| Contents |
|
|
|
|
|
Tree-cotton intercropping land extraction based on multi-source high resolution satellite imagery |
| WANG Yu1, 2, FU Meichen1, WANG Li2, WANG Changyao2 |
1. Land Use and Technology Department, China University of Geosciences(Beijing), Beijing 100083, China;
2. The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China |
|
|
|
|
Abstract The intercropping system of tree-cotton is widespread in Xinjiang because it may increase yield and revenue especially during the early years of tree plantations. The statistics of the intercropped area is a key element for yield estimation. A method which can extract the tree-cotton intercropped ratio from planting area themetic map is proposed in this paper. The VHR (very high resolution) QuickBird imagery and multispectral high spatial resolution (GF-1) data were combined for extracting the intercropped ratio using the object-oriented approach and multi-seasonal classification approach respectively. Farmland extraction is a critical step to produce the intercropped information. Since multi-resolution segmentation (MRS) has been proved to be one of the most successful image segmentation algorithms, the trial-and-error process has been used to determine the three main optimal segmentation parameters (scale, shape, compactness) to identify farmland and tree canopy hierarchically. The new rule sets which consider optimal,shape and semantic features have been implemented to compile the farmland thematic map. Then, the GLCM-based texture feature has been proposed to distinguish the tree canopy when the image is segmented again. Intercropping ratio in each crop segmentation unit is calculated by stacking the farmland themetic layer and the tree canopy layer together. Since then, multi-seasonal classification approach has been used to extract the tree-cotton intercropping ratio from the intercropping ratio map. In addition, this work presents two varying images composed of GF-1 and Landsat8. By analyzing the phenologycal calendar, optimum temporal periods for cotton and other major crops are initially determined. Cotton planting areas are extracted by field samples supported supervised classification. The GF-1 accuracy achieves 89.16% which is by far better than TM results. Finally, tree-cotton interplanting area and ratio are extracted based on tree-crop intercropping map and cotton planting map.
|
| Keywords
incident angle effect
Lambert’s cosine law
wide-swath
sea ice
image segmentation
|
|
Issue Date: 03 May 2017
|
|
|
[1] 林 涛,田立文,崔建平,等.南疆果棉间作系统棉花优质高效种植存在的技术问题及对策[C]//中国棉花学会2010年年会论文集.延吉:中国棉花学会,2010:101-103.
Lin T,Tian L W,Cui J P,et al.Study on the technical problems and countermeasures of cotton quality and efficient cultivation in fruit cotton intercropping system from southern Xinjiang[C]//The Paper Collection of 2010 China Cotton Association Academic Conference.Yanji:The Chinese Society of Cotton,2010:101-103.
[2] 郭仁松,徐海江,刘正兴,等.适宜新疆枣棉间作种植模式棉花品种筛选研究[J].棉花科学,2013,35(4):16-21.
Guo R S,Xu H J,Liu Z X,et al.Screening cotton varieties of jujube-cotton intercropping planting mode in Xinjiang[J].Cotton Sciences,2013,35(4):16-21.
[3] 夏婵娟,史彦江.枣棉间作的生态效应对棉花产量的影响[J].西安工程大学学报,2012,26(2):161-167.
Xia C J,Shi Y J.Development effect on crop ecology and yield in jujube-cotton intercropping[J].Journal of Xi'an Polytechnic University,2012,26(2):161-167.
[4] 赵 英,张 斌,王明珠.农林复合系统中物种间水肥光竞争机理分析与评价[J].生态学报,2006,26(6):1792-1801.
Zhao Y,Zhang B,Wang M Z.Assessment of competition for water,fertilizer and light between components in the alley cropping system[J].Acta Ecologica Sinica,2006,26(6):1792-1801.
[5] 宋锋惠,吴正保,史彦江.枣棉间作对棉花产量和光环境的影响[J].新疆农业科学,2011,48(9):1624-1628.
Song F H,Wu Z B,Shi Y J.The effect of jujube-cotton intercropping system on the cotton yield and light environment[J].Xinjiang Agricultural Sciences,2011,48(9):1624-1628.
[6] Zhang D S,Zhang L Z,Liu J G,et al.Plant density affects light interception and yield in cotton grown as companion crop in young jujube plantations[J].Field Crops Research,2014,169:132-139.
[7] Mao L L,Zhang L Z,Zhao X H,et al.Crop growth, light utilization and yield of relay intercropped cotton as affected by plant density and a plant growth regulator[J].Field Crops Research,2014,155:67-76.
[8] 吴健生,刘建政,黄秀兰,等.基于面向对象分类的土地整理区农田灌排系统自动化识别[J].农业工程学报,2012,28(8):25-31.
Wu J S,Liu J Z,Huang X L,et al.Automatic identification of irrigation and drainage system in land reclamation area based on object-oriented classification[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(8):25-31.
[9] 张艳玲,冯凤英,闫浩文.高分辨率影像农田信息提取方法[J].地理空间信息,2010,8(1):78-80.
Zhang Y L,Feng F Y,Yan H W.Method for extracting farmland information from high resolution satellite image[J].Geospatial Information,2010,8(1):78-80.
[10] 朱超洪,刘 勇.基于影像认知和地学理解的面向对象分类研究[J].遥感技术与应用,2012,27(4):536-541.
Zhu C H,Liu Y.A study on object-oriented remote sensing image classification based on image cognition and geographical understanding[J].Remote Sensing Technology and Application,2012,27(4):536-541.
[11] 陈 杰,陈铁桥,梅小明,等.基于最优尺度选择的高分辨率遥感影像丘陵农田提取[J].农业工程学报,2014,30(5):99-106.
Chen J,Chen T Q,Mei X M,et al.Hilly farmland extraction from high resolution remote sensing imagery based on optimal scale selection[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(5):99-106.
[12] 张锦水,潘耀忠,韩立建,等.光谱与纹理信息复合的土地利用/覆盖变化动态监测研究[J].遥感学报,2007,11(4):500-510.
Zhang J S,Pan Y Z,Han L J,et al.Land use/cover change detection with multi-source data[J].Journal of Remote Sensing,2007,11(4):500-510.
[13] 胡潭高,朱文泉,阳小琼,等.高分辨率遥感图像耕地地块提取方法研究[J].光谱学与光谱分析,2009,29(10):2703-2707.
Hu T G,Zhu W Q,Yang X Q,et al.Farmland parcel extraction based on high resolution remote sensing image[J].Spectroscopy and Spectral Analysis,2009,29(10):2703-2707.
[14] Esch T,Metz A,Marconcini M,et al.Combined use of multi-seasonal high and medium resolution satellite imagery for parcel-related mapping of cropland and grassland[J].International Journal of Applied Earth Observation and Geoinformation,2014,28:230-237.
[15] 谭永生,沈掌泉,贾春燕,等.QuickBird全色与多光谱影像融合方法比较研究[J].科技通报,2008,24(4):498-503.
Tan Y S,Shen Z Q,Jia C Y,et al.Study on fusion algorithms of QuickBird PAN and multi spectral images[J].Bulletin of Science and Technology,2008,24(4):498-503.
[16] 邬明权,牛 铮,王长耀.多源遥感数据时空融合模型应用分析[J].地球信息科学,2014,16(5):776-783.
Wu M Q,Niu Z,Wang C Y.Assessing the accuracy of spatial and temporal image fusion model of complex area in south China[J].Journal of Geo-Information Science,2014,16(5):776-783.
[17] 曹 宝,秦其明,马海建,等.面向对象方法在SPOT5遥感图像分类中的应用——以北京市海淀区为例[J].地理与地理信息科学,2006,22(2):46-49,54.
Cao B,Qin Q M,Ma H J,et al.Application of object-oriented approach to SPOT5 image classification:A case study in Haidian District,Beijing City[J].Geography and Geo-Information Science,2006,22(2):46-49,54.
[18] Liu Y,Bian L,Meng Y H,et al.Discrepancy measures for selecting optimal combination of parameter values in object-based image analysis[J].ISPRS Journal of Photogrammetry and Remote Sensing,2012,68:144-156.
[19] Witharana C,Civco D L.Optimizing multi-resolution segmentation scale using empirical methods:Exploring the sensitivity of the supervised discrepancy measure Euclidean distance 2(ED2)[J].ISPRS Journal of Photogrammetry and Remote Sensing,2014,87:108-121.
[20] 白文路.多光谱遥感影像的纹理特征研究[D].哈尔滨:哈尔滨工业大学,2010.
Bai W L.Texture Feature Research of Multi-Spectral Remote Sensing Image[D].Harbin:Harbin Institute of Technology,2010.
[21] 潘耀忠,李 乐,张锦水,等.基于典型物候特征的MODIS-EVI时间序列数据农作物种植面积提取方法——小区域冬小麦实验研究[J].遥感学报,2011,15(3):578-594.
Pan Y Z,Li L,Zhang J S,et al.Crop area estimation based on MODIS-EVI time series according to distinct characteristics of key phenology phases:A case study of winter wheat area estimation in small-scale area[J].Journal of Remote Sensing,2011,15(3):578-594.
[22] 赵良斌,曹卫斌,唐春华,等.新疆棉花遥感识别最佳时相的选择[J].新疆农业科学,2008,45(4):618-622.
Zhao L B,Cao W B,Tang C H,et al.Selection of the optimum temporal for cotton remote sensing identification in Xinjiang[J].Xinjiang Agricultural Sciences,2008,45(4):618-622.
[23] 郝鹏宇,牛 铮,王 力,等.基于历史时序植被指数库的多源数据作物面积自动提取方法[J].农业工程学报,2012,28(23):123-131.
Hao P Y,Niu Z,Wang L,et al.Multi-source automatic crop pattern mapping based on historical vegetation index profiles[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(23):123-131.
[24] Gallego F J,Kussul N,Skakun S,et al.Efficiency assessment of using satellite data for crop area estimation in Ukraine[J].International Journal of Applied Earth Observation and Geoinformation,2014,29:22-30.
[25] Kowalik W,Dabrowska-Zielinska K,Meroni M,et al.Yield estimation using SPOT-VEGETATION products:A case study of wheat in European countries[J].International Journal of Applied Earth Observation and Geoinformation,2014,32:228-239. |
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
| |
Shared |
|
|
|
|
| |
Discussed |
|
|
|
|
2017,
Vol. 29
