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Toprak nemi tahmini için Radarsat-2 verisinden çoklu saçılma katsayılarının elde edilmesi

Obtaining multiple scattering coefficients from Radarsat-2 data for soil moisture estimation

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Abstract (2. Language): 
The control of agricultural areas with the aid of remote sensing techniques and GPS technology yields better results with less cost and time when compared to standard soil measurements. In this study, it is aimed to extract multiple scattering coefficients from Radarsat-2 data in order to establish an association between remote sensing techniques and soil characteristics (soil moisture, dielectric coefficient, etc.). Different regions of the electromagnetic spectrum are being studied for the purpose of estimating soil moisture with remote sensing data. Because microwave sensors are sensitive to changes in soil moisture content, it is more appropriate to use these sensors in soil moisture estimation Therefore; synthetic aperture radar (SAR) sensor operating in the microwave range of the electromagnetic spectrum is capable of producing appropriate images with high resolution for agricultural purpose soil monitoring. Moreover, it is used for agricultural monitoring, plant growth, yield, mapping and estimation of soil moisture (Tehrani 2014). Among the different types of remote sensing sensors, SAR sensors (Radarsat-1, Envisat-Asar, Radarsat-2, and ERS-1/2) have a great potential in basin-scale soil moisture estimates (Moran ve ark. 2004). In addition, with polarimetric SAR, much better information can be obtained than with single band SAR. Furthermore, polarimetric SAR can provide more information with multiple polarizations (hh, hv, vh, vv) and penetrate into canopy where plant cover is dominant. For this reason, polarimetric SAR data gives a good result in estimating soil moisture on bare soil and vegetated areas. The experiments were carried out on agricultural sites in the Dicle University campus and calculation of scattering coefficients from the RadarSat-2 data consisted of several steps. At the first stage, a Radarsat-2 data was obtained from densely vegetated study area on April 8, 2015 and simultaneous local measurements were made on this area. In the second stage, various pre-processing steps (calibration, filtering, and terrain correction) have been employed to remove disorders from the Radarsat-2 data and the terrain correction process has been provided for fitting the terrain onto a real map coordinate system. At the other stage, the GPS coordinates of the points at which each ground moisture measurement was taken, were transferred to Rdarsat-2 data. In the last stage, a standard SAR backscattering technique was applied to the Radarsat-2 data of April 8, 2015 in order to calculate multiple scattering coefficients over the study areas dominated by dense vegetation cover. Then, four different backscattering parameters (σhh, σhv, σvh, σvv) were calculated from the parcels corresponding to each ground measurement point. Finally, these operations were repeated for 285 measurement points obtained on April 8, 2015 and a data matrix of 285x4 lengths was generated to evaluate the effect of vegetation cover. Furthermore, the statistical measurements of multi scattering coefficients were computed from this data matrix.
Abstract (Original Language): 
Uzaktan algılama teknikleri ile tarımsal alanların kontrolü, GPS (Küresel Konumlama Sistemi) teknolojisiyle beraber kullanıldığında, standart toprak ölçümlerine nazaran daha az bir maliyet ve zamanla, daha iyi sonuçlar vermektedir. Bu çalışmada, uzaktan algılama teknikleri ile toprak karakteristikleri (toprak nemi, dielektrik katsayısı gibi) arasında bir ilişkinin kurulabilmesi için Radarsat–2 verisinden çoklu saçılma katsayılarının çıkarılması amaçlanmıştır. Çalışma, Dicle havzasında yer alan Dicle Üniversitesi kampüsündeki tarımsal alanlar üzerinde gerçekleştirilmiş ve Radarsat–2 verisinden saçılma katsayılarının hesaplanması işlemi, birkaç aşamadan oluşmuştur. İlk aşamada, uydunun bölgeden geçiş dönemi dikkate alınarak yoğun vejetasyonlu tarımsal arazilerden 8 Nisan 2015 tarihinde bir Radarsat–2 verisi elde edilmiş ve bu araziler üzerinde eş zamanlı olarak yersel ölçümler yapılmıştır. İkinci aşamada, Radarsat–2 verilerinin bozukluklardan arındırılması için çeşitli ön işlemler uygulanmış ve arazilerin gerçek bir harita koordinat sistemi üzerine oturtulması için de arazi düzeltme işlemi sağlanmıştır. Daha sonra her bir yersel toprak nem ölçümünün alındığı noktaların GPS koordinatları bu veriye aktarılmıştır. Son aşamada ise yoğun bitki örtüsünün hâkim olduğu çalışma alanlarına ait çoklu saçılma katsayılarını hesaplamak için önişlemi tamamlanmış 8 Nisan 2015 tarihli Radarsat–2 verisine standart sar geri saçılma tekniği uygulanmış ve her bir ölçüm noktasına karşılık gelen parsellerden dört adet sigma geri saçılma parametresi (σhh, σhv, σvh, σvv) hesaplanmıştır. Ardından, bu katsayılar bütün ölçüm noktaları için hesaplanarak bu döneme ait bir veri matrisi oluşturulmuştur.

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