A knowledge-based approach to mapping degraded meadows on the Qinghai–Tibet Plateau, China

Gao, Jay; Li, X. L.

doi:10.1080/01431161.2017.1348642

Cited by 5 publications

(7 citation statements)

References 13 publications

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“…Results showed that overall accuracy was over 80%, with user's accuracy (complement of commission error) for the 'Significant decrease' and 'Potential decrease' classes being 75% and 74.8% while producer's accuracy (complement of omission error) being 70% and 50.3%. These accuracy measure are commensurate with previous studies on mapping land surface changes over small areas using moderate to high-spatial resolution satellite data (Dimobe et al 2015;Gao and Li 2017;Lu et al 2007;Vågen et al 2016;Žížala et al 2017). There are differences between our produced map (30-m vegetation cover changes) and the validation data (1km buffers with both soil and vegetation condition changes), and while we recognize that uncertainties may exist in our accuracy assessment, these field observations are the best on offer validation data available.…”

Section: Using Vegetation Cover Change Mapping As a Start For Land Condition And Degradation Assessmentsupporting

confidence: 84%

Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

Xie

Phinn

Game

et al. 2019

Remote Sensing of Environment

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Globally, the area of agricultural land is shrinking in part due to environmental degradation.Acquisition and restoration of degraded lands no longer used for agriculture may present a major conservation opportunity with minimal social and political opposition. The ability to efficiently and accurately identify these lands from regional to global scales will aid conservation management, ultimately enhancing the global prospects of achieving the Sustainable Development Goals (SDGs). Remote Sensing provides a potential tool to identify areas where surface property changes can be mapped and linked with land degradation. In this study, we begin to tackle a small section of this challenge by presenting novel approach to mapping changes in vegetation cover amounts at the pixel level (30m), using Google Earth Engine (GEE). We illustrate our approach across large-scale rangelands in Queensland Australia, using three decades of Landsat satellite imagery along with field observations of land condition scores for validation. The approach used an existing method for dynamic reference cover to remove the rainfall variability and focused on the human management effects on the vegetation cover changes.Results showed the identified vegetation cover changes could be categorized into five classes of decrease, increase or stable cover compared with a set reference level, which was obtained from locations of the most persistent ground cover across all dry years. In total, vegetation cover decrease was observed in 20% of our study area, with similar portion of lands recovering and the rest (~ 60%) staying stable. The lands with decrease in vegetation cover, covering a considerable area of ~ 2 × 10 5 km 2 , exhibited a markedly reduced resilience to droughts. The accuracy assessment yielded an overall classification accuracy of 82.6% (± 3.32 standard error) with 75.0% (±5.16%) and 70.0% (±4.13%) producer's and user's accuracy for areas experiencing a significant decrease in vegetation cover, respectively.Identifying areas of degraded land will require multiple stages of spatial data analysis and this work provided the first stage for identifying vegetation cover changes in large-scale rangeland environment, and provides a platform for future research and development to identify degraded lands and their utility for achieving conservation endeavours.

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Section: Using Vegetation Cover Change Mapping As a Start For Land Condition And Degradation Assessmentsupporting

confidence: 84%

Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

Xie

Phinn

Game

et al. 2019

Remote Sensing of Environment

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“…The quantity of vegetative cover on the ground is commonly measured using normalized difference vegetation index (NDVI) that had a theoretical range of 0–255 after the NDVI image was saved in 8 bits. The exact NDVI ranges adopted are 108–122 for severe, 122–135 for moderate, and 135–140 for slight degradation (Gao & Li, ). The remotely sensed results were verified in a post‐classification trip in August 2016 to the area.…”

Section: Methodsmentioning

confidence: 99%

“…The recoded NDVI layers of degraded meadows were then vectorized and intersected with the on‐screen digitized channel layer from the color composite (Figure ) that had been buffered at a width of 60 m using ‘erase.’ This processing essentially removed all those mapped heitutan within a distance of 60 m from a channel from the output (Gao & Li, ). The same routine of processing was applied to all three images with the same parameters so that the results were highly consistent and comparable to one another.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, meadow degradation has been extensively studied, including quantitative assessment of degradation classifications (Li et al, ), comparison of soil seed bank in a degraded alpine meadow with that of an enclosed meadow (Ma, Zhou, Lü, & Du, ), and plant diversity of degraded alpine meadows (Wang, Long, Wang, Jing, & Shi, ). In addition, the spatial distribution of degraded meadows has been mapped automatically from satellite images (An, Xu, Li, & Liang, ; Gao & Li, ). Landsat Thematic Mapper (TM) imagery has proved adequate in mapping degraded meadows (Zhu, Chao, Yang, & Zhang, ).…”

Section: Introductionmentioning

confidence: 99%

“…So far nobody has systematically studied the topographic properties of degraded meadows in relation to those of the general terrain, even though topographic properties have been explored in relation to the local distribution of woodland and steppe communities (Liu, Cui, Pott, & Speier, ), landslide types and slope stability (Gao & Maro, ; Zhang et al, ), and vegetation changes on the Loess Plateau of West China (Zhang, Zhang, Zhang, Zhao, & Liu, ). On the other hand, topography plays a critical role in meadow degradation in that it affects the (re)distribution of moisture and energy over the landscape, both of which are crucial to the healthy functioning of alpine meadows (Gao & Li, ). In fact, elevation is synonymous with accessibility in the plateau setting.…”

Section: Introductionmentioning

confidence: 99%

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A topographic perspective on the distribution of degraded meadows and their changes on the Qinghai‐Tibet Plateau, West China

Gao

Zhang

2018

Land Degrad Dev

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Meadow degradation is a serious environmental and ecological problem on the Qinghai‐Tibet Plateau. A topographic perspective on the changes in the severity of meadow degradation can yield vital information on the effectiveness of rehabilitative measures and efforts. This study aims to reveal the topographic properties of degraded meadows in relation to those of the general terrain in the Qingzhen Township of southern Qinghai Province of China comparatively. After degraded meadows were mapped at 3 levels of severity from satellite images recorded in 1995, 2001, and 2015, the topographic features of degraded meadows, intact meadows, and the changes between them were explored in a geographic information system. It is found that degraded meadows increased by 528.07 ha (15.21%) during 1995–2001, but lost 1,495.67 ha (37.40%) during 2001–2015. The most and the least severely degraded meadows experienced a loss whereas moderately degraded meadows increased, with most changes taking place between adjoining levels of severity. Topographically, the changes in degradation severity bear a consistent relationship with elevation and slope gradient in that more severely degraded meadows are located at a lower elevation of a gentler slope. The changes from degraded to intact meadows take place at a lower elevation on a gentler slope, an outcome likely attributable to the rehabilitative efforts.

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Effects of degradation severity on the physical, chemical and mechanical properties of topsoil in alpine meadow on the Qinghai-Tibet Plateau, west China

Chen

et al. 2020

CATENA

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A knowledge-based approach to mapping degraded meadows on the Qinghai–Tibet Plateau, China

Cited by 5 publications

References 13 publications

Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands - A first step towards identifying degraded lands for conservation

A topographic perspective on the distribution of degraded meadows and their changes on the Qinghai‐Tibet Plateau, West China

Effects of degradation severity on the physical, chemical and mechanical properties of topsoil in alpine meadow on the Qinghai-Tibet Plateau, west China

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