Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multipli...Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables. How these variables affect their corresponding spatial heterogeneities, however, have received little attention. In this paper, we examined the effects of characteristics of normalized difference vegetation index （NDVI） and its related bands variable images, namely red and near infrared （NIR）, on their corresponding spatial heterogeneity detection based on variogram models. In a coastal wetland region, two groups of study sites with distinct fractal vegetation cover were tested and analyzed. The results show that： l） in high fractal vegetation cover （H-FVC） area, NDV! and NIR variables display a similar ability in detecting the spatial he- terogeneity caused by vegetation growing status structure; 2） in low fractal vegetation cover （L-FVC） area, the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3） generally, NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers. Moreover, as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account, the proposed variogram analysis method can make the variable selection objectively and scientifically, especially in studies related to spatial heterogeneity using remotely sensed data.展开更多
Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has ...Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.展开更多
Through an analysis of Landsat multispectral images of visible, thermal and near-infrared bands, the spatiotemporal change of biophysical parameters： NDVI （normalized difference vegetation index）, blackbody tempera...Through an analysis of Landsat multispectral images of visible, thermal and near-infrared bands, the spatiotemporal change of biophysical parameters： NDVI （normalized difference vegetation index）, blackbody temperature and albedo, were estimated for Mexicali city, using principal component analysis and time series. The satellite images correspond to the dates： April 6, 1993; May 3, 2000; May 12, 2003; May 17, 2008 and May 26, 2011; the results reveal a change in relation to urban growth. In 1993, the vegetation was 20% and in 2011 it decreased to 3.8%. The blackbody temperature increased from 34.0 ℃ to 41.0 ℃ and albedo decreased by 0.37 compared to 1993. The most deteriorated area appears in surroundings of the city because of the change in the vegetation cover by the urban elements.展开更多
Rocky desertification is a serious threat to socioeconomic development and the ecological security of karst areas. The control of rocky desertification has therefore become a major concern of both the Chinese governme...Rocky desertification is a serious threat to socioeconomic development and the ecological security of karst areas. The control of rocky desertification has therefore become a major concern of both the Chinese government and local populations living in karst areas. In this paper, we used the national evaluation system for monitoring rocky desertification, and adjusted relevant indices. For example, we improved the system＇s base rock exposure index with Normalized Difference Rock index（NDRI）, substituted a soil erosion index for soil depth, and from these obtained the categories and spatial distribution of rocky desertification. We also studied the main factors and functional mechanisms of rocky desertification with consideration given to natural geographic conditions such as soil, physiognomy, elevation, slope and river network density, and, also human interference factors such as population density, GDP, population distribution, and from these got spatial distribution characteristics and influencing factors of rocky desertification in Qiandongnan prefecture. Results indicate that the primary soil types of rocky desertification in the research areas include yellow, limestone and paddy soils. These rocky desertification areas are more likely to contain limestone soil than purple soil, and least likely to contain paddy soil. The distribution of moderate or severe rocky desertification in areas with moderate to steep slope is 40%, where sloping agricultural land comprises a large proportion of the total. Rocky desertification is widely distributed in regions with precipitation between 1000–1200 mm, and this precipitation is the main factor causing greater soil erosion in limestone soil base and sloping agricultural areas. Moreover, desertification is closely related to the distribution of residential areas, population density, poverty and sloping agricultural land展开更多
基金Under the auspices of National Key Technology Research and Development Program of China (No.2009BADB3B01-05)Knowledge Innovation Programs of Chinese Academy of Sciences (No. KSCX1-YW-09-13)
文摘Spatial heterogeneity is widely used in diverse applications, such as recognizing ecological process, guiding ecological restoration, managing land use, etc. Many researches have focused on the inherent scale multiplicity of spatial heterogeneity by using various environmental variables. How these variables affect their corresponding spatial heterogeneities, however, have received little attention. In this paper, we examined the effects of characteristics of normalized difference vegetation index （NDVI） and its related bands variable images, namely red and near infrared （NIR）, on their corresponding spatial heterogeneity detection based on variogram models. In a coastal wetland region, two groups of study sites with distinct fractal vegetation cover were tested and analyzed. The results show that： l） in high fractal vegetation cover （H-FVC） area, NDV! and NIR variables display a similar ability in detecting the spatial he- terogeneity caused by vegetation growing status structure; 2） in low fractal vegetation cover （L-FVC） area, the NIR and red variables outperform NDVI in the survey of soil spatial heterogeneity; and 3） generally, NIR variable is ubiquitously applicable for vegetation spatial heterogeneity investigation in different fractal vegetation covers. Moreover, as variable selection for remote sensing applications should fully take the characteristics of variables and the study object into account, the proposed variogram analysis method can make the variable selection objectively and scientifically, especially in studies related to spatial heterogeneity using remotely sensed data.
基金Under the auspices of National Natural Science Foundation of China(No.41071267,41001254)Natural Science Foundation of Fujian Province(No.2012I0005,2012J01167)
文摘Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.
文摘Through an analysis of Landsat multispectral images of visible, thermal and near-infrared bands, the spatiotemporal change of biophysical parameters： NDVI （normalized difference vegetation index）, blackbody temperature and albedo, were estimated for Mexicali city, using principal component analysis and time series. The satellite images correspond to the dates： April 6, 1993; May 3, 2000; May 12, 2003; May 17, 2008 and May 26, 2011; the results reveal a change in relation to urban growth. In 1993, the vegetation was 20% and in 2011 it decreased to 3.8%. The blackbody temperature increased from 34.0 ℃ to 41.0 ℃ and albedo decreased by 0.37 compared to 1993. The most deteriorated area appears in surroundings of the city because of the change in the vegetation cover by the urban elements.
基金National Key Research and Development Program of China(2016YFC0503700)
文摘Rocky desertification is a serious threat to socioeconomic development and the ecological security of karst areas. The control of rocky desertification has therefore become a major concern of both the Chinese government and local populations living in karst areas. In this paper, we used the national evaluation system for monitoring rocky desertification, and adjusted relevant indices. For example, we improved the system＇s base rock exposure index with Normalized Difference Rock index（NDRI）, substituted a soil erosion index for soil depth, and from these obtained the categories and spatial distribution of rocky desertification. We also studied the main factors and functional mechanisms of rocky desertification with consideration given to natural geographic conditions such as soil, physiognomy, elevation, slope and river network density, and, also human interference factors such as population density, GDP, population distribution, and from these got spatial distribution characteristics and influencing factors of rocky desertification in Qiandongnan prefecture. Results indicate that the primary soil types of rocky desertification in the research areas include yellow, limestone and paddy soils. These rocky desertification areas are more likely to contain limestone soil than purple soil, and least likely to contain paddy soil. The distribution of moderate or severe rocky desertification in areas with moderate to steep slope is 40%, where sloping agricultural land comprises a large proportion of the total. Rocky desertification is widely distributed in regions with precipitation between 1000–1200 mm, and this precipitation is the main factor causing greater soil erosion in limestone soil base and sloping agricultural areas. Moreover, desertification is closely related to the distribution of residential areas, population density, poverty and sloping agricultural land
