Cropping pattern classification using artificial neural networks and evapotranspiration estimation in the Eastern Mediterranean region of Turkey

Abstract

Determination of cropping pattern is a very important factor in quantifying irrigation water requirements at a catchment scale. In this regard, remote sensing is a robust tool for generating spatial-temporal variation of crops. This study focuses on crop classification by using remotely sensed data coupled with ground truth data. Therefore, this study aimed at both classifying each crop type and calculating crop evapotranspiration (ETc) based on reference evapotranspiration (ETo) by using the Penman-Monteith evapotranspiration model and crop coefficient (Kc). ETo was estimated by using data from two meteorological stations located in the study area. To this end, this study was conducted in Akarsu Irrigation District (≈95 km2), a sub-catchment in the Lower Seyhan Plain (LSP), in the 2021 hydrological year. Ground truth data were collected in the two growing seasons. The ENVI program was used to classify crop types from Sentinel 2A-2B satellite images with 10-m by 10-m spatial resolution. Image analysis results demonstrated that bare soil and citrus made up more than half of the area in the winter season, while corn and citrus were preponderant in summer. In addition, the total reference evapotranspiration and crop evapotranspiration were about 1308 mm and 890 mm, respectively in the 2021 water year. ETc values for second crop soybean, first crop corn, wheat, and citrus showed agreement with previous studies of direct methods of evapotranspiration in the Cukurova region. Furthermore, research findings led us to conclude that using remotely sensed satellite data in cropping pattern determination is promising in identifying the crops grown in large agricultural lands. Moreover, remote sensing images can be used to classify accurately crops in the winter and summer seasons, and this study has expanded the application value of remotely sensed data in large-scale irrigation schemes.

Developing a New ANN Model to Estimate Daily Actual Evapotranspiration Using Limited Climatic Data and Remote Sensing Techniques for Sustainable Water Management

“…the winter season, i.e., in December, January, and February [5,7]. As reported by Cetin et al [7], due to meteorological and geographical factors, the definition of the water year, i.e., hydrological year, varies from region to region.…”

“…The research area that has gained popularity under the name Akarsu Irrigation District (hereafter, AID, A = 9495 ha ≈ 95 km 2 , Figure 1) in the studies carried out so far is located in the Lower Seyhan Plain (LSP) in the southeastern part of the Mediterranean region of Turkiye. The LSP shows typical characteristics of a deltaic plain with a rather flat topography (a slope of 1% or less) and a large-scale irrigation and drainage network [5,7]. The Mediterranean climate, characterized by warm and rainy in the winter season, whereas dry and hot in the summer season, prevails utterly in the LSP and, in turn, in the study area.…”

“…The Mediterranean climate, characterized by warm and rainy in the winter season, whereas dry and hot in the summer season, prevails utterly in the LSP and, in turn, in the study area. The average annual precipitation of the basin is approximately 650 mm [5]. In the LSP of Turkiye, there is a very remarkable difference in temperature and evaporation values in the irrigation season, i.e., in July and August in particular, compared to those in the winter season, i.e., in December, January, and February [5,7].…”

“…The average annual precipitation of the basin is approximately 650 mm [5]. In the LSP of Turkiye, there is a very remarkable difference in temperature and evaporation values in the irrigation season, i.e., in July and August in particular, compared to those in the winter season, i.e., in December, January, and February [5,7]. As reported by Cetin et al [7], due to meteorological and geographical factors, the definition of the water year, i.e., hydrological year, varies from region to region.…”

“…Nevertheless, it is not an easy task to acquire a representative ETa value for it can be determined directly using either a lysimeter or water-balance work/approach which are rather labor-intensive, time-consuming, and very expensive, thereby threatening the sustainability of freshwater resources. As stated clearly by Allen et al [2], Rawat et al [3], Gharbia et al [4], and Alsenjar et al [5], among others, ETa describes the physical processes of the amount of water that can occur either through evaporation or transpiration according to climatic conditions, crop types, and soil status. Since direct methods of ETa calculation focus only on one point or parcel, they have limitations in showing the variation in ETa spatially and temporally at a large scale [6], particularly in areas with large irrigation schemes of >100,000 ha as in Turkiye.…”