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| Type: | Resource | |
| Storage: | The size of this resource is 848.7 MB | |
| Created: | Oct 27, 2021 at 10:11 a.m. | |
| Last updated: | Oct 27, 2021 at 3:04 p.m. | |
| Citation: | See how to cite this resource | |
| Content types: | Geographic Raster Content |
| Sharing Status: | Public |
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| Views: | 614 |
| Downloads: | 75 |
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Abstract
Abstract: Remote sensing methodologies could contribute to a more sustainable agriculture, such as monitoring soil preparation for cultivation, which should be done properly, according to the topographic characteristics and the crop’s nature. The objectives of this work are to (1) demonstrate the potential of unmanned aerial vehicle (UAV) technology in the acquisition of 3D data before and after soil tillage, for the quantification of mobilised soil volume; (2) propose a methodology that enables the co-registration of multi-temporal DTMs that were obtained from UAV surveys; and (3) show the relevance of quality control and positional accuracy assessment in processing and results. An unchanged-area-matching method based on multiple linear regression analysis was implemented to reduce the deviation between the Digital Terrain Models (DTMs) to calculate a more reliable mobilised soil volume. The production of DTMs followed the usual photogrammetric-based Structure from Motion (SfM) workflow; the extraction of fill and cut areas was made through raster spatial modelling and statistical tools to support the analysis. Results highlight that the quality of the differential DTM should be ensured for a reliable estimation of areas and mobilised soil volume. This study is a contribution to the use of multi-temporal DTMs produced from different UAV surveys. Furthermore, it demonstrates the potential of UAV data in the understanding of soil variability within precision agriculture.
Subject Keywords
Coverage
Spatial
Temporal
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Content
Data Services
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
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| Portuguese Foundation for Science and Technology (FCT) | PTDC/CTA-OHR/32360/2017 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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