Analyzing Temporal Characteristics of Winter Catch Crops Using Sentinel-1 Time Series DOI Creative Commons
Shanmugapriya Selvaraj, Damian Bargiel, Abdelaziz Htitiou

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(19), P. 3737 - 3737

Published: Oct. 8, 2024

Catch crops are intermediate sown between two main crop cycles. Their adoption into the cropping system has increased considerably in last years due to its numerous benefits, particular potential carbon fixation and preventing nitrogen leaching during winter. The growth period of catch Germany is often marked by dense cloud cover, which limits land surface monitoring through optical remote sensing. In such conditions, synthetic aperture radar (SAR) emerges as a viable option. Despite known advantages SAR, understanding temporal behavior parameters relation remains largely unexplored. Hence, this study, we exploited time series Sentinel-1 data within Copernicus Space Component study characteristics over test site center Germany. Radar VV, VH, VH/VV backscatter, dpRVI (dual-pol Vegetation Index) VV coherence were extracted, profiles interpreted for preceding along with situ, temperature, precipitation data. Additionally, examined winter (winter oilseed rape cereals), that grown parallel growing cycle. Based on analyzed patterns, defined 22 descriptive features from dpRVI, specific identification. Then, conducted Kruskal–Wallis extracted parameters, both crop-wise group-wise, assess significance statistical differences among different groups. Our results reveal there exists unique pattern compared crops, each these possess sensitivity crops. Parameters VH sensitive phenological stages structure. On other hand, found be highly biomass. Coherence can used detect sowing harvest events. analysis reveals wheat barley dominant before Moreover, rape, cereals) cultivated cycle distinguished exploiting observed window differences. provide information about sowing, harvest, vigor, biomass, early/late die-off nature types. test, high H-statistic low p-value several predictors indicates significant variability at 0.001 level. Furthermore, Dunn’s post hoc group pairs highlights substantial cold-sensitive legume groups (p < 0.001).

Language: Английский

Analyzing Temporal Characteristics of Winter Catch Crops Using Sentinel-1 Time Series DOI Creative Commons
Shanmugapriya Selvaraj, Damian Bargiel, Abdelaziz Htitiou

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(19), P. 3737 - 3737

Published: Oct. 8, 2024

Catch crops are intermediate sown between two main crop cycles. Their adoption into the cropping system has increased considerably in last years due to its numerous benefits, particular potential carbon fixation and preventing nitrogen leaching during winter. The growth period of catch Germany is often marked by dense cloud cover, which limits land surface monitoring through optical remote sensing. In such conditions, synthetic aperture radar (SAR) emerges as a viable option. Despite known advantages SAR, understanding temporal behavior parameters relation remains largely unexplored. Hence, this study, we exploited time series Sentinel-1 data within Copernicus Space Component study characteristics over test site center Germany. Radar VV, VH, VH/VV backscatter, dpRVI (dual-pol Vegetation Index) VV coherence were extracted, profiles interpreted for preceding along with situ, temperature, precipitation data. Additionally, examined winter (winter oilseed rape cereals), that grown parallel growing cycle. Based on analyzed patterns, defined 22 descriptive features from dpRVI, specific identification. Then, conducted Kruskal–Wallis extracted parameters, both crop-wise group-wise, assess significance statistical differences among different groups. Our results reveal there exists unique pattern compared crops, each these possess sensitivity crops. Parameters VH sensitive phenological stages structure. On other hand, found be highly biomass. Coherence can used detect sowing harvest events. analysis reveals wheat barley dominant before Moreover, rape, cereals) cultivated cycle distinguished exploiting observed window differences. provide information about sowing, harvest, vigor, biomass, early/late die-off nature types. test, high H-statistic low p-value several predictors indicates significant variability at 0.001 level. Furthermore, Dunn’s post hoc group pairs highlights substantial cold-sensitive legume groups (p < 0.001).

Language: Английский

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