Relating landscape characteristics to non-point source pollution in mine waste-located watersheds using geospatial techniques

Xiao, Huaguo; Ji, Wei

doi:10.1016/j.jenvman.2005.12.009

Cited by 128 publications

(68 citation statements)

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“…Some use bivariate correlation to measure the direction and strength of the impact of each land use type [37,42,49]. Another group uses simple linear regression models so that the impact of each type on temperature can be quantified individually [80][81][82]. Others take best subset regressions that selectively incorporate land use types into the regression model to obtain the best fitted curve [26,38,47,74].…”

Section: Discussionmentioning

confidence: 99%

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

Kim¹,

Kim²

2017

Sustainability

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Abstract:There is a growing interest in understanding how the built environment affects temperature in cities. This study explores the impact of land use on temperature and how it varies by season and time of day in Seoul, South Korea. Unlike other studies that rely on extracted data from remotely sensed information, this study uses land use data from local GIS and near-ground temperature data from a network of state-run weather stations. To deal with multicollinearity among the land use variables, partial least squares regression models were used for analysis. Results suggest that residential and commercial uses and roads increase the temperature while open spaces decrease it. In detail, central commercial use, high-density residential use, and roads were influential heaters, while greenery was an influential cooler throughout the year. This study suggests the need for place-based planning and design solutions that help build climate resilience of cities.

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Section: Discussionmentioning

confidence: 99%

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

Kim¹,

Kim²

2017

Sustainability

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“…At the present time, remote sensing is also becoming an important tool for analysis of land-cover changes in an area with large surface mines, because ecological disasters caused by pollution by heavy metals are affecting our living environment [8]. Thus, vegetation mapping and classification is used to enable prediction of potential pollution sources.…”

Section: Introductionmentioning

confidence: 99%

Changes in Croplands as a Result of Large Scale Mining and the Associated Impact on Food Security Studied Using Time-Series Landsat Images

Matějı́ček

Kopačková

2010

Remote Sensing

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Geographic information systems and satellite remote sensing information are emerging technologies in land-cover change assessment. They now provide an opportunity to gain insights into land-cover change properties through the spatio-temporal data capture over several decades. The time series of Landsat images covering the 1985-2009 period is used here to explore the impacts of surface mining and reclamation, which constitute a dominant force in land-cover changes in the northwestern regions of the Czech Republic. Advanced quantification of the extent of mining activities is important for assessing how these land-cover changes affect ecosystem services such as croplands. The images employed from 1985, 1988, 1990, 2000, 2002, 2003, 2004, 2005, 2006, 2007, 2008, and 2009 ). Thus, the approximate land-cover stability of the 3,280 km 2 strip during the whole 1985-2009 period is used to explore land-cover disturbances in the local areas of surface mines. In the case of NDVI, it also includes variations, presumably caused by seasonal vegetation effects, and local meteorological conditions. However, the main trends related to mining activities during the long-term period can be clearly understood. As a OPEN ACCESSRemote Sensing 2010, 2 1464 result, other objectives can be explored in the 1985-2009 period, such as cropland changes to other land use classes, changes of cropland patterns, and their impacts on food security. The presented spatio-temporal modeling based on long time series from 12 satellite images provides considerable experience for processing NDVI in the framework of identification of land-cover classes and also, to a certain degree, cropland variability with its impact on food security.

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“…Therefore, Therefore, it is very important to explore the relationship between land use/cover types and water quality for development and management of the basin. (Uuemaa et al, 2005;Xiao et al, 2007;Wan et al, 2014). At present, numerous scholars have extensively applied statistical methods to indicate mutual relation between land use/cover change and water quality in various research zones (Céréghino et al,2009;Bierman et al,2011;Huang et al,2013b).…”

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confidence: 99%

Recognition of spatial framework for water quality and its relation with land use/cover types from a new perspective: A case study of Jinghe Oasis in Xinjiang, China

Zhang

Wang

2017

Preprint

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Quality evaluation for surface water is an important issue in water resource management and protection. To understand the relation between the spatial framework of water quality in Jinghe Oasis and the change in land use/cover type, we first divide 47 water sampling sites measured in May and October 2015 into 6 cluster layers using the self-organizing map (SOM) method based on non-hierarchical k-means classification, and then determine the distribution characteristics of water quality from the time sequence. Water quality indices include chemical oxygen demand (COD), biological oxygen demand (BOD), suspended solids (SS), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH 3 −N), chromaticity (SD), and turbidity (NUT). On the basis of the results, we collect data regarding changes in farmland land, forest-grass land, water body, salinized land, and other land types during the wet and dry seasons and combine these data with the classification results of the GF-1 remote sensing satellite obtained in May and October 2015. We then discuss the influences of land use/cover type on water quality at different layers and seasons. The results indicate that Clusters 1 to 3 provide monitoring samples for the wet season (May 2015), whereas Clusters 4 to 6 provide monitoring samples for the dry season (October 2015). In general, the COD, SS, NUT, TN, and NH 3 −N contents are high in Clusters 1and 2. The SD values for Clusters 1, 4, and 6 are high. Moreover, high BOD and TP values are mainly concentrated in Clusters 4 and 6. Through the discussion on the relation between different layers of water quality and land use/cover type change, we determine that the influences of farmland land, forest-grassland, and salinized land are significant on the water quality parameters in Jinghe Oasis. In Clusters 1, 2, and 6, the size of the water area also influences the change in water quality parameters to a certain extent. In addition, the influences of various land use/cover types on the water quality parameters in the research zone during different seasons exhibit the following order: farmland land → forest-grass land → salinized land → water body → others.Moreover, influence is less during the wet season than during the dry season. In conclusion, developing research on the relation between the spatial framework of water quality in Jinghe Oasis and land use/cover type change will be significant for the time sequence distribution of water quality in arid regions from both theoretical and practical perspectives.Key words: SOM; Water quality spatial distribution; Land use/cover; Correlation analysis; GIS IntroductionWater quality is of great importance to the study of water resources in arid regions. Accurate information on the spatial distribution of surface water quality is imperative for assessment of environmental monitoring, land surface water management as well as watershed changes (NRC, 2008;Sun et al., 2012). Land use/cover change in drainage basins significantly influences water quality in rivers, lakes, rive...

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Relating landscape characteristics to non-point source pollution in mine waste-located watersheds using geospatial techniques

Cited by 128 publications

References 13 publications

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

The Seasonal and Diurnal Influence of Surrounding Land Use on Temperature: Findings from Seoul, South Korea

Changes in Croplands as a Result of Large Scale Mining and the Associated Impact on Food Security Studied Using Time-Series Landsat Images

Recognition of spatial framework for water quality and its relation with land use/cover types from a new perspective: A case study of Jinghe Oasis in Xinjiang, China

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