Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index

Yu, Xiaojing; Her, Younggu; Zhu, Xujun; Lu, Chunxia; Li, Xuefei

doi:10.3390/su13095274

Cited by 2 publications

(2 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Recently, remote sensing images have been used increasingly to support land use analysis and research [16][17][18]. Satellite data like Landsat, Sentinel images can be used free of charge to support land use mapping and cultivated land monitoring [19][20][21][22][23][24]. Traditional methods for extracting ground objects mainly consider the gray value of pixels; however, this does not adequately use information about the image space and texture and may result in a low classification accuracy [25].…”

Section: Introductionmentioning

confidence: 99%

Dynamics of Land and Water Resources and Utilization of Cultivated Land in the Yellow River Beach Area of China

Run

Qin

et al. 2022

Water

View full text Add to dashboard Cite

Image analysis of the Yellow River beach area since 1987 provided land use and water body patterns to support effective agricultural and environmental management. Landsat and Sentinel-2A/B images, and data from the Third National Land Survey, were used to examine the water body and land use patterns. The continuous beach land since 1987 was calculated from annual vegetation and water body indexes while that of cultivated land was extracted from the Third National Land Survey. Object-Oriented Feature Extraction was used to extract staple crops. The results showed that 58.26% of the beach area was cultivated land. Continuous beach land covered an area of 1630.98 km2 and was consisted of scattered patches that were unevenly distributed between the north and south banks of the Yellow River. The staple crop types in the beach area, winter wheat and summer corn accounted for 72.37% and 68.03% of the total cultivated land. Affected by the strategy on the Yellow River basin in China, as the ecological space and protection continue to increase, this study provides basic scientific references for the correct use of cultivated land resources and protection of the balance of soil and water resources dynamic utilization and balance of cultivated land protection and ecological protection.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamics of Land and Water Resources and Utilization of Cultivated Land in the Yellow River Beach Area of China

Run

Qin

et al. 2022

Water

View full text Add to dashboard Cite

show abstract

“…However, such methods are difficult to apply for Landsat data because of the low observation frequency of this satellite system. Computationally intensive methods, based on modelling of the annual dynamics of field's reflectance, are required to implement "MODIS-like" processing scheme on Landsat imagery [26,27].…”

Section: Introductionmentioning

confidence: 99%

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

et al. 2022

View full text Add to dashboard Cite

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels.

show abstract

Multi-Temporal Arable Land Monitoring in Arid Region of Northwest China Using a New Extraction Index

Cited by 2 publications

References 35 publications

Dynamics of Land and Water Resources and Utilization of Cultivated Land in the Yellow River Beach Area of China

Dynamics of Land and Water Resources and Utilization of Cultivated Land in the Yellow River Beach Area of China

Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

Contact Info

Product

Resources

About