Study on Dynamic Changes of Soil Erosion in the North and South Mountains of Lanzhou

2021 ◽  
Author(s):  
Hua Zhang ◽  
Jinping Lei ◽  
Cungang Xu ◽  
Yuxin Yin
Keyword(s):  
Soil Erosion ◽  
Environmental Factors ◽  
Water Area ◽  
Vegetation Coverage ◽  
Dynamic Changes ◽  
The North ◽  
Joint Influence ◽  
Bare Land ◽  
Temporal And Spatial ◽  
North And South

Abstract This study takes the north and south mountains of Lanzhou as the study area, calculates the soil erosion modulus of the north and south mountains of Lanzhou based on the five major soil erosion factors in the RUSLE model and analyzes the temporal and spatial dynamic changes of soil erosion and the characteristics of soil erosion under different environmental factors. The results show that the soil erosion intensity of the north and south mountains of Lanzhou is mainly micro erosion in 1995, 2000, 2005, 2010, 2015 and 2018. They are distributed in the northwest and southeast of the north and south mountains. Under different environmental factors, the soil erosion modulus first increased and then decreased with the increase of altitude; the soil erosion modulus increased with the increase of slope; the average soil erosion modulus of grassland and woodland was larger, and the average soil erosion modulus of water area was the smallest; except for bare land, the average soil erosion modulus decreased with the increase of vegetation coverage. The soil erosion modulus in the greening range is lower than that outside the greening scope, mainly the result of the joint influence of precipitation, soil and vegetation.

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.

High temporal-and spatial-resolution green vegetation coverage generation and its application in soil erosion monitoring

2019 ◽  
Vol 39 (15) ◽  
Author(s):  
方天纵 FANG Tianzong ◽  
秦朋遥 QIN Pengyao ◽  
王黎明 WANG Liming ◽  
李晓松 LI Xiaosong
Keyword(s):  
Soil Erosion ◽  
Spatial Resolution ◽  
Vegetation Coverage ◽  
Green Vegetation ◽  
Temporal And Spatial

scholarly journals Studi Karakteristik Suhu Permukaan Laut (SPL) Di Perairan Selat Lombok Menggunakan Citra Satelit EOS Aqua MODIS

2021 ◽  
Vol 4 (2) ◽  
pp. 22
Author(s):  
Fitra Cahya Prima ◽  
I Wayan Gede Astawa Karang ◽  
I Gede Hendrawan
Keyword(s):  
Pacific Ocean ◽  
Indian Ocean ◽  
Atmospheric Conditions ◽  
The North ◽  
The Pacific ◽  
The Indian Ocean ◽  
The Pacific Ocean ◽  
Sst Anomaly ◽  
Temporal And Spatial ◽  
North And South

The Lombok Strait is a strait located between Lombok Island and Bali Island which connects the waters of the Bali Sea to the Indian Ocean, whose SST conditions vary with oceanographic-atmospheric conditions in the Indian Ocean and the Pacific Ocean. This research aims to determine the temporal and spatial SST in the North and South Lombok Strait. Therefore, this study divides the Lombok Strait area into two because of the influence of the Pacific Ocean and the Indian Ocean. The method used in this research is descriptive and statistical analysis. The highest average monthly SST in the northern and southern Lombok Strait occurred in April at 29.11 °C and the lowest in August at 26.82°C. For the average seasonal SST, the highest occurred at transition I of 28.86°C, and the lowest occurred in the eastern season at 27.39°C. The highest average annual SST occurred in 2010 at 28.83°C and the lowest occurred in 2018 at 27.69°C. The northern SST anomaly has the same fluctuation as ENSO with inversely proportional IOD. Southern SST anomaly has fluctuation which is inversely proportional to ENSO and IOD. The correlation between SST anomaly in the north and ENSO correlates 0.90 (very strong), while with IOD it correlates 0.12 (very low). The correlation between SST anomaly in the southern part and ENSO correlates -0.11 (very low), while with IOD it correlates -0.73 (strong)

scholarly journals Investigation of Runoff and Sediment Yields Under Different Crop and Tillage Conditions by Field Artificial Rainfall Experiments

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1019 ◽  
Author(s):  
Mengjing Guo ◽  
Tiegang Zhang ◽  
Zhanbin Li ◽  
Guoce Xu
Keyword(s):  
Soil Erosion ◽  
Sediment Yield ◽  
Vegetation Coverage ◽  
Sediment Yields ◽  
Artificial Rainfall ◽  
Crop Type ◽  
Bare Land ◽  
Crop Types ◽  
Slope Treatment ◽  
Moisture Conditions

Crop types and tillage measures on slopes have significant impacts on regional water and soil conservation. In this study, we investigated the influences of multiple crop types and tillage measures on water and sediment yields based on plot-scale experiments under artificial rainfall. The objective of the study is to find the best combination of crop type and tillage measure from the perspective of reducing soil erosion. We performed artificial rainfall experiments under eight slope treatments, which are the bare-land (BL, as a reference), peanut monoculture (PL), corn monoculture (CL), bare land (upper slope) mixed with peanut monoculture (lower slope) (BP), corn and peanut intercropping (TCP), corn and soybean intercropping (TCS), downslope ridge cultivation (BS) slope, and straw-mulched (SC), respectively. Under similar rainfall intensity and initial soil moisture conditions, these treatments except for BS efficiently reduced sediment yield compared to the BL slope. In comparison, the most effective slope treatment to reduce soil erosion is TCP, followed by PL and TCS. The amount of sediment yielded from the three treatments accounts for 0.4%, 2.0%, and 3.3% of the sediment yielded from BL. We recommend the three slope treatments as the preferred choices among eight treatments. Also, the lower sediment yield in the three slope treatments benefits from their higher vegetation coverage. Vegetation coverage plays a greater role in regulating sediment yield than the surface runoff at a plot scale.

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