Modeling the Driving Forces of the Land Use and Land Cover Changes Along the Upper Yangtze River of China

2009 ◽  
Vol 45 (3) ◽  
pp. 454-465 ◽  
Author(s):  
Run Sheng Yin ◽  
Qing Xiang ◽  
Jin Tao Xu ◽  
Xiang Zheng Deng
2019 ◽  
Vol 11 (19) ◽  
pp. 5300
Author(s):  
Pei Xu ◽  
Yingman Guo ◽  
Bin Fu

Water retention is an important factor in ecosystem services, owing to its relationships with climate and land-cover change; however, quantifying the independent and combined impacts of these variables remains a challenge. We use scenario analysis and the InVEST model to assess individual or combined impacts of climate and land cover on water retention in the Upper Yangtze River Basin. Water retention decreased from 1986 to 2015 at a rate of 2.97 mm/10a in response to increasing precipitation (3.94 mm/10a) and potential evapotranspiration (16.47 mm/10a). The rate of water retention change showed regional variability (from 68 to −18 mm/a), with some eastern regions experiencing an increase and most other regions experiencing a decrease. Farmland showed the highest decrease (10,772 km2), with land mainly converted into forest (58.17%) and shrub land (21.13%) from 2000 to 2015. The impact of climate change (−12.02 mm) on water retention generally was greater than the impact of land cover change (−4.14 mm), at the basin scale. Among 22 climate zones, 77.27% primarily were impacted by climate change; 22.73% primarily were impacted by land cover change. Our results demonstrate that both individualistic and integrated approaches toward climate and vegetation management is necessary to mitigate the impacts of climate change on water resources.


2019 ◽  
Vol 11 (8) ◽  
pp. 2370 ◽  
Author(s):  
Xiaowei Chuai ◽  
Jiqun Wen ◽  
Dachang Zhuang ◽  
Xiaomin Guo ◽  
Ye Yuan ◽  
...  

China is experiencing substantial land-use and land-cover change (LUCC), especially in coastal regions, and these changes have caused many ecological problems. This study selected a typical region of Jiangsu Province and completed a comprehensive and detailed spatial-temporal analysis regarding LUCC and the driving forces. The results show that the rate of land-use change has been accelerating, with land-use experiencing the most substantial changes from 2005 to 2010 for most land-use types and the period from 2010 to 2015 showing a reversed changing trend. Built-up land that occupies cropland was the main characteristic of land-use type change. Southern Jiangsu and the coastline region presented more obvious land-use changes. Social-economic development was the main factor driving increased built-up land expansion and cropland reduction. In addition, land-use policy can significantly affect land-use type changes. For land-cover changes, the normalized difference vegetation index (NDVI) for the land area without land-use type changes increased by 0.005 per year overall. Areas with increasing trends accounted for 82.43% of the total area. Both precipitation and temperature displayed more areas that were positively correlated with NDVI, especially for temperature. Temperature correlated more strongly with NDVI change than precipitation for most vegetation types. Our study can be used as a reference for land-use managers to ensure sustainable and ecological land-use and coastal management.


2017 ◽  
Vol 9 (3) ◽  
pp. 351 ◽  
Author(s):  
Bruno Meneses ◽  
Eusébio Reis ◽  
Susana Pereira ◽  
Maria Vale ◽  
Rui Reis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Belayneh Bufebo ◽  
Eyasu Elias

Land use change is one of the challenges that aggravate environmental problems. Understanding the scope of land use change, driving forces, and consequences is very crucial for proper management of land resources. We investigated land use/land cover changes using remote sensing data (for the years 1973, 1995, and 2017), and field observation, household survey, key informant interview, and focus group discussion were used to determine the drivers and consequences of land use/land cover changes in Shenkolla watershed, south central Ethiopia. Unsupervised and supervised classification techniques were employed to get thematic information from satellite imagery. ArcGIS 10.3 and QGIS v 3.0 softwares were used to accomplish the analysis. The results disclosed that Shenkolla watershed has changed significantly during the past 4 decades between 1973 and 2017. This observed change indicates a reduction in forest land and an increase in agricultural land. Forest land was reduced from 29.51% in 1973 to 20.52% in 2017, but agricultural land was expanded from 70.49% in 1973 to 79.48% in 2017. Agricultural expansion, policy change and social unrest, population pressure, shortage of farm land, and biophysical factors were major driving forces of the LU/LC changes. Environmental implications such as climate change, biodiversity loss, scarcity of basic forest products, habitat alteration, decline in quality and availability of water, and crop yield reduction are the consequences of the LU/LC change. The expansion of agricultural land at the expense of forest cover in Shenkolla watershed has negative implications on the natural resources and the livelihood of local people. Hence, appropriate measures need to be employed to reduce the dramatic change in land use and to harmonize environmental conservation with human livelihood.


2021 ◽  
Vol 14 (1) ◽  
pp. 41-52
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Saima Siddiqui ◽  
Muhammad Imran ◽  
Muhammad Farhan

Change of land use and land cover (LULC) has been a key issue of natural resource conservation policies and environmental monitoring. In this study, we used multi-temporal remote sensing data and spatial analysis to assess the land cover changes in Fateh Jhang, Attock District, Pakistan. Landsat 7 (ETM+) for the years 2000, 2005 and 2010 and Landsat 8 (OLI/TIRS) for the year 2015 were classified using the maximum likelihood algorithms into built-up area, barren land, vegetation and water area. Post-classification methods of change detection were then used to assess the variation that took place over the study period. It was found that the area of vegetation has decreased by about 176.19 sq. km from 2000 to 2015 as it was converted to other land cover types. The built-up area has increased by 5.75%. The Overall Accuracy and Kappa coefficient were estimated at 0.92 and 0.77, 0.92 and 0.78, 0.90 and 0.76, 0.92 and 0.74, for the years 2000, 2005, 2010 and 2015, respectively. It turned out that economic development, climate change and population growth are the main driving forces behind the change. Future research will examine the effects of changing land use types on Land Surface Temperature (LST) over a given time period.


Sign in / Sign up

Export Citation Format

Share Document