scholarly journals Spatiotemporal Evolution of Fractional Vegetation Cover and Its Response to Climate Change Based on MODIS Data in the Subtropical Region of China

2021 ◽  
Vol 13 (5) ◽  
pp. 913
Author(s):  
Hua Liu ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
Di’en Zhu ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Distribution Area ◽  
Spatiotemporal Pattern ◽  
Climate Factors ◽  
Important Indicator ◽  
Fractional Vegetation Cover ◽  
Annual Minimum Temperature ◽  
Total Study Area

The subtropical vegetation plays an important role in maintaining the structure and function of global ecosystems, and its contribution to the global carbon balance are receiving increasing attention. The fractional vegetation cover (FVC) as an important indicator for monitoring environment change, is widely used to analyze the spatiotemporal pattern of regional and even global vegetation. China is an important distribution area of subtropical vegetation. Therefore, we first used the dimidiate pixel model to extract the subtropical FVC of China during 2001–2018 based on MODIS land surface reflectance data, and then used the linear regression analysis and the variation coefficient to explore its spatiotemporal variations characteristics. Finally, the partial correlation analysis and the partial derivative model were used to analyze the influences and contributions of climate factors on FVC, respectively. The results showed that (1) the subtropical FVC had obvious spatiotemporal heterogeneity; the FVC high-coverage and medium-coverage zones were concentratedly and their combined area accounted for more than 70% of the total study area. (2) The interannual variation in the average subtropical FVC from 2001 to 2018 showed a significant growth trend. (3) In 76.28% of the study area, the regional FVC showed an increasing trend, and the remaining regional FVC showed a decreasing trend. However, the overall fluctuations in the FVC (increasing or decreasing) in the region were relatively stable. (4) The influences of climate factors to the FVC exhibited obvious spatial differences. More than half of all pixels exhibited the influence of the average annual minimum temperature and the annual precipitation had positive on FVC, while the average annual maximum temperature had negative on FVC. (5) The contributions of climate changes to FVC had obvious heterogeneity, and the average annual minimum temperature was the main contribution factor affecting the dynamic variations of FVC.

scholarly journals Spatiotemporal analysis of rabies in cattle in central Mexico

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Isabel Bárcenas-Reyes ◽  
Diana Paulina Nieves-Martínez ◽  
José Quintín Cuador-Gil ◽  
Elizabeth Loza-Rubio ◽  
Sara González-Ruíz ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Spatial Epidemiology ◽  
Risk Estimation ◽  
Regional Distribution ◽  
Spatiotemporal Analysis ◽  
Maximum Temperature ◽  
Spatial Continuity ◽  
Simple Kriging ◽  
Annual Minimum Temperature

Spatial epidemiology of bat-transmitted rabies in cattle has been limited to spatial distribution of cases, an approach that does not identify hidden patterns and the spread resulting in outbreaks in endemic and susceptible areas. Therefore, the purpose of this study was to determine the relationship between the three variables average annual maximum, annual minimum temperature and precipitation in the region on the one hand, and the spatial distribution of cases on the other, using geographic information systems and co-Kriging considering that these environmental variables condition the existence of the rabies vector Desmodus rotundus. A stationary behaviour between the primary and the secondary variables was verified by basic statistics and moving window statistics. The directions of greater and lesser spatial continuity were determined by experimental cross-semivariograms. It was found that the highest risk for bovine paralytic rabies occurs in areas known as La Huasteca Potosina and La Sierra Gorda that are characterized by a maximum temperature of 29.5 °C, a minimum temperature of 16.5 °C and precipitation of 1200 mm. A risk estimation map was obtained for the presence of rabies with a determination coefficient greater than 95%, and a correlation coefficient greater than 0.95. Our conclusion is that ordinary co- Kriging provides a better estimation of risk and spatial distribution of rabies than simple Kriging, making this the method recommended for risk estimation and regional distribution of rabies.

scholarly journals Generating High Spatio-Temporal Resolution Fractional Vegetation Cover by Fusing GF-1 WFV and MODIS Data

2019 ◽  
Vol 11 (19) ◽  
pp. 2324 ◽  
Author(s):  
Tao ◽  
Jia ◽  
Zhao ◽  
Wei ◽  
Xie ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Vegetation Cover ◽  
Field Survey ◽  
Lower Probability ◽  
Important Indicator ◽  
The Real ◽  
Modis Data ◽  
Fractional Vegetation Cover ◽  
Spatio Temporal ◽  
Reflectance Data

As an important indicator to characterize the surface vegetation, fractional vegetation cover (FVC) with high spatio-temporal resolution is essential for earth surface process simulation. However, due to technical limitations and the influence of weather, it is difficult to generate temporally continuous FVC with high spatio-temporal resolution based on a single remote-sensing data source. Therefore, the objective of this study is to explore the feasibility of generating high spatio-temporal resolution FVC based on the fusion of GaoFen-1 Wide Field View (GF-1 WFV) data and Moderate-resolution Imaging Spectroradiometer (MODIS) data. Two fusion strategies were employed to identify a suitable fusion method: (i) fusing reflectance data from GF-1 WFV and MODIS firstly and then estimating FVC from the reflectance fusion result (strategy FC, Fusion_then_FVC). (ii) fusing the FVC estimated from GF-1 WFV and MODIS reflectance data directly (strategy CF, FVC_then_Fusion). The FVC generated using strategies FC and CF were evaluated based on FVC estimated from the real GF-1 WFV data and the field survey FVC, respectively. The results indicated that strategy CF achieved higher accuracies with less computational cost than those of strategy FC both in the comparisons with FVC estimated from the real GF-1 WFV (CF:R2 = 0.9580, RMSE = 0.0576; FC: R2 = 0.9345, RMSE = 0.0719) and the field survey FVC data (CF: R2 = 0.8138, RMSE = 0.0985; FC: R2 = 0.7173, RMSE = 0.1214). Strategy CF preserved spatial details more accurately than strategy FC and had a lower probability of generating abnormal values. It could be concluded that fusing GF-1 WFV and MODIS data for generating high spatio-temporal resolution FVC with good quality was feasible, and strategy CF was more suitable for generating FVC given its advantages in estimation accuracy and computational efficiency.

scholarly journals Long term monthly and inter-seasonal weather variability analysis for the lower Shivalik foothills of Punjab

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 173-180
Author(s):  
NAVNEET KAUR ◽  
M.J. SINGH ◽  
SUKHJEET KAUR
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
Post Monsoon ◽  
Sunshine Hours ◽  
Annual Minimum Temperature ◽  
Weather Parameters

This paper aims to study the long-term trends in different weather parameters, i.e., temperature, rainfall, rainy days, sunshine hours, evaporation, relative humidity and temperature over Lower Shivalik foothills of Punjab. The daily weather data of about 35 years from agrometeorological observatory of Regional Research Station Ballowal Saunkhri representing Lower Shivalik foothills had been used for trend analysis for kharif (May - October), rabi (November - April), winter (January - February), pre-monsoon (March - May), monsoon (June - September) and post monsoon (October - December) season. The linear regression method has been used to estimate the magnitude of change per year and its coefficient of determination, whose statistical significance was checked by the F test. The annual maximum temperature, morning and evening relative humidity has increased whereas rainfall, evaporation sunshine hours and wind speed has decreased significantly at this region. No significant change in annual minimum temperature and diurnal range has been observed. Monthly maximum temperature revealed significant increase except January, June and December, whereas, monthly minimum temperature increased significantly for February, March and October and decreased for June. Among different seasons, maximum temperature increased significantly for all seasons except winter season, whereas, minimum temperature increased significantly for kharif and post monsoon season only. The evaporation, sunshine hours and wind speed have also decreased and relative humidity decreased significantly at this region. Significant reduction in kharif, monsoon and post monsoon rainfall has been observed at Lower Shivalik foothills. As the region lacks assured irrigation facilities so decreasing rainfall and change in the other weather parameters will have profound effects on the agriculture in this region so there is need to develop climate resilient agricultural technologies.

scholarly journals Long-Term Trend Analysis in Annual and Seasonal Precipitation, Maximum and Minimum Temperatures in the Southwest United States

Climate ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 142
Author(s):  
Koffi Djaman ◽  
Komlan Koudahe ◽  
Ansoumana Bodian ◽  
Lamine Diop ◽  
Papa Malick Ndiaye
Keyword(s):  
United States ◽  
Trend Analysis ◽  
Minimum Temperature ◽  
Test Method ◽  
Maximum Temperature ◽  
Crop Season ◽  
Southwest United States ◽  
Annual Minimum Temperature ◽  
Increasing Trend

The objective of this study is to perform trend analysis in the historic data sets of annual and crop season [May–September] precipitation and daily maximum and minimum temperatures across the southwest United States. Eighteen ground-based weather stations were considered across the southwest United States for a total period from 1902 to 2017. The non-parametric Mann–Kendall test method was used for the significance of the trend analysis and the Sen’s slope estimator was used to derive the long-term average rates of change in the parameters. The results showed a decreasing trend in annual precipitation at 44.4% of the stations with the Sen’s slopes varying from −1.35 to −0.02 mm/year while the other stations showed an increasing trend. Crop season total precipitation showed non-significant variation at most of the stations except two stations in Arizona. Seventy-five percent of the stations showed increasing trend in annual maximum temperature at the rates that varied from 0.6 to 3.1 °C per century. Air cooling varied from 0.2 to 1.0 °C per century with dominant warming phenomenon at the regional scale of the southwest United States. Average annual minimum temperature had increased at 69% of the stations at the rates that varied from 0.1 to 8 °C over the last century, while the annual temperature amplitude showed a decreasing trend at 63% of stations. Crop season maximum temperature had significant increasing trend at 68.8% of the stations at the rates varying from 0.7 to 3.5 °C per century, while the season minimum temperature had increased at 75% of the stations.

scholarly journals Agro-Climatic Characterization of Two Selected Stations in the Southern West Bengal, India

2013 ◽  
Vol 8 (1-2) ◽  
pp. 49-54
Author(s):  
Saon Banerjee ◽  
Asis Mukherj ◽  
Apurba Mukhopadhayal ◽  
B Saikia ◽  
S Bandyaopadhaya ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
West Bengal ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Chain Model ◽  
Climatic Trend ◽  
Annual Minimum Temperature

Maximum temperature, minimum temperature and rainfall data of Bankura (1992-2007) and Canning (1960-2006) were analyzed for assessing climatic trend and agro-climatic characterization of red-lateritic and coastal Zones of West Bengal respectively. These two zones are the most vulnerable regions to climate change in West Bengal, hence selected for the present study. While average values of annual maximum temperature and annual minimum temperature were used for climatic trend analysis, no definite trend was observed. So, maximum temperature of the hottest month and minimum temperature of the coldest month were used for detecting climatic trend. The maximum temperature shows positive trend for both the stations. An increasing trend of annual rainfall was also observed. In case of agro-climatic characterization the agricultural draught, meteorological draught, seasonal rainfall and rainfall probability using Markov-chain model were analyzed for the said two stations. Kharif crops of Bankura encountered two years (2000 & 2005) agricultural draught within 2000 -2007, whereas kharif crops of Canning encountered agricultural draught in 2006 within the said period. Likewise, the deviation of seasonal rainfall and probability of two consecutive wet weeks with different levels (10, 20,30,40,50 and 60 mm) of weekly total rainfall was worked out. DOI: http://dx.doi.org/10.3329/jsf.v8i1-2.14619 J. Sci. Foundation, 8(1&2): 49-54, June-December 2010

scholarly journals Analysis of Past and Projected Trends of Rainfall and Temperature Parameters in Eastern and Western Hararghe Zones, Ethiopia

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 67
Author(s):  
Helen Teshome ◽  
Kindie Tesfaye ◽  
Nigussie Dechassa ◽  
Tamado Tana ◽  
Matthew Huber
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Climate Change And Variability ◽  
Annual Minimum Temperature ◽  
Increasing Trend ◽  
Rcp 8.5 ◽  
The Mean ◽  
East And West

Smallholder farmers in East and West Hararghe zones, Ethiopia frequently face problems of climate extremes. Knowledge of past and projected climate change and variability at local and regional scales can help develop adaptation measures. A study was therefore conducted to investigate the spatio-temporal dynamics of rainfall and temperature in the past (1988–2017) and projected periods of 2030 and 2050 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) at selected stations in East and West Hararghe zones, Ethiopia. To detect the trends and magnitude of change Mann–Kendall test and Sen’s slope estimator were employed, respectively. The result of the study indicated that for the last three decades annual and seasonal and monthly rainfall showed high variability but the changes are not statistically significant. On the other hand, the minimum temperature of the ‘Belg’ season showed a significant (p < 0.05) increment. The mean annual minimum temperature is projected to increase by 0.34 °C and 2.52 °C for 2030, and 0.41 °C and 4.15 °C for 2050 under RCP4.5 and RCP8.5, respectively. Additionally, the mean maximum temperature is projected to change by −0.02 °C and 1.14 °C for 2030, and 0.54 °C and 1.87 °C for 2050 under RCP4.5 and RCP 8.5, respectively. Annual rainfall amount is also projected to increase by 2.5% and 29% for 2030, and 12% and 32% for 2050 under RCP4.5 and RCP 8.5, respectively. Hence, it is concluded that there was an increasing trend in the Belg season minimum temperature. A significant increasing trend in rainfall and temperature are projected compared to the baseline period for most of the districts studied. This implies a need to design climate-smart crop and livestock production strategies, as well as an early warning system to counter the drastic effects of climate change and variability on agricultural production and farmers’ livelihood in the region.

scholarly journals Annually Urban Fractional Vegetation Cover Dynamic Mapping in Hefei, China (1999–2018)

2021 ◽  
Vol 13 (11) ◽  
pp. 2126
Author(s):  
Yuliang Wang ◽  
Mingshi Li
Keyword(s):  
Standard Deviation ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Dynamic Range ◽  
Dynamic Change ◽  
Estimation Model ◽  
Sparse Vegetation ◽  
Fractional Vegetation Cover ◽  
Dynamic Mapping ◽  
Multi Temporal

Vegetation measures are crucial for assessing changes in the ecological environment. Fractional vegetation cover (FVC) provides information on the growth status, distribution characteristics, and structural changes of vegetation. An in-depth understanding of the dynamic changes in urban FVC contributes to the sustainable development of ecological civilization in the urbanization process. However, dynamic change detection of urban FVC using multi-temporal remote sensing images is a complex process and challenge. This paper proposed an improved FVC estimation model by fusing the optimized dynamic range vegetation index (ODRVI) model. The ODRVI model improved sensitivity to the water content, roughness degree, and soil type by minimizing the influence of bare soil in areas of sparse vegetation cover. The ODRVI model enhanced the stability of FVC estimation in the near-infrared (NIR) band in areas of dense and sparse vegetation cover through introducing the vegetation canopy vertical porosity (VCVP) model. The verification results confirmed that the proposed model had better performance than typical vegetation index (VI) models for multi-temporal Landsat images. The coefficient of determination (R2) between the ODRVI model and the FVC was 0.9572, which was 7.4% higher than the average R2 of other typical VI models. Moreover, the annual urban FVC dynamics were mapped using the proposed improved FVC estimation model in Hefei, China (1999–2018). The total area of all grades FVC decreased by 33.08% during the past 20 years in Hefei, China. The areas of the extremely low, low, and medium grades FVC exhibited apparent inter-annual fluctuations. The maximum standard deviation of the area change of the medium grade FVC was 13.35%. For other grades of FVC, the order of standard deviation of the change ratio was extremely low FVC > low FVC > medium-high FVC > high FVC. The dynamic mapping of FVC revealed the influence intensity and direction of the urban sprawl on vegetation coverage, which contributes to the strategic development of sustainable urban management plans.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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