Improving the spatiotemporal fusion accuracy of fractional vegetation cover in agricultural regions by combining vegetation growth models

Ecological degradation caused by rapid urbanisation has presented great challenges in southern China. Fractional vegetation cover (FVC) has long been the most common and sensitive index to describe vegetation growth and to monitor vegetation degradation. However, most of the studies have failed to adequately explore the complexity of the relationship between fractional vegetation cover (FVC) and impact factors. In this research, we first constructed a Semi-parametric Geographically Weighted Regression (SGWR) model to analyse both the stationary and nonstationary spatial relationships between FVC and driving factors in Guangdong province in southern China on a county level. Then, climate, topographic, land cover, and socio-economic factors were introduced into the model to distinguish impacts on FVC from 2000–2015. Results suggest that the positive and negative effects of rainfall and elevation coefficients alternated, and local urban land and population estimates indicated a negative association between FVC and the modelled factors in each period. The SGWR FVC make significantly improves performance of the geographically weighted regression and ordinary least squares models, with adjusted R2 higher than 0.78. The findings of this research demonstrated that, although urbanisation in the Pearl River Delta in Guangdong has encroached on the regional vegetation cover, the total vegetation area remained unchanged with the implementation of protection policies and regulations.

Download Full-text

A Time-Efficient Fractional Vegetation Cover Estimation Method Using the Dynamic Vegetation Growth Information From Time Series GLASS FVC Product

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2019.2954291 ◽

2020 ◽

Vol 17 (10) ◽

pp. 1672-1676

Author(s):

Yixuan Tu ◽

Kun Jia ◽

Xiangqin Wei ◽

Yunjun Yao ◽

Mu Xia ◽

...

Keyword(s):

Time Series ◽

Vegetation Cover ◽

Estimation Method ◽

Vegetation Growth ◽

Fractional Vegetation Cover

Download Full-text

Responses of Xilingol Fractional Vegetation Cover to Climate Change and Human Activities

Scientific Programming ◽

10.1155/2021/5169913 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Xiangyang Song ◽

Xiang Chen ◽

Xiaodong Wang ◽

Nitu Wu ◽

Aijun Liu ◽

...

Keyword(s):

Climate Change ◽

Human Activities ◽

Vegetation Cover ◽

Evaluation Method ◽

Anthropogenic Activities ◽

Meteorological Data ◽

Vegetation Coverage ◽

Vegetation Growth ◽

Modis Ndvi ◽

Fractional Vegetation Cover

Based on the MODIS NDVI product data source of Xilingol from 2010 to 2019, we use the pixel dichotomous model to retrieve the vegetation coverage in our study. The spatiotemporal changes of the vegetation cover were analyzed in the model by using the meteorological data from researched sites or the vicinal meteorological stations for evaluating the meteorological influence on the vegetation cover changes. Based on this, an evaluation method was established to estimate the relative influences of the climate changes and anthropogenic activities. The main conclusions are as follows: (1) Fractional vegetation cover in Xilingol was decreased from the northeast to the southwest. (2) The overall trend in Xilingol fractional vegetation cover in the 10-year period shows a fluctuating increasing trend. (3) An opposite distribution pattern was detected between mean precipitation and mean temperature in the study site. (4) Compared with temperature, annual precipitation has a higher correlation with fractional vegetation cover in the study site and is the main climatic factor that affects vegetation growth in the study site. (5) During the 10-year period in the study site, anthropogenic human activities have slightly greater inhibitory effects on vegetation growth than promoting effects. (6) Climate change is a major factor to accelerate grassland degradation from 2010 to 2019 in vegetation degradation regions. The promotion effect of precipitation on vegetation coverage is obviously higher than the limitation of human activities, which leads to the increase of vegetation coverage in 2010–2019.

Download Full-text

An Automatic Extraction Approach to Fractional Vegetation Cover of Saline Land with Digital Images

Geo-information Science ◽

10.3724/sp.j.1047.2013.00618 ◽

2013 ◽

Vol 15 (4) ◽

pp. 618 ◽

Cited By ~ 1

Author(s):

Yanling DING ◽

Kai ZHAO ◽

Xiaofeng LI ◽

Xingming ZHENG

Keyword(s):

Vegetation Cover ◽

Digital Images ◽

Automatic Extraction ◽

Fractional Vegetation Cover ◽

Saline Land

Download Full-text

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

Remote Sensing ◽

10.3390/rs13050913 ◽

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.

Download Full-text

Comparison of Satellite and Drone-Based Images at Two Spatial Scales to Evaluate Vegetation Regeneration after Post-Fire Treatments in a Mediterranean Forest

Applied Sciences ◽

10.3390/app11125423 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5423

Author(s):

Jose Luis Martinez ◽

Manuel Esteban Lucas-Borja ◽

Pedro Antonio Plaza-Alvarez ◽

Pietro Denisi ◽

Miguel Angel Moreno ◽

...

Keyword(s):

Vegetation Cover ◽

Spatial Scales ◽

Soil Surface ◽

Plant Biodiversity ◽

Mediterranean Forests ◽

Experimental Conditions ◽

Vegetation Growth ◽

Surface Conditions ◽

Vegetation Regeneration ◽

Forest Managers

The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of remote sensing, which makes these evaluation activities quicker and easier, have rarely been carried out in the Mediterranean forests, subjected to wildfire and post-fire stabilization techniques. To fill this gap, this study evaluates the feasibility of satellite (using LANDSAT8 images) and drone surveys to evaluate changes in vegetation cover and composition after wildfire and two hillslope stabilization treatments (log erosion barriers, LEBs, and contour-felled log debris, CFDs) in a forest of Central Eastern Spain. Surveys by drone were able to detect the variability of vegetation cover among burned and unburned areas through the Visible Atmospherically Resistant Index (VARI), but gave unrealistic results when the effectiveness of a post-fire treatment must be evaluated. LANDSAT8 images may be instead misleading to evaluate the changes in land cover after wildfire and post-fire treatments, due to the lack of correlation between VARI and vegetation cover. The spatial analysis has shown that: (i) the post-fire restoration strategy of landscape managers that have prioritized steeper slopes for treatments was successful; (ii) vegetation growth, at least in the experimental conditions, played a limited influence on soil surface conditions, since no significant increases in terrain roughness were detected in treated areas.

Download Full-text

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

Remote Sensing ◽

10.3390/rs13112126 ◽

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.

Download Full-text