为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息...为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息丰富的3月份多光谱影像进行主成分变换,选取第1主成分(PC1)作为光谱特征参数,最后基于分类回归树(classification and regression tree,CART)算法进行决策树监督分类。总体分类精度达到92.26%,Kappa系数为0.91,比最大似然法分类结果精度提高了2.58%。研究表明:构建的NDVI时间序列曲线对研究区内的地类具有较强的代表性,提取的时间维和光谱维的分类参数对各地类均有很好地区分性,CART决策树算法分类结果清晰准确且精度较高。该方法为HJ小卫星在干旱半干旱区等区域的深入应用提供科学依据和实证基础。展开更多
The objective of this study is to analyze soil physical and chemical properties,soil comprehensive functions and impact factors after different years of reclamation.Based on the survey data taken from 216 soil samplin...The objective of this study is to analyze soil physical and chemical properties,soil comprehensive functions and impact factors after different years of reclamation.Based on the survey data taken from 216 soil sampling points in the Fengxian Reclamation Area of the Changjiang (Yangtze) River Estuary,China in April 2009 and remotely sensed TM data in 2006,while by virtue of multivariate analysis of variance (MANOVA),geo-statistical analysis (GA),prin-cipal component analysis (PCA) and canonical correspondence analysis (CCA),it was concluded that:1) With the in-crease in reclamation time,soil moisture,soil salinity,soil electric conductivity and soil particle size tended to decline,yet soil organic matter tended to increase.Soil available phosphorous tended to increase in the early reclamation period,yet it tended to decline after about 49 years of reclamation.Soil nitrate nitrogen,soil ammonia nitrogen and pH changed slightly in different reclamation years.Soil physical and chemical properties reached a steady state after about 30 years of reclamation.2) According to the results of PCA analysis,the weighted value (0.97 in total) that represents soil nutrient factors (soil nitrate nitrogen,soil organic matter,soil available phosphorous,soil ammonia nitrogen,pH and soil particle size) were higher than the weighted value (0.48 in total) of soil limiting factors (soil salinity,soil elec-tric conductivity and soil moisture).The higher the F value is,the better the soil quality is.3) Different land use types play different roles in the soil function maturity process,with farmlands providing the best contribution.4) Soil physi-cal and chemical properties in the reclamation area were mainly influenced by reclamation time,and then by land use types.The correlation (0.1905) of the composite index of soil function (F) with reclamation time was greater than that with land use types (-0.1161).展开更多
It is very difficult to have remote sensing data with both high spatial resolution and high temporal frequency; thus, two categories of land-use mapping methodology have been developed separately for coarser resolutio...It is very difficult to have remote sensing data with both high spatial resolution and high temporal frequency; thus, two categories of land-use mapping methodology have been developed separately for coarser resolution and finer resolution data. The first category uses time series of data to retrieve the variation of land surface for classification, which are usually used for coarser resolution data with high temporal frequency. The second category uses fine spatial resolution data to classify different land surface. With the launch of Chinese satellite constellation HJ-1in 2008, four 30 m spatial resolution CCDs with about 360 km coverage for each one onboard two satellites made a revisit period of two days, which brought a new type of data with both high spatial resolution and high temporal frequency. Therefore, by taking the spatiotemporal advantage of HJ-1/CCD data we propose a new method for finer resolution land cover mapping using the time series HJ-1/CCD data, which can greatly improve the land cover mapping accuracy. In our two study areas, the very high resolution remote sensing data within Google Earth are used to validate the land cover mapping results, which shows a very high mapping accuracy of 95.76% and 83.78% and a high Kappa coefficient of 0.9423 and 0.8165 in the Dahuofang area of Liaoning Province and the Heiquan area of Gansu Province respectively.展开更多
文摘为了实现干旱半干旱灌区地表信息低成本、高效率的动态监测,利用HJ-CCD数据的多时相和多光谱信息,探讨了平罗县土地利用遥感分类方法。首先建立研究区内典型地物的NDVI时间序列曲线,提取反映该区物候模式的时序特征参数;然后对土壤信息丰富的3月份多光谱影像进行主成分变换,选取第1主成分(PC1)作为光谱特征参数,最后基于分类回归树(classification and regression tree,CART)算法进行决策树监督分类。总体分类精度达到92.26%,Kappa系数为0.91,比最大似然法分类结果精度提高了2.58%。研究表明:构建的NDVI时间序列曲线对研究区内的地类具有较强的代表性,提取的时间维和光谱维的分类参数对各地类均有很好地区分性,CART决策树算法分类结果清晰准确且精度较高。该方法为HJ小卫星在干旱半干旱区等区域的深入应用提供科学依据和实证基础。
基金Under the auspices of Ministry of Education,China (No.108148)State Key Laboratory of Urban and Regional Ecology (No.SKLURE2010-2-2)+2 种基金National Basic Research Program of China (No.2010CB951203)Key Research Program of Shanghai Science & Technology (No.08231200700,08231200702)111 Project,Ministry of Education,China (No.B08022)
文摘The objective of this study is to analyze soil physical and chemical properties,soil comprehensive functions and impact factors after different years of reclamation.Based on the survey data taken from 216 soil sampling points in the Fengxian Reclamation Area of the Changjiang (Yangtze) River Estuary,China in April 2009 and remotely sensed TM data in 2006,while by virtue of multivariate analysis of variance (MANOVA),geo-statistical analysis (GA),prin-cipal component analysis (PCA) and canonical correspondence analysis (CCA),it was concluded that:1) With the in-crease in reclamation time,soil moisture,soil salinity,soil electric conductivity and soil particle size tended to decline,yet soil organic matter tended to increase.Soil available phosphorous tended to increase in the early reclamation period,yet it tended to decline after about 49 years of reclamation.Soil nitrate nitrogen,soil ammonia nitrogen and pH changed slightly in different reclamation years.Soil physical and chemical properties reached a steady state after about 30 years of reclamation.2) According to the results of PCA analysis,the weighted value (0.97 in total) that represents soil nutrient factors (soil nitrate nitrogen,soil organic matter,soil available phosphorous,soil ammonia nitrogen,pH and soil particle size) were higher than the weighted value (0.48 in total) of soil limiting factors (soil salinity,soil elec-tric conductivity and soil moisture).The higher the F value is,the better the soil quality is.3) Different land use types play different roles in the soil function maturity process,with farmlands providing the best contribution.4) Soil physi-cal and chemical properties in the reclamation area were mainly influenced by reclamation time,and then by land use types.The correlation (0.1905) of the composite index of soil function (F) with reclamation time was greater than that with land use types (-0.1161).
基金supported by the Chinese Academy of Sciences Action Plan for West Development Project (Grant No. KZCX2-XB3-15)the National High-tech R&D Program of China (Grant No. 2012AA12A304)
文摘It is very difficult to have remote sensing data with both high spatial resolution and high temporal frequency; thus, two categories of land-use mapping methodology have been developed separately for coarser resolution and finer resolution data. The first category uses time series of data to retrieve the variation of land surface for classification, which are usually used for coarser resolution data with high temporal frequency. The second category uses fine spatial resolution data to classify different land surface. With the launch of Chinese satellite constellation HJ-1in 2008, four 30 m spatial resolution CCDs with about 360 km coverage for each one onboard two satellites made a revisit period of two days, which brought a new type of data with both high spatial resolution and high temporal frequency. Therefore, by taking the spatiotemporal advantage of HJ-1/CCD data we propose a new method for finer resolution land cover mapping using the time series HJ-1/CCD data, which can greatly improve the land cover mapping accuracy. In our two study areas, the very high resolution remote sensing data within Google Earth are used to validate the land cover mapping results, which shows a very high mapping accuracy of 95.76% and 83.78% and a high Kappa coefficient of 0.9423 and 0.8165 in the Dahuofang area of Liaoning Province and the Heiquan area of Gansu Province respectively.
