基于HJ卫星的中国南方地区甘蔗面积提取研究
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摘要
为研究大范围甘蔗种植面积的提取方法,以广西、云南、广东湛江和海南为研究区,以30 m空间分辨率的多时相HJ卫星影像为数据源,采用基于NDVI时间序列的决策树分类模型提取研究区内2014/2015年度甘蔗种植面积。结合农业部门的统计数据对甘蔗种植面积提取结果进行精度评价,总体精度达到87.5%。对研究区广东湛江甘蔗种植区域进行抽样调查,抽样调查精度达到93.2%,Kappa系数为0.81。表明该方法可以高效地应用于中国南方地区的甘蔗种植空间信息识别。
This study aims to propose an extraction method of sugarcane planting in large area using remote sensing data. Taking Guangxi Zhuang Autonomous Region, Yunnan Province, Hainan Province and Zhanjiang City in Guangdong Province as the study areas, the time-series Chinese HJ-1 CCD images were obtained covering the sugarcane growing period in the study areas. The decision tree classification method was applied on the base of the time-series NDVI threshold for sugarcane mapping over the large areas during 2014/2015 sugarcane harvest year. The overall accuracy was 87.5% compared with the statistics of local agricultural department. The independent field survey sampling points were used to evaluate the classification accuracy in Zhanjiang City. The confusion matrix analysis showed that the overall classification accuracy was 93.2% and the Kappa coefficient was 0.81. The results showed that this method was feasible, efficient, and applicable in extracting the planting area of sugarcane in southern China.
This study aims to propose an extraction method of sugarcane planting in large area using remote sensing data. Taking Guangxi Zhuang Autonomous Region, Yunnan Province, Hainan Province and Zhanjiang City in Guangdong Province as the study areas, the time-series Chinese HJ-1 CCD images were obtained covering the sugarcane growing period in the study areas. The decision tree classification method was applied on the base of the time-series NDVI threshold for sugarcane mapping over the large areas during 2014/2015 sugarcane harvest year. The overall accuracy was 87.5% compared with the statistics of local agricultural department. The independent field survey sampling points were used to evaluate the classification accuracy in Zhanjiang City. The confusion matrix analysis showed that the overall classification accuracy was 93.2% and the Kappa coefficient was 0.81. The results showed that this method was feasible, efficient, and applicable in extracting the planting area of sugarcane in southern China.
引文
[1]陈伟绩.有机—无机复混肥对甘蔗生长和土壤养分的效应研究[D].福州:福建农林大学,2007.
[2] Zhang D, Song X, Mansaray L R, et al. Estimating leaf area index of sugarcane based on multi-temporal digital images[A].//Fifth International Conference on Agro-Geoinformatics[C]. IEEE,2016.
[3]马尚杰,裴志远,汪庆发,等.基于多时相环境星数据的甘蔗收割过程遥感监测[J].农业工程学报,2011,27(3):215-219.
[4]玉苏普江·艾麦提,买合皮热提·吾拉木,玉苏甫·买买提,等.基于多时相HJ卫星的渭干河-库车河绿洲主要农作物种植信息提取[J].中国农业资源与区划,2014,35(5):38-43.
[5] Huang S L, Potter C, Crabtree R L, et al. Fusing optical and radar data to estimate sagebrush, herbaceous, and bare ground cover in Yellowstone[J]. Remote Sensing of Environment,2010,114(2):251-264.
[6]陈健,刘云慧,宇振荣.基于时序MODIS-EVI数据的冬小麦种植信息提取[J].中国农学通报,2011,27(1):446-450.
[7]刘庆生,黄翀,刘高焕,等.基于关键期HJ卫星数据提取无棣县作物种植面积[J].中国农学通报,2014,30(26):284-290.
[8]武永利,赵永强,靳宁.单时相MERSI数据在冬小麦种植面积监测中的应用[J].中国农学通报,2011,27(14):127-131.
[9] Laurila H, Karjalainen M, Kleemola J, et al. Cereal yield modeling in Finland using optical and radar remote sensing[J]. Remote Sensing,2010,2(9):2185-2239.
[10] Jgpw C, Buker C, Hjcvan L, et al. A framework for monitoring crop growth by combining directional and spectral remote sensing information[J]. Remote Sensing of Environment,1994,50(2):161-170.
[11]孙华生.利用多时相MODIS数据提取中国水稻种植面积和长势信息[D].杭州:浙江大学,2009.
[12]张建国,李宪文,吴延磊.面向对象的冬小麦种植面积遥感估算研究[J].农业工程学报,2008,24(5):156-160.
[13] Fortes C., DemattêJ A M. Discrimination of sugarcane varieties using Landsat 7 ETM+spectral data[J]. International Journal of Remote Sensing,2006,27(7):1395-1412.
[14] Almeida T I R, De Souza Filho C R, Rossetto R. ASTER and Landsat ETM+images applied to sugarcane yield forecast[J].International Journal of Remote Sensing,2006,27(19):4057-4069.
[15] Vieira M A, Formaggio A R, RennóC D, et al. Object Based Image Analysis and Data Mining applied to a remotely sensed Landsat time-series to map sugarcane over large areas[J]. Remote Sensing of Environment,2012,123(8):553-562.
[16]邬明权,王长耀,牛铮.利用多源时序遥感数据提取大范围水稻种植面积[J].农业工程学报,2010,26(7):240-244.
[17]朱长明,骆剑承,沈占锋,等.基于地块特征基元与多时相遥感数据的冬小麦播种面积快速提取[J].农业工程学报,2011,27(9):94-99.
[18]刘国栋,邬明权,牛铮,等.基于GF-1卫星数据的农作物种植面积遥感抽样调查方法[J].农业工程学报,2015,31(5):160-166.
[19]王利民,刘佳,杨福刚,等.基于GF-1卫星遥感的冬小麦面积早期识别[J].农业工程学报,2015,31(11):194-201.
[20]马尚杰,裴志远,汪庆发,等.基于多时相环境星数据的崇左市甘蔗遥感监测[J].河北遥感,2013(1):26-29.
[21]丁美花,谭宗琨,李辉,等.基于HJ-1卫星数据的甘蔗种植面积调查方法探讨[J].中国农业气象,2012,33(2):265-270.
[22]刘吉凯,钟仕全,徐雅,等.基于多时相GF-1WFV数据的南方丘陵地区甘蔗种植面积提取[J].广东农业科学,2014,41(18):149-154.
[23]陈刘凤,林开平,胡宝清,等.基于Landsat8_OLI数据的甘蔗种植面积监测[J].南方农业学报,2015,46(11):2068-2072.
[24]中国统计年鉴[M].北京:中国统计出版社,2015:403-405.
[25]贺俊杰.锡林郭勒草地NDVI和牧草估产产量的变化特征[J].中国农学通报,2015,31(17):1-5.
[26]王柳,段英.利用遥感影像进行植被分布分析[J].测绘与空间地理信息,2012,35(3):140-142.
[2] Zhang D, Song X, Mansaray L R, et al. Estimating leaf area index of sugarcane based on multi-temporal digital images[A].//Fifth International Conference on Agro-Geoinformatics[C]. IEEE,2016.
[3]马尚杰,裴志远,汪庆发,等.基于多时相环境星数据的甘蔗收割过程遥感监测[J].农业工程学报,2011,27(3):215-219.
[4]玉苏普江·艾麦提,买合皮热提·吾拉木,玉苏甫·买买提,等.基于多时相HJ卫星的渭干河-库车河绿洲主要农作物种植信息提取[J].中国农业资源与区划,2014,35(5):38-43.
[5] Huang S L, Potter C, Crabtree R L, et al. Fusing optical and radar data to estimate sagebrush, herbaceous, and bare ground cover in Yellowstone[J]. Remote Sensing of Environment,2010,114(2):251-264.
[6]陈健,刘云慧,宇振荣.基于时序MODIS-EVI数据的冬小麦种植信息提取[J].中国农学通报,2011,27(1):446-450.
[7]刘庆生,黄翀,刘高焕,等.基于关键期HJ卫星数据提取无棣县作物种植面积[J].中国农学通报,2014,30(26):284-290.
[8]武永利,赵永强,靳宁.单时相MERSI数据在冬小麦种植面积监测中的应用[J].中国农学通报,2011,27(14):127-131.
[9] Laurila H, Karjalainen M, Kleemola J, et al. Cereal yield modeling in Finland using optical and radar remote sensing[J]. Remote Sensing,2010,2(9):2185-2239.
[10] Jgpw C, Buker C, Hjcvan L, et al. A framework for monitoring crop growth by combining directional and spectral remote sensing information[J]. Remote Sensing of Environment,1994,50(2):161-170.
[11]孙华生.利用多时相MODIS数据提取中国水稻种植面积和长势信息[D].杭州:浙江大学,2009.
[12]张建国,李宪文,吴延磊.面向对象的冬小麦种植面积遥感估算研究[J].农业工程学报,2008,24(5):156-160.
[13] Fortes C., DemattêJ A M. Discrimination of sugarcane varieties using Landsat 7 ETM+spectral data[J]. International Journal of Remote Sensing,2006,27(7):1395-1412.
[14] Almeida T I R, De Souza Filho C R, Rossetto R. ASTER and Landsat ETM+images applied to sugarcane yield forecast[J].International Journal of Remote Sensing,2006,27(19):4057-4069.
[15] Vieira M A, Formaggio A R, RennóC D, et al. Object Based Image Analysis and Data Mining applied to a remotely sensed Landsat time-series to map sugarcane over large areas[J]. Remote Sensing of Environment,2012,123(8):553-562.
[16]邬明权,王长耀,牛铮.利用多源时序遥感数据提取大范围水稻种植面积[J].农业工程学报,2010,26(7):240-244.
[17]朱长明,骆剑承,沈占锋,等.基于地块特征基元与多时相遥感数据的冬小麦播种面积快速提取[J].农业工程学报,2011,27(9):94-99.
[18]刘国栋,邬明权,牛铮,等.基于GF-1卫星数据的农作物种植面积遥感抽样调查方法[J].农业工程学报,2015,31(5):160-166.
[19]王利民,刘佳,杨福刚,等.基于GF-1卫星遥感的冬小麦面积早期识别[J].农业工程学报,2015,31(11):194-201.
[20]马尚杰,裴志远,汪庆发,等.基于多时相环境星数据的崇左市甘蔗遥感监测[J].河北遥感,2013(1):26-29.
[21]丁美花,谭宗琨,李辉,等.基于HJ-1卫星数据的甘蔗种植面积调查方法探讨[J].中国农业气象,2012,33(2):265-270.
[22]刘吉凯,钟仕全,徐雅,等.基于多时相GF-1WFV数据的南方丘陵地区甘蔗种植面积提取[J].广东农业科学,2014,41(18):149-154.
[23]陈刘凤,林开平,胡宝清,等.基于Landsat8_OLI数据的甘蔗种植面积监测[J].南方农业学报,2015,46(11):2068-2072.
[24]中国统计年鉴[M].北京:中国统计出版社,2015:403-405.
[25]贺俊杰.锡林郭勒草地NDVI和牧草估产产量的变化特征[J].中国农学通报,2015,31(17):1-5.
[26]王柳,段英.利用遥感影像进行植被分布分析[J].测绘与空间地理信息,2012,35(3):140-142.