基于植被物候特征与监督分类的青南高原信息提取

doi:10.11873/j.issn.1004-0323.2009.2.223

閬ユ劅鎶�鏈笌搴旂敤鈥衡�� 2009, Vol. 24 鈥衡�� Issue (2): 223-229.DOI: 10.11873/j.issn.1004-0323.2009.2.223

鈥� 鎶�鏈爺绌朵笌鍥惧儚澶勭悊鈥� 涓婁竴绡� 涓嬩竴绡�

鍩轰簬妞嶈鐗╁�欑壒寰佷笌鐩戠潱鍒嗙被鐨勯潚鍗楅珮鍘熶俊鎭彁鍙�

閮壋鑺��^1,3,鍒樺織绾�^2,3,璋㈡槑鍏�^1,3

锛�1.鎴愰兘淇℃伅宸ョ▼瀛﹂櫌鐢靛瓙宸ョ▼绯粅鍥涘窛鎴愰兘 610225|2.鎴愰兘淇℃伅宸ョ▼瀛﹂櫌璧勬簮鐜绯粅
鍥涘窛鎴愰兘 610225锛�3.涓浗姘旇薄灞�澶ф皵鎺㈡祴閲嶇偣寮�鏀惧疄楠屽|鍥涘窛鎴愰兘 610225 锛�

鏀剁鏃ユ湡:2008-09-08 淇洖鏃ユ湡:2009-03-09 鍑虹増鏃ユ湡:2009-04-20 鍙戝竷鏃ユ湡:2012-02-29
浣滆�呯畝浠�:閮壋鑺�(1983-),濂�,纭曞＋鐮旂┒鐢�,鐮旂┒鏂瑰悜涓哄崼鏄熼仴鎰熷浘鍍忓鐞嗐�侲-mail:fayegyf@126.com銆�

Vegetation Information Extraction in the South Qinghai Plateau顎僓sing Phenology and Supervised Classification

GUO Yan-fen顎�^1,3顎�,LIU Zhi-hong顎嬵��^2,3顎�,XIE Ming-yuan顎嬵��^1,3

(1.Department of Electronic Engineering,Chengdu University of Information Technology,Chengdu 610225,China;2.Department of Resource and Environment,Chengdu University of Information Technology,顎僀hengdu 610225,China;3.CMA Key Laboratory of Atmospheric Sounding,Chengdu 610225,China)

Received:2008-09-08 Revised:2009-03-09 Online:2009-04-20 Published:2012-02-29

鎽樿/Abstract

鎽樿锛�

閽堝澶у昂搴﹀尯鍩熺殑妞嶈淇℃伅鎻愬彇锛岀敱浜庤寖鍥村箍闃斻�佸湴褰㈠鏉傘�佹皵鍊欒骏寮傦紝鍒嗙被绮惧害鐨勬彁楂樻槸涓簾寰呰В鍐崇殑闂锛涢�氳繃瀵归潚鍗楅珮鍘熼噰鐢ㄥ垎鍖哄鐞�,鍒╃敤妞嶈鎸囨暟鐨勭壒鎬э紝灏嗗熀浜庢椂闂村簭鍒楃殑NDVI鏁版嵁鎵�鍙嶆槧鐨勬琚墿鍊欑煡璇嗭紝杈呭姪淇℃伅DEM鍜孏IS鏁版嵁鍔犲叆鐩戠潱鍒嗙被绯荤粺锛岃繘琛屾琚俊鎭彁鍙栵紝骞惰繘琛屼簡鍒嗙被绮惧害璇勪环銆傜爺绌剁粨鏋滆〃鏄庯紝鍒╃敤璇ユ柟娉曞闈掑崡楂樺師鐨�3涓湴鍖哄垎绫诲悗锛屽叾鍒嗙被绮惧害閮借揪鍒颁簡83.3%浠ヤ笂锛岃揪鍒颁簡杈冨ソ鐨勫垎绫荤粨鏋溿�傚湪鐩戠潱鍒嗙被鐨勮缁冨尯閫夊彇杩囩▼涓紝灏嗘琚墿鍊欑壒寰佷綔涓虹煡璇嗭紝缁撳悎鐩瑙ｈ瘧鍜孌EM杈呭姪鐭ヨ瘑甯姪閫夊彇璁粌鍖虹殑鏂规硶锛屽悓鏃跺弬鑰僄IS鍦熷湴鍒╃敤鏁版嵁锛屼娇寰楄缁冨尯鐨勯�夊彇鏇村噯纭彲闈狅紝鍙繘涓�姝ユ彁楂樺垎绫荤簿搴︺��

鍏抽敭璇�: 妞嶈鐗╁�欑壒寰�, NDVI, 鐩戠潱鍒嗙被, 鍒嗗尯, 淇℃伅鎻愬彇, 绮惧害璇勪环

Abstract:

Because of wide ranges,complicated terrains and disparate climates,it is an important problem to increase the classification accuracy for vegetation information extraction in wide ranges.In this paper,it uses division processing and joins vegetation phonological knowledge reflected by NDVI series data and auxiliary information including DEM and GIS data into the supervised classification system to extract vegetation of South Qinghai Plateau.The classification accuracy has reached more than 83.3% by using the method mentioned above and achieved better classification results.It is reliable to help select training areas,using vegetation phonological knowledge,visual interpretation and DEM data and taking land-use data into account.It makes training areas more accurate and improves the accuracy.

Key words: Vegetation phonological feature, NDVI Supervised classification, Division Iinformation extraction锛汚ccuracy assessment

涓浘鍒嗙被鍙�:

TP 79

閮壋鑺�,鍒樺織绾�,璋㈡槑鍏�. 鍩轰簬妞嶈鐗╁�欑壒寰佷笌鐩戠潱鍒嗙被鐨勯潚鍗楅珮鍘熶俊鎭彁鍙朳J]. 閬ユ劅鎶�鏈笌搴旂敤, 2009, 24(2): 223-229.

GUO Yan-fen,LIU Zhi-hong,XIE Ming-yuan. Vegetation Information Extraction in the South Qinghai Plateau顎僓sing Phenology and Supervised Classification[J]. Remote Sensing Technology and Application, 2009, 24(2): 223-229.

鍙傝�冩枃鐚�

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鍩轰簬妞嶈鐗╁�欑壒寰佷笌鐩戠潱鍒嗙被鐨勯潚鍗楅珮鍘熶俊鎭彁鍙�

Vegetation Information Extraction in the South Qinghai Plateau顎僓sing Phenology and Supervised Classification

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鎽樿/Abstract

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鍙傝�冩枃鐚�

鐩稿叧鏂囩珷 15

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