AI Summary & Key Takeaways
AI InsightThe results hinted that the using medium and low resolution satellite imagery could improve the data collection and reporting from irrigated agriculture in developing countries.
📌 3 Key Takeaways
Abstract
Consistent and well-timed information regarding the extent of irrigated areas is very important for the development of the agricultural sector. This study investigated the reliability of traditional estimates of irrigated area coverages from three micro-dam irrigation schemes. High resolution Google Earth (GE) and medium resolution satellite imagery coupled with an intensive ground survey were employed to determine irrigation area coverages. Landsat-8 image pre-processing and classification was carried out in ENVI 5.0 software. In comparison to the Landsat-8 based estimates, the traditional method over-estimated 87% of the total 14 cases considered. The level of discrepancies in scheme area coverages range from a minimum of -20% (underestimated) to a maximum of 224%. Besides this, the traditional estimates were ranging from -1.8 to 238% of GE-based estimates. Whereas, the Landsat-8 based estimates slightly overestimated it by 1.8% -16% of GE-based estimates. On the other hand, the traditional estimates tend to underestimate/ignore crops with smaller area coverages and overestimate crops with relatively larger area coverages. The results hinted that the using medium and low resolution satellite imagery could improve the data collection and reporting from irrigated agriculture in developing countries.