Landsat 8 Uydu Görüntü Uygulaması – Ürün Fenolojisinin Haritalanması İçin NDVI Zaman Serisi: Afganistan’ın Balkh ve Jawzjan Bölgeleri Örneği

Abstract

Bu makalede tarımsal ürünlerin yetiştirme sezonu boyunca nihai verimini etkileyen fenolojik dönemleri temsil edebilecek Landsat 8 görüntüsünden elde edilen normalize edilmiş vejetasyon indeksi (NDVI) değişiminin ortaya konulması hedeflenmiştir. Amerika Birleşik Devletleri Jeoloji Araştırmaları Kurumundan (USGS) elde edilen Landsat 16-gün 30 m çözünürlüklü NDVI zaman serileri verisi kullanılarak geniş coğrafi alanlar üzerindeki ürünlerin mevsimsel fenolojik değişimlerini haritalama amacıyla etkin bir metot geliştirilmiştir. Landsat 8 verilerinin işlenmesi için Google Earth Engine (GEE) platformu kullanılmıştır. Bulut örtüsüne ve bulut gölgelerine sahip alanlar maskelenmiş, verilerle doldurulmamış ve yansıma değerlerinin zaman serisine çift lojistik filtresi uyarlanmıştır. NDVI zaman serilerinden elde edilen fenolojik metrikler TIMESAT yazılımı ile elde edilmiştir. 2015 ve 2016 yılı yetiştirme sezonu için mevsimsel veriler sağlanmış ve çalışma alanı için fenoloji haritaları oluşturulmuştur.

Keywords

• NDVI,ürün fenolojisi,uzaktan algılama

Application of Landsat 8 Satellite Image – NDVI Time Series for Crop Phenology Mapping: Case Study Balkh and Jawzjan Regions of Afghanistan

Abstract

In this article, it was targeted to reveal the variations of NDVI which may represent the phenological stages of agricultural crops derived from Landsat 8 imagery from the start to end of growing seasons which eventually influence the final yields. An effective method was developed to map seasonal phenological variations of crops over large geographic regions using 16-day Landsat 30 m resolution NDVI time series data obtained from USGS. The Google Earth Engine (GEE) platform was used for processing the Landsat 8 data. The areas with cloud cover and cloud shadows were masked out, filled by no data and smoothing double logistic filter was fitted on the time series of the reflectance values. Phenological metrics extracted from the NDVI time series were obtained by the TIMESAT software. Seasonal data were extracted for growing seasons of the years of 2015 and 2016. The phenology maps were created for study area.

Keywords

• NDVI,crop phenology,remote sensing

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