Hyper-spectral response and estimation model of soil degradation in Kenli County, the Yellow River Delta

Chang, Chunyan; Fen, LIN; Zhou, Xue; Zhao, Gengxing

doi:10.1371/journal.pone.0227594

Cited by 6 publications

(2 citation statements)

References 34 publications

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“…The northwest wind prevails in winter and the southeast wind prevails in summer. The local crops mainly include winter wheat, corn, rice and cotton [17][18][19].…”

Section: Study Areamentioning

confidence: 99%

Determining Optimal Sampling Numbers to Investigate the Soil Organic Matter in a Typical County of the Yellow River Delta, China

et al. 2022

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Soil organic matter (SOM) plays a crucial role in promoting soil tillage, improving soil fertility and providing crop nutrients. Investigation and sampling are the premise and basis for understanding the spatial distribution of SOM. The number of sampling points will affect the accuracy of spatial variation of SOM. Therefore, it is important scientific work to determine a reasonable number of sampling points under the premise of ensuring accuracy. In this study, Kenli County, a typical area of the Yellow River Delta in China, was taken as an example to investigate the effect of different sampling points on spatial-variation expression of SOM. A total of 12 sample subsets (including 900 samples) were randomly sampled at equal intervals from the 900 sample points, using geographic information system (GIS) technology and geostatistical analyses to explore the optimal number of samples. The results showed that the SOM content in the study area had a lower-middle degree of variation. As the number of sample points decreased, the spatial distribution of SOM showed the gradual weakening of detail-characterization ability; and when the number of sample points was too small (<100), there was a wrong expression that was not consistent with the actual situation. The value of RMSE has no obvious regularity with the change of sample number. The values of both ME and ASE showed a significant inflection point when the number of samples was 150 and remained around 0 and 4 as the number of samples increased, respectively. Combined with the three indicators of ME, RMSE and ASE, collecting at least 150 samples can satisfy the spatial-variation expression of SOM, equivalent to 107 sample points within the area of 1000 km2. The research results could provide important references for investigation of SOM content in areas with similar natural geographical conditions.

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“…The northwest wind prevails in winter and the southeast wind prevails in summer. The local crops mainly include winter wheat, corn, rice and cotton [17][18][19].…”

Section: Study Areamentioning

confidence: 99%

Determining Optimal Sampling Numbers to Investigate the Soil Organic Matter in a Typical County of the Yellow River Delta, China

et al. 2022

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“…Remote sensing technology provides a more convenient and efficient tool to obtain the corresponding environmental variables [ 10 ]. Of course, some studies have also attempted to directly estimate soil pH by hyper-spectral or visible and near-infrared (VIS/NIR) diffuse reflectance spectroscopy to avoid tedious sampling work [ 11 , 12 ]. Meanwhile, geostatistical models such as kriging, inverse distance weighted (IDW), radial basis function (RBF), and multiple linear regression (MLR), random forests, and geographically weighted regression (GWR) are used to varying degrees [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution and Estimation Model of Soil pH in Coastal Eastern China

Xie

Qiu

Feng

et al. 2022

IJERPH

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Soil pH is an essential indicator for assessing soil quality and soil health. In this study, based on the Chinese farmland soil survey dataset and meteorological dataset, the spatial distribution characteristics of soil pH in coastal eastern China were analyzed using kriging interpolation. The relationships between hydrothermal conditions and soil pH were explored using regression analysis with mean annual precipitation (MAP), mean annual temperature (MAT), the ratio of precipitation to temperature (P/T), and the product of precipitation and temperature (P*T) as the main explanatory variables. Based on this, a model that can rapidly estimate soil pH was established. The results showed that: (a) The spatial heterogeneity of soil pH in coastal eastern China was obvious, with the values gradually decreasing from north to south, ranging from 4.5 to 8.5; (b) soil pH was significantly correlated with all explanatory variables at the 0.01 level. In general, MAP was the main factor affecting soil pH (r = −0.7244), followed by P/T (r = −0.6007). In the regions with MAP < 800 mm, soil pH was negatively correlated with MAP (r = −0.4631) and P/T (r = −0.7041), respectively, and positively correlated with MAT (r = 0.6093) and P*T (r = 0.3951), respectively. In the regions with MAP > 800 mm, soil pH was negatively correlated with MAP (r = −0.6651), MAT (r = −0.5047), P/T (r = −0.3268), and P*T (r = −0.5808), respectively. (c) The estimation model of soil pH was: y = 23.4572 − 6.3930 × lgMAP + 0.1312 × MAT. It has been verified to have a high accuracy (r = 0.7743, p < 0.01). The mean error, the mean absolute error, and the root mean square error were 0.0450, 0.5300, and 0.7193, respectively. It provides a new path for rapid estimation of the regional soil pH, which is important for improving the management of agricultural production and slowing down soil degradation.

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A synthesis on land degradation in the context of sustainable development goals

Nedd,

Anandhi

2024

Land Degrad Dev

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Land degradation (LD) is a severe and well‐known global concern. Therefore, this review aimed to find broader connections between LD and the Sustainable Development Goals (SDGs). This literature review aims to synthesize the definitions, processes, assessments, and challenges associated with LD. Furthermore, we developed a universally applicable and concise definition of LD that links a wide range of contexts and studies. Specifically, we categorized LD‐related processes into physical, chemical, and biological processes and synthesized 20 methods/formulas used in the assessment of LD. Finally, we synthesized the most significant challenges in the context of the resolution of LD and provided corresponding recommendations. The review also identified the main SDG targets that LD directly affects and the role of LD in relation to the SDGs. Overall, we expect this literature review to be a valuable resource for researchers and practitioners aiming to obtain a comprehensive understanding of LD. The findings of this study shed light on various aspects of LD concerning the SDGs. The LD and the SDGs' processes, challenges, and interactions can be a valuable resource for researchers and policymakers. The information can facilitate sustainable and scientifically rooted use of land resources and provide knowledge and advice on combating LD to reach the specific SDGs associated with LD.

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Hyper-spectral response and estimation model of soil degradation in Kenli County, the Yellow River Delta

Cited by 6 publications

References 34 publications

Determining Optimal Sampling Numbers to Investigate the Soil Organic Matter in a Typical County of the Yellow River Delta, China

Determining Optimal Sampling Numbers to Investigate the Soil Organic Matter in a Typical County of the Yellow River Delta, China

Spatial Distribution and Estimation Model of Soil pH in Coastal Eastern China

A synthesis on land degradation in the context of sustainable development goals

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