[1]ÐìêÏÔóÓî,Áõ ³å,ÆëÊö»ª*,µÈ.»ùÓÚËæ»úÉ­ÁÖËã·¨µÄ¸ÓÄϸÌéÙ¹ûÔ°Ò£¸ÐÐÅÏ¢ÌáÈ¡[J].½­Î÷ʦ·¶´óѧѧ±¨(×ÔÈ»¿Æѧ°æ),2018,(04):434-440.[doi:10.16357/j.cnki.issn1000-5862.2018.04.20]
¡¡XU Hanzeyu,LIU Chong,QI Shuhua*,et al.The Detection of Citrus Orchards in Southern Jiangxi Province with Landsat Images Using Random Forest Classifier[J].Journal of Jiangxi Normal University:Natural Science Edition,2018,(04):434-440.[doi:10.16357/j.cnki.issn1000-5862.2018.04.20]
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2018Äê04ÆÚ
Ò³Âë:
434-440
À¸Ä¿:
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2018-08-20

ÎÄÕÂÐÅÏ¢/Info

Title:
The Detection of Citrus Orchards in Southern Jiangxi Province with Landsat Images Using Random Forest Classifier
ÎÄÕ±àºÅ:
1000-5862(2018)04-0434-07
×÷Õß:
ÐìêÏÔóÓî1Áõ ³å2ÆëÊö»ª123*ÕÔ¹ú˧4
1.½­Î÷ʦ·¶´óѧµØÀíÓë»·¾³Ñ§Ôº,½­Î÷ Äϲý 330022; 2.½­Î÷ʦ·¶´óѧ۶ÑôºþʪµØÓëÁ÷ÓòÑо¿½ÌÓý²¿ÖصãʵÑéÊÒ,½­Î÷ Äϲý 330022; 3.½­Î÷Ê¡Û¶ÑôºþÁ÷Óò×ÊÔ´ÀûÓÃÓë×ÛºÏÖÎÀíÖصãʵÑéÊÒ,½­Î÷ Äϲý 330022; 4.¸£½¨Ê¡ÁÖÒµµ÷²é¹æ»®Ôº,¸£½¨ ¸£ÖÝ 350003
Author(s):
XU Hanzeyu1LIU Chong2QI Shuhua123*ZHAO Guoshuai4
1.School of Geography and Environment,Jiangxi Normal University,Nanchang Jiangxi 330022,China; 2.Key Laboratory of Poyang Lake Wetland and Watershed Research,Ministry of Education,Jiangxi Normal University,Nanchang Jiangxi 330022,China; 3.Jiangxi Provinci
¹Ø¼ü´Ê:
Ò£¸Ð ·ÖÀà Ëæ»úÉ­ÁÖ ¸ÓÄÏ ¸ÌéÙ¹ûÔ°
Keywords:
remote sensing classifier random forest Gannan citrus orchard
·ÖÀàºÅ:
TP 391.4
DOI:
10.16357/j.cnki.issn1000-5862.2018.04.20
ÎÄÏ×±êÖ¾Âë:
A
ÕªÒª:
Ñ¡Ôñ´º¡¢Çï¼¾µÍÔÆÁ¿Landsat-8ÎÀÐÇÒ£¸ÐÓ°Ïñ,¹¹½¨°üº¬Óжà¹âÆ×µØ±í·´ÉäÂÊ¡¢¹âÆ×Ö¸Êý¡¢¼¸ºÎÎÆÀíºÍµØÐÎÒò×ӵķÖÀàÌØÕ÷¼¯,ͨ¹ýËæ»úÉ­ÁÖ·ÖÀàËã·¨¿ªÕ¹¸ÓÄϸÌéÙ¹ûÔ°¿Õ¼ä·Ö²¼Ò£¸ÐÖÆͼÑо¿.Ñо¿½á¹û±íÃ÷:ÀûÓôº¼¾Ó°ÏñÌáÈ¡µÄ¸ÌéÙ¹ûÔ°ÕûÌ徫¶ÈΪ91.12%,KappaϵÊýΪ0.88,ÓÅÓÚÇï¼¾Ó°ÏñÌáÈ¡½á¹û; Ëæ»úÉ­ÁÖËã·¨ÔÚ¸ÓÄϸÌéÙ¹û԰ʶ±ðÖÆͼÖоßÓнϸߵķÖÀྫ¶ÈºÍ½ÏºÃµÄÊÊÓÃÐÔ,ÀûÓýµÎ¬µÄ·ÖÀàÌØÕ÷ÌáÈ¡¸ÌéÙ¹ûÔ°Ò²¾ßÓнϸ߾«¶È; ¸ÓÄϸÌéÙ¹ûÔ°Ãæ»ýÔ¼1 794.26 km2,¾ßÓÐÒ»¶¨±ÈÀýµÄ¶¸ÆÂÖÖÖ²ÏÖÏó,Ñ°ÎÚ¡¢ÐÅ·á¡¢°²Ô¶µÈ3ÏصĸÌéÙ¹ûÔ°³ÊÏÖ¹æÄ£»¯¡¢Á¬Æ¬»¯µÄ¾°¹Û.
Abstract:
Several Landsat OLI images acquired in spring and autumn are selected to map citrus orchards distribution.Random Forest(RF)classifier is utilized to implement a supervised classification on the dataset including multi-spectral reflectance,vegetation and moisture indices,texture information and topographic features.The results show that classification with spring image is successful with an overall accuracy(OA)of 91.12% and a Kappa statistic of 0.88.And it is superior to that with autumn images.RF is highly suitable for the identi-fication and classification of citrus orchards.And classification with an optimal subset of discrimination features is also acceptable with a high accuracy.The area of citrus orchards is about 1 794.26 km2 and a certain proportion of citrus orchards is cultivated on steep slopes.The landscape characteristics of citrus orchards in some counties such as Xunwu,Xinfeng and Anyuan became single,continuous and massive.

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ÊÕ¸åÈÕÆÚ:2018-01-25
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¸üÐÂÈÕÆÚ/Last Update: 2018-08-20