Regional Crop Characterization Using Multi-Temporal Optical and Synthetic Aperture Radar Earth Observations Data

2022 ◽  
pp. 1-20
Author(s):  
Hazhir Bahrami ◽  
Saeid Homayouni ◽  
Heather McNairn ◽  
Mehdi Hosseini ◽  
Masoud Mahdianpari
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Earth Observations ◽  
Multi Temporal ◽  
Aperture Radar

scholarly journals Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

2021 ◽  
Vol 13 (4) ◽  
pp. 604
Author(s):  
Donato Amitrano ◽  
Gerardo Di Martino ◽  
Raffaella Guida ◽  
Pasquale Iervolino ◽  
Antonio Iodice ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Microwave Remote Sensing ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Special Focus ◽  
Arid Environments ◽  
Synthetic Aperture Radar Data ◽  
Multi Temporal ◽  
Aperture Radar

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special focus on topics like forestry, water resources management in semi-arid environments and floods. The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions for boosting their usage among end-users.

scholarly journals A COMBINATION OF NEIGHBORHOOD BASED RATIO OPERATOR AND CONVOLUTIONAL WAVELET NEURAL NETWORKS FOR CHANGE DETECTION IN MULTI-TEMPORAL SYNTHETIC APERTURE RADAR IMAGES

2021 ◽  
Vol 226 (06) ◽  
pp. 97-104
Author(s):  
Nguyễn Hùng An ◽  
Nguyễn Tiến Phát
Keyword(s):  
Neural Networks ◽  
Synthetic Aperture Radar ◽  
Change Detection ◽  
Synthetic Aperture ◽  
Wavelet Neural Networks ◽  
Radar Images ◽  
Multi Temporal ◽  
Aperture Radar

Phát hiện sự thay đổi trong ảnh SAR đa thời gian được ứng dụng rộng rãi trong các ứng dụng thực tế về hoạt động quản lý kiểm tra, giám sát tài nguyên trên đất liền và trên biển với quy mô rộng lớn. Có rất nhiều thuật toán phát hiện sự thay đổi sử dụng hai ảnh SAR đa thời gian. Nguyên tắc phổ biến của chúng là thực hiện phân tích ảnh sai khác được tạo ra từ toán tử tỷ số của hai ảnh SAR đa thời gian nhằm phát hiện các sự thay đổi giữa chúng. Để cải thiện độ chính xác phát hiện, toán tử tỷ số và các phiên bản cải tiến của toán tử này thường được sử dụng kết hợp với các phương pháp xử lý tinh hơn nữa. Bài báo này đề xuất một giải pháp phát hiện sự thay đổi bằng cách kết hợp toán tỷ số dựa trên  lân cận và thuật toán mạng nơ ron wavelet tích chập để cải thiện độ chính xác phát hiện  sự thay đổi trong ảnh SAR đa thời gian.

scholarly journals Evaluation of Coherent and Incoherent Landslide Detection Methods Based on Synthetic Aperture Radar for Rapid Response: A Case Study for the 2018 Hokkaido Landslides

2020 ◽  
Vol 12 (2) ◽  
pp. 265 ◽  
Author(s):  
Jungkyo Jung ◽  
Sang-Ho Yun
Keyword(s):  
Synthetic Aperture Radar ◽  
Urban Areas ◽  
Rapid Response ◽  
Synthetic Aperture ◽  
Detection Methods ◽  
Intensity Correlation ◽  
Low Coherence ◽  
Multi Temporal ◽  
Log Ratio ◽  
Aperture Radar

Damage mapping using Synthetic Aperture Radar (SAR) imagery has been studied in recent decades to support rapid response to natural disasters. Many researches have been developing coherent and incoherent change detection. However, their performances can vary depending on the types of the damages, the characteristics of the scatterers and the corresponding capability of algorithms. In particular, the coherence-based methods have been used as promising detectors over urban areas where high coherences are observed, but their detection accuracies still remain controversial over the area where low coherences are mainly observed such as the 2018 Hokkaido landslides. In order to understand the characteristics of landslide (damage) detectors for low-coherence areas and find an alternative and complementary method, we designed the coherence difference, coherence normalized difference, log-ratio, intensity correlation difference, and normalized differences of the intensity correlation assuming limited availability of dataset, and also developed multi-temporal algorithms using the coherence, intensity, and intensity correlation. They were tested and evaluated using multiple polygons extracted from aerial photos. We were able to observe that the multi-temporal intensity correlation method has the potential to detect the landslides over the low coherence region and all types of land uses.

scholarly journals Sensitivity Analysis of Multi-Temporal Sentinel-1 SAR Parameters to Crop Height and Canopy Coverage

2019 ◽  
Vol 9 (4) ◽  
pp. 655 ◽  
Author(s):  
Rouhollah Nasirzadehdizaji ◽  
Fusun Balik Sanli ◽  
Saygin Abdikan ◽  
Ziyadin Cakir ◽  
Aliihsan Sekertekin ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Early Stage ◽  
Strong Relationship ◽  
Synthetic Aperture ◽  
Crop Height ◽  
Canopy Coverage ◽  
Broad Leaf ◽  
Multi Temporal ◽  
Low Sensitivity ◽  
Aperture Radar

The Polarimetric Synthetic Aperture Radar technique has provided various opportunities and challenges in agricultural activities mainly on crop management. The aim of this study is to investigate the sensitivity of 10 parameters derived from multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) data, to crop height and canopy coverage (CC) of maize, sunflower, and wheat. The correlation coefficient values indicate a high correlation for maize during the early growing stage. The coefficient determinations (R2) of 0.82 and 0.81 indicate that there is a strong relationship between the maize height and SAR parameters including VV + VH and VV, respectively. The maize CC is well correlated with VV parameter (R2 = 0.73), but it is observed that at the later growing stage the correlation became weaker. This means that the sensitivity decreases with increasing vegetation cover growth. Compared to maize, the sensitivity of SAR parameters to wheat variables is often good at the early stage. However, the highest correlation with wheat height represented by Alpha (α) decomposition parameter (R2 = 0.67). The sunflower height has an insignificant correlation with the majority of SAR parameters and only VH polarization shows low sensitivity (R2 = 0.31). The sunflower CC shows relatively higher correlation with VV polarization (R2 = 0.46) at the early stage while no considerable correlation is observed at the later stage. It is found that Sentinel-1 has a high potential for estimation of crop height and CC of the maize as a broad-leaf crop. The same is not true for sunflower as another broad-leaf crop.

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