Spatial Variability of Soil Salinity and its Influence on Rice Yield in Salt-Affected Areas using Remote Sensing Techniques

• Published in: International Journal of Environmental and Rural Development Vol. 12; no. 1; pp. 29 - 34
• Main Authors: OO, AUNG NAING, THET, LWIN BO BO
• Format: Journal Article
• Language: English
• Published: Institute of Environmental Rehabilitation and Conservation, Research Center 2022
• Subjects: salinity stress; Sentinel-2 satellite imagery; vegetation index
• ISSN: 2185-159X; 2433-3700
• DOI: 10.32115/ijerd.12.1_29

Soil salinity has become one of the major constraints to sustain crop production in Myanmar, especially in the dry zone areas. Salinity stress and its spatial distribution has been a useful for crop monitoring. Unevenness in early crop growth stage can support to identify yield- limiting factors such as soil salinity, nutrient availability, and soil moisture. Remote sensing techniques have been used to collect reflectance numbers from crop canopies and to analyze the vegetative index (VI). VI has been related with percentage of ground cover, chlorophyll content of plant, and nitrogen use efficiency. This study aims to monitor the influence of salinity stress on the growth, yield and chlorophyll content of rice by using remote sensing techniques. This study was conducted in the salt-affected soils at Myittha Township, the central dry zone of Myanmar during the rainy season of 2019. Electrical conductivity (EC) and chlorophyll content in rice plant were collected at early growth and tillering stages of rice. Sentinel-2 satellite imagery was used in the analysis for those two growth stages. Total grain yield of rice was also measured. The acquired images analysis was implemented with ArcGIS 10.7 software to calculate vegetative indices. The results showed that significant relationships were found between plant chlorophyll content and the normalized difference vegetation index (NDVI) values under different salinity levels. A relationship was also observed between NDVI and rice grain yield. Identifying the spatial distribution of salinity stress using the spectral vegetation indices would be effective for increasing rice yield in the salt-affected areas.