Mapping and Monitoring Surface Water and Wetlands with Synthetic Aperture Radar

2015 ◽  
pp. 138-155
Keyword(s):  
Surface Water ◽  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Aperture Radar

scholarly journals Semi-Automated Surface Water Detection with Synthetic Aperture Radar Data: A Wetland Case Study

2017 ◽  
Vol 9 (12) ◽  
pp. 1209 ◽  
Author(s):  
Amir Behnamian ◽  
Sarah Banks ◽  
Lori White ◽  
Brian Brisco ◽  
Koreen Millard ◽  
...  
Keyword(s):  
Surface Water ◽  
Synthetic Aperture Radar ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Data ◽  
Water Detection ◽  
Aperture Radar

scholarly journals DINAMIKA GENANGAN PESISIR JAKARTA BERDASARKAN DATA MULTI-TEMPORAL SATELIT MENGGUNAKAN INDEKS AIR DAN POLARISASI RADAR

2020 ◽  
Vol 12 (3) ◽  
pp. 885-901
Author(s):  
Asmadin Asmadin ◽  
Vincentius Paulus Siregar ◽  
Ibnu Sofian ◽  
Indra Jaya ◽  
Antonius Bambang Wijanarto
Keyword(s):  
Surface Water ◽  
Synthetic Aperture Radar ◽  
Baseline Data ◽  
Synthetic Aperture ◽  
Landsat 8 ◽  
Dynamic Surface ◽  
Water Index ◽  
Normalized Difference Water Index ◽  
Multi Temporal ◽  
Aperture Radar

Kombinasi baseline data pengindraan jauh sistem aktif dan pasif memiliki banyak keuntungan dalam pemantauan dinamika genangan pesisir. Kedua jenis sensor satelit mengatasi kesenjangan informasi genangan, terutama pada area yang ditutupi awan/bayangan. Tujuan utama penelitian ini adalah untuk mengkaji dinamika genangan di wilayah pesisir Jakarta berdasarkan data multi-temporal sensor optik dari Landsat 8 dan Synthetic Aperture Radar (SAR) Sentinel 1A. Metode penelitian ini menggunakan dua algoritma indeks air. Algoritma tersebut yaitu Modified Normalized Difference Water Index (MNDWI) dan Dynamic Surface Water Extent (DSWE) berdasarkan nilai spektral reflektansi dan formula empirik. Metode lainnya adalah menggunakan nilai rata-rata koefisien backscatter air dari analisis polarisasi tunggal Vertikal Vertikal (VV) dan Vertikal Horisontal (VH). Hasil studi menunjukkan bahwa penggunaan kedua tipe data satelit dengan baseline data 8, 9, 15 dan 16 hari cukup efektif memantau dinamika genangan selama 8-49 hari, termasuk area yang tertutup awan dan bayangan. Berdasarkan nilai threshold dari MNDWI >0,123 dan koefisien backscattering air -19dB cukup efisien digunakan untuk mengesktrak informasi data satelit. Algoritma empiris tersebut menghasilkan kenampakan genangan, terutama di sepanjang tanggul pantai, waduk, ekosistem mangrove dan lahan terbangun. Hasil pemantauan satelit menunjukkan bahwa puncak genangan terjadi pada 30 Mei 2016 dan masih terlihat pada 15 Juni 2016. Kombinasi metode pengindraan jauh tersebut cukup efektif dan efisien untuk memantau genangan secara dinamis.

scholarly journals Automated SAR Image Thresholds for Water Mask Production in Alberta’s Boreal Region

2020 ◽  
Vol 12 (14) ◽  
pp. 2223
Author(s):  
Craig Mahoney ◽  
Michael Merchant ◽  
Lyle Boychuk ◽  
Chris Hopkinson ◽  
Brian Brisco
Keyword(s):  
Surface Water ◽  
Synthetic Aperture Radar ◽  
Large Scale ◽  
Synthetic Aperture ◽  
Threshold Selection ◽  
Anthropogenic Pressures ◽  
Novel Method ◽  
Water Mapping ◽  
Sar Imagery ◽  
Aperture Radar

Mapping and monitoring surface water features is important for sustainably managing this critical natural resource that is in decline due to numerous natural and anthropogenic pressures. Satellite Synthetic Aperture Radar is a popular and inexpensive solution for such exercises over large scales through the application of thresholds to distinguish water from non-water. Despite improvements to threshold methods, threshold selection is traditionally manual, which introduces subjectivity and inconsistency over large scales. This study presents a novel method for objectively determining and applying a threshold to determine water masks from Synthetic Aperture Radar (SAR) imagery on a scene-by-scene basis. The method was applied to Radarsat-2 and simulated Radarsat Constellation Mission scenes, and validated against two independent validation sources with high accuracy (Kappa ranging from 0.85 to 0.93). Expectedly, greatest misclassification occurs near shorelines, which are often ecologically important zones. Comparisons between Radarsat-2 and Radarsat Constellation Mission thresholds and outputs suggest that the latter is a capable successor for surface water applications. This work represents a foundational step toward objectivity and consistency in large-scale water mapping and monitoring.

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