Dual-polarimetric descriptors from Sentinel-1 GRD SAR data for crop growth assessment

Accurate and high-resolution spatio-temporal information about crop phenology obtained from Synthetic Aperture Radar (SAR) data is an essential component for crop management and yield estimation at a local scale. Crop growth monitoring studies seldom exploit complete polarimetric information contained in dual-pol GRD SAR data. In this study, we propose three polarimetric descriptors: the pseudo scattering-type parameter (θc), the pseudo scattering entropy parameter (Hc), and the co-pol purity parameter (mc) from dual-pol S1 GRD SAR data. We also introduce a novel unsupervised clustering framework using Hc and θc with six clustering zones to represent various scattering mechanisms. We implemented the proposed algorithm on the cloud-based Google Earth Engine (GEE) platform for Sentinel-1 SAR data. We have shown the sensitivity of these descriptors over a time series of data for wheat and canola crops at a test site in Canada. From the leaf development stage to the flowering stage for both crops, the pseudo scattering-type parameter θc changes by approximately 17°. Moreover, within the entire phenology window, both mc and Hc varies by about 0.6. The effectiveness of θc and Hc to cluster the phenological stages for the two crops is also evident from the clustering plot. During the leaf development stage, about 90 % of the sampling points were clustered into the low to medium entropy scattering zone for both the crops. Throughout the flowering stage, the entire cluster shifted into the high entropy vegetation scattering zone. Finally, during the ripening stage, the clusters of sample points were split between the high entropy vegetation scattering zone and the high entropy distributed scattering zone, with > 55 % of the sampling points in the high entropy distributed scattering zone. This innovative clustering framework will facilitate<br>the operational use of S1 GRD SAR data for agricultural applications.<div><b><br></b></div><div>This article is submitted to ISPRS Journal of Photogrammetry and Remote Sensing<br><br></div>

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Novel Clustering Schemes for Full and Compact Polarimetric SAR Data: A Case Study for Rice Phenology Characterization

10.36227/techrxiv.12793796.v1 ◽

2020 ◽

Author(s):

Subhadip Dey ◽

Avik Bhattacharya ◽

Debanshu Ratha ◽

Dipankar Mandal ◽

Heather McNairn ◽

...

Keyword(s):

Morphological Characteristics ◽

Temporal Analysis ◽

Crop Growth ◽

Unsupervised Clustering ◽

Degree Of Polarization ◽

Growth Stages ◽

Phenological Stages ◽

Sar Images ◽

Sar Data ◽

Type Parameter

Information on rice phenological stages from Synthetic Aperture Radar (SAR)images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Among the existing unsupervised clustering techniques using full-polarimetric (FP) SAR images, the eigenvalue-eigenvector based roll-invariant scattering-type parameter, and the scattering entropy parameter are widely used in the literature. In this study, we utilize a unique target scattering-type parameter, which jointly uses the Barakat degree of polarization and the elements of the polarimetric coherency matrix. In particular, the degree of polarization attributes to scattering randomness from a target. The scattering randomness in crops increases with advancements in its growth stages due to the development of branches and foliage. Hence, the degree of polarization varies with changes in the crop growth stages. Besides, the elements of the coherency matrices are directly related to the crop geometry as well as soil and crop water content. There-fore, this complementarity information captures the scattering randomness at each crop growth stage while taking into account diverse crop morphological characteristics. Likewise, we also utilize an equivalent parameter proposed for compact-polarimetric (CP) SAR data. These scattering-type parameters are analogous to the Cloude-Pottier’s parameter for FP SAR data and the ellipticity parameter for CP SAR data. Besides this, we also introduce new clustering schemes for both FP and CP SAR data for segmenting diverse scattering mechanisms across the phenological stages of rice. In this study, we use the RADARSAT-2 FP and simulated CP SAR data acquired over the Indian test site of Vijayawada under the Joint Experiment for Crop Assessment and Monitoring (JECAM) initiative. The temporal analysis of the scattering-type parameters and the new clustering schemes help us to investigate detailed scattering characteristics from rice across its phenological stages.<div>(Submitted to ISPRS journal)</div>

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Dual polarimetric radar vegetation index for crop growth monitoring using sentinel-1 SAR data

Remote Sensing of Environment ◽

10.1016/j.rse.2020.111954 ◽

2020 ◽

Vol 247 ◽

pp. 111954 ◽

Cited By ~ 2

Author(s):

Dipankar Mandal ◽

Vineet Kumar ◽

Debanshu Ratha ◽

Subhadip Dey ◽

Avik Bhattacharya ◽

...

Keyword(s):

Vegetation Index ◽

Crop Growth ◽

Growth Monitoring ◽

Polarimetric Radar ◽

Sar Data

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Dual-polarimetric descriptors from Sentinel-1 GRD SAR data for crop growth assessment

ISPRS Journal of Photogrammetry and Remote Sensing ◽

10.1016/j.isprsjprs.2021.05.013 ◽

2021 ◽

Vol 178 ◽

pp. 20-35

Author(s):

Narayanarao Bhogapurapu ◽

Subhadip Dey ◽

Avik Bhattacharya ◽

Dipankar Mandal ◽

Juan M. Lopez-Sanchez ◽

...

Keyword(s):

Crop Growth ◽

Sar Data ◽

Growth Assessment

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A survey of high resolution image processing techniques for cereal crop growth monitoring

Information Processing in Agriculture ◽

10.1016/j.inpa.2021.02.005 ◽

2021 ◽

Author(s):

Sanaz Rasti ◽

Chris J. Bleakley ◽

N.M. Holden ◽

Rebecca Whetton ◽

David Langton ◽

...

Keyword(s):

Image Processing ◽

High Resolution ◽

Crop Growth ◽

Growth Monitoring ◽

Cereal Crop ◽

Image Processing Techniques ◽

Resolution Image ◽

High Resolution Image ◽

Processing Techniques

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Assessing water-limited crop production with a scatterometer based crop growth monitoring system

IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120) ◽

10.1109/igarss.2000.857316 ◽

2002 ◽

Cited By ~ 1

Author(s):

W. Wagner ◽

K. Scipal ◽

H. Boogard ◽

K. van Diepen ◽

R. Beck ◽

...

Keyword(s):

Monitoring System ◽

Crop Production ◽

Crop Growth ◽

Growth Monitoring

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KONDISI WISATA MANGROVE DI DESA PASAR BANGGI, KABUPATEN REMBANG Mangrove Tourism Conditions in Pasar Banggi Village, Rembang Regency

Management of Aquatic Resources Journal (MAQUARES) ◽

10.14710/marj.v8i3.24259 ◽

2019 ◽

Vol 8 (3) ◽

pp. 221-225

Author(s):

Danang Adi Saputro ◽

Frida Purwanti ◽

Siti Rudiyanti

Keyword(s):

Species Composition ◽

Mangrove Forest ◽

Mangrove Ecosystem ◽

Google Earth ◽

Survey Method ◽

Systematic Sampling ◽

Sampling Techniques ◽

Mangrove Species ◽

Sampling Points ◽

Exploratory Survey

ABSTRAK Mangrove merupakan tumbuhan yang hidup di daerah pasang surut sebagai ekosistem interface antara daratan dengan lautan. Ekosistem mangrove di desa Pasar Banggi Kabupaten Rembang merupakan perpaduan antara mangrove alami dan hasil rehabilitasi. Tujuan penelitian ini untuk mengetahui kondisi mangrove di Desa Pasar Banggi, Rembang dilihat dari komposisi jenis, kerapatan dan ketebalan mangrove serta menganalisis tingkat kesesuaian wisata mangrove di Desa Pasar Banggi, Rembang. Metode yang digunakan adalah metode survey lapangan yang bersifat eksploratif, dimana teknis pengumpulan data menggunakan sistematik sampling. Data yang diambil meliputi 5 variabel yaitu: jenis, kerapatan mangrove dan asosiasi biota (hasil pengamatan lapangan dan perbandingan dari penelitian terdahulu), ketebalan (citra Google Earth Oktober 2016), pasang surut (data BMKG Oktober 2016). Pengambilan sampel dilakukan pada 3 stasiun, dimana setiap stasiun terdapat 3 titik sampling. Komposisi jenis mangrove di desa Pasar Banggi terdapat 3 jenis mangrove yaitu Rhizopora stylosa, R. mucronata, dan R. Apiculata, dengan kerapatan mangrove tertinggi yaitu 62 ind/100m2 dan ketebalan mangrove tertinggi sepanjang 139 m. Kondisi hutan mangrove desa Pasar Banggi termasuk dalam kategori sesuai (S2) untuk kegiatan wisata berkelanjutan di Kabupaten Rembang. ABSTRACT Mangroves are plants that grow in a tidal areas an interface ecosystems between terrestrial and marine. Mangrove ecosystem in the Pasar Banggi Village, Rembang Regency is a combination results of natural mangrove and rehabilitation. The purpose of this study were to determine condition of mangroves in the Pasar Banggi Village, Rembang, seen from the species composition, density and thickness of mangroves and to analyze the suitability level of mangrove tourism in the Pasar Banggi Village, Rembang. The method used in this study was an exploratory survey method, data collected using systematic sampling techniques. Mangrove tourism data collection was carried out of 5 variables, i.e.: type of mangrove, density of mangroves and associations of biota (from observations and comparisons of previous studies), thickness (Google Earth image October 2016), tides (data BMKG October 2016). Sampling was conducted at 3 stations, each station has 3 sampling points. The composition of mangrove species in Pasar Banggi village consists of 3 types of mangroves, namely Rhizopora stylosa, R. mucronata, and R. Apiculata, with the highest density of mangrove 62 ind / 100m2 and the highest thickness of mangrove along 139 m. The condition of mangrove forest in the Pasar Banggi village was included in the appropriate category (S2) for sustainable tourism activities in the Rembang Regency.

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