Spatial distribution of inter- and intra-crop variability using time-weighted dynamic time warping analysis from Sentinel-1 datasets

Moharana, Shreedevi and K B V N, Phanindra and Chintala, Syam and et al, . (2021) Spatial distribution of inter- and intra-crop variability using time-weighted dynamic time warping analysis from Sentinel-1 datasets. Remote Sensing Applications: Society and Environment, 24. ISSN 2352-9385

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This study investigates the robustness of an advanced classification algorithm to spatially map heterogeneous, fragmented croplands using multi-temporal synthetic aperture radar (SAR) datasets. Four parameters derived from Sentinel-1 (backscatters in dual-polarization: σVHo, σVVo, cross-ratio ([Formula presented]), and radar vegetation index (RVI)) were considered to develop temporal patterns and correlate with un-classified time-series satellite imagery using time-weighted dynamic time warping (TWDTW) algorithm. Pixel and parcel based classifications were considered to identify four crop varieties (paddy, sugarcane, cotton and vegetables) subjected to two water limiting conditions (low stress-LS, high stress-HS). In-situ data were split-sampled (30:70 ratio) between training (to develop temporal patterns) and testing (to validate classification output). Overall accuracy of pixel and parcel based classifications were 63% and 76% with a Kappa coefficient of 0.58 and 0.73 respectively. In conclusion, parcel based TWDTW algorithm conditioned by temporal signatures of RVI has effectively delineated croplands with varying irrigation treatments for yield and damage assessment modeling studies. © 2021

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Item Type: Article
Additional Information: The first and corresponding author acknowledges Science and Engineering Research Board (SERB) , Government of India for the financial support provided through National Post-Doctoral Fellowship (NPDF, Award No: NPDF/2018/003745 ). Authors acknowledge the project staff Mr. G. Rajender and Mr. B. Yadagiri, for their support in data collection and thanks to Amrit for his support.
Uncontrolled Keywords: Fragmented lands; Pixel and parcel classification; Sentinel-1; Temporal patterns; TWDTW
Subjects: Civil Engineering
Divisions: Department of Civil Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 30 Sep 2022 10:51
Last Modified: 30 Sep 2022 10:51
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