Monitoring on Land Cover Pattern and Crops Structure of Oasis Irrigation Area of Middle Reaches in Heihe River Basin Using Remote Sensing Data
Received date: 2013-05-07
Revised date: 2013-07-15
Online published: 2013-08-10
The land cover pattern and crops structure of oasis irrigation area of middle reaches in the Heihe River Basin were monitored using CASI aerial data with high spatial and spectral resolution as transects. We designed a hierarchical classification structure integrated by pixelbased classification and object-based classification to map land cover types and crop planting structure in this region. According to surveyed reference data about land cover and visual interpretation from high resolution imagery, the accuracy of the classification result about land cover and crops pattern from CASI transect data was evaluated, and the result showed that overall accuracy was 84.61%, Kappa coefficient was 0.8262. Compared with landsat TM/ETM+ land cover product in Zhangye in 2007 within flight transects, CASI aerial data with high resolution was able to effectively identify the trees, shrubs and various crops. Land cover pattern of oasis irrigation area and various crop proportions within cropland area were analyzed using CASI classification result. The result showed that almost 59.1% of oasis irrigation area of middle reaches in the Heihe River Basin was barren or builtup region, and vegetated region accounted for 39.8%. Cropland, trees and grassland accounted for 39.4%, 5.3% and 0.1% respectively, and corn was staple crop, accounting for 96.1% within cropland area. This study demonstrated that aerial remote sensing data with high quality and high spatial resolution was able to effectively monitor spatial heterogeneity of underlying surface in the basin, and offer high-resolution information about underlying surface types for study on eco-hydrological process.
Key words： Aerial transect; Remote sensing; Hyperspectral; CASI; Classification
Wang Zhihui , Liu Liangyun . Monitoring on Land Cover Pattern and Crops Structure of Oasis Irrigation Area of Middle Reaches in Heihe River Basin Using Remote Sensing Data[J]. Advances in Earth Science, 2013 , 28(8) : 948 -956 . DOI: 10.11867/j.issn.1001-8166.2013.08.0948
[1]Chu Duo, Basanta Shrestha, Wang Wei, et al. Land cover mapping in the Tibet Plateau using MODIS imagery[J].Resources Science, 2010, 32(11):2 152-2 159.[除多，Basanta Shrestha，王伟,等. 基于MODIS的西藏高原土地覆盖分类研究[J].资源科学, 2010, 32(11):2 152-2 159.]
[2]Liu Qingfeng, Liu Jiping, Song Kaishan. Land cover classification based on MODIS/NDVI times series data[J]. Journal of the Graduate School of the Chinese Academy of Sciences, 2010, 27(2):163-169.[刘庆凤，刘吉平，宋开山. 基于MODIS/NDVI时序数据的土地覆盖分类[J]. 中国科学院研究生院学报, 2010, 27(2):163-169.]
[3]Liu Yonghong, Niu Zheng. Reginal land cover image classification and accuracy evaluation using MODIS data[J]. Remote Sensing Technology and Application, 2004, 19(4):217-224.[刘勇洪，牛铮. 基于MODIS遥感数据的宏观土地覆盖特征分类方法与精度分析研究[J].遥感技术与应用, 2004, 19(4):217-224.]
[4]Friedl M A, Sulla-Menashe D, Tan B, et al. MODIS collection 5 global land cover: Algorithm refinements and characterization of new datasets [J]. Remote Sensing of Environment,2010,114(1):168-182.
[5]Sulla-Menashe D, Friedl M A, Krankina O N, et al. Hierarchical mapping of Northren Eurasian land cover using MODIS data [J]. Remote Sensing of Environment, 2011, 115(2):392-403.
[6]Al-Kofahi S, Steele C, Vanleeuwen D, et al. Mapping land cover in urban residential landscapes using very high spatial resolution aerial photographs [J]. Urban Forestry & Urban Greening, 2012, 11(3): 291-301.
[7]Lucas R, Bunting P, Paterson M, et al. Classification of Australian forest communities using aerial photography, CASI and HyMap data[J]. Remote Sensing of Environment, 2008, 112(5): 2 088-2 103.
[8]Cleve C, Kelly M, Kearns F R, et al. Classification of the wildland-urban interface: A comparison of pixel-and object-based classifications using high-resolution aerial photography. [J]. Environment and Urban Systems, 2008, 32(4): 317-326.
[9]Wu Bingfang, Li Qiangzi. Crop acreage estimation using two individual sampling frameworks with stratification[J]. Journal of Remote Sensing, 2004, 8(6)：551-569.[吴炳方，李强子. 基于两个独立抽样框架的农作物种植面积遥感估算方法[J]. 遥感学报，2004,8(6)：551-569.]
[10]Liu Haiqi, Jin Minyu. Applications of remote sensing in agriculture in the United States[J]. China Agricultural Resources and Regional Planning, 1999, 20(2): 56-60.[刘海启，金敏毓.美国农业遥感技术应用状况概述[J].中国农业资源与区划,1999,20(2): 56-60.]
[11]Li Xin, Liu Shaomin, Ma Mingguo, et al. HiWATER: An integrated remote sensing experiment on hydrological and ecological process in the Heihe River Basin[J]. Advances in Earth Science, 2012, 27(5)：481-498.[李新，刘绍民，马明国，等. 黑河流域生态—水文过程综合遥感观测联合试验总体设计[J]. 地球科学进展，2012，27(5): 481-498.]
[12]Tian Jing, Su Hongbo, Chen Shaohui, et al. Spatial-temporal processes of desertification and oasification in the middle reaches of the Heihe River based on remote sensing[J]. Resources Science, 2011, 33(2): 347-355.[田静，苏红波，陈少辉，等. 黑河中游绿洲化荒漠化的时空变化遥感分析[J]. 资源科学, 2011, 33(2): 347-355.]
[13]Liu Jiyuan, Liu Mingliang, Tian Hanqin, et al. Spatia land temporal patterns of China’s cropland during 1990-2000: An analysis based on Landsat TM data[J]. Remote Sensing of Environment, 2005, 98: 442-456.
[14]Tang Huajun, Wu Wenbin, Yang Peng, et al. Recent progresses in monitoring crop spatial patterns by using remote sensing technologies[J]. Scientia Agricultura Sinica, 2010, 43(14)：2 879-2 888.[唐华俊，吴文斌，杨鹏，等. 农作物空间格局遥感监测研究进展[J]. 中国农业科学，2010，43(14)：2 879-2 888.]
[15]Schotten C G J, van Rooy W W L, Janssen L L F. Assessment of the capabilities of multi-temporal ERS-1 SAR data to discriminate between agricultural crops[J]. International Journal of Remote Sensing, 1995, 16(14): 2 619-2 637.
[16]Yu Qingxiao, Yuan Can, Fu Z, et al. An autonomous restaurant service robot with high positioning accuracy[J]. Industrial Robot: An International Journal，2012， 39(3)：271-281.
[17]Comaniciu D, Meer P. Mean shift: A robust approach toward feature space analysis[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence，2002，24(5): 603-619.
[18]Wang Zhihui, Li Shiming, Zhang Yiwei. The study on the detection of the variations of forest resources based on C5.0 algorithm—A case of Culai forest in Shandong[J]. Journal of Northwest Forestry University,2011，26(5)：185-191.[王志慧，李世明，张艺伟. 基于C5.0算法的森林资源变化检测方法研究——以山东省徂徕山林区为例[J].西北林学院学报，2011，26(5)：185-191.]
[19]Liu Liangyun, Wang Jihua, Zhao Chunjiang, et al. Study of floating prior probability MLC based on spatial features and local spatial autocorrelation[J]. Journal of Remote Sensing, 2006, 10(2):227-235.[刘良云，王纪华，赵春江，等. 基于地物空间信息的浮动先验概率的最大似然分类研究[J].遥感学报,2006,10(2):227-235.]
[20]Hansen M C, Defries R S, Townshend J, et al. Global land cover classification at 1 km spatial resolution using a classification tree approach [J]. International Journal of Remote Sensing，2000，21(6/7):1 331-1 364.
[21]Blaschke T. Object based image analysis for remote sensing [J]. ISPRS Journal of Photogrammetry and Remote Sensing，2005，65(1):2-16.
[22]Friedl M A, McIver D K, Hodges J C F, et al. Global land cover mapping from MODIS: Algorithms and early results [J]. Remote Sensing of Environment，2002，83(2):287-302.
[23]Loveland T R, Reed B C, Brown J F, et al. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data [J]. International Journal of Remote Sensing，2002，21(6/7):1 303-1 330.
[24]Li Xin, Li Xiaowen, Li Zenyuan, et al. Watershed allied telemetry experimental research [J]. Journal of Geophysical Research，2009，114(22)：D22103.
[25]Guanter L, Víctor Estellés, Moreno J. Spectral calibration and atmospheric correction of ultra-fine spectral and spatial resolution remote sensing data: Application to CASI-1500 data [J]. Remote Sensing of Environment，2007，109 (1):54-65.
/
| 〈 |
|
〉 |
甘公网安备62010202000687
