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Xiao
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PreprintSeasonal patterns of canopy photosynthesis captured by remotely sensed sun-induced fluorescence and vegetation indexes in mid-to-high latitude forests : a cross-platform comparison( 2018-06) Lu, Xinchen ; Cheng, Xiao ; Li, Xianglan ; Chen, Jiquan ; Sun, Minmin ; Ji, Ming ; He, Hong ; Wang, Siyu ; Li, Sen ; Tang, JianwuCharacterized by the noticeable seasonal patterns of photosynthesis, mid-to-high latitude forests are sensitive to climate change and crucial for understanding the global carbon cycle. To monitor the seasonal cycle of the canopy photosynthesis from space, several remote sensing based indexes, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and leaf area index (LAI), have been implemented within the past decades. Recently, satellite-derived sun-induced fluorescence (SIF) has shown great potentials of providing retrievals that are more related to photosynthesis process. However, the potentials of different canopy measurements have not been thoroughly assessed in the context of recent advances of new satellites and proposals of improved indexes. Here, we present a cross-site intercomparison of one emerging remote sensing based index of phenological index (PI) and two SIF datasets against the conventional indexes of NDVI, EVI and LAI to capture the seasonal cycles of canopy photosynthesis. NDVI, EVI, LAI and PI were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements, while SIF were evaluated from Global Ozone Monitoring Experiment-2 (GOME-2) and Orbiting Carbon Observatory-2 (OCO-2) observations. Results indicated that GOME-2 SIF was highly correlated with gross primary productivity (GPP) and absorbed photosynthetically active radiation (APAR) during the growing seasons. Key phenological metrics captured by SIF from GOME-2 and OCO-2 matched closely with photosynthesis phenology as inferred by GPP. However, the applications of OCO-2 SIF for phenological studies may be limited only for a small range of sites (at site-level) due to a limited spatial sampling. Among the MODIS estimations, PI and NDVI provided most reliable predictions of start of growing seasons, while no indexes accurately captured the end of growing seasons.
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ArticleAerial photography based census of Adélie Penguin and its application in CH4 and N2O budget estimation in Victoria Land, Antarctic(Nature Publishing Group, 2017-10-11) He, Hong ; Cheng, Xiao ; Li, Xianglan ; Zhu, Renbin ; Hui, Fengming ; Wu, Wenhui ; Zhao, Tiancheng ; Kang, Jing ; Tang, JianwuPenguin guano provides favorable conditions for production and emission of greenhouse gases (GHGs). Many studies have been conducted to determine the GHG fluxes from penguin colonies, however, at regional scale, there is still no accurate estimation of total GHG emissions. We used object-based image analysis (OBIA) method to estimate the Adélie penguin (Pygoscelis adeliae) population based on aerial photography data. A model was developed to estimate total GHG emission potential from Adélie penguin colonies during breeding seasons in 1983 and 2012, respectively. Results indicated that OBIA method was effective for extracting penguin information from aerial photographs. There were 17,120 and 21,183 Adélie penguin breeding pairs on Inexpressible Island in 1983 and 2012, respectively, with overall accuracy of the estimation of 76.8%. The main reasons for the increase in Adélie penguin populations were attributed to increase in temperature, sea ice and phytoplankton. The average estimated CH4 and N2O emissions tended to be increasing during the period from 1983 to 2012 and CH4 was the main GHG emitted from penguin colonies. Total global warming potential (GWP) of CH4 and N2O emissions was 5303 kg CO2-eq in 1983 and 6561 kg CO2-eq in 2012, respectively.
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PreprintOpportunities and challenges of high-resolution remote sensing of sun-induced fluorescence( 2017-08-17) Lu, Xinchen ; Cheng, Xiao ; Li, Xianglan ; Tang, JianwuEstimating plant photosynthesis and gross primary production (GPP) regionally and globally remains challenging despite its primary role in driving ecosystem productivity and carbon cycling. Recently, satellite-derived sun-induced fluorescence (SIF) provides an alternative approach to investigate GPP from space. However, our ability to apply SIF to estimating GPP at large scales is still lacking, primarily because the SIF-GPP relationships at various spatial and temporal scales is not fully understood. The coarse spatial representativeness (around 0.5 degrees or coarser) of previous remotely sensed SIF data makes it difficult to compare and validate the eddy covariance (EC) based GPP measurements. Orbiting Carbon Observatory-2 (OCO-2) has shown prospects in providing remotely sensed SIF at significantly improved spatial resolutions (around 1.3 km by 2.25 km) that are comparable to ground-based GPP measurements. However, OCO-2 operates at a 16-day revisiting schedule at a sparse spatial sampling strategy. We found that for most EC sites, the observations of OCO-2 passing through are extremely limited. The average number of successfully retrieved SIF by OCO-2 encompassing each site within a year is only 3.17. For EC sites with high companion OCO-2 coverages, we found a strong correlation between GPP and SIF. Despite challenges, the emerging new, high-spatial-resolution remotely sensed SIF data provide unprecedented opportunities to estimate GPP over time and space and its underlying mechanism. We recommend that to fully use the remotely sensed SIF data, a research agenda is critically needed to improve our understanding of the relationship between SIF and GPP across biomes, ecosystems, and even species. We recommend maintaining and upgrading the current EC sites and adding ground-based SIF measurements to provide another scale of SIF observation. We also recommend construction of new EC sites to be within the belts of the observations of OCO-2 or other remotely sensed SIF products to fully use the satellite information.