Application of Drone and WorldView-4 Satellite Data in Mapping and Monitoring Grazing Land Cover and Pasture Quality: Pre- and Post-Flooding

Akumu, Clement E.; Amadi, Eze O.; Dennis, Sam

doi:10.3390/land10030321

Cited by 13 publications

(2 citation statements)

References 31 publications

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“…Each of these platforms may be fitted with multiple EO sensor payloads [6,7], with advantages and disadvantages in terms of spatial, radiometric, and temporal coverage and performance. As such, a combination of data sources may be capable of enhancing the quality and type of remote sensing products that can be produced [8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

The Ground to Space CALibration Experiment (G-SCALE): Simultaneous Validation of UAV, Airborne, and Satellite Imagers for Earth Observation Using Specular Targets

Russell¹,

Soffer

Ientilucci

et al. 2023

Remote Sensing

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The objective of the Ground to Space CALibration Experiment (G-SCALE) is to demonstrate the use of convex mirrors as a radiometric and spatial calibration and validation technology for Earth Observation assets, operating at multiple altitudes and spatial scales. Specifically, point sources with NIST-traceable absolute radiance signal are evaluated for simultaneous vicarious calibration of multi- and hyperspectral sensors in the VNIR/SWIR range, aboard Unmanned Aerial Vehicles (UAVs), manned aircraft, and satellite platforms. We introduce the experimental process, field site, instrumentation, and preliminary results of the G-SCALE, providing context for forthcoming papers that will detail the results of intercomparison between sensor technologies and remote sensing applications utilizing the mirror-based calibration approach, which is scalable across a wide range of pixel sizes with appropriate facilities. The experiment was carried out at the Rochester Institute of Technology’s Tait Preserve in Penfield, NY, USA on 23 July 2021. The G-SCALE represents a unique, international collaboration between commercial, academic, and government entities for the purpose of evaluating a novel method to improve vicarious calibration and validation for Earth Observation.

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Section: Introductionmentioning

confidence: 99%

The Ground to Space CALibration Experiment (G-SCALE): Simultaneous Validation of UAV, Airborne, and Satellite Imagers for Earth Observation Using Specular Targets

Russell¹,

Soffer

Ientilucci

et al. 2023

Remote Sensing

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show abstract

“…Recent studies applied UAVs in assessing forest condition, 19 , 32 – 34 precision agriculture, 21 , 23 , 24 , 35 and mapping, modeling, and monitoring landslides 36 – 43 Several approaches have been employed to calibrate satellite imagery with UAV multispectral data and field radiometric measurements.…”

Section: Introductionmentioning

confidence: 99%

Bias correction of Sentinel-2 with unmanned aerial vehicle multispectral data for use in monitoring walnut fruit forest in western Tien Shan, Kyrgyzstan

Isaev

Kulikov

Shibkov

et al. 2022

J. Appl. Rem. Sens.

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The scope of our work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from Western Tian Shan for monitoring applications in walnut fruit forests. Because acquiring field data on walnut fruit forests is difficult due to access limitations in the Tian Shan, remote sensing offers a unique opportunity to increase spatial and temporal coverage of ecological parameters. Sentinel-2 satellites launched in 2015 have been providing images at spatial resolutions of 10 to 20 m; however, difficulties remain as information retrieved from Sentinel pixels result from a mixture of objects that affect reflectance signals. We used submeter multispectral UAV images to assess the sensitivity of Sentinel-2 normalized difference vegetation index (NDVI) to subpixel vegetation. Results showed that Sentinel-2 data overestimates NDVI in regions with open terrain and grass, and underestimates NDVI in areas with trees. By implementing a bias correction method, the accuracy of the Sentinel-2 derived NDVI increased; R 2 values increased from 0.59 to 0.88 (p value < 0.001). We also showed that drought index derived from Sentinel-2 vegetation condition index (VCI) is well correlated with the ground-based standard precipitation index (SPI). Using this bias correction method, on average the correlation increased by 3% between VCI and SPI.

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Pre-flood and Post-flood Classification of Landsat 8 OLI Images of Florida in USA with Low Time Complexity

Rai,

Mandal,

Singh

2023

J Indian Soc Remote Sens

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Application of Drone and WorldView-4 Satellite Data in Mapping and Monitoring Grazing Land Cover and Pasture Quality: Pre- and Post-Flooding

Cited by 13 publications

References 31 publications

The Ground to Space CALibration Experiment (G-SCALE): Simultaneous Validation of UAV, Airborne, and Satellite Imagers for Earth Observation Using Specular Targets

The Ground to Space CALibration Experiment (G-SCALE): Simultaneous Validation of UAV, Airborne, and Satellite Imagers for Earth Observation Using Specular Targets

Bias correction of Sentinel-2 with unmanned aerial vehicle multispectral data for use in monitoring walnut fruit forest in western Tien Shan, Kyrgyzstan

Pre-flood and Post-flood Classification of Landsat 8 OLI Images of Florida in USA with Low Time Complexity

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