Corn Monitoring and Crop Yield Using Optical and Microwave Remote Sensing

Soria-Ruiz, Jesús; Fernandez-Ordonez, Yolanda M.; McNairn, Heather

doi:10.5772/8311

Cited by 24 publications

(18 citation statements)

References 18 publications

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“…During this phase, vegetation scattering will increase in an approximately linear fashion in relation to VWC (Dobson and Ulaby, 1986) and plant density where a wet canopy may increase the C band scattering by as much as 3 dB (Brown et al, 2003). For broad leaf crops, backscatter increases with VWC which eventually results in signal saturation at both C and L bands, whereas small leaf and grain crops have a dynamic backscatter relationship throughout their growth cycle allowing for differentiation of a soil signal (Paloscia, 2002;Soria-Ruiz et al, 2009). In contrast to grain crops, tree canopies tend to backscatter the majority of the radar signal from the crown (Dobson et al, 1992).…”

Section: Reference Contributionmentioning

confidence: 97%

Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications

Kornelsen

Coulibaly

2013

Journal of Hydrology

258

131

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Section: Reference Contributionmentioning

confidence: 97%

Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications

Kornelsen

Coulibaly

2013

Journal of Hydrology

258

131

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“…Current SAR systems have become increasingly a beneficial source to help agriculture monitoring (Soria-Ruiz et al, 2009, Canisius et al, 2017.…”

Section: Introductionmentioning

confidence: 99%

Backscatter Analysis Using Multi-Temporal Sentinel-1 Sar Data for Crop Growth of Maize in Konya Basin, Turkey

Abdikan

Şekertekin

Ustunern

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Temporal monitoring of crop types is essential for the sustainable management of agricultural activities on both national and global levels. As a practical and efficient tool, remote sensing is widely used in such applications. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to investigate the performance of the sensor backscatter image on crop monitoring. Multi-temporal C-band VV and VH polarized SAR images were acquired simultaneously by in-situ measurements which was conducted at Konya basin, central Anatolia Turkey. During the measurements, plant height of maize plant was collected and relationship between backscatter values and plant height was analysed. The maize growth development was described under Biologische Bundesanstalt, bundessortenamt und CHemische industrie (BBCH). Under BBCH stages, the test site was classified as leaf development, stem elongation, heading and flowering in general. The correlation coefficient values indicated high correlation for both polarimetry during the early stages of the plant, while late stages indicated lower values in both polarimetry. As a last step, multi-temporal coverage of crop fields was analysed to map seasonal land use. To this aim, object based image classification was applied following image segmentation. About 80% accuracies of land use maps were created in this experiment. As preliminary results, it is concluded that Sentinel-1 data provides beneficial information about plant growth. Dual-polarized Sentinel-1 data has high potential for multi-temporal analyses for agriculture monitoring and reliable mapping.

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“…Thus, backscatter intensities are expected to be higher for yam fields than rice. Additionally, previous studies that used SAR data for crop mapping have distinguished between "broad leafed" and "fine/narrow leaf" crops and noted the usefulness of radar data in differentiating them based on their canopy architecture [24,25]. Broad-leaved crops have higher backscatter intensity than fine-leaved crops, due to a high absorption of the radar signal in the latter [75].…”

Section: Contribution Of Tsx Data To Crop Mappingmentioning

confidence: 99%

“…Thus, in vegetation studies, radar backscatter intensities will differ based on the size, shape and orientation of the canopy components (e.g., leaves, stalks, fruit, etc.). Crops with different canopy architecture and cropping characteristics (e.g., planting in mounds) can be distinguished based on their backscatter intensities [23][24][25]. The recent introduction of dual and quad-polarization acquisition modes in many radar satellites (e.g., Radarsat-2, PALSAR, TerraSAR-X) further increases the information content in radar data.…”

Section: Introductionmentioning

confidence: 99%

Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa

et al. 2014

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Crop mapping in West Africa is challenging, due to the unavailability of adequate satellite images (as a result of excessive cloud cover), small agricultural fields and a heterogeneous landscape. To address this challenge, we integrated high spatial resolution multi-temporal optical (RapidEye) and dual polarized (VV/VH) SAR (TerraSAR-X) data to map crops and crop groups in northwestern Benin using the random forest classification algorithm. The overall goal was to ascertain the contribution of the SAR data to crop mapping in the region. A per-pixel classification result was overlaid with vector field boundaries derived from image segmentation, and a crop type was determined for each field based on the modal class within the field. A per-field accuracy assessment was conducted by comparing the final classification result with reference data derived from a field campaign. Results indicate that the integration of RapidEye and TerraSAR-X data improved classification accuracy by 10%-15% over the use of RapidEye only. The VV polarization was found to better discriminate crop types than the VH polarization. The research has shown that if optical and SAR data are available for the whole cropping season, classification accuracies of up to 75% are achievable.

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Corn Monitoring and Crop Yield Using Optical and Microwave Remote Sensing

Cited by 24 publications

References 18 publications

Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications

Advances in soil moisture retrieval from synthetic aperture radar and hydrological applications

Backscatter Analysis Using Multi-Temporal Sentinel-1 Sar Data for Crop Growth of Maize in Konya Basin, Turkey

Integration of Optical and Synthetic Aperture Radar Imagery for Improving Crop Mapping in Northwestern Benin, West Africa

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