Evaluation of soil fertility using combination of Landsat 8 and Sentinel­2 data in agricultural lands.

Today, remote sensing is widely used to estimate soil properties. Because it is an easy and accessible way to estimate soil properties that are difficult to estimate in the field. Based on this, to evaluate the soil fertility (SF), soil sampling was performed irregularly from the surface depth of 0-30 cm in 216 points, 11 soil properties were measured, and the soil fertility index (SFI) was calculated by soil properties. Simultaneously, we combined satellite images of Landsat 8 and Sentinel-2 using the Gram-Schmidt algorithm. Finally, multiple linear regression SFI was calculated using satellite data, as well as the spatial distribution of SFI was obtained in very low, low, moderate, high, and very high classes. Our findings showed that the combination of Landsat 8 and Sentinel-2 data using the Gram-Schmidt algorithm has a higher correlation with SFI than when these data are individually. Therefore, combined Landsat 8 and Sentinel 2 data were used for SFI modeling. Using model selection procedure indices (including Cp, AIC, and ρc criteria), the visible range bands, notably blue (r = 0.65), green (r = 0.63), and red (r = 0.61), provide the best model for estimating SFI (R2 = 0.43, Cp = 3.34, AIC = -277.4, and ρc = 0.44). Therefore, these bands were used to estimate the SFI index. Also, the spatial distribution of the SIF index showed that the most significant area was related to the low class, and the lowest area belonged to the high and very high fertility classes. According to these results, it can be concluded that using the combination of Landsat 8 and Sentinel 2 bands to estimate soil fertility index in agricultural lands can increase the accuracy of soil fertility estimation.

Biodiversity and agriculture in dynamic landscapes: Integrating ground and remotely-sensed baseline surveys.

Sustainable biodiversity and land management require a cost-effective means of forecasting landscape response to environmental change. Conventional species-based, regional biodiversity assessments are rarely adequate for policy planning and decision making. We show how new ground and remotely-sensed survey methods can be coordinated to help elucidate and predict relationships between biodiversity, land use and soil properties along complex biophysical gradients that typify many similar landscapes worldwide. In the lower Zambezi valley, Mozambique we used environmental, gradient-directed transects (gradsects) to sample vascular plant species, plant functional types, vegetation structure, soil properties and land-use characteristics. Soil fertility indices were derived using novel multidimensional scaling of soil properties. To facilitate spatial analysis, we applied a probabilistic remote sensing approach, analyzing Landsat 7 satellite imagery to map photosynthetically active and inactive vegetation and bare soil along each gradsect. Despite the relatively low sample number, we found highly significant correlations between single and combined sets of specific plant, soil and remotely sensed variables that permitted testable spatial projections of biodiversity and soil fertility across the regional land-use mosaic. This integrative and rapid approach provides a low-cost, high-return and readily transferable methodology that permits the ready identification of testable biodiversity indicators for adaptive management of biodiversity and potential agricultural productivity.

Novel Weighting Method for Evaluating Forest Soil Fertility Index: A Structural Equation Model.

Understanding nutrient quantity and quality in forest soils is important for sustainable management of forest resources and maintaining forest ecosystem services. In this study, six soil nutrient indicators, including soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) were measured in five different aged stands of Chinese fir forests in subtropical China. A structural equation model (SEM) was developed based on these soil nutrients indicators in order to better evaluate the soil fertility index (SFI) in these studied forests. The results show that soil nutrient contents changed with the soil depth in different age groups. The SOM decreased in a specific order: over mature > mature > near mature > middle > young stands. The TN content of the soil gradually decreased with increased soil depth throughout all age groups. The SEM indicated that the TN had the highest weight of 0.4154, while the TP had the lowest weight at 0.1991 for estimating the SFI. The weights of other indicators (AN, SOM, AP, and AK) ranged 0.2138−0.3855 in our study. The established SEM satisfied the fitness reference values and was able to accurately describe the forest soil nutrient status through the SFI. The overall SFI values were significantly higher in over mature stands than in young-aged stands and in topsoil than in deeper soil in all examined forests. Soil TN, AP, and AK were the most important nutrient indicators to the evaluation of the SFI in the study sites. The results confirmed that the SEM was suitable to estimate the weights of the SFI and better describe the soil nutrient status in forests. Our research provides an innovative approach to assess a soil nutrient status and soil fertility and provides a scientific basis for accurate implementation of soil nutrient assessment in forest ecosystems.

(3-Aminopropyl)triethoxysilane and iron rice straw biochar composites for the sorption of Cr (VI) and Zn (II) using the extract of heavy metals contaminated soil.

Heavy metals like Cr (VI), when released into the environment, pose a serious threat to animal and human health. In this study, iron and (3-Aminopropyl)triethoxysilane (APTES) biochar composites were prepared from the biochar, which was produced through the pyrolysis of rice straw at 400 and 600 °C, using the chemical processes with an aim that the doping of pristine biochar structure with the Fe and NH2 radicals would enhance the removal of Cr (VI) and Zn (II) adsorption in both aqueous solution and soil. Both biochar composites were mixed at a rate of 3% (w/w) with the mine soil for the soil incubation test, and after completion of the test, a soil fertility index (SFI) was calculated. Results showed that both iron and APTES biochar composites followed the Langmuir-Freundlich isotherm showing the maximum removal capacity of 100.59 mg/g for Cr (VI) by APTES/SiBC 600 and maximum adsorption capacity of 83.92 mg/g for Zn2+ by Fe/BC 400. The SFI of the mine-soil amended with both Fe and APTES biochar composites were 16.67 and 13.04%, respectively higher than the controlled study. The mitotic index of the A. cepa cells that grew up in the soil amended with Fe/BC and APTES/SiBC were 40.47 and 44.45%, respectively, higher than the controlled study. The results indicated that the incorporation of the Fe and APTES biochar composites in the soil effectively reduced the metal toxicity and improved the soil physicochemical properties. This study opens up the prospects of using biochar composites in contaminated soil and water treatments.

Soil fertility evaluation and spatial distribution of grasslands in Qilian Mountains Nature Reserve of eastern Qinghai-Tibetan Plateau.

The study assessed the overall soil characteristics of grasslands on Qilian Mountains and rated the soil nutrient status with classification standard of the second national soil survey of China. Nemerow index method was used to evaluate the soil fertility of different grassland types. GIS was used to analyze the spatial distribution of the soil nutrients and provided a database for the grassland's ecological protection and restoration. The study graded the soil organic matter (SOM), total N, and available K at level 2 (high) or above for most regions, available soil-P at level 4, while the soil bulk density, total porosity and pH were 0.77-1.32 g cm-3, 35.36-58.83% and 7.63-8.54, respectively. The rank of comprehensive soil fertility index was temperate steppe (TS) > alpine meadow (AM) > alpine steppe (AS) >upland meadow (UM) >alpine desert (AD)> lowland meadow (LM)> temperate desert steppe (TDS)> temperate desert (TD). The areas with high, medium and low soil fertility accounted for 63.19%, 34.24% and 2.57% of the total grassland area. Soil fertility of different grassland types had different main limiting factors, for instance, the pH, total N and SOM were the main factors limiting soil fertility in LM, while pH and available P were the main factors limiting soil fertility in UM, AM, TS and AS. In summary, the grassland soil fertility was generally at the mid-upper level, and the main limiting factors were found in the different types of the grasslands and their spatial distributions were figured out. Our findings also indicated that the typical grasslands and meadows may require phosphorus application, while for desert grasslands, both nitrogen and phosphorus were required to improve their comprehensive soil fertility and grassland productivity.

Potassium-iron rice straw biochar composite for sorption of nitrate, phosphate, and ammonium ions in soil for timely and controlled release.

In this study, potassium-iron rice straw biochar composite (KRSB) was produced and compared with rice straw biochar (RSB) for the sorption of NO3-, PO43-, and NH4+ in aqueous medium and soil column. RSB was produced by pyrolyzing rice straw at 400 and 600 °C in a slow pyrolysis unit. KRSB was produced through chemical and hydrothermal treatments of rice straw biochar produced at 400 and 600 °C. Batch experiment results indicate that the KRSB showed better sorption capacity for nitrate, phosphate, and ammonium ions compared to pristine RSB. The sorption isotherms of all three nutrients (NO3-, PO43-, and NH4+) were better-explained by the Langmuir-Freundlich isotherm model. The column leaching experiment showed that the KRSB loaded soil reached maximum sorption capacity for PO43- and NO3- within six and eight days, respectively but, it showed poor sorption capacity for NH4+. The soil fertility index in the 400 and 600 KRSB amended soils were significantly increased by 50.68 and 52.85%, respectively compared to the control. Results indicated that KRSB could be utilized in the soil in two ways: first, to keep the nutrients attached to its surface and second, to release the nutrients in a phased and timely manner to increase their availability for plants.