Abstract
Abstract. Turkey has favorable agricultural conditions (i.e. fertile soils, climate and rainfall) and can grow almost any type of crop in many regions, making it one of the leading sectors of the economy. For sustainable agriculture management, all factors affecting the agricultural products should be analyzed on a spatial-temporal basis. Therefore, nowadays space technologies such as remote sensing are important tools in providing an accurate mapping of the agricultural fields with timely monitoring and higher repetition frequency and accuracy. In this study, object based classification method was applied to 2017 Sentinel 2 Level 2A satellite image in order to map crop types in the Adana, Çukurova region in Turkey. Support Vector Machine (SVM) was used as a classifier. Texture information were incorporated to spectral wavebands of Sentinel-2 image, to increase the classification accuracy. In this context, all of the textural features of Gray-Level Co-occurrence Matrix (GLCM) were tested and Entropy, Standard deviation, and Mean textural features were found to be the most suitable among them. Multi-spectral and textural features were used as an input separately and/or in combination to evaluate the potential of texture in differentiating crop types and the accuracy of output thematic maps. As a result, with the addition of textural features, it was observed that the Overall Accuracy and Kappa coefficient increased by 7% and 8%, respectively.
Highlights
Monitoring cropland has a profound impact on environmental planning, food security, and crop yield estimation
Multispectral and textural features were used as an input separately and/or in combination to evaluate the potential of texture in differentiating crop types and the accuracy of output thematic maps
Image classifications made with spectral bands only and spectral bands together with 3 textural features were compared to evaluate the effect of texture on classification accuracy
Summary
Monitoring cropland has a profound impact on environmental planning, food security, and crop yield estimation. According to the estimates of the United Nations, the world population has reached approximately 7.7 billion (United Nations, 2019). Due to the growing population, the need for agricultural production, which is the main component of the food supply, has become very important in the last few decades. Favorable climate, and rainfall conditions allow almost all types of crop products to be grown in many parts of Turkey, the total agricultural cultivated area is about 23 million ha in 2019 according to the Turkish Statistical Institute (TURKSTAT, 2020). Remote sensing technology that maximizes the use of cultivated areas fosters the development of sustainable agriculture and helps farmers better manage resources such as water, pesticides, and fertilizers. Satellite images are considered a potentially important tool for studying vegetation from local to global
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