Application of Remotely Sensed Imagery and Socioeconomic Surveys to Map Crop Choices in the Bekaa Valley (Lebanon)

Abstract

Based on remotely sensed imagery and socioeconomic data, this research analyzes the reasons why farmers choose one crop over another in the Bekaa Valley in Lebanon. This study mapped the area of the cultivated crop in 2017 with Sentinel-2 images. An accurate and new method was developed to extract the field boundaries from the evolution of the normalized difference vegetation index (NDVI) profile throughout the season. We collected 386 GPS locations for fields that are used for crop cultivation, from which the NDVI profile was extracted. The 386 reference fields were separated into two groups: reference locations and test locations. The Euclidean distance (ED) was calculated between these two groups, and the classification was strongly correlated to the known crop type in the field (overall accuracy: 90%). Our study area cultivated wheat (32%), spring potatoes (25%), spring vegetables (27%), orchards (11%), vineyards (7%), and alfalfa (<1%). Socioeconomic surveys showed that farmers favored these crops over others on account of their profitability. Nonetheless, the surveys highlighted a paradox: despite the lack of a political frame for agriculture in Lebanon, farmers’ crop choices strongly depend on a few existing policies.