Identification of Dominant Factors Affecting Soil Erosion and Water Yield within Key Ecological Functional Areas

2020 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Land Use Type ◽  
Functional Areas

<p>Soil conservation and water retention are important metrics for designating key ecological functional areas. However, research on the quantitative identification of dominant environmental factors in different ecological functional areas remains relatively inadequate, which is unfavorable for zone-based management of key ecological functional areas. This paper presents a case study of Beijing’s key ecological functional areas. In order to objectively reflect the ecological characteristics of key ecological functional areas in Beijing which is mainly dominated by mountainous areas, the application of remote sensing data about high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations, soil erosion and water yield were calculated using the Revised Universal Soil Loss Equation (RUSLE) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s key ecological functional areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different key ecological function areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s key ecological function areas, explaining greater than 30% of its spatial heterogeneity. Land use type can explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various key ecological functional areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in key ecological functional areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ecological functional areas. Thus, in efforts to enhance key ecological functional areas protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ecological functional areas.</p>

scholarly journals Identification of Dominant Factors Affecting Soil Erosion and Water Yield within Ecological Red Line Areas

2020 ◽  
Vol 12 (3) ◽  
pp. 399 ◽  
Author(s):  
Jiangbo Gao ◽  
Yuan Jiang ◽  
Huan Wang ◽  
Liyuan Zuo
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Water Yield ◽  
Land Use Type ◽  
Functional Areas ◽  
Red Line

Soil conservation and water retention are important metrics for designating key ecological functional areas and ecological red line (ERL) areas. However, research on the quantitative identification of dominant environmental factors in different ecological red line areas remains relatively inadequate, which is unfavorable for the zone-based management of ecological functional areas. This paper presents a case study of Beijing’s ERL areas. In order to objectively reflect the ecological characteristics of ERL areas in Beijing, which is mainly dominated by mountainous areas, the application of remote sensing data at a high resolution is important for the improvement of model calculation and spatial heterogeneity. Based on multi-source remote sensing data, meteorological and soil observations as well as soil erosion and water yield were calculated using the revised universal soil loss equation (RUSLE) and integrated valuation of ecosystem services and tradeoffs (InVEST) model. Combining the influencing factors, including slope, precipitation, land use type, vegetation coverage, geomorphological type, and elevation, a quantitative attribution analysis was performed on soil erosion and water yield in Beijing’s ERL areas using the geographical detector. The power of each influencing factor and their interaction factors in explaining the spatial distribution of soil erosion or water yield varied significantly among different ERL areas. Vegetation coverage was the dominant factor affecting soil erosion in Beijing’s ERL areas, explaining greater than 30% of its spatial heterogeneity. Land use type could explain the spatial heterogeneity of water yield more than 60%. In addition, the combination of vegetation coverage and slope was found to significantly enhance the spatial distribution of soil erosion (>55% in various ERL areas). The superposition of land use type and slope explained greater than 70% of the spatial distribution for water yield in ERL areas. The geographical detector results indicated that the high soil erosion risk areas and high water yield areas varied significantly among different ERL areas. Thus, in efforts to enhance ERL protection, focus should be placed on the spatial heterogeneity of soil erosion and water yield in different ERL areas.

scholarly journals Temporal and Spatial Heterogeneity of Soil Erosion and a Quantitative Analysis of its Determinants in the Three Gorges Reservoir Area, China

2020 ◽  
Vol 17 (22) ◽  
pp. 8486
Author(s):  
Lin Chu ◽  
Tiancheng Sun ◽  
Tianwei Wang ◽  
Zhaoxia Li ◽  
Chongfa Cai
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Heterogeneity ◽  
Soil Loss ◽  
Three Gorges Reservoir ◽  
Vegetation Coverage ◽  
Three Gorges Reservoir Area ◽  
Land Use Type ◽  
Three Gorges ◽  
The Three Gorges

As the most typical ecologically fragile area in South China, the Three Gorges Reservoir Area (TGRA) suffers from water and soil loss, which has threatened the local ecological environment. Understanding the spatial heterogeneity of soil erosion and exploring its determinants are of great significance in preventing soil erosion and maintaining ecological sustainability in the TGRA. This study investigates the spatial heterogeneity of soil erosion and quantitatively identifies the determinants in the TGRA based on the Chinese Soil Loss Equation (CSLE) and geographical detector method. This study concluded that the soil erosion status generally improved from 1990 to 2015, showing an increasing trend from 1990 to 2000 and a decreasing trend from 2000 to 2010. Slope, land use, and vegetation coverage were the dominant individual factors affecting soil erosion in the TGRA. For the interaction factor, the combinations of land-use type and slope and vegetation coverage and slope were the key determinants, explaining 68.7% and 63.1% of the spatial heterogeneity of soil erosion in the TGRA from 1990 to 2015, respectively. Moderate and higher levels of soil erosion occurred in areas where the slope was greater than 25°. Among the land-use types, dry land and bare land were prone to soil erosion. These findings reveal that land-use type and vegetation coverage should be considered for the effective prevention of soil erosion, and cultivation on sloped farmland should be prohibited, especially on slopes higher than 25° in the TGRA.

scholarly journals Spatiotemporal Differentiation and the Factors of Ecological Vulnerability in the Toutun River Basin Based on Remote Sensing Data

2019 ◽  
Vol 11 (15) ◽  
pp. 4160 ◽  
Author(s):  
Qin Liu ◽  
Tiange Shi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
River Basin ◽  
Hot Spot ◽  
Remote Sensing Data ◽  
Cold Spot ◽  
Strengthening Effect ◽  
Land Use Type ◽  
Sensing Data ◽  
Ecological Vulnerability

Ecological vulnerability assessment increases the knowledge of ecological status and contributes to formulating local plans of sustainable development. A methodology based on remote sensing data and spatial principal component analysis was introduced to discuss ecological vulnerability in the Toutun River Basin (TRB). Exploratory spatial data analysis and a geo-detector were employed to evaluate the spatial and temporal distribution characteristics of ecological vulnerability and detect the driving factors. Four results were presented: (1) During 2003 and 2017, the average values of humidity, greenness, and heat in TRB increased by 49.71%, 11.63%, and 6.51% respectively, and the average values of dryness decreased by 165.24%. However, the extreme differences in greenness, dryness, and heat tended to be obvious. (2) The study area was mainly dominated by a high and extreme vulnerability grade, and the ecological vulnerability grades showed the distribution pattern that the northern desert area was more vulnerable than the central artificial oasis, and the central artificial oasis was more vulnerable than the southern mountainous area. (3) Ecological vulnerability in TRB showed significant spatial autocorrelation characteristics, and the trend was enhanced. The spatial distribution of hot/cold spots presented the characteristics of “hot spot—cold spot—secondary hot spot—cold spot” from north to south. (4) The explanatory power of each factor of ecological vulnerability was temperature (0.5955) > land use (0.5701) > precipitation (0.5289) > elevation (0.4879) > slope (0.3660) > administrative division (0.1541). The interactions of any two factors showed a non-linear strengthening effect, among which, land use type ∩ elevation (0.7899), land use type ∩ precipitation (0.7867), and land use type ∩ temperature (0.7791) were the significant interaction for ecological vulnerability. Overall, remote sensing data contribute to realizing a quick and objective evaluation of ecological vulnerability and provide valuable information for decision making concerning ecology management and region development.

scholarly journals Environmental Quality Assessment of Urban Ecology based on Spatial Heterogeneity and Remote Sensing Imagery

2019 ◽  
Author(s):  
Iswari Nur Hidayati ◽  
R Suharyadi ◽  
Projo Danoedoro
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Heterogeneity ◽  
Urban Ecology ◽  
Vegetation Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Ecological Index ◽  
Sensing Data

The phenomenon of urban ecology is very comprehensive, for example, rapid land-use changes, decrease in vegetation cover, dynamic urban climate, high population density, and lack of urban green space. Temporal resolution and spatial resolution of remote sensing data are fundamental requirements for spatial heterogeneity research. Remote sensing data is very effective and efficient for measuring, mapping, monitoring, and modeling spatial heterogeneity in urban areas. The advantage of remote sensing data is that it can be processed by visual and digital analysis, index transformation, image enhancement, and digital classification. Therefore, various information related to the quality of urban ecology can be processed quickly and accurately. This study integrates urban ecological, environmental data such as vegetation, built-up land, climate, and soil moisture based on spectral image response. The combination of various indices obtained from spatial data, thematic data, and spatial heterogeneity analysis can provide information related to urban ecological status. The results of this study can measure the pressure of environment caused by human activities such as urbanization, vegetation cover and agriculture land decreases, and urban micro-climate phenomenon. Using the same data source indicators, this method is comparable at different spatiotemporal scales and can avoid the variations or errors in weight definitions caused by individual characteristics. Land use changes can be seen from the results of the ecological index. Change is influenced by human behavior in the environment. In 2002, the ecological index illustrated that regions with low ecology still spread. Whereas in 2017, good and bad ecological indices are clustered.

scholarly journals Monitoring and analysis of the expansion of the Ajmr Port, Davao City, Philippines using multi-source remote sensing data

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7512 ◽  
Author(s):  
Humei Li ◽  
Mingquan Wu ◽  
Dinghui Tian ◽  
Lianxi Wu ◽  
Zheng Niu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Good Condition ◽  
Coastal Region ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Port Area ◽  
The Impact ◽  
Port Construction ◽  
Port Expansion

Ports have been built or expanded in a number of countries to cater to increasing maritime trade in the 21st century. Port expansion is associated with economic and environmental impacts on the local and regional scales, and these impacts can be studied using remote sensing. The present study presents new results from multi-source remote sensing monitoring of the Ajmr Port expansion. An analysis of land use and vegetation coverage at the port is used to monitor the impact of port construction on the local ecology, while changes in roads, buildings, and lights are used to monitor the economic impact. The results show that: (1) After nine years of expansion, the port area has gradually expanded from the central to the southern coastal area, with an increase of 21.68 hectares during the expansion period. After the expansion, the area of builidings and construction in the study area increased significantly, while the area of water and green areas decreased significantly, indicating that the port construction changed the land use structure of the area. (2) From the perspective of vegetation coverage, the vegetation coverage within 5 km from the port is in good condition. After 9 years, the vegetation coverage in the region between 0.6 and 1 increased from 43.71% to 44.25%, reflecting the higher overall greening level in the region. (3) By analyzing the increase in roads and buildings, it can be seen that the port’s comprehensive transportation capacity has improved, the population of the region has increased significantly. As the scale of construction has been continuously expanded , the prosperity as increased. (4) By analyzing the changes in the light index, the light data from the northeast to the southwest in the region is very obvious, and it is clearly located along the coast, indicating that the economic development of the coastal zone is faster than other regions, and the coastal region has promoted the development of the inland region.

scholarly journals Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

2014 ◽  
Vol 11 (1) ◽  
pp. 1073-1123 ◽  
Author(s):  
P. Karimi ◽  
W. G. M. Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Distribution ◽  
Hydrological Modeling ◽  
Remote Sensing Data ◽  
Actual Evapotranspiration ◽  
Primary Concern ◽  
Suitable Alternative ◽  
Sensing Data ◽  
Water Accounting

Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of one season to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the spatial distribution of evapotranspiration can be mapped with an overall accuracy of 95% (STD 5%) and rainfall with an overall accuracy of 82% (STD 15%). Land use can be identified with an overall accuracy of 85% (STD 7%). Hence, more scientific work is needed to improve spatial mapping of rainfall using multiple space-borne sensors. Actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

Monitoring land use change in the Lake Taupo catchment between 1975, 1990 and 2002 using satellite remote sensing data

2007 ◽  
pp. 17-22
Author(s):  
H. Lilienthal ◽  
A. Brauer ◽  
K. Betteridge ◽  
E. Schnug
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Remote Sensing ◽  
Remote Sensing Data ◽  
Native Vegetation ◽  
Lake Water Quality ◽  
Livestock Farming ◽  
Slow Decline

Conversion of native vegetation into farmed grassland in the Lake Taupo catchment commenced in the late 1950s. The lake's iconic value is being threatened by the slow decline in lake water quality that has become apparent since the 1970s. Keywords: satellite remote sensing, nitrate leaching, land use change, livestock farming, land management

scholarly journals Topographic Position, Land Use and Soil Management Effects on Soil Organic Carbon (Vineyard Region of Niš, Serbia)

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1438
Author(s):  
Snežana Jakšić ◽  
Jordana Ninkov ◽  
Stanko Milić ◽  
Jovica Vasin ◽  
Milorad Živanov ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Layer ◽  
Spatial Distribution ◽  
Soil Erosion ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Compaction ◽  
Soil Management ◽  
Forest Land ◽  
Topographic Position

Spatial distribution of soil organic carbon (SOC) is the result of a combination of various factors related to both the natural environment and anthropogenic activities. The aim of this study was to examine (i) the state of SOC in topsoil and subsoil of vineyards compared to the nearest forest, (ii) the influence of soil management on SOC, (iii) the variation in SOC content with topographic position, (iv) the intensity of soil erosion in order to estimate the leaching of SOC from upper to lower topographic positions, and (v) the significance of SOC for the reduction of soil’s susceptibility to compaction. The study area was the vineyard region of Niš, which represents a medium-sized vineyard region in Serbia. About 32% of the total land area is affected, to some degree, by soil erosion. However, according to the mean annual soil loss rate, the total area is classified as having tolerable erosion risk. Land use was shown to be an important factor that controls SOC content. The vineyards contained less SOC than forest land. The SOC content was affected by topographic position. The interactive effect of topographic position and land use on SOC was significant. The SOC of forest land was significantly higher at the upper position than at the middle and lower positions. Spatial distribution of organic carbon in vineyards was not influenced by altitude, but occurred as a consequence of different soil management practices. The deep tillage at 60–80 cm, along with application of organic amendments, showed the potential to preserve SOC in the subsoil and prevent carbon loss from the surface layer. Penetrometric resistance values indicated optimum soil compaction in the surface layer of the soil, while low permeability was observed in deeper layers. Increases in SOC content reduce soil compaction and thus the risk of erosion and landslides. Knowledge of soil carbon distribution as a function of topographic position, land use and soil management is important for sustainable production and climate change mitigation.

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