A method for field inspection of natural resource surveys using UAV-based geographic information video technology

doi:10.6046/zrzyyg.2023259

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Abstract

Field verification of natural resources is a vital part of natural resource surveys. To address issues such as low efficiency and security risks encountered in traditional field verification methods, this study developed an application scheme for field verification utilizing UAV-based geographic information video technology. First, this study examined the characteristics of UAV-based geographic information video technology. Based on these characteristics, as well as the requirements of field verification, the features for the field verification were categorized into two types: land use classification and measurement assessment. Subsequently, the UAV-based geographic information video acquisition was designed for each type. The collected videos were then combined with a geographic information system (GIS) platform for feature evaluation and measurement. The application scheme was tested based on production practices. The test results indicate that the proposed scheme can improve the efficiency of the field inspection, with the measurement accuracy meeting the demand for actual production needs. Furthermore, the scheme can overcome the limitations of ground-based photography and reduce safety risks.

Keywords UAV field verification natural resource surveys geographic information video

ZTFLH:

TP79

Issue Date: 17 February 2025

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	Articles by authors

	Yunkai WANG
	Anmin LI
	Nan LIN
	Yijie CAO

Cite this article:

Yunkai WANG,Anmin LI,Nan LIN, et al. A method for field inspection of natural resource surveys using UAV-based geographic information video technology[J]. Remote Sensing for Natural Resources, 2025, 37(1): 76-81.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2023259 OR https://www.gtzyyg.com/EN/Y2025/V37/I1/76

Fig.1 The general guidelines

Fig.2 Illustration of the UAV integration relationship

Fig.3 Flight route

Tab.1 Comparison of the results of patch classification judgment

Fig.4 Screenshots of UAV geographic information video

Fig.5 Comparison of image spot segmentation results

Tab.2 Statistical table of point position accuracy comparison

Tab.3 Statistical table of area accuracy comparison

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