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| 1 | Using vegetation indices and texture measures to estimate vegetation fractional coverage (VFC) of planted and natural forests in Nanjing city, China显示文摘 | Zhujun Gu Weimin Ju Lin Li Dengqiu Li Yibo Liu Weiliang Fan | 2012 | Advances in Space Research2012，，： | 1 |
| 2 | Eucalyptus carbon stock estimation in subtropical regions with the modeling strategy of sample plots–airborne LiDAR–Landsat time series data显示文摘Updating eucalyptus carbon stock data in a timely manner is essential for better understanding and quantifying its effects on ecological and hydrological processes.At present,there are no suitable methods to accurately estimate the eucalyptus carbon stock in a large area.This research aimed to explore the transferability of the eucalyptus carbon stock estimation model at temporal and spatial scales and assess modeling performance through the strategy of combining sample plots,airborne LiDAR and Landsat time series data in subtropical regions of China.Specifically,eucalyptus carbon stock estimates in typical sites were obtained by applying the developed models with the combination of airborne LiDAR and field measurement data;the eucalyptus plantation ages were estimated using the random localization segmentation approach from Landsat time series data;and regional models were developed by linking LiDAR-derived eucalyptus carbon stock and vegetation age(e.g.,months or years).To examine the models’robustness,the developed models at the regional scale were transferred to estimate carbon stocks at the spatial and temporal scales,and the modeling results were evaluated using validation samples accordingly.The results showed that carbon stock can be successfully estimated using the age-based models(both age variables in months and years as predictor variables),but the month-based models produced better estimates with a root mean square error(RMSE)of 6.51 t⋅ha1 for Yunxiao County,Fujian Province,and 6.33 t⋅ha1 for Gaofeng Forest Farm,Guangxi Zhuang Autonomous Region.Particularly,the month-based models were superior for estimating the carbon stocks of young eucalyptus plantations of less than two years.The model transferability analyses showed that the month-based models had higher transferability than the year-based models at the temporal scale,indicating their possibility for analysis of carbon stock change.However,both the month-based and year-based models expressed relatively poor transferability at a spatial scale.This study provides new insights for cost-effective monitoring of carbon stock change in intensively managed plantation forests. | Xiandie Jiang Dengqiu Li Guiying Li Dengsheng Lu | 2023 | Forest Ecosystems2023，10，6： | 0 |
| 3 | Comments on ‘FNIP1 regulates adipocyte browning and systemic glucose homeostasis in mice by shaping intracellular calcium dynamics'显示文摘Owing to its remarkable benefits on metabolic health and its demonstrated presence in adult humans,beige or‘brite'adipocytes holdgreatpromiseto combat obesity and metabolic diseases.Delineation of the mechanisms involved inadipocyte‘beiging'or‘browning'is thus of particular interest. | Yujing Yin Dengqiu Xu Yan Mao Zhenji Gan | 2022 | Journal of Molecular Cell Biology2022，14，5： | 0 |
| 4 | Integration of Landsat time-series vegetation indices improves consistency of change detection显示文摘Vegetation indices(VIs)were used to detect when and where vegetation changes occurred.However,different VIs have different or even diametrically opposite results,which obstructed the in-depth understanding of vegetation change.Therefore,this study examined the spatial and temporal consistency offive VIs(EVI;NBR;NDMI;NDVI;and NIRv)in detecting abrupt and gradual vegetation changes,and provided an ensemble algorithm which integrated the change detection results of thefive indices to reduce the uncertainty of change detection using a single index.The spatial consistency of thefive indices in abrupt change detection accounted for 50.6%of the study area,but the temporal consistency was low(21.6%).Wetness indices(NBR,NDMI)were more sensitive to negative abrupt changes,greenness indices(EVI,NDVI,NIRv)were more sensitive to positive abrupt changes;and both types of indices were similar in detecting gradual and total changes.The overall accuracy of the ensemble method was 81.60%and higher than that of any single index in abrupt change detection.This study provides a comprehensive evaluation of the spatial and temporal inconsistencies of change detection in model-fitting errors and various types of vegetation changes.The proposed ensemble method can support robust change-detection. | Mingxing Zhou Dengqiu Li Kuo Liao Dengsheng Lu | 2023 | International Journal of Digital Earth2023，16，1： | 0 |
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