Remote-sensing estimation of grassland vegetation coverage in Inner Mongolia, China

2011 ◽  
Vol 35 (6) ◽  
pp. 615-622 ◽  
Author(s):  
Jing-Fang ZHU ◽  
Bai-Ling XING ◽  
Wei-Min JU ◽  
Gao-Long ZHU ◽  
Yi-Bo LIU
Keyword(s):  
Remote Sensing ◽  
Inner Mongolia ◽  
Vegetation Coverage ◽  
Grassland Vegetation

Research on Wind Erosion of Xilamuren Grassland, Inner Mongolia

2014 ◽  
Vol 955-959 ◽  
pp. 3505-3508 ◽  
Author(s):  
Tian Ming Gao ◽  
Rui Qiang Zhang ◽  
Jian Ying Guo
Keyword(s):  
Inner Mongolia ◽  
Wind Erosion ◽  
Initial Period ◽  
Northern China ◽  
Vegetation Coverage ◽  
Available Phosphorus ◽  
Grassland Vegetation ◽  
Available Nitrogen ◽  
Vegetation Height ◽  
Degraded Grassland

In northern China, grassland has degraded severely and wind erosion occurs remarkably due to irrational land use in recent years. By employing sand sampler and mobile wind tunnel, an observation for 6 years was made to analyze the mechanisms of wind erosion in Xilamuren grassland, the central of Yinshan Mountains, Inner Mongolia. Results show that: (1) vegetation is the decisive factor for controlling wind erosion and the inhibiting effect of vegetation height on wind erosion is greater than that of vegetation coverage. (2) Wind erosion modulus in the initial period of enclosure reaches 1313.7 t km-2a-1 and with the improvement of the grassland vegetation, wind erosion decreases year by year. (3) For every 1000 kg soil eroded by wind, 15 kg organic matter, 227g available nitrogen, 262g available phosphorus and 120g available potassium lose in the region at the same time, being a tremendous fertility loss. Therefore, the protection of base grassland and restoration of degraded grassland are two fundamental approaches to control wind erosion on the grassland.

scholarly journals Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland

2021 ◽  
Vol 13 (4) ◽  
pp. 656
Author(s):  
Xiang Zhang ◽  
Yuhai Bao ◽  
Dongliang Wang ◽  
Xiaoping Xin ◽  
Lei Ding ◽  
...  
Keyword(s):  
Major Effect ◽  
Canopy Height ◽  
Vegetation Coverage ◽  
Accurate Estimation ◽  
Grassland Vegetation ◽  
Pixel Resolution ◽  
Aerial Vehicle ◽  
Grazing Intensities ◽  
Vegetation Parameters ◽  
Mongolian Grassland

The accurate estimation of grassland vegetation parameters at a high spatial resolution is important for the sustainable management of grassland areas. Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) sensors with a single laser beam emission capability can rapidly detect grassland vegetation parameters, such as canopy height, fractional vegetation coverage (FVC) and aboveground biomass (AGB). However, there have been few reports on the ability to detect grassland vegetation parameters based on RIEGL VUX-1 UAV LiDAR (Riegl VUX-1) systems. In this paper, we investigated the ability of Riegl VUX-1 to model the AGB at a 0.1 m pixel resolution in the Hulun Buir grazing platform under different grazing intensities. The LiDAR-derived minimum, mean, and maximum canopy heights and FVC were used to estimate the AGB across the entire grazing platform. The flight height of the LiDAR-derived vegetation parameters was also analyzed. The following results were determined: (1) The Riegl VUX-1-derived AGB was predicted to range from 29 g/m2 to 563 g/m2 under different grazing conditions. (2) The LiDAR-derived maximum canopy height and FVC were the best predictors of grassland AGB (R2 = 0.54, root-mean-square error (RMSE) = 64.76 g/m2). (3) For different UAV flight altitudes from 40 m to 110 m, different flight heights showed no major effect on the derived canopy height. The LiDAR-derived canopy height decreased from 9.19 cm to 8.17 cm, and the standard deviation of the LiDAR-derived canopy height decreased from 3.31 cm to 2.35 cm with increasing UAV flight altitudes. These conclusions could be useful for estimating grasslands in smaller areas and serving as references for other remote sensing datasets for estimating grasslands in larger areas.

scholarly journals Spatial and Temporal Changes in Vegetation in the Ruoergai Region, China

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 76
Author(s):  
Yahui Guo ◽  
Jing Zeng ◽  
Wenxiang Wu ◽  
Shunqiang Hu ◽  
Guangxu Liu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Linear Trend ◽  
Spectral Characteristics ◽  
Growth Conditions ◽  
Temporal Changes ◽  
Vegetation Coverage ◽  
Dynamic Changes ◽  
Spatial And Temporal Changes ◽  
Temporal And Spatial

Timely monitoring of the changes in coverage and growth conditions of vegetation (forest, grass) is very important for preserving the regional and global ecological environment. Vegetation information is mainly reflected by its spectral characteristics, namely, differences and changes in green plant leaves and vegetation canopies in remote sensing domains. The normalized difference vegetation index (NDVI) is commonly used to describe the dynamic changes in vegetation, but the NDVI sequence is not long enough to support the exploration of dynamic changes due to many reasons, such as changes in remote sensing sensors. Thus, the NDVI from different sensors should be scientifically combined using logical methods. In this study, the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI from the Advanced Very High Resolution Radiometer (AVHRR) and Moderate-resolution Imaging Spectroradiometer (MODIS) NDVI are combined using the Savitzky–Golay (SG) method and then utilized to investigate the temporal and spatial changes in the vegetation of the Ruoergai wetland area (RWA). The dynamic spatial and temporal changes and trends of the NDVI sequence in the RWA are analyzed to evaluate and monitor the growth conditions of vegetation in this region. In regard to annual changes, the average annual NDVI shows an overall increasing trend in this region during the past three decades, with a linear trend coefficient of 0.013/10a, indicating that the vegetation coverage has been continuously improving. In regard to seasonal changes, the linear trend coefficients of NDVI are 0.020, 0.021, 0.004, and 0.004/10a for spring, summer, autumn, and winter, respectively. The linear regression coefficient between the gross domestic product (GDP) and NDVI is also calculated, and the coefficients are 0.0024, 0.0015, and 0.0020, with coefficients of determination (R2) of 0.453, 0.463, and 0.444 for Aba, Ruoergai, and Hongyuan, respectively. Thus, the positive correlation coefficients between the GDP and the growth of NDVI may indicate that increased societal development promotes vegetation in some respects by resulting in the planting of more trees or the promotion of tree protection activities. Through the analysis of the temporal and spatial NDVI, it can be assessed that the vegetation coverage is relatively large and the growth condition of vegetation in this region is good overall.

Regulation and Critical Threshold of Grass Cover on Slope Runoff in LoessHilly Gully Region under Artificial

2021 ◽  
Author(s):  
Qiufen Zhang ◽  
Xizhi Lv ◽  
Rongxin Chen ◽  
Yongxin Ni ◽  
Li Ma
Keyword(s):  
Soil Erosion ◽  
Rainfall Intensity ◽  
Climatic Conditions ◽  
Vegetation Coverage ◽  
Critical Threshold ◽  
Runoff Generation ◽  
Grassland Vegetation ◽  
Slope Flow ◽  
The Impact ◽  
Slope Runoff

<p>The slope runoff caused by rainstorm is the main cause of serious soil and water loss in the loess hilly area, the grassland vegetation has a good inhibitory effect on the slope runoff, it is of great significance to reveal the role of grassland vegetation in the process of runoff generation and control mechanism for controlling soil erosion in this area. In this study, typical grassland slopes in hilly and gully regions of the loess plateau were taken as research objects. Through artificial rainfall in the field, the response rules of slope rainfall-runoff process to different grass coverage were explored. The results show that: (1) The time for the slope flow to stabilize is prolonged with the increase of vegetation coverage, and shortened with the increase of rainfall intensity; (2) At 60 mm·h <sup>−1</sup> rainfall intensity, the threshold of grassland vegetation coverage is 75.38%; at 90 mm·h<sup> −1</sup> rainfall intensity, the threshold of grassland vegetation coverage is 90.54%; at 120 mm·h <sup>−1</sup> rainfall intensity, the impact of grassland vegetation coverage on runoff is not significant; (3) the Reynolds number and Froude number of slope flow are 40.07‒695.22 and 0.33‒1.56 respectively, the drag coefficient is 1.42‒43.53. Under conditions of heavy rainfall, the ability of grassland to regulate slope runoff is limited. If only turf protection is considered, about 90% of grassland coverage can effectively cope with soil erosion caused by climatic conditions in loess hilly and gully regions. Therefore, in loess hilly areas where heavy rains frequently occur, grassland's protective effect on soil erosion is obviously insufficient, and investment in vegetation measures for trees and shrubs should be strengthened.</p>

scholarly journals Monitoring Changes to Arctic Vegetation and Glaciers at Ny-Ålesund, Svalbard, Based on Time Series Remote Sensing

2021 ◽  
Vol 13 (19) ◽  
pp. 3845
Author(s):  
Guangbo Ren ◽  
Jianbu Wang ◽  
Yunfei Lu ◽  
Peiqiang Wu ◽  
Xiaoqing Lu ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Time Series ◽  
High Latitude ◽  
Global Climate ◽  
Meteorological Data ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Coastal Regions ◽  
Average Annual Temperature

Climate change has profoundly affected global ecological security. The most vulnerable region on Earth is the high-latitude Arctic. Identifying the changes in vegetation coverage and glaciers in high-latitude Arctic coastal regions is important for understanding the process and impact of global climate change. Ny-Ålesund, the northern-most human settlement, is typical of these coastal regions and was used as a study site. Vegetation and glacier changes over the past 35 years were studied using time series remote sensing data from Landsat 5/7/8 acquired in 1985, 1989, 2000, 2011, 2015 and 2019. Site survey data in 2019, a digital elevation model from 2009 and meteorological data observed from 1985 to 2019 were also used. The vegetation in the Ny-Ålesund coastal zone showed a trend of declining and then increasing, with a breaking point in 2000. However, the area of vegetation with coverage greater than 30% increased over the whole study period, and the wetland moss area also increased, which may be caused by the accelerated melting of glaciers. Human activities were responsible for the decline in vegetation cover around Ny-Ålesund owing to the construction of the town and airport. Even in areas with vegetation coverage of only 13%, there were at least five species of high-latitude plants. The melting rate of five major glaciers in the study area accelerated, and approximately 82% of the reduction in glacier area occurred after 2000. The elevation of the lowest boundary of the five glaciers increased by 50–70 m. The increase in precipitation and the average annual temperature after 2000 explains the changes in both vegetation coverage and glaciers in the study period.

scholarly journals Remote Sensing Dynamic Estimation of Grass Production in Xilinguole, Inner Mongolia

2011 ◽  
Vol 41 (12) ◽  
pp. 1185-1195 ◽  
Author(s):  
Bin XU ◽  
HaiLong Ma ◽  
JinYa LI ◽  
YunXiang JIN ◽  
DaoLong Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Inner Mongolia ◽  
Grass Production ◽  
Dynamic Estimation
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