Examining Land-Use/Land-Cover Change in the Lake Dianchi Watershed of the Yunnan-Guizhou Plateau of Southwest China with Remote Sensing and GIS Techniques: 1974–2008

Zhao, Yaolong; Zhang, Ke; Fu, Yingchun; Zhang, Hong

doi:10.3390/ijerph9113843

Cited by 54 publications

(24 citation statements)

References 60 publications

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“…Lake Dianchi (24 • 51 N, 102 • 42 E) lies in the center of the watershed, with an area of 309.5 km 2 and a storage capacity of 1.56 billion m 3 (at a water level of 1887.4 m). As the largest lake on the Yunnan-Guizhou Plateau and the sixth-largest freshwater lake in China, Lake Dianchi has been given the name of "Pearl of the Plateau" concerning its significant functions for water supply, flood regulation, fisheries and biodiversity conservation Zhao et al, 2012). Although the Lake Dianchi basin area makes up only 13.9 % of Kunming, it contributed 75.5 % of the city's gross domestic product, acting as the most active economic area in Yunnan Province (Pan and Gao, 2010).…”

Section: Characterization Of the Lake Dianchi Basinmentioning

confidence: 99%

Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China

et al. 2014

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Abstract. Net anthropogenic nitrogen inputs (NANI) with components of atmospheric N deposition, synthetic N fertilizer, agricultural N fixation and N in net food and feed imports from 15 catchments in the Lake Dianchi basin were determined over an 11-year period (2000-2010). The 15 catchments range in size from 44 km 2 to 316 km 2 with an average of 175 km 2 . To reduce uncertainty from scale change methodology, results from data extraction by area-weighting and land use-weighting methods were compared. Results show that the methodology for extrapolating data from the county scale to watersheds has a great influence on NANI computation for catchments in the Lake Dianchi basin, and that estimates of NANI between the two methods have an average difference of 30 % on a catchment basis, while a smaller difference (15 %) was observed on the whole Lake Dianchi basin basis. The riverine N export has a stronger linear relationship with NANI computed by the land useweighting method, which we believe is more reliable. Overall, nitrogen inputs assessed by the NANI approach for the Lake Dianchi basin are 9900 kg N km −2 yr −1 , ranging from 6600 to 28 000 kg N km −2 yr −1 among the 15 catchments. Synthetic N fertilizer is the largest component of NANI in most subwatersheds. On average, riverine flux of nitrogen in catchments of the Lake Dianchi basin averages 83 % of NANI, far higher than generally observed in North America and Europe. Saturated N sinks and a limited capacity for denitrification in rivers may be responsible for this high percentage of riverine N export. Overall, the NANI methodology should be applicable in small watersheds when sufficiently detailed data are available to estimate its components.

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Section: Characterization Of the Lake Dianchi Basinmentioning

confidence: 99%

Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China

et al. 2014

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“…Analyzing and interpreting such data over time plays a critical role in monitoring changes, and facilitates identification of driving forces that bring changes in the landscape [20]. Several studies have integrated landscape metrics with LULC classifications derived from remote sensing images to quantify the patterns of a landscape and relate to the processes driving the changes [4,20,23]. For example, Wang and Wang [4] used LULC data derived from remote sensing images, in combination with landscape metrics, to evaluate changes in the landscape of Yanqi Basin, China.…”

Section: Introductionmentioning

confidence: 99%

“…There have been a number of studies on the effects of LULC changes on the spatial patterns of the landscape and water quality of lake basins [4,23,35]. Thus, some studies suggested the study of LULC changes as a critical step that should be considered in the environmental protection strategy and sustainable resource management of lake basins.…”

Section: Introductionmentioning

confidence: 99%

Land Use and Land Cover Changes and Their Effects on the Landscape of Abaya-Chamo Basin, Southern Ethiopia

Woldeyohannes

Cotter

Kelboro

et al. 2018

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This study uses a combination of remote sensing data, field interviews and observations, and landscape indices to examine the dynamics of land use and land cover (LULC), identify their driving forces, and analyze their effects on the landscape of Abaya-Chamo Basin (ACB) between 1985, 1995, and 2010. The results reveal that the landscape of ACB has changed considerably during the past 25 years between 1985 and 2010. The main changes observed imply a rapid reduction in shrubland (28.82%) and natural grassland (33.13%), and an increase in arable land (59.15%). The basin has become more fragmented and formed less connected patches in 2010 compared to 1985. Rapid population growth, internal migration, policy shifts, and regime change were identified as the key driving forces of LULC changes in ACB. The LULC changes and related trend of increasing landscape fragmentation in the basin increased soil erosion, the volume of surface runoff, and sediment transport in the landscape and, consequently, affected the levels and water quality of the lakes found in the rift floor. Furthermore, the destruction and fragmentation of shrubland and natural grassland led to the decline of wild plants and animals previously prominent in the basin. Therefore, protective measures that take into consideration the economic, social, and ecological dynamics of the basin are urgently needed to save the aquatic and terrestrial ecosystems of the basin from further damage.

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“…This technology can provide information on both biological (vegetation and its dynamics) and physical conditions (variations in terrain and morphological features) of LULCC. However, standard LULCC information generated from remote sensing data over the decades continues to be a challenging task, owing to the prevailing variations in spatial resolution of satellite data [10][11][12]. Numerous recent and on-going studies have improved both the measurements and understanding of factors influencing LULCC at the global scale, which in turn have paved the way to assimilate them in climate models [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

et al. 2015

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India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for Remote Sens. 2015, 7 2403 comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

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Examining Land-Use/Land-Cover Change in the Lake Dianchi Watershed of the Yunnan-Guizhou Plateau of Southwest China with Remote Sensing and GIS Techniques: 1974–2008

Cited by 54 publications

References 60 publications

Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China

Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China

Land Use and Land Cover Changes and Their Effects on the Landscape of Abaya-Chamo Basin, Southern Ethiopia

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

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