劅鍏堥獙淇℃伅鐨勫彾闈㈢Н鎸囨暟鍙嶆紨[J]. 閬ユ劅鎶�鏈笌搴旂敤, 2019, 34(6): 1235-1244.

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GlobalLeaf Spectral Characteristics of Typical Vegetation and It鈥檚 Impacts on LAI Inversion

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