Accuracy Assessment of the Planar Morphology of Valley Bank Gullies Extracted with High Resolution Remote Sensing Imagery on the Loess Plateau, China

Yixian Chen, Juying Jiao, Yanhong Wei, Hengkang Zhao, Weijie Yu, Binting Cao, Haiyan Xu, Fangchen Yan, Duoyang Wu and Hang Li
Additional contact information
Yixian Chen: State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
Juying Jiao: State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
Yanhong Wei: State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
Hengkang Zhao: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Weijie Yu: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Binting Cao: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Haiyan Xu: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Fangchen Yan: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Duoyang Wu: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
Hang Li: Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China

IJERPH, 2019, vol. 16, issue 3, 1-19

Abstract: Gully erosion is a serious environmental problem worldwide, causing soil loss, land degradation, silting up of reservoirs and even catastrophic flooding. Mapping gully features from remote sensing imagery is crucial for assisting in understanding gully erosion mechanisms, predicting its development processes and assessing its environmental and socio-economic effects over large areas, especially under the increasing global climate extremes and intensive human activities. However, the potential of using increasingly available high-resolution remote sensing imagery to detect and delineate gullies has been less evaluated. Hence, 130 gullies occurred along a transect were selected from a typical watershed in the hilly and gully region of the Chinese Loess Plateau, and visually interpreted from a Pleiades-1B satellite image (panchromatic-sharpened image at 0.5 m resolution fused with 2.0 m multi-spectral bands). The interpreted gullies were compared with their measured data obtained in the field using a differential global positioning system (GPS). Results showed that gullies could generally be accurately interpreted from the image, with an average relative error of gully area and gully perimeter being 11.1% and 8.9%, respectively, and 74.2% and 82.3% of the relative errors for gully area and gully perimeter were within 15%. But involving field measurements of gullies in present imagery-based gully studies is still recommended. To judge whether gullies were mapped accurately further, a standard adopting one-pixel tolerance along the mapped gully edges was proposed and proved to be practical. Correlation analysis indicated that larger gullies could be interpreted more accurately but increasing gully shape complexity would decrease interpreting accuracy. Overall lower vegetation coverage in winter due to the withering and falling of vegetation rarely affected gully interpreting. Furthermore, gully detectability on remote sensing imagery in this region was lower than the other places of the world, due to the overall broken topography in the Loess Plateau, thus images with higher resolution than normally perceived are needed when mapping erosion features here. Taking these influencing factors (gully dimension and shape complexity, vegetation coverage, topography) into account will be favorable to select appropriate imagery and gullies (as study objects) in future imagery-based gully studies. Finally, two linear regression models were built to correct gully area ( A ip , m 2 ) and gully perimeter ( P ip , m) visually extracted, by connecting them with the measured area ( A ms , m 2 ) and perimeter ( P ms , m). The correction models were A m s = 1.021 A i p + 0.139 and P m s = 0.949 P i p + 0.722 , respectively. These models could be helpful for improving the accuracy of interpreting results, and further accurately estimating gully development and developing more effective automated gully extraction methods on the Loess Plateau of China.

Keywords: valley bank gully; Pleiades imagery; visual interpretation; accuracy assessing standard; gully detection limit; gully dimensions; vegetation cover; gully shape complexity; broken topography (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/16/3/369/pdf (application/pdf)
https://www.mdpi.com/1660-4601/16/3/369/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:16:y:2019:i:3:p:369-:d:201477

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().