Landsat TM data(June 23,1988,May 6,2007) and Landsat ETM+data(May 10,2000) of Neijiang City,Sichuan Province was taken as the data source,brightness temperature of the study area was obtained by using TM/ETM+thermal i...Landsat TM data(June 23,1988,May 6,2007) and Landsat ETM+data(May 10,2000) of Neijiang City,Sichuan Province was taken as the data source,brightness temperature of the study area was obtained by using TM/ETM+thermal infrared wave,and also normalized difference vegetation index(NDVI) was calculated.NDVI of the study area on June 23,1988,May 6,2007,and May 10,2000 was respectively obtained by using Band Math,the least square fitting was adopted to simulate the correlation between surface temperature and vegetation cover.Moreover,linear regression analysis of the correlation between vegetation cover and NDVI was carried out in Excel.The results showed that(a) most of the constructed area has a low NDVI value because there are large areas of hard surface such as buildings and roads,but less vegetation cover;(b) the quarters with better vegetation cover have higher NDVI values;the Tuojiang River has a negative NDVI value;rural areas have better vegetation cover and higher NDVI values.Brightness temperature and vegetation cover has distinct negative correlation,specifically,the higher the vegetation cover is,the lower the surface temperature is,and vice versa.展开更多
The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-eff...The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-efficient real-time nutrition diagnosis technology in citrus orchards.The fluorescent values of leaves and canopy based on the Multiplex 3.6 sensor,canopy hyperspectral reflectance data based on the FieldSpec4 radiometer and spectral reflectance based on low-altitude multispectral remote sensing were collected from leaves of Shatang mandarin and then analyzed.Additionally,the associations of the leaf SPAD(soil and plant analyzer development)value with the ratio vegetation index(RVI)and normalized differential vegetation index(NDVI)were analyzed.The leaf SPAD value predictive model was established by means of univariate and multiple linear regressions and the partial least squares method.Variable distribution maps of the relative canopy chlorophyll content based on spectral reflectance in the orchard were automatically created.The results showed that the correlations of the SPAD values obtained from the Multiplex 3.6 sensor,FieldSpec4 radiometer and low-altitude multispectral remote sensing were highly significant.The measures of goodness of fit of the predictive models were R^(2)=0.7063,RMSECV=3.7892,RE=5.96%,and RMSEP=3.7760 based on RVI_((570/800)) and R^(2)=0.7343,RMSECV=3.6535,RE=5.49%,and RMSEP=3.3578 based on NDVI[(570,800)(570,950)(700,840)].The technique to create spatial distribution maps of the relative canopy chlorophyll content in the orchard was established based on sensor information that directly reflected the chlorophyll content of the plants in different parts of the orchard,which in turn provides evidence for implementation of orchard productivity evaluation and precision in fertilization management.展开更多
文摘Landsat TM data(June 23,1988,May 6,2007) and Landsat ETM+data(May 10,2000) of Neijiang City,Sichuan Province was taken as the data source,brightness temperature of the study area was obtained by using TM/ETM+thermal infrared wave,and also normalized difference vegetation index(NDVI) was calculated.NDVI of the study area on June 23,1988,May 6,2007,and May 10,2000 was respectively obtained by using Band Math,the least square fitting was adopted to simulate the correlation between surface temperature and vegetation cover.Moreover,linear regression analysis of the correlation between vegetation cover and NDVI was carried out in Excel.The results showed that(a) most of the constructed area has a low NDVI value because there are large areas of hard surface such as buildings and roads,but less vegetation cover;(b) the quarters with better vegetation cover have higher NDVI values;the Tuojiang River has a negative NDVI value;rural areas have better vegetation cover and higher NDVI values.Brightness temperature and vegetation cover has distinct negative correlation,specifically,the higher the vegetation cover is,the lower the surface temperature is,and vice versa.
基金supported by the China National Key Research and Development Project(2016YFD0200703)the China National Science&Technology Support Program(2014BAD16B0103)+1 种基金the China Chongqing Science&Technology Support&Demonstration Project(CSTC2014fazktpt80015)the Jiangxi Province 2011 Collaborative Innovation Special Funds“Co-Innovation Center of the South China Mountain Orchard Intelligent Management Technology and Equipment”(Jiangxi Finance Refers to[2014]No.156).
文摘The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-efficient real-time nutrition diagnosis technology in citrus orchards.The fluorescent values of leaves and canopy based on the Multiplex 3.6 sensor,canopy hyperspectral reflectance data based on the FieldSpec4 radiometer and spectral reflectance based on low-altitude multispectral remote sensing were collected from leaves of Shatang mandarin and then analyzed.Additionally,the associations of the leaf SPAD(soil and plant analyzer development)value with the ratio vegetation index(RVI)and normalized differential vegetation index(NDVI)were analyzed.The leaf SPAD value predictive model was established by means of univariate and multiple linear regressions and the partial least squares method.Variable distribution maps of the relative canopy chlorophyll content based on spectral reflectance in the orchard were automatically created.The results showed that the correlations of the SPAD values obtained from the Multiplex 3.6 sensor,FieldSpec4 radiometer and low-altitude multispectral remote sensing were highly significant.The measures of goodness of fit of the predictive models were R^(2)=0.7063,RMSECV=3.7892,RE=5.96%,and RMSEP=3.7760 based on RVI_((570/800)) and R^(2)=0.7343,RMSECV=3.6535,RE=5.49%,and RMSEP=3.3578 based on NDVI[(570,800)(570,950)(700,840)].The technique to create spatial distribution maps of the relative canopy chlorophyll content in the orchard was established based on sensor information that directly reflected the chlorophyll content of the plants in different parts of the orchard,which in turn provides evidence for implementation of orchard productivity evaluation and precision in fertilization management.
