Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In...Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM＋ images of 1989, 2001, and 2006, and supported by Geographic Information System （GIS） spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSl （vegetation, bare soil and shadow indices） suitable for TM/ETM＋ irrlages, constructed with FCD （forest canopy density） model principle and put forward by ITTO （International Tropical Timber Organization）, was used, and it was applied to estimate the VFC. The estimation accuracy was later prow^n to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover diigital images to deeply analyze the reason behind the variation.展开更多
The objective of this paper is to improve the monitoring speed and precision of fractional vegetation cover (fc). It mainly focuses on fc estimation when fcmax and fcmin are not approximately equal to 100% and 0%, res...The objective of this paper is to improve the monitoring speed and precision of fractional vegetation cover (fc). It mainly focuses on fc estimation when fcmax and fcmin are not approximately equal to 100% and 0%, respectively due to using remote sensing image with medium or low spatial resolution. Meanwhile, we present a new method of fc estimation based on a random set of fc maximum and minimum values from digital camera (DC) survey data and a di- midiate pixel model. The results show that this is a convenient, efficient and accurate method for fc monitoring, with the maximum error -0.172 and correlation coefficient of 0.974 between DC survey data and the estimated value of the remote sensing model. The remaining DC survey data can be used as verification data for the precision of the fc estimation. In general, the estimation of fc based on DC survey data and a remote sensing model is a brand-new development trend and deserves further extensive utilization.展开更多
Leaf area index(LAI) is a key factor that determines a forest ecosystem's net primary production and energy exchange between the atmosphere and land surfaces.LAI can be measured in many ways, but there has been li...Leaf area index(LAI) is a key factor that determines a forest ecosystem's net primary production and energy exchange between the atmosphere and land surfaces.LAI can be measured in many ways, but there has been little research to compare LAI estimated by different methods. In this study, we compared the LAI results from two different approaches, i.e., the dimidiate pixel model(DPM) and an empirical statistic model(ESM) using ZY-3 high-accuracy satellite images validated by field data. We explored the relationship of LAI of Larix principis-rupprechtii Mayr plantations with topographic conditions. The results show that DPM improves the simulation of LAI(r = 0.86,RMSE = 0.57) compared with ESM(r = 0.62, RMSE =0.79). We further concluded that elevation and slope significantly affect the distribution of LAI. The maximum peak of LAI appeared at an aspect of east and southeast at an elevation of 1700–2000 m. Our results suggest that ZY-3 can satisfy the needs of quantitative monitoring of leaf area indices in small-scale catchment areas. DPM provides a simple and accurate method to obtain forest vegetation parameters in the case of non-ground measurement points.展开更多
As China has recently launched the GaoFen-1 satellite(GF-1)carrying on the wide-field view(WFV)sensor,it is a challenging task to make full use of its observations to produce the fractional vegetation cover(FVC).In li...As China has recently launched the GaoFen-1 satellite(GF-1)carrying on the wide-field view(WFV)sensor,it is a challenging task to make full use of its observations to produce the fractional vegetation cover(FVC).In light of this,our study presents a comprehensive algorithm to generate a 16 m/10-day FVC product by considering the vegetation types characteristics.For forests,considering the foliage clumping effect,FVC was estimated from the gap probability theory using GF-1 leaf area index(LAI)and clumping index(CI)as a priori knowledge;for non-forests,FVC was estimated from the dimidiate pixel model using GF-1 normalized difference vegetation index(NDVI).The performance of GF-1 FVC from 2018 to 2020 was evaluated using FVC ground measurements obtained from 7 sites for crops,grasslands,and forests in China.The direct validation indicated that the performance of the FVC product was satisfactory,as evidenced by R2=0.55,RMSE=0.15 and BIAS=0.01 for all vegetation types.Furthermore,the GF-1 FVC exhibited better performance compared to the GEOV3 FVC at a spatial resolution of 300 meters.Moreover,the 10-day temporal interval of GF-1 FVC product successfully facilitated the extraction of regional phenological information at a spatial resolution of 16 meters.展开更多
基金supported by the National Basic Research Program of China (2009CB421302)the Joint Fundsof the National Natural Science Foundation of China(U1138303)+4 种基金the National Natural Science Foundation of China(41261090,41161063)the Open Foundation of State Key Laboratory of Resources and Environment Information Systems (2010KF0003SA)Scientific Research Foundation for Doctor (BS110125)Xinjiang Natural Science Foundation for Young Scholars (2012211B04)Research Fund for Training Young Teachers (XJEDU2012S03)
文摘Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM＋ images of 1989, 2001, and 2006, and supported by Geographic Information System （GIS） spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSl （vegetation, bare soil and shadow indices） suitable for TM/ETM＋ irrlages, constructed with FCD （forest canopy density） model principle and put forward by ITTO （International Tropical Timber Organization）, was used, and it was applied to estimate the VFC. The estimation accuracy was later prow^n to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover diigital images to deeply analyze the reason behind the variation.
基金Projects NCET-04-0484 supported by the New-Century Outstanding Young Scientist Program from the Ministry of Education and D0605046040191-101Beijing Science and Technology Program
文摘The objective of this paper is to improve the monitoring speed and precision of fractional vegetation cover (fc). It mainly focuses on fc estimation when fcmax and fcmin are not approximately equal to 100% and 0%, respectively due to using remote sensing image with medium or low spatial resolution. Meanwhile, we present a new method of fc estimation based on a random set of fc maximum and minimum values from digital camera (DC) survey data and a di- midiate pixel model. The results show that this is a convenient, efficient and accurate method for fc monitoring, with the maximum error -0.172 and correlation coefficient of 0.974 between DC survey data and the estimated value of the remote sensing model. The remaining DC survey data can be used as verification data for the precision of the fc estimation. In general, the estimation of fc based on DC survey data and a remote sensing model is a brand-new development trend and deserves further extensive utilization.
基金supported by the National Forestry Public Welfare Professional Scientific Research Project(No.201404213)the National Key Research and Development Program of China(No.2016YFD0600205)
文摘Leaf area index(LAI) is a key factor that determines a forest ecosystem's net primary production and energy exchange between the atmosphere and land surfaces.LAI can be measured in many ways, but there has been little research to compare LAI estimated by different methods. In this study, we compared the LAI results from two different approaches, i.e., the dimidiate pixel model(DPM) and an empirical statistic model(ESM) using ZY-3 high-accuracy satellite images validated by field data. We explored the relationship of LAI of Larix principis-rupprechtii Mayr plantations with topographic conditions. The results show that DPM improves the simulation of LAI(r = 0.86,RMSE = 0.57) compared with ESM(r = 0.62, RMSE =0.79). We further concluded that elevation and slope significantly affect the distribution of LAI. The maximum peak of LAI appeared at an aspect of east and southeast at an elevation of 1700–2000 m. Our results suggest that ZY-3 can satisfy the needs of quantitative monitoring of leaf area indices in small-scale catchment areas. DPM provides a simple and accurate method to obtain forest vegetation parameters in the case of non-ground measurement points.
基金supported by National Key Research and Development Program under Grant 2019YFE0126700the National Natural Science Foundation of China under Grant 41871265.
文摘As China has recently launched the GaoFen-1 satellite(GF-1)carrying on the wide-field view(WFV)sensor,it is a challenging task to make full use of its observations to produce the fractional vegetation cover(FVC).In light of this,our study presents a comprehensive algorithm to generate a 16 m/10-day FVC product by considering the vegetation types characteristics.For forests,considering the foliage clumping effect,FVC was estimated from the gap probability theory using GF-1 leaf area index(LAI)and clumping index(CI)as a priori knowledge;for non-forests,FVC was estimated from the dimidiate pixel model using GF-1 normalized difference vegetation index(NDVI).The performance of GF-1 FVC from 2018 to 2020 was evaluated using FVC ground measurements obtained from 7 sites for crops,grasslands,and forests in China.The direct validation indicated that the performance of the FVC product was satisfactory,as evidenced by R2=0.55,RMSE=0.15 and BIAS=0.01 for all vegetation types.Furthermore,the GF-1 FVC exhibited better performance compared to the GEOV3 FVC at a spatial resolution of 300 meters.Moreover,the 10-day temporal interval of GF-1 FVC product successfully facilitated the extraction of regional phenological information at a spatial resolution of 16 meters.
