Journal of Geo-information Science >
Progress on Methods of Grassland Degradation and Weed Invasion Monitoring Based on Remote Sensing
Received date: 2012-11-30
Revised date: 2013-06-28
Online published: 2013-09-29
Grassland degradation is one of the important ecological problems in China. During recent years, influenced by global warming and increasing human activities, different degrees of grassland degradation have occurred in China, which has become a research focus in the field of grassland ecology. Based on the systematic summary of studies in the grassland degradation and weed invasion in the latest decade, the limitations of traditional methods of monitoring grassland degradation and weed invasion by remote sensing are put forward, and some important study directions and priorities for future are reviewed. Grassland degradation is often shown as decline in species of high quality forage and increase in the number of weed species at the community scale. In the process of grassland degradation, weed species invasion leads to the increase of vegetation coverage. And thus traditional methods of monitoring grassland degradation based on the decrease of vegetation coverage, productivity and grass yield are limited in detecting the change characteristics of plant population, especially the process of weed species invasion. The results of our research show that there exists great limitations in using traditional methods to detect the change characteristics of plant population, but the weed invasion monitoring method using hyper-spectral data can detect the weed species in plant population and retrieve the area proportion, height and coverage, through making full use of the ample spectral information of hyper-spectral data, and integrate field measuring using spectrometer with quantitative analysis of spectral difference of plant population characteristics on grassland degradation. The studies on methods of monitoring grassland degradation and weed invasion using hyper-spectral data can provide important indicators of community succession process and trend for grassland degradation monitoring and treatment. It can also effectively solve the defects in traditional methods of monitoring grassland degradation based on remote sensing and provide new remote sensing methods for monitoring grassland degradation and weed invasion.
Key words: grassland degradation; weed invasion; remote sensing monitoring
JUE Dan, LI Shuang, XU Xin-Liang, WANG Chang-Zuo, TONG La-Ga . Progress on Methods of Grassland Degradation and Weed Invasion Monitoring Based on Remote Sensing[J]. Journal of Geo-information Science, 2013 , 15(5) : 761 -767 . DOI: 10.3724/SP.J.1047.2013.00761
[1] 王轶,李瑞敏,王祎萍,等.草地退化的地质指标体系[J].地质通报,2011,30(11):1744-1751.
[2] 闫玉春,唐海萍.草地退化相关概念辨析[J].草业学报, 2008,17(1):93-99.
[3] 李寿.青藏高原草地退化与草地有毒有害植物[J].草业与畜牧,2010(8):30-34.
[4] 曹静娟,尚占环,郭瑞英,等. 甘肃臭草入侵对亚高山草地 土壤碳氮库的影响[J]. 草原与草坪,2010,30(5):11-14.
[5] 姚凤军,齐凤林.退化草地生态系统研究现状[J].畜牧兽医科技信息,2008(11):95-96.
[6] Tsuyoshi A, Kensuke K. Grassland degradation in China: Methods of monitoring, Management and restoration[J]. Japanese Society of Grassland Science,2007(57):1-17.
[7] 公延明,胡玉昆,阿德力·麦地等.巴音布鲁克高寒草地退化演替阶段植物群落特性研究[J].干旱区资源与环境, 2010,24(6):149-152.
[8] 赵成章,龙瑞军.石羊河上游甘肃臭草型退化草地植被恢 复过程[J].山地学报,2008,26(3):286-292.
[9] 周家福,干友民,李志丹,等.川西北高寒草地退化演替群落的数量分类与排序[J].湖北农业科学,2008,47(2):207-210.
[10] Wang C, Zhou B, Palm H. Detecting invasive Sericea Lespedeza (Lespedeza cuneata) in Mid-Missouri Pastureland using hyperspectral imagery[J]. Environmental Management, 2008,41(6):853-862.
[11] Feng J, Wang T, Qi S Z, et al. Land degradation in the source region of the Yellow River, northeast Qinghai-Xizang Plateau: classification and evaluation[J]. Environ Geol, 2005(47):459-466.
[12] Feng Y, Lu Q, Tokola T, et al. Assessment of grassland degradation In Guinan County, Qinghai Province, China, in the past 30 years[J]. Land Degradation & Development, 2009(20):55-68.
[13] Liu L S, Zhang Y L, Bai W Q, et al. Characteristics of grassland degradation and driving forces in the source region of the Yellow River from 1985 to 2000[J]. J Geographical Sciences, 2006,16(2):131-142.
[14] 才红梅.乌兰县不同退化程度高寒草甸草地群落结构特征分析[J].养殖与饲料,2011(6):54-55.
[15] 李里,刘伟.退化草地植物功能群和物种丰富度与群落生产力关系的研究[J].草地学报,2011,19(6):917-921.
[16] 张静,李希来,王金山,等.三江源地区不同退化程度草地群落结构特征的变化[J]. 湖北农业科学,2009,48(9): 2125-2129.
[17] 伏洋,张国胜,李凤霞,等.青海省草地生态环境变化态势及驱动力分析[J].草业科学,2007,24(5):1-8.
[18] 马玉寿,尚占环,施建军,等.黄河源区“黑土滩”退化草地群落类型多样性及其群落结构研究[J].草业科学,2006, 23(12):6-11.
[19] 王彦龙,马玉寿,孙小弟,等.大武地区不同程度退化草地群落结构及植物量分析[J].青海畜牧兽医,2007,37(6): 1-3.
[20] 程晓月,后源,任国华,等“. 黑土滩”退化高寒草地6种常见毒杂草水浸液对垂穗披碱草的化感作用[J].西北植物学报,2011,31(10):2057-2064.
[21] 赵新全,周华坤.三江源区生态环境退化、恢复治理及其可持续发展[J].中国科学院院刊,2005,20(6):471-476.
[22] 刘纪远,徐新良,邵全琴.近30 年来青海三江源地区草地 退化的时空特征[J].地理学报,2008,63(4):364-376.
[23] 刘纪远,邵全琴,樊江文.三江源区草地生态系统综合评估指标体系[J].地理研究,2009,28(2):273-283.
[24] 臧淑英,那晓东,冯仲科.基于植被指数的大庆地区草地退化因子遥感定量反演模型的研制[J].北京林业大学学报,2008,30(增刊1):98-104.
[25] 杨文才,吴新宏,张德罡,等.基于MODIS-NDVI 的三江源区称多县高寒草地退化现状评价[J].草原与草坪,2011, 31(5):50-54.
[26] Gao Q, Wan Y, Xu H, et al. A. Alpine grassland degradation index and its response to recent climate variability in Northern Tibet, China[J]. Quaternary International, 2010, 226(1-2):143-150.
[27] 吴红,安如,李晓雪,等.基于净初级生产力变化的草地退化监测研究[J].草业科学,2011,28(4):536-542.
[28] 徐剑波,陈进发,胡月明,等.青海省玛多县草地退化现状及动态变化研究[J].草业科学,2011,28(3):359-364.
[29] 杜自强,王建,李建龙,等.黑河中上游典型地区草地植被退化遥感动态监测[J]. 农业工程学报,2010,26(4): 180-185.
[30] Zomer R J, Trabucco A, Ustin S L. Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing[J]. Journal of Environmental Management,2009,90(7):2170-2177.
[31] 周磊,辛晓平,李刚,等.高光谱遥感在草原监测中的应用[J].草业科学,2009,26(4):20-27.
[32] Darvishzadeh R, Atzberger C, Skidmore A, et al. Mapping grassland leaf area index with airborne hyperspectral imagery: A comparison study of statistical approaches and inversion of radiative transfer models[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2011,66(6): 894-906.
[33] Skidmore A K, Ferwerda J G, Mutanga O, et al. Forage quality of savannas-Simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery[J]. Remote Sensing of Environment,2010, 114(1):64-72.
[34] Lu S, Shimizu Y, Ishii J, et al. Estimation of abundance and distribution of two moist tall grasses in the Watarase wetland, Japan, using hyperspectral imagery[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2009,64 (6):674-682.
[35] 娜日苏,格根图,德勒格日玛.退化草甸草原近地面光谱特征初探[J].安徽农业科学,2010,38(5):2512-2514.
[36] Phinn S, Roelfsema C, Dekker A, et al. Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia) [J]. Remote Sensing of Environment, 2008,112(8):3413-3425.
[37] Ishii J, Lu S, Funakoshi S, et al. Mapping potential habitats of threatened plant species in a moist tall grassland using hyperspectral imagery[J]. Biodiversity and Conservation, 2009,18(9):2521-2535.
[38] 刘振国,李镇清.退化草原冷蒿群落13 年不同放牧强度后的植物多样性[J].生态学报,2006,26(2):475-482.
[39] 王焕炯,范闻捷,崔要奎,等.草地退化的高光谱遥感监测方法[J].光谱学与光谱分析,2010,30(10):2734-2738.
/
〈 |
|
〉 |