scholarly journals Estimation of Soil Salt and Ion Contents Based on Hyperspectral Remote Sensing Data: A Case Study of Baidunzi Basin, China

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 559
Author(s):  
Libing Wang ◽  
Bo Zhang ◽  
Qian Shen ◽  
Yue Yao ◽  
Shengyin Zhang ◽  
...  
Keyword(s):  
Input Data ◽  
Mean Squared Error ◽  
Salt Content ◽  
Principal Component ◽  
Hyperspectral Data ◽  
Dynamic Monitoring ◽  
Soil Composition ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Wide Range

Soil salinity due to irrigation diversion affects regional agriculture, and the development of soil composition estimation models for the dynamic monitoring of regional salinity is important for salinity control. In this study, we evaluated the performance of hyperspectral data measured using an analytical spectral device (ASD) field spec standard-res hand-held spectrometer and satellite sensor visible shortwave infrared advanced hyperspectral imager (AHSI) in estimating the soil salt content (SSC). First derivative analysis (FDA) and principal component analysis (PCA) were applied to the data using the raw spectra (RS) to select the best model input data. We tested the ability of these three groups of data as input data for partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR). Finally, an estimation model of the SSC, Na+, Cl−, and SO42− contents was established using the best input data and modeling method, and a spatial distribution map of the soil composition content was drawn. The results show that the soil spectra obtained from the satellite hyperspectral data (AHSI) and laboratory spectral data (ASD) were consistent when the SSC was low, and as the SSC increased, the spectral curves of the ASD data showed little change in the curve characteristics, while the AHSI data showed more pronounced features, and this change was manifested in the AHSI images as darker pixels with a lower SSC and brighter pixels with a higher SSC. The AHSI data demonstrated a strong response to the change in SSC; therefore, the AHSI data had a greater advantage compared with the ASD data in estimating the soil salt content. In the modeling process, RS performed the best in estimating the SSC and Na+ content, with the R2 reaching 0.79 and 0.58, respectively, and obtaining low root mean squared error (RMSE) values. FDA and PCA performed the best in estimating Cl− and SO42−, while MLR outperformed PLSR and PCR in estimating the content of the soil components in the region. In addition, the hyperspectral camera data used in this study were very cost-effective and can potentially be used for the evaluation of soil salinization with a wide range and high accuracy, thus reducing the errors associated with the collection of individual samples using hand-held hyperspectral instruments.

scholarly journals Quantitative Estimating Salt Content of Saline Soil Using Laboratory Hyperspectral Data Treated by Fractional Derivative

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Dong Zhang ◽  
Tashpolat Tiyip ◽  
Jianli Ding ◽  
Fei Zhang ◽  
Ilyas Nurmemet ◽  
...  
Keyword(s):  
Fractional Derivative ◽  
Spectral Reflectance ◽  
Salt Content ◽  
Hyperspectral Data ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Lake Basin ◽  
Soil Salt Content ◽  
Soil Salt

Most present researches on estimation of soil salinity by hyperspectral data have focused on the spectral reflectance or their integer derivatives but ignored the fractional derivative information of hyperspectral data. Motivated by this situation, the selected study area is the Ebinur Lake basin located in the southwest border in the Xinjiang Uygur Autonomous Region, China, with severe salinization. The field work was conducted from 15 to 25 October, 2014, and a total of 180 soil samples were collected from 45 sampling sites; after measuring the soil salt content and spectral reflectance in the laboratory, the range from 0 to 2 was divided into 11 orders (interval 0.2) and then the hyperspectral data were treated by 4 kinds of mathematical transformations and 11 orders of fractional derivatives. Combined with the soil salt content, partial least square regression method was applied for model calibrations and predictions and some indexes were used to evaluate the performance of models. The results showed that the retrieval model built up by 250 bands based on 1.2-order derivative of 1/lg⁡R had excellent capacity of estimating soil salt content in the study area (RMSEC=14.685 g/kg, RMSEP=14.713 g/kg, R2C=0.782, R2P=0.768, and RPD = 2.080). This study provides an application reference for quantitative estimations of other land surface parameters and some other applications on hyperspectral technology.

Monitoring soil salt content using HJ-1A hyperspectral data: A case study of coastal areas in Rudong County, Eastern China

2014 ◽  
Vol 25 (2) ◽  
pp. 213-223 ◽  
Author(s):  
Jianguo Li ◽  
Lijie Pu ◽  
Ming Zhu ◽  
Xiaoqing Dai ◽  
Yan Xu ◽  
...  
Keyword(s):  
Eastern China ◽  
Salt Content ◽  
Coastal Areas ◽  
Hyperspectral Data ◽  
Soil Salt Content ◽  
Soil Salt

scholarly journals Determination of Soil Salt Content Using a Probability Neural Network Model Based on Particle Swarm Optimization in Areas Affected and Non-Affected by Human Activities

2018 ◽  
Vol 10 (9) ◽  
pp. 1387 ◽  
Author(s):  
Chengbiao Fu ◽  
Shu Gan ◽  
Xiping Yuan ◽  
Heigang Xiong ◽  
Anhong Tian
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Human Activities ◽  
Salt Content ◽  
Particle Swarm ◽  
Wave Band ◽  
Swarm Optimization ◽  
Affected Area ◽  
Soil Salt Content ◽  
Soil Salt

Traditional partial least squares regression (PLSR) and artificial neural networks (ANN) have been widely applied to estimate salt content from spectral reflectance in many different saline environments around the world. However, these methods entail a great amount of calculation, and their accuracy is low. To overcome these problems, a probability neural network (PNN) model based on particle swarm optimization was used in this study to build soil salt content models. Furthermore, there is a clear correlation between the level of human activities and the degree of salinization of an environment. This paper is the first to discuss this matter. Here, the performance of the PNN model to estimate soil salt content from reflectance data was investigated in areas non-affected (Area A) and affected (Area B) by human activities. The study area is located in Xingjinag, China. Different mathematical procedures, five wave band intervals, and two types of signal input sources were used for cross analysis. The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to deviation (RPD) index values were compared to verify the reliability of the model. Particle swarm optimization was used to adjust the optimal smoothing parameters of the PNN model and to avoid the long training processes required by the traditional ANN. The results show that the optimal wave band interval of the PNN is between 1000 nm and 1350 nm in Area A and between 400 nm and 700 nm in Area B. The reciprocal (1/R) transformation after Savitzky-Golay (SG) smoothing of the signal source is optimal for both areas. The RPD for both is greater than 30, which shows that the PNN model is applicable to areas with and without human activities and the prediction results are very good. The results indicated that the optimal wave band intervals for PNN modeling differed in areas affected and non-affected by human activities. The optimal interval of the artificial activities region falls in the visible light portion of the spectrum, and the optimized wave band region without human activities falls in the near-infrared short-wave portion of the spectrum.

Functions of Cotton Yield Response to Soil Salinity in Akesu River Irrigation District

2012 ◽  
Vol 535-537 ◽  
pp. 486-494
Author(s):  
Yu Zhang ◽  
Pei Tong Cong ◽  
Shun Jun Hu ◽  
Li Hong Wang ◽  
Feng Qing Guo ◽  
...  
Keyword(s):  
Salt Tolerance ◽  
Salt Content ◽  
Soil Layer ◽  
Relative Yield ◽  
Irrigation District ◽  
Yield Response ◽  
Yield Reduction ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Salinized Soil

Based on experimental data from the five observation points during the three years, the linear subsected functions and the nonlinear s-shaped functions between the cotton relative yield and soil salt content on the salinized soil about the 0-20cm soil layer and the 0-40cm soil layer in Akesu River Irrigation District were constructed by linear regression and nonlinear least square approximation. Their applicabilities were analyzed and compared and it was found the nonlinear s-shaped function of the 0-20cm soil layer to fit better with the response relationship between the cotton relative yield and the soil salt content on the salinity soil than others in Akesu River Irrigation District.which and the indexes of cotton salt tolerance were definited, and then the indexes of cotton salt tolerance were drawn on with the function with better applicability. From the function, some indexes of salt tolerance，which contained the cotton critical soil salt content, the cotton threshold soil salt content, the soil salt content at the fastest rate of cotton relative yield reduction, and the soil salt content at the 50% cotton relative yield reduction, and so on, were determined, which can be provide as the important references for the agricultural planting, improvement of salinized soil and irrigation with saline water in Akesu River Irrigation District.

scholarly journals Cultivation of dandelion (Taraxacum erythropodium) on coastal saline land based on the control of salinity and fertilizer

2019 ◽  
Vol 31 (2) ◽  
pp. 277-284
Author(s):  
Zhe Wu ◽  
Zhizhong Xue ◽  
Haishan Li ◽  
Xiaodong Zhang ◽  
Xiuping Wang ◽  
...  
Keyword(s):  
Quality Control ◽  
Salt Tolerance ◽  
Salt Content ◽  
Technical Support ◽  
Physiological Parameters ◽  
Fresh Leaf ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Leaf Yield ◽  
Saline Land

AbstractDandelion (Taraxacum spp.) is a widely distributed weed; in China, however, dandelion has been considered to be a kind of medicinal and edible vegetable in recent years. This transition from weed to vegetable requires corresponding cultivation and management. Thus, the production of dandelion on saline land was conducted based on the evaluation of dandelion salt tolerance. Low soil salt content (< 0.3%) did not significantly affect dandelion growth, and the salt tolerance threshold of dandelion ranged from 0.4% to 0.43% according to the correlation between salt content and morphological and physiological parameters, which was for guiding the preparation of saline land for dandelion field cultivation. Different fertilizer treatments significantly affected the leaf yield of dandelion, and the maximum fresh leaf yield of ~10.5 t ha−1 was obtained when urea was applied in batches at a ratio of 2:2:1 in the sowing, seedling and flowering stages, respectively. This research provided the theoretical and technical support for the cultivation on saline land, laying the foundation for further study of quality control for the cultivation of dandelion on saline land.

scholarly journals Suaeda salsa/Zea mays L. intercropping in saline soil on plant growth and rhizospheric physiological processes

2021 ◽  
Author(s):  
Shoule Wang ◽  
Zhenyong Zhao ◽  
Shaoqing Ge ◽  
Ke Zhang ◽  
Changyan Tian ◽  
...  
Keyword(s):  
Zea Mays ◽  
Saline Soil ◽  
Salt Content ◽  
Treated Group ◽  
Suaeda Salsa ◽  
Nitrogen And Phosphorus ◽  
Available Nitrogen ◽  
Physiological Processes ◽  
Soil Salt Content ◽  
Soil Salt

Abstract Background and aims Halophytes possess the capacity to uptake high levels of salt through physiological processes and their root architecture. Here, we investigated whether halophyte/non-halophyte intercropping in saline soil decreases the soil salt content and contains root-dialogue. Methods Field and pot experiments were conducted to determine the plant biomasses and salt and nutrient distributions in three suaeda (Suaeda salsa) / maize (Zea mays L.) intercropping systems. The three treatments were set up by non-barrier, nylon barrier and plastic barrier between plant roots. Results The biomass of the non-barrier-treated maize was significantly lower than that of the nylon barrier-treated maize, whereas the suaeda root biomass showed a limited increase. The soil salt content negatively affected the non-barrier group’s roots compared with those in the nylon and plastic barrier-treated groups, and it was also higher on the maize side of the nylon-barrier treatment. There were higher available nitrogen and phosphorus contents in the soil of the non-barrier- and nylon barrier-treated groups compared with the plastic barrier-treated group. In addition, the pH was lower, and the available potassium content was higher, which suggested that rhizospheric processes occurred between the two species. Conclusions The suaeda/maize intercropping would decrease the soil salt content, and they also revealed potential rhizospheric effects though the role of root, which provides an effective way for the improvement of saline-alkali land.

Salt-tolerance identification and quality evaluation of Abelmoschus manihot (L.) Medik

2020 ◽  
Vol 100 (5) ◽  
pp. 568-574
Author(s):  
Zhe Wu ◽  
Zhizhong Xue ◽  
Xuelin Lu ◽  
Yinsuo Jia ◽  
Xiuping Wang ◽  
...  
Keyword(s):  
Salt Tolerance ◽  
Quality Evaluation ◽  
Salt Content ◽  
Northern China ◽  
High Yield ◽  
Edible Plant ◽  
High Quality ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Functional Components

Abelmoschus manihot (L.) Medik. is a medicinal and edible plant. To evaluate its suitability for cultivation on the coastal saline-alkali land in northern China for high quality functional products, salt-tolerance identification and flavonoid contents were evaluated under saline treatments. Results showed that the salt-tolerance threshold of A. manihot ranged from 4.1 to 6.9 g L−1; however, low soil salt content (<3 g L−1) had the best growth and accumulation of total flavonoids. Sixteen kinds of common functional components such as hyperoside, rutoside, and quercetin were found. Of these components, the four (myricetin-3-0-glucoside, rutoside, quercetin-3′-0-glucoside, and gossypetin-8-0-β-d-glucuronic acid) with the highest content were chosen as the quality evaluation indexes. High levels of quality and yield occurred at a soil salt content of 3 g L−1. Our results suggested that soil salt content should not exceed 3 g L−1 in field cultivation for high quality and high yield of A. manihot.

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