Correlation of Spatial Variability of Soil Macronutrients with Crop Performance by Using Satellite and Remote Sensing Indices for Site Specific Agriculture: Chakwal Region

Abstract

Site-specific agriculture includes the application of soil on variable areas rather than the whole field and requires the knowledge of spatial variability of soil nutrients in the area. A survey was conducted to find out the spatial variation of soil macronutrient, to prepare the soil fertility maps and to correlate soil nutrients with NDVI values, at University Research Farm, Koont, Chakwal. Soil samples were collected and analyzed for soil macronutrient (NO 3 -N, P, K, SO 4 -S and CaCO 3 ) concentration through standard procedures. Obtained data were analyzed by using GIS and ordinary statistics to predict the spatial variability and preparation of digital maps of the soil macronutrients. NDVI values were calculated by acquiring the cloud free landsat images of study area to correlate with soil macronutrients. The results showed that, NO 3 -N and Available P were deficient in study area and were having the mean value of 7.54 mg kg -1 and 6.64 mg kg -1 respectively. K and SO 4 -S were in satisfactory ranges and were having average values of 130.3 mg kg -1 and 8.69 mg kg -1 respectively. Study area was classified as moderately calcareous soil and lime content were having the mean value of 7.88%. Geostatistical analysis showed that NO 3 -N and available P were strongly spatial dependent while K, SO 4 -S and CaCO 3 were moderately spatial dependent. Pearson correlation analysis among NDVI values and soil parameters showed that NO 3 -N, P, K and CaCO 3 were significantly positively correlated with NDVI values whereas SO 4 -S showed non-significant positive correlation with NDVI values. Study recommended that spatial variability of soil properties should be taken in account in decision making processes regarding farm operations such as fertilizer application, more studies on different spatial scale should be conducted and use of such techniques in profitable and sustainable site-specific agriculture should be promoted.

Spatial variability in soil nutrients and fertility mapping using geospatial techniques in Kurnool division of Andhra Pradesh

“…Verhulst et al (2008) confirmed that the spatial variability of soil properties influence the crop performance which affects the spectral characteristics of vegetation and correlated with the NDVI values. Comparable outcome was reported by Zeeshan et al (2017) that the soil macronutrients were significantly and positively correlated with NDVI values of studied area of Chakwal region, Pakistan. The NDVI values have shown best relationship with soil nitrogen and organic carbon as higher nitrogen content enhances the chlorophyll content and leading to increased NDVI values.…”

A New Method for Estimating Soil Fertility Using Extreme Gradient Boosting and a Backpropagation Neural Network

“…Thus, some scholars used vegetation spectra to assess soil fertility. However, these studies [10][11][12]51,52] lacked quantitative information on soil fertility and their reliability could not be verified by ground-truth data. In this study, we selected five soil fertility indicators (pH, SOM, TN, AP, and AK) based on previous studies [5,53] and calculated the SFI using a fuzzy approach.…”

“…Current studies that used crop spectral indices to estimate soil fertility [10][11][12]51,52] focused primarily on indices in the vis-NIR spectral range and did not consider other spectral indices (e.g., red-edge bands). References [54,55] showed that red-edge bands provided abundant information not contained in the red, green, and short-wave infrared bands.…”

“…The crop spectral index-based method evaluates the correlation between spectral vegetation indices and soil fertility. Zeeshan et al [10] found that a higher normalized difference vegetation index (NDVI) value corresponds to better soil fertility. Wang et al [11] set thresholds for the NDVI based on cotton growth and performed density partitioning to obtain information on different levels of soil fertility in cotton fields.…”