Eco‐environmental evaluation with remote sensing in the middle and upper areas of the Yellow River drainage basin

Wang, X.; Ren, Ze; Tan, Kelong

doi:10.1080/01431160701241704

Cited by 12 publications

(4 citation statements)

References 4 publications

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“…Since 1855, the Yellow River changed the trajectory of its lower reaches into the Bohai Sea. Until now the entire drainage basin covers an area of more than 750,000 km 2 (Wang et al, 2007). In this paper, we selected Dongying city as the case study area to detect and monitor the dynamic change of YRD.…”

Section: Study Areamentioning

confidence: 99%

“…As previous studies reported, the annual average sediment discharge of Yellow River during 1950-1968 was 12.26×10 9 metric tons, then 8.34×10 9 t (1968-1985), 3.30×10 9 t from 1986 to 2002, and during 2001-2005, the sediment load was merely 1.51×10 9 t (Peng et al, 2010), one eighth of that during 1950-1968. The riverine sediment supply has been reduced, and global sea level is rising (Wonsuck, 2012), commonly leading to prominent physical, ecological and geomorphological effects on YRD (Wang et al, 2007). Whether the Yellow River is still building land becomes a topic of public concern.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic change of the Yellow River Delta Using Historical Data and Remote Sensing Imagery

Yu¹,

Zhao²,

Yan³

2015

Proceedings of the 4th International Conference on Information Technology and Management Innovation

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Historical data since 1855 and Landsat remote sensing images for the year 2006, 2009 and 2013 were selected as the main data sources and RS/GIS spatial analysis tools were combined to investigate the mouth channel change of Yellow River and monitor the dynamic change of Yellow River Delta. The results demonstrated that since the Yellow River changed its trajectory into Bohai Sea in 1855, its mouth channel migrated ten times and displayed various patterns; during 2006-2013, the area of Yellow River Delta was reduced by 18.54% (86.25 km 2 ). Considering land recession will bring about serious effects, decision makers shall implement effective policies in advance to combat various ramifications caused by land decreasing.

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Section: Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic change of the Yellow River Delta Using Historical Data and Remote Sensing Imagery

Yu¹,

Zhao²,

Yan³

2015

Proceedings of the 4th International Conference on Information Technology and Management Innovation

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“…They are also frequently used to map expansion of an urban boundary (Ji et al 2001); assess ecosystem services (Chen et al 2009, Nelson 2009, Tallis and Polasky 2009 and assist in the development, modification and monitoring of environmental planning and policy (Laba et al 1997, Xiuwan 2002, Hill and Smith 2005, Wang et al 2007. Depending on the application and research question(s), the range of thematic map complexity varies from the simplest binary classifications (e.g.…”

Section: Introductionmentioning

confidence: 99%

An edge-oriented approach to thematic map error assessment

Sweeney

2012

Geocarto International

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The objective of this analysis is to develop a method of classification error assessment that can contribute to techniques designed to evaluate change products with an emphasis on edge locations in landscapes. Reference land-cover data were developed within 10 randomly sampled regions across the study site, approximately 9 km 2 each. Sample pixels were partitioned and allocated among two domain categories, interior and edge. The assignment of pixels to domain categories was based on neighbourhood heterogeneity. Classification error was assessed within domain categories on a pixel-by-pixel basis, evaluating agreement between map values and majority land cover. To demonstrate the methodology, we present summary results for this technique applied to a land-cover classification of southcentral Indiana. Omission error was less than 8.3% within interior domains and from 25.8% to 36.4% in the edge. Commission error was below 26.7% within the interior domains and ranged from 13.9 to 74.6% in the edge domains.

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“…In order to explore the spatial heterogeneity of the ecological vulnerability of wetlands in the YRB, a study constructed a comprehensive evaluation system and model for the ecological vulnerability of coastal wetlands, and found that the ecological vulnerability of the YRB is generally at a medium level [ 10 ]. Other scholars comprehensively evaluated the environmental quality of the middle and upper reaches of the YRB, studied and analysed the environmental status and overall environmental quality of each ecosystem region, and summarized the distribution of the environmental quality in the three regions [ 11 ]. Based on a multidimensional perspective, scholars in related fields established a comprehensive evaluation indicator system for the evaluation of urban resilience in the Yellow River basin [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Evolution and Spatial Network Analysis of the Urban Ecological Carrying Capacity in the Yellow River Basin

Liu

Yang

Zhou

et al. 2021

IJERPH

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Based on the panel data of 82 cities in the Yellow River Basin (YRB) during 2008–2017, this paper calculated the urban ecological carrying capacity (UECC) index by means of the entropy method, drew a spatiotemporal evolution map using ArcGIS10.3 software, used a spatial cold–hot spot model to explore the spatial characteristics of the UECC index, and used the revised gravity model to construct the spatial network of the UECC. In addition, through social network analysis, we obtained the spatial network correlation characteristics of the UECC of 82 cities in the YRB. The study found the following: (1) The UECC index of the cities in the YRB increased steadily, and showed strong non-stationarity in space. The cold and hot spot patterns both changed greatly. Overall, the changes of the hot and cold spots were very significant. (2) The spatial correlation and linkage effects of the UECC in the YRB were not significant. The central cities with higher point centrality and closeness centrality showed the same spatial distribution, and most of them are located in the midstream and downstream of the YRB. The central cities in the midstream and downstream of the YRB had high betweenness centrality, and stood in the center of the association network. (3) The four plates in the spatial correlation network of the UECC in the YRB all showed their advantages and functions. The first plate was the net spillover plate, which was principally allocated in the upstream and midstream of the YRB. The second plate was the broker plate, which was principally located in the midstream and downstream of the YRB, and a few cities in the upper reaches. The third plate was the net inflow plate, which was distributed sporadically in the upstream and downstream of the YRB. The fourth plate was the broker plate, which was scattered in upstream, midstream, and downstream of the YRB. Therefore, it is necessary to shorten the gap of and promote the improvement of the UECC in the YRB.

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Eco‐environmental evaluation with remote sensing in the middle and upper areas of the Yellow River drainage basin

Cited by 12 publications

References 4 publications

Dynamic change of the Yellow River Delta Using Historical Data and Remote Sensing Imagery

Dynamic change of the Yellow River Delta Using Historical Data and Remote Sensing Imagery

An edge-oriented approach to thematic map error assessment

Spatiotemporal Evolution and Spatial Network Analysis of the Urban Ecological Carrying Capacity in the Yellow River Basin

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