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147 results on '"Hao, Xianjun"'

2. Efficacy of Nitrogen-fixing Bacteria Combined with Different Nitrogen Fertilizers in Improving Enzymatic Activity and Nitrogen in Reclaimed Soil

Author

WANG Shuaibing, MENG Huisheng, WU Xin, ZHANG Jie, HAO Xianjun, HONG Jianping, and JIAO Jincheng

Subjects
nitrogen fertilizer forms, nitrogen-fixing bacteria, dissolved total nitrogen, reclaimed soil, soil enzyme activity, Agriculture (General), S1-972, Irrigation engineering. Reclamation of wasteland. Drainage, TC801-978
Abstract

【Objective】 Reclaimed soils are usually poor in nutrients and the aim of this paper is to investigate the efficacy of nitrogen-fixing bacteria combined with different nitrogen fertilizations in improving fertility of reclaimed soils. 【Method】 The experiments were conducted in pots filled with soil collected from a subsidized coal mining. The soil was incubated with nitrogen-fixing bacteria combined with different nitrogen fertilizers. In each treatment, we measured carbon and nitrogen in microbial biomass, enzymatic activity, total nitrogen, and ammonium and nitrate nitrogen in the soil. 【Result】 Combining nitrogen-fixing bacteria with ammonium or nitrate nitrogen fertilizer increases carbon and nitrogen in microbial biomass, total dissolved nitrogen, ammonium nitrogen in the soil. Compared with treatment with nitrate and ammonium nitrogen fertilization only, their combination with nitrogen-fixing bacteria increases the activity of catalase, sucrase, protease and urease by 4.96%, 17.85%, 12.53% and 6.12% respectively. Correlation analysis shows a close relationship between soil nutrients, enzymatic activity and carbon and nitrogen in microbial biomass; the activity of sucrase, protease and urease is positively correlated with total nitrogen, total dissolved nitrogen and ammonium nitrogen in the soil (P

Published
2022
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6. A Study of California Drought and Wildland Fires Using Satellite Remote Sensing Measurements

Author

SMALL, JOHN and Hao, Xianjun

Abstract

With climate change increasing global temperatures, the threat of wildland fires has become more prevalent because of the dry and hot weather conditions. Knowledge of how and when wildland fires occur can help mitigate their disastrous effects. This project aims to investigate if precipitation trends in California can help scientists understand the patterns of these fires in that state. In this study, we analyzed wildland fire events in California from 2002 to 2019 and satellite remote sensing measurements of monthly precipitation from the NASA Giovanni system. Monthly precipitation anomaly time series was generated to evaluate the dry conditions in California. Compared with records of wildland fires in California collected from the National Interagency Fire Center, precipitation anomalies during fire season show remarkable connections with annual burned areas. In California, the peak fire season is from August to December, so precipitation anomaly time series of these five months in each year was generated for quantitative assessment. Regression analysis shows a moderate negative correlation between monthly precipitation anomaly during peak fire season and the area burned by wildland fires. The correlation suggests a link between precipitation and the damage caused by wildland fires in California. Further investigation into this topic may develop a method for predicting the area of wildland fire damage based on precipitation forecasting from climate models, providing decision supports for government agencies to prepare accordingly., Journal of Student-Scientists' Research, Vol. 2 (2020)

Published
2022
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7. Changes in the Toolik Lake Ecosystem of Alaska in the Past Decades

Author

HAO, LINA and Hao, Xianjun

Abstract

Arctic regions are experiencing faster climate change than any other region in the world. Since the Arctic plays a critical role in the carbon cycle and strongly affects the thermal state of the surrounding permafrost, it is important to understand the impact of Arctic climate changes. This study investigates the climate and ecosystem changes of the Toolik Lake area in Alaska. Satellite remote sensing measurements and long-term baseline environmental and biological data from the Environmental Data Center (EDC) of the Toolik Field Station (TFS) were used to analyze this climate change and its impact on ecosystems. Land surface temperature (LST) data from the Terra/MODIS satellite remote sensing measurements show significant warming of the Toolik lake area in the past two decades, with an increasing trend of 1.049K/decade and 1.186K/decade for daytime and nighttime LST respectively. MODIS NDVI data during the summer season also shows a significant greening trend. EDC field observations show that air temperature above the Toolik lake has an increasing trend of 0.6762K/Decade from 1988 to the present, and 0.8598K/decade from 2000 to present, indicating that there has been faster warming in the past two decades. The thawing times of the Toolik Lake and the inlet river are becoming earlier, and the freezing times of the Toolik Lake and the inlet river are becoming later, causing the ice-free period of the lake to increase significantly. These changes have considerable impacts on local and regional ecosystems; for example, the first seen times of the Arctic ground squirrel around the study area are becoming earlier, and the hibernation periods are becoming shorter, as shown from the EDC field survey data. This study confirmed the rapid warming of Arctic regions and showed changes in the Toolik Lake ecosystem caused by climate change. In future research, these methods can be applied to other regions near the Arctic to gain further insight into changes in the Arctic regions caused by climate change., Journal of Student-Scientists' Research, Vol. 2 (2020)

Published
2022
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18. Assessment of the Reprocessed Suomi NPP VIIRS Enterprise Cloud Mask Product

Author

Lin, Lin, Lin, Lin, Hao, Xianjun, Zhang, Bin, Zou, Cheng-Zhi, Cao, Changyong, Lin, Lin, Lin, Lin, Hao, Xianjun, Zhang, Bin, Zou, Cheng-Zhi, and Cao, Changyong

Abstract

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite continually provides global observations used to retrieve over 20 VIIRS Environmental Data Record (EDR) products. Among them, the cloud mask product is essential for many other VIIRS EDR products such as aerosols, ocean color, and active fire. The reprocessed S-NPP VIIRS Sensor Data Record (SDR) data produced by NOAA/Center for Satellite Applications and Research (STAR) have shown improved stability and consistency. Recently, the VIIRS Enterprise Cloud Mask (ECM) has been reprocessed using the reprocessed VIIRS SDR data. This study assesses the reprocessed ECM product by comparing the reprocessed cloud mask types and cloud probability with those from the operational VIIRS ECM product. It found that the overall differences are small. Most of the discrepancies occur between neighboring types at the cloud edge. These findings help lay the foundation for the user community to understand the reprocessed ECM product. In addition, due to the better quality of the reprocessed VIIRS SDR data that are utilized to generate the reprocessed ECM product, it is expected that the reprocessed ECM product will have better stability and consistency compared to the operational ECM products. Therefore, the reprocessed ECM product is a useful benchmark for the user community.

Published
2021

24. Earth Observations

Author

Chiu, Long, primary, Hao, Xianjun, additional, Resmini, Ronald, additional, Sun, Donglian, additional, Stefanidis, Anthony, additional, Qu, John, additional, and Yang, Ruixin, additional

Published
2010
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26. The Reprocessed Suomi NPP Satellite Observations

Author

Zou, Cheng-Zhi, primary, Zhou, Lihang, additional, Lin, Lin, additional, Sun, Ninghai, additional, Chen, Yong, additional, Flynn, Lawrence E., additional, Zhang, Bin, additional, Cao, Changyong, additional, Iturbide-Sanchez, Flavio, additional, Beck, Trevor, additional, Yan, Banghua, additional, Kalluri, Satya, additional, Bai, Yan, additional, Blonski, Slawomir, additional, Choi, Taeyoung, additional, Divakarla, Murty, additional, Gu, Yalong, additional, Hao, Xianjun, additional, Li, Wei, additional, Liang, Ding, additional, Niu, Jianguo, additional, Shao, Xi, additional, Strow, Larrabee, additional, Tobin, David C., additional, Tremblay, Denis, additional, Uprety, Sirish, additional, Wang, Wenhui, additional, Xu, Hui, additional, Yang, Hu, additional, and Goldberg, Mitchell D., additional

Published
2020
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40. Towards estimation of canopy foliar biomass with spectral reflectance measurements

Author

Wang, Lingli, Hunt, E. Raymond, Jr., Qu, John J., Hao, Xianjun, Daughtry, Craig S.T., Wang, Lingli, Hunt, E. Raymond, Jr., Qu, John J., Hao, Xianjun, and Daughtry, Craig S.T.

Abstract

Canopy foliar biomass, defined as the product of leaf dry matter content and leaf area index, is an important measurement for global biogeochemical cycles. This study explores the potential for retrieving foliar biomass in green canopies using a spectral index, the Normalized Dry Matter Index (NDMI). This narrow-band index is based on absorption at the C–H bond stretch overtone and is correlated with leaf dry matter content in fresh green leaves. PROSPECT and SAIL model simulations suggest that the NDMI at the canopy scale is able to minimize the effects of leaf thickness and leaf water content and to maximize sensitivity to variation in canopy foliar biomass. The simulation outputs were analyzed with an ANOVA, and 87% of the variation in the NDMI is explained by leaf dry matter content. The NDMI was linearly related to foliar biomass (g cm−2) from model simulations (R2=0.97). The NDMI calculated from spectral reflectances for one to four stacked leaves was also correlated with total leaf biomass (R2=0.59). These results suggest that it may be possible to determine foliar biomass from airborne and satellite-borne imaging spectrometers, such as NASA's HyspIRI mission.

Published
2011

43. Bridging Earth Observations: Remote Sensing Measurements, Fire Modeling and Air Quality Decision Support System in the Eastern United States

Author

Qu, John J., Hao, Xianjun, Yang, Ruixin, Somers, William, Dasgupta, Swarvanu, Bhoi, Sanjeeb, Kafatos, Menas, Liu, Yongqiang, Achtemeier, Gary, Riebau, Allen R., Coronado, Patrick, Qu, John J., Hao, Xianjun, Yang, Ruixin, Somers, William, Dasgupta, Swarvanu, Bhoi, Sanjeeb, Kafatos, Menas, Liu, Yongqiang, Achtemeier, Gary, Riebau, Allen R., and Coronado, Patrick

Abstract

Prescribed burning is a major tool used by land managers to reduce the threat of catastrophic wildfires and for maintaining forest ecosystem productivity, health, and diversity. However, smoke from fire emissions frequently impacts the air quality of populated areas and is governed by state air quality regulations in most areas. High-resolution models are very useful tools for understanding fire emissions, smoke dispersion, and the air quality effects. The state-of-the-art fire and air quality decision support systems (DSS) such as CAMQ / SMOKE / Bluesky (CSB) provide fire managers and air quality managers with information needed for planning fuels treatments and supporting state air quality smoke regulatory actions, especially as related to prescribed fires.

Published
2005

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