Spatiotemporal Variability of Soil Nitrogen in Relation to Environmental Factors in a Low Hilly Region of Southeastern China
Abstract
:1. Introduction
- (1)
- No systematic methodology exists that can be used to analyze the spatiotemporal changes in soil TN in conjunction with agricultural protection policies. Timely monitoring of the spatial distribution of soil TN can provide information on both the location and the amount of N in the soil; thus, explicitly linking changes in soil TN to agricultural protection regulations could be useful for understanding the dynamic patterns of N in soil [10] and for assessing the degree to which the Chinese STFFT decrease or increase soil TN in agricultural land.
- (2)
- Most DSM studies have focused on integrating hyperspectral data with field surveys and environmental parameters to monitor changes in soil TN [17]. However, archives of satellite sensor imagery such as Landsat data also include useful information that has not been fully exploited.
- (3)
- While DSM has been hailed as a very useful technique for assessing and monitoring soil TN [11], its applications thus far have been restricted to flat lands, partly because of the easy accessibility of such regions and partly because of the less complex environment. In contrast, the challenging environments of mountainous regions, which exhibit nonlinear relationships between soil properties and environmental predictors, have prevented researchers from analyzing the spatiotemporal patterns of soil TN therein [17], especially in terms of the relationship between soil TN and agricultural protection policies.
2. Materials and Methods
2.1. Site Description
2.2. Datasets
2.2.1. Soil Sample Collection and Laboratory Analysis
2.2.2. Environmental Variables
2.2.3. Remote Sensing Variables
2.2.4. Other Datasets
2.3. Prediction Models
2.3.1. Random Forest
2.3.2. Model Validation and Uncertainty
2.4. Data Processing
3. Results
3.1. Descriptive Statistics
3.2. Model Performance
3.3. Relative Importance of Environmental Variables
3.4. Spatiotemporal Distribution of Soil TN
4. Discussion
4.1. Model Performance
4.2. Roles of Environmental Factors
4.3. Spatiotemporal Distributions of Soil TN
4.3.1. Spatial Patterns of Soil TN
4.3.2. Temporal Changes in Soil TN
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
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Variables | Name | Unit | Scale | Source |
---|---|---|---|---|
Soil Type | ST | - | 1:50,000 | Digitized soil type map of Fuyang District |
Climate | MAP | mm | 1000 m | World climate database (1950–2010) |
MAT | °C | (http://www.worldclim.org/) | ||
Topography | Elevation | M | 30 m | DEM data, Geospatial Data Cloud site, Chinese Academy of Sciences (http://www.gscloud.cn) |
Slope | ° | |||
TWI | - | |||
Remote Sensing | BRed | - | 79 m & 30 m | Landsat 3 MSS on 5 August 1979 (79 m); Landsat 5 TM on 26 July 2004 (30 m); Landsat 8 OLI on 22 July 2014 (30 m); USGS (https://glovis.usgs.gov/) |
BNIR | - | |||
NDVI | - |
Year | Number | Min (g/kg) | Max (g/kg) | Mean (g/kg) | SD (g/kg) | CV (%) |
---|---|---|---|---|---|---|
1979 | 231 | 0.60 | 2.50 | 1.65 | 0.36 | 21.82 |
2004 | 267 | 0.44 | 3.70 | 1.90 | 0.56 | 29.47 |
2014 | 220 | 0.40 | 3.50 | 1.76 | 0.69 | 47.26 |
Year | Elevation | Slope | TWI | MAT | MAP | ST | BRed | BNIR | NDVI |
---|---|---|---|---|---|---|---|---|---|
1979 | 0.42 b | 0.24 a | −0.31 b | 0.18 | 0.36 b | 0.37 b | −0.01 | 0.21 | 0.15 |
2004 | 0.29 a | −0.06 | −0.41 b | −0.14 | 0.27 b | 0.24 a | −0.31 b | −0.33 b | 0.18 |
2014 | −0.21 a | −0.21 a | −0.29 | 0.22 | −0.32 b | 0.25 a | −0.11 | 0.44 b | 0.38 b |
Year | Index | Min | Max | Mean | SD |
---|---|---|---|---|---|
1979 | RMSE | 0.33 | 0.34 | 0.3312 | 0.0039 |
R2 | 0.44 | 0.50 | 0.4677 | 0.0180 | |
2004 | RMSE | 0.47 | 0.50 | 0.4833 | 0.0054 |
R2 | 0.59 | 0.64 | 0.6286 | 0.0149 | |
2014 | RMSE | 0.59 | 0.61 | 0.5968 | 0.0067 |
R2 | 0.54 | 0.62 | 0.5796 | 0.0194 |
Classification | Level | TN | 1979 | 2004 | 2014 | |||
---|---|---|---|---|---|---|---|---|
(g/kg) | Area (ha) | Percentage (%) | Area (ha) | Percentage (%) | Area (ha) | Percentage (%) | ||
High | I | >2.0 | 0 | 0 | 8559 | 31.67 | 201 | 0.73 |
II | 1.5–2.0 | 3395 | 11.07 | 16,183 | 59.89 | 11,982 | 43.55 | |
Medium | III | 1.0–1.5 | 23,409 | 76.32 | 2280 | 8.44 | 14,671 | 53.32 |
IV | 0.75–1.0 | 3868 | 12.61 | 0 | 0 | 620 | 2.22 | |
Low | V | 0.5–0.75 | 0 | 0 | 0 | 0 | 40 | 0.2 |
VI | ≤0.5 | 0 | 0 | 0 | 0 | 0 | 0 |
Region | Sub-Region | Characteristics |
---|---|---|
Farmland regions | Grain functional region | Relatively concentrated contiguous and well-established rice cultivation areas delineated by the Bureau of Agriculture |
Basic farmland region | Higher-quality arable areas delineated by the Land and Resources Bureau. The scope of this area did not include the aforementioned grain functional region in the present study | |
Ordinary farmland region | The remainder of cultivated land areas with lower-quality characteristics | |
Geographic regions | River falley plain region | Mainly including valleys and river plains with a relative height ranging from 0 to 50 m |
Low hilly region | With a relative height ranging from 50 to 150 m | |
Low mountain and hilly region | Mainly including the surrounding low mountains and hilly areas with a relative height exceeding 150 m |
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He, S.; Zhu, H.; Shahtahmassebi, A.R.; Qiu, L.; Wu, C.; Shen, Z.; Wang, K. Spatiotemporal Variability of Soil Nitrogen in Relation to Environmental Factors in a Low Hilly Region of Southeastern China. Int. J. Environ. Res. Public Health 2018, 15, 2113. https://doi.org/10.3390/ijerph15102113
He S, Zhu H, Shahtahmassebi AR, Qiu L, Wu C, Shen Z, Wang K. Spatiotemporal Variability of Soil Nitrogen in Relation to Environmental Factors in a Low Hilly Region of Southeastern China. International Journal of Environmental Research and Public Health. 2018; 15(10):2113. https://doi.org/10.3390/ijerph15102113
Chicago/Turabian StyleHe, Shan, Hailun Zhu, Amir Reza Shahtahmassebi, Lefeng Qiu, Chaofan Wu, Zhangquan Shen, and Ke Wang. 2018. "Spatiotemporal Variability of Soil Nitrogen in Relation to Environmental Factors in a Low Hilly Region of Southeastern China" International Journal of Environmental Research and Public Health 15, no. 10: 2113. https://doi.org/10.3390/ijerph15102113