scholarly journals Estimation of Soil Respiration by Its Driving Factors Based on Multi-Source Data in a Sub-Alpine Meadow in North China

2019 ◽  
Vol 11 (12) ◽  
pp. 3274 ◽  
Author(s):  
Yanan Liang ◽  
Yanpeng Cai ◽  
Junxia Yan ◽  
Hongjian Li
Keyword(s):  
Remote Sensing ◽  
Soil Respiration ◽  
Seasonal Variations ◽  
Land Surface ◽  
North China ◽  
Alpine Meadow ◽  
Temporal Variations ◽  
Exponential Model ◽  
Climatic Conditions ◽  
Significant Difference

Soil respiration (Rs) in high-altitude areas are normally sensitive to varying climatic conditions. The objective of this research was mainly to explore temporal variations in Rs rates and the corresponding controlling factors for the establishment of appropriate fitting models in a sub-alpine meadow of north China. The data was obtained through field measuring and extraction of the Moderate Resolution Imaging Spectroradiometer (MODIS) in the geographical unit of the study site over the period of 2007 to 2015. The main results were as follows: (1) seasonal variations in Rs rates, soil temperature (Ts), land surface temperature (LST), and normalized difference vegetation index (NDVI) all produced symmetrical bell type patterns, while soil moisture (Ms) showed a fluctuating pattern, (2) a Ts-exponential model could greatly capture seasonal variations of Rs rates in the study site, reflecting the role of temperature as a dominant driving factor in determining Rs temporal variations in alpine meadow areas, (3) there was no significant difference between the performing indicators evaluating the proposed Ts-exponential model and the LST-exponential model. This indicated great potential for applying remote sensing products to estimate seasonal Rs rates and 4) seasonal variations in Rs rates towards temperature sensitivity (Q10) showed a concave curve and dramatically decreased as the temperature increased from −1 to 11 °C. Overall, the results indicated that attention to significant effects of climatic conditions on Rs, particularly in areas of low temperature, should be warranted. Also, applicability of remote sensing products for estimating Rs was reflected and demonstrated.

scholarly journals Spatial and temporal variations of CO<sub>2</sub> mole fractions observed at Beijing, Xianghe and Xinglong in North China

2021 ◽  
Author(s):  
Yang Yang ◽  
Minqiang Zhou ◽  
Ting Wang ◽  
Bo Yao ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Human Activities ◽  
North China ◽  
Terrestrial Ecosystem ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Boundary Layer Height ◽  
The Mean ◽  
The Impact ◽  
First Time

Abstract. Atmospheric CO2 mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using the Picarro G2301 Cavity Ring-Down Spectroscopy instruments. The measurement system is described comprehensively for the first time. The geo-distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO2 mole fractions at BJ, XH, and XL between October 2018 and September 2019 are 448.4 ± 12.8 ppm, 436.0 ± 9.2 ppm and 420.6 ± 8.2 ppm, respectively. The seasonal variations of CO2 at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO2 at BJ and XH are more affected by human activities as compared to XL. By using CO2 at XL as the background, CO2 enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO2 are driven by the boundary layer height, photosynthesis and human activities at BJ, XH and XL. Moreover, we address the impact of the wind on the CO2 mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations of CO2 mole fractions in North China.

scholarly journals Temporal variations in rockfall and rock-wall retreat rates in a deglaciated valley over the past 11 k.y.

Geology ◽  
2020 ◽  
Vol 48 (6) ◽  
pp. 594-598 ◽  
Author(s):  
Solmaz Mohadjer ◽  
Todd A. Ehlers ◽  
Matthias Nettesheim ◽  
Marco B. Ott ◽  
Christoph Glotzbach ◽  
...  
Keyword(s):  
Power Law ◽  
Time Scale ◽  
Temporal Variations ◽  
Climatic Conditions ◽  
Short Time Scale ◽  
Similar Frequency ◽  
Rock Wall ◽  
Significant Difference ◽  
Long Time ◽  
Frequency Magnitude

Abstract This study addresses the temporal variations in rockfall activity in the 5.2 km2 calcareous cliffs of the deglaciated Lauterbrunnen Valley, Switzerland. We did this using 19 campaigns of repeated terrestrial laser scans (TLS) over 5.2 yr, power-law predicted behavior from extrapolation of the TLS-derived frequency-magnitude relationship, and estimates of long-time-scale (∼11 k.y.) activity based on the volume of preserved postglacial rockfall talus. Results from the short-time-scale observations indicate no statistically significant difference between TLS observations averaging over 1.5 versus 5.2 yr. Rock-wall retreat rates in both cases are 0.03–0.08 mm/yr. In contrast, the power-law predicted rock-wall retreat rates are 0.14–0.22 mm/yr, and long-term rates from talus volumes are 0.27–0.38 mm/yr. These results suggest (1) short (1.5 yr) TLS inventories of rockfalls provide (within uncertainties) similar frequency-magnitude relationships as longer (5.2 yr) inventories, thereby suggesting short observation periods may be sufficient for hazard characterization from TLS, and (2) higher rock-wall retreat rates over long time scales (Holocene averaged) may reflect debuttressing and stress relaxation effects after glacial retreat, and/or enhanced rockfall activity under periglacial (climatic) conditions.

scholarly journals THE IMPACTS OF TYPICAL DROUGHT EVENTS ON TERRESTRIAL VEGETATION IN CHINA

2018 ◽  
Vol XLII-3 ◽  
pp. 2073-2077
Author(s):  
J. Yang ◽  
J. Wu ◽  
H. Zhou ◽  
X. Han
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
North China ◽  
Southwest China ◽  
Drought Event ◽  
Area Index ◽  
Effective Measure ◽  
The North ◽  
Drought Disaster ◽  
Effects Of Drought

In our study, according to the statistical results of standardized precipitation evapotranspiration index (SPEI), we chose two drought events which occurred in the North China during 2001 and in the Southwest China from 2009 to 2010. And two of the Global Land Surface Satellite (GLASS) products had been used to evaluate the impacts of drought on vegetation, including the leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (FAPAR). The results show that: (1) In the development process of a drought event, the anomaly of remote sensing parameters (LAI and FAPAR) usually falls firstly and then rises as the drought changes from moderate to severe and then to moderate. This indicates that the effects of drought on vegetation remote sensing parameters are closely related to the severity of drought disaster. (2) The response of different vegetation types to the drought disaster is different. Compared with the forests, the response of grasslands to drought disaster is earlier. For example, the duration affected by drought disaster in grassland is longer 1/3 than the forests in the Southwest China. (3) Irrigation is an effective measure to mitigate the effects of drought. Irrigated croplands are less affected by drought than non-irrigated croplands and grasslands. In the North China, the decrease amplitude of irrigated croplands’ remote sensing parameters is about half of non-irrigated croplands’.

scholarly journals Remote Sensing Derived Indices for Tracking Urban Land Surface Change in Case of Earthquake Recovery

2020 ◽  
Vol 12 (5) ◽  
pp. 895 ◽  
Author(s):  
Sahar Derakhshan ◽  
Susan L. Cutter ◽  
Cuizhen Wang
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Disaster Recovery ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Variations ◽  
Growth Trend ◽  
Reconstruction Process ◽  
Water Index ◽  
Post Disaster

The study of post-disaster recovery requires an understanding of the reconstruction process and growth trend of the impacted regions. In case of earthquakes, while remote sensing has been applied for response and damage assessment, its application has not been investigated thoroughly for monitoring the recovery dynamics in spatially and temporally explicit dimensions. The need and necessity for tracking the change in the built-environment through time is essential for post-disaster recovery modeling, and remote sensing is particularly useful for obtaining this information when other sources of data are scarce or unavailable. Additionally, the longitudinal study of repeated observations over time in the built-up areas has its own complexities and limitations. Hence, a model is needed to overcome these barriers to extract the temporal variations from before to after the disaster event. In this study, a method is introduced by using three spectral indices of UI (urban index), NDVI (normalized difference vegetation index) and MNDWI (modified normalized difference water index) in a conditional algebra, to build a knowledge-based classifier for extracting the urban/built-up features. This method enables more precise distinction of features based on environmental and socioeconomic variability, by providing flexibility in defining the indices’ thresholds with the conditional algebra statements according to local characteristics. The proposed method is applied and implemented in three earthquake cases: New Zealand in 2010, Italy in 2009, and Iran in 2003. The overall accuracies of all built-up/non-urban classifications range between 92% to 96.29%; and the Kappa values vary from 0.79 to 0.91. The annual analysis of each case, spanning from 10 years pre-event, immediate post-event, and until present time (2019), demonstrates the inter-annual change in urban/built-up land surface of the three cases. Results in this study allow a deeper understanding of how the earthquake has impacted the region and how the urban growth is altered after the disaster.

scholarly journals Spatial and temporal variations of CO<sub>2</sub> mole fractions observed at Beijing, Xianghe, and Xinglong in North China

2021 ◽  
Vol 21 (15) ◽  
pp. 11741-11757
Author(s):  
Yang Yang ◽  
Minqiang Zhou ◽  
Ting Wang ◽  
Bo Yao ◽  
Pengfei Han ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Human Activities ◽  
North China ◽  
Terrestrial Ecosystem ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Boundary Layer Height ◽  
The Usa ◽  
Geographical Distances ◽  
The Impact

Abstract. Atmospheric CO2 mole fractions are observed at Beijing (BJ), Xianghe (XH), and Xinglong (XL) in North China using Picarro G2301 cavity ring-down spectroscopy instruments. The measurement system is described comprehensively for the first time. The geographical distances among these three sites are within 200 km, but they have very different surrounding environments: BJ is inside the megacity; XH is in the suburban area; XL is in the countryside on a mountain. The mean and standard deviation of CO2 mole fractions at BJ, XH, and XL between October 2018 and September 2019 are 448.4±12.8, 436.0±9.2, and 420.6±8.2 ppm, respectively. The seasonal variations of CO2 at these three sites are similar, with a maximum in winter and a minimum in summer, which is dominated by the terrestrial ecosystem. However, the seasonal variations of CO2 at BJ and XH are more affected by human activities as compared to XL. Using CO2 at XL as the background, CO2 enhancements are observed simultaneously at BJ and XH. The diurnal variations of CO2 are driven by the boundary layer height, photosynthesis, and human activities at BJ, XH, and XL. We also compare the CO2 measurements at BJ, XH, and XL with five urban sites in the USA, and it is found that the CO2 mean concentration at BJ is the largest. Moreover, we address the impact of the wind on the CO2 mole fractions at BJ and XL. This study provides an insight into the spatial and temporal variations of CO2 mole fractions in North China.

scholarly journals Assessing Remote Sensing Vegetation Index Sensitivities for Tall Fescue (Schedonorus arundinaceus) Plant Health with Varying Endophyte and Fertilizer Types: A Case for Improving Poultry Manuresheds

2021 ◽  
Vol 13 (3) ◽  
pp. 521
Author(s):  
K. Colton Flynn ◽  
Trey Lee ◽  
Dinku Endale ◽  
Alan Franzluebbers ◽  
Shengfang Ma ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Tall Fescue ◽  
Land Surface ◽  
Vegetation Index ◽  
Fungal Endophyte ◽  
Plant Health ◽  
Broiler Litter ◽  
Significant Difference ◽  
Schedonorus Arundinaceus

Tall fescue (Schedonorus arundinaceus) is a common perennial forage in cattle pastures of the southeastern United States. A mutualistic fungal endophyte normally infects the grass and produces ergot alkaloids toxic to livestock, but fungal biotypes that have no ergot alkaloid production have been developed. Here remote sensing methods were used to assess plant health in 1 ha grazed paddocks with application amongst different combinations of fertilizer sources (inorganic and broiler litter) and endophyte associations (wild, novel–tall fescue MaxQ type with novel endophyte, and free). Broiler litter fertilization is common in the region due to the presence of many chicken farms. Moreover, broiler litter costs are comparable to inorganic fertilizer depending on distance from source to application. Incorporating remote sensing, we tested the sensitivity of three indices: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and land surface water index (LSWI) to assess fescue plant health. Indices were obtained from satellite imagery provided by Landsat 7 ETM+ between the years 2005 and 2009. Sensitivity analytics suggested that LSWI was the optimum index to determine fescue plant health. The year experiencing drought (determined by annual precipitation) showed significant difference between fertilizer types (p = 0.05) and a nearly significant difference between endophyte associations (p = 0.08). There was no significant difference in years with normal or wet precipitation rates due to tall fescue endophyte association or type of fertilization. Limited availability of satellite imagery during parts of the five years of study might have influenced outcomes of statistical analyses. Nevertheless, the data and findings point to the potential use of satellite imagery in assessing grazingland tall fescue health and advancing the concept of poultry manureshed in the region or elsewhere where poultry manure production is extensive.

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