Pamuk Bitkisi Üretim Alanı Ortam Nem ve Sıcaklık Değerlerinin, SAR ve Optik Uydu Görüntüleri ile Tahmin Edebilirliğinin Araştırılması

Year 2023, Volume: 13 Issue: 3, 2217 - 2228, 01.09.2023

Serkan Kılıçaslan , Remzi Ekinci , Mehmet Cengiz Arslanoglu

https://doi.org/10.21597/jist.1265099

Cited By: 1

Abstract

Mardin İli Artuklu ve Kızıltepe İlçelerine bağlı 8 adet köy ve 27 adet pamuk parselinde yürütülen çalışmada, arazilerde ortam nem ve sıcaklık değerleri, 6 saat aralıklar ile datalogger cihazları ile ölçülmüş ve kayıt altına alınmıştır. Data loggerlardan elde edilen veriler, Google Earth Engine (GEE) ortamında hazırlanan Sentinel-1 ve Landsat-8 uydu verileriyle analiz edilerek aralarındaki ilişki irdelenmiştir. Ortam nemi (ON) değerleri ile VV (R2=0.63), VV-VH (R2=0.68), Toprak Nem İndeksi (SMI) (R2=0.84) arasında yüksek ilişki saptanırken, VH (R2=0.05), LEE_VH (R2=0.07), LEE_VV (R2=0.56), GAMMA_VH (R2=0.09), GAMMA_VV (R2=0.50), MALIK_VH (R2=0.07), MALIK_VV (R2=0.57) ve Arazi Yüzey Sıcaklığı (LST) (R2=0.35) arasında düşük ilişki saptanmıştır. Ortam sıcaklığı (OS) değerleri ile LST (R2=0.80**) arasında yüksek ilişki saptanırken, VV (R2=0.51), VH (R2=0.06), VV-VH (R2=0.49), LEE_VH (R2=0.09), LEE_VV (R2=0.49), GAMMA_VH (R2=0.11, GAMMA_VV (R2=0.08), MALIK_VH (R2=0.08), MALIK_VV (R2=0.49) ve SMI (R2=0.50) arasında düşük ilişki saptanmıştır. Geniş ölçekli arazi çalışmalarında ortam nemi değerlerinin tahmin edilmesinde VV, VV-VH ve SMI indisi; ortam sıcaklığı değerlerinin tahmin edilmesinde LST bandı yüksek doğruluk ile kullanılabileceği sonucuna varıldığından tavsiye edilmiştir.

Keywords

Pamuk, Sıcaklık, Nem, SAR, Google Earth Engine

Supporting Institution

Dicle Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi

Project Number

FBE.21.009

Thanks

Bu çalışma, Serkan KILIÇASLAN tarafından Dicle Üniversitesi Fen Bilimleri Enstitüsü Tarla Bitkileri ana bilim dalında yürütülen “Pamukta (G. hirsutum L.) Bitki-Su İlişkisinin Saptanmasında Uydu Görüntülerinin Kullanma Olanaklarının Araştırılması” başlıklı Doktora tez çalışmasından üretilmiş olup, Dicle Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi tarafından FBE.21.009 nolu proje numarası ile desteklenmiştir. Bilimsel Araştırma Koordinasyon Birimi’ne desteğinden ötürü teşekkür ederiz.

Investigation of Predictability of Cotton Plant Production Area Ambient Humidity and Temperature Values with SAR and Optical Satellite Images

Abstract

In the study carried out in 8 villages and 27 cotton parcels of Mardin Province Artuklu and Kızıltepe Districts, ambient humidity and temperature values in the field were measured and recorded with data logger devices at 6-hour intervals. The data obtained from the data loggers were analyzed with the Sentinel-1 and Landsat-8 satellite data prepared in the Google Earth Engine (GEE) environment and the relationship between them was examined. While a high correlation was found between ambient humidity (ON) values and VV (R2=0.63), VV-VH (R2=0.68), Soil Moisture Index (SMI) (R2=0.84), low correlation was found between VV (R2=0.51), VH (R2=0.06), VV-VH (R2=0.49), LEE_VH (R2=0.09), LEE_VV (R2=0.49), GAMMA_VH (R2=0.11, GAMMA_VV (R2=0.08), MALIK_VH (R2=0.08), MALIK_VV (R2=0.49), SMI (R2=0.50). A high correlation was found between ambient temperature (OS) values and Land Surface Temperature (LST) (R2=0.80**). However, a low correlation was found between ambient temperature (OS) and VV (R2=0.51), VH (R2=0.06), VV-VH (R2=0.49), LEE_VH (R2=0.09), LEE_VV (R2=0.49), GAMMA_VH (R2=0.11, GAMMA_VV (R2=0.08), MALIK_VH (R2=0.08), MALIK_VV (R2=0.49), SMI (R2=0.50). In large-scale field studies; VV, VV-VH and SMI index in estimating ambient humidity values; as it was concluded that the LST band can be used with high accuracy in estimating ambient temperature values, it has been recommended.

Keywords

Cotton, Temperature, Moisture, SAR, Google Earth Engine

Project Number

FBE.21.009

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