Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in ...Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in Lake Taihu, China from 2018 to 2019 is collected and collocated with GF-1 satellite data. This study develops a general and reliable estimation of Chl-a concentration from GF-1 WFV data under turbid inland water conditions. The collocated data are classified according to season and used in random forest(RF) regression to train models for retrieving the lake Chl-a concentration. A composite index is developed to select the most important variables in the models. The models trained for each season show a better performance than the model trained by using the whole year data in terms of the coefficient of determination(R^(2)) between retrievals and observations. Specifically, the R2 values in spring, summer, autumn, and winter are 0.88, 0.88, 0.94, and 0.74, respectively;whereas that using the whole year data is only 0.71. The Chl-a concentration in Lake Taihu exhibits an obvious seasonal change with the highest in summer, followed by autumn and spring, and the lowest in winter. The Chl-a concentration also displays an obvious spatial variation with season. A high concentration occurs mainly in the northwest of the lake. The temporal and spatial changes of Chl-a concentration are almost consistent with the changes in the areas and times of cyanobacteria blooms based on Moderate Resolution Imaging Spectroradiometer(MODIS) data. The proposed algorithm can be operated without a priori knowledge on atmospheric conditions and water quality. Our study also demonstrates that GF-1 data are increasingly valuable for monitoring the Chl-a concentration of inland water bodies in China at a high spatial resolution.展开更多
The precise glacier boundary is a fundamental requirement for glacier inventory,the assessment of climate change and water management in remote mountain areas.However,some glaciers in mountain areas are covered by deb...The precise glacier boundary is a fundamental requirement for glacier inventory,the assessment of climate change and water management in remote mountain areas.However,some glaciers in mountain areas are covered by debris.The high spatial resolution images bring opportunities in mapping debris-covered glaciers.To discuss the capability of Chinese GaoFen-1 satellite lacking the short wave infrared band and thermal infrared band in mapping glaciers,this study distinguished supraglacial terrain from surrounding debris by combining GaoFen-1(GF-1)wide-field-view(WFV)images,the ratio of the thermal infrared imagery and morphometric parameters(DEM and slope)with 30 m resolution.The overall accuracy of 90.94%indicated that this method was effective for mapping supraglacial terrain in mountain areas.Comparing this result with the combination of GF-1 WFV and low-resolution morphometric parameters shows that a high-quality DEM and the thermal infrared band enhanced the accuracy of glacier mapping especially debris-covered ice in steep terrain.The user's and producer's accuracies of glacier area were also improved from 89.67%and 85.95%to 92.83%and 90.34%,respectively.GF data is recommended for mapping heavily debris-covered glaciers and will be combined with SAR data for future studies.展开更多
叶面积指数(leaf area index,LAI)是研究植被生态系统结构和功能的核心参数之一,遥感是获取大范围动态LAI的一个主要技术手段。但目前国际上没有高分辨率的LAI标准化产品,本研究利用高分一号(GF-1)宽幅相机高时空分辨率的特点,基于三维...叶面积指数(leaf area index,LAI)是研究植被生态系统结构和功能的核心参数之一,遥感是获取大范围动态LAI的一个主要技术手段。但目前国际上没有高分辨率的LAI标准化产品,本研究利用高分一号(GF-1)宽幅相机高时空分辨率的特点,基于三维随机辐射传输模型生产了MuSyQ(Multi-source data Synergized Quantitative remote sensing production system)高分系列中国地区2018–2020年16米/10天分辨率的标准化LAI产品01版。本产品可为中国地区植被变化分析、农林业示范应用、生态环境监测提供可靠的数据支撑。展开更多
基金Supported by the National Key Research and Development Program of China(2018YFC1506500)Foundation for Key Scientific Research of Jiangsu Meteorological Bureau(KZ202003)。
文摘Wide-field-of-view(WFV) imager that observes the earth environment with four solar reflective bands in a spatial resolution of 16 m is equipped on board Gaofen-1(GF-1) satellite. Chlorophyll-a(Chl-a) concentration in Lake Taihu, China from 2018 to 2019 is collected and collocated with GF-1 satellite data. This study develops a general and reliable estimation of Chl-a concentration from GF-1 WFV data under turbid inland water conditions. The collocated data are classified according to season and used in random forest(RF) regression to train models for retrieving the lake Chl-a concentration. A composite index is developed to select the most important variables in the models. The models trained for each season show a better performance than the model trained by using the whole year data in terms of the coefficient of determination(R^(2)) between retrievals and observations. Specifically, the R2 values in spring, summer, autumn, and winter are 0.88, 0.88, 0.94, and 0.74, respectively;whereas that using the whole year data is only 0.71. The Chl-a concentration in Lake Taihu exhibits an obvious seasonal change with the highest in summer, followed by autumn and spring, and the lowest in winter. The Chl-a concentration also displays an obvious spatial variation with season. A high concentration occurs mainly in the northwest of the lake. The temporal and spatial changes of Chl-a concentration are almost consistent with the changes in the areas and times of cyanobacteria blooms based on Moderate Resolution Imaging Spectroradiometer(MODIS) data. The proposed algorithm can be operated without a priori knowledge on atmospheric conditions and water quality. Our study also demonstrates that GF-1 data are increasingly valuable for monitoring the Chl-a concentration of inland water bodies in China at a high spatial resolution.
基金Science&Technology Basic Resources Investigation Program of China(Grant Nos.2017FY100502,2017FY100503)the National Natural Science Foundation of China(Grant Nos.41471291,41801273)
文摘The precise glacier boundary is a fundamental requirement for glacier inventory,the assessment of climate change and water management in remote mountain areas.However,some glaciers in mountain areas are covered by debris.The high spatial resolution images bring opportunities in mapping debris-covered glaciers.To discuss the capability of Chinese GaoFen-1 satellite lacking the short wave infrared band and thermal infrared band in mapping glaciers,this study distinguished supraglacial terrain from surrounding debris by combining GaoFen-1(GF-1)wide-field-view(WFV)images,the ratio of the thermal infrared imagery and morphometric parameters(DEM and slope)with 30 m resolution.The overall accuracy of 90.94%indicated that this method was effective for mapping supraglacial terrain in mountain areas.Comparing this result with the combination of GF-1 WFV and low-resolution morphometric parameters shows that a high-quality DEM and the thermal infrared band enhanced the accuracy of glacier mapping especially debris-covered ice in steep terrain.The user's and producer's accuracies of glacier area were also improved from 89.67%and 85.95%to 92.83%and 90.34%,respectively.GF data is recommended for mapping heavily debris-covered glaciers and will be combined with SAR data for future studies.
文摘叶面积指数(leaf area index,LAI)是研究植被生态系统结构和功能的核心参数之一,遥感是获取大范围动态LAI的一个主要技术手段。但目前国际上没有高分辨率的LAI标准化产品,本研究利用高分一号(GF-1)宽幅相机高时空分辨率的特点,基于三维随机辐射传输模型生产了MuSyQ(Multi-source data Synergized Quantitative remote sensing production system)高分系列中国地区2018–2020年16米/10天分辨率的标准化LAI产品01版。本产品可为中国地区植被变化分析、农林业示范应用、生态环境监测提供可靠的数据支撑。
