Abstract
Saffron (Crocus sativus L.) is the most expensive spice worldwide and is predominantly produced in the Khorasan Province situated in north-east Iran. Climatic shifts and lowering groundwater tables negatively affect saffron yields in this region, which are determined by environmental factors, agronomical practices, and crop age. Nonetheless, spatially explicit information on changes in saffron cultivation is scarce, underlining a need for better monitoring tools. This study aims to evaluate the utility of Sentinel-2 (S2) time series in accurately mapping saffron fields and their ages (i.e., how many years saffron was cultivated in a field), based on its unique phenology. To separate saffron from other land covers, we first derived 252 spectral-temporal features by calculating 21 spectral features (10 individual bands plus 11 vegetation indices) for each of the 12 months. A Random Forest (RF) algorithm was then used in combination with field data to retain only features of high importance for saffron classification. These features comprised vegetation indices that incorporated spectral information from red, and near- and shortwave infrared bands during the phenological phases of the rapid green-up (February to March) and the dormant period (August to October). The RF classifier resulted in a saffron map for the year 2019 with a high classification accuracy based on these features. Compared against an independent in-situ saffron field dataset, 87.6% of the existing fields were correctly classified as saffron. To assess saffron field ages, we analysed the spectral separability of different age groups using the NDVI time series. We found that NDVI levels between December and May allowed for effectively separating 1st, 2nd, 3rd, 4th-6th, and 7th-8th year saffron fields. An RF-based classification of field ages resulted in an overall accuracy of 86.8%. This study demonstrated that S2 time series data allow for accurately mapping saffron fields and their age groups. Our findings provide a solid basis for mapping saffron across larger areas and for monitoring changes in saffron distribution. Such information is crucial for understanding how anthropogenic and climate change impacts will affect the future of saffron cultivation.
Highlights
Saffron (Crocus sativus L.) is an autumnal-flowering perennial geophyte whose dried scarlet stigmas are known as the costliest spice and have been dubbed “the red gold” (Basker & Negbi, 1983; Negbi, 1999; Winterhalter & Steaubinger, 2000; Fernandez, 2004)
This study demonstrated that S2 time series allowed for accurately mapping saffron cultivation areas and field age
Using the Random Forest (RF) classifier, we first selected an optimal set of spectral-temporal features for discriminating saffron from other crops
Summary
Saffron (Crocus sativus L.) is an autumnal-flowering perennial geophyte whose dried scarlet stigmas are known as the costliest spice and have been dubbed “the red gold” (Basker & Negbi, 1983; Negbi, 1999; Winterhalter & Steaubinger, 2000; Fernandez, 2004). The main reason for saffron’s high price is its low productivity per hectare and the intensive labour demand for cultivation, harvesting, and processing (Kumar et al, 2009; Ghorbani & Koocheki, 2017). Owing to its edible and medicinal value, consumer interest in saffron has increased globally, resulting in increased global demand (Abdullaev & Frenkel, 1999; Kumar et al, 2009). Iran is the dominant producer of saffron products worldwide, ac counting for more than 90% of the world’s saffron exports and 60% of the global saffron cultivation area (Ghorbani, 2007). The saffron crop adapts well to the hot arid climatic conditions in Iran. The saffron daughter corms can survive inside the soil during the hot summer due to their heat-tolerant characteristics and require a period of cold (
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