scholarly journals The Spatiotemporal Variability of Evapotranspiration and Its Response to Climate Change and Land Use/Land Cover Change in the Three Gorges Reservoir

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1739 ◽  
Author(s):  
Hejia Wang ◽  
Weihua Xiao ◽  
Yong Zhao ◽  
Yicheng Wang ◽  
Baodeng Hou ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Three Gorges Reservoir ◽  
Water Bodies ◽  
Spatiotemporal Variability ◽  
Land Use Land Cover ◽  
Three Gorges ◽  
The Three Gorges

Evapotranspiration (ET) has undergone profound changes as a result of global climate change and anthropogenic activities. The construction of the Three Gorges Reservoir (TGR) has led to changes in its land use/land cover (LUCC) and local climate, which in turn has changed ET processes in the TGR region. In this paper, the CLM4.5 land surface model is used to simulate and analyze the spatiotemporal variability of ET between 1993 and 2013. Four experiments were conducted to quantify the contribution rate of climate change and LUCC to changes in ET processes. The results show that the climate showed a warming and drying trend from 1993 to 2013, and the LUCC indicates decreasing cropland with increasing forest, grassland, water bodies and urban areas. These changes increased the mean annual ET by 13.76 mm after impoundment. Spatially, the vegetation transpiration accounts for the largest proportion in ET. The decreasing relative humidity and increasing wind speeds led to an increase in vegetation transpiration and ground evaporation, respectively, in the center of the TGR region, while the LUCC drove changes in ET in water bodies, urban areas and high-altitude regions in the TGR region.

scholarly journals Land Use and Land Cover Mapping Using RapidEye Imagery Based on a Novel Band Attention Deep Learning Method in the Three Gorges Reservoir Area

2021 ◽  
Vol 13 (6) ◽  
pp. 1225
Author(s):  
Xin Zhang ◽  
Ling Du ◽  
Shen Tan ◽  
Fangming Wu ◽  
Liang Zhu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Deep Learning ◽  
Land Cover ◽  
Three Gorges Reservoir ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Reservoir Area ◽  
The Three Gorges ◽  
Traditional Classification

Land use/land cover (LULC) change has been recognized as one of the most important indicators to study ecological and environmental changes. Remote sensing provides an effective way to map and monitor LULC change in real time and for large areas. However, with the increasing spatial resolution of remote sensing imagery, traditional classification approaches cannot fully represent the spectral and spatial information from objects and thus have limitations in classification results, such as the “salt and pepper” effect. Nowadays, the deep semantic segmentation methods have shown great potential to solve this challenge. In this study, we developed an adaptive band attention (BA) deep learning model based on U-Net to classify the LULC in the Three Gorges Reservoir Area (TGRA) combining RapidEye imagery and topographic information. The BA module adaptively weighted input bands in convolution layers to address the different importance of the bands. By comparing the performance of our model with two typical traditional pixel-based methods including classification and regression tree (CART) and random forest (RF), we found a higher overall accuracy (OA) and a higher Intersection over Union (IoU) for all classification categories using our model. The OA and mean IoU of our model were 0.77 and 0.60, respectively, with the BA module and were 0.75 and 0.58, respectively, without the BA module. The OA and mean IoU of CART and RF were both below 0.51 and 0.30, respectively, although RF slightly outperformed CART. Our model also showed a reasonable classification accuracy in independent areas well outside the training area, which indicates the strong model generalizability in the spatial domain. This study demonstrates the novelty of our proposed model for large-scale LULC mapping using high-resolution remote sensing data, which well overcomes the limitations of traditional classification approaches and suggests the consideration of band weighting in convolution layers.

scholarly journals Variations in ecosystem service value in response to land use/land cover changes in Central Asia from 1995–2035

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7665 ◽  
Author(s):  
Jiangyue Li ◽  
Hongxing Chen ◽  
Chi Zhang ◽  
Tao Pan
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Central Asia ◽  
Ecosystem Service ◽  
Urban Areas ◽  
Water Bodies ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Rapid Urbanization

Acute farmland expansion and rapid urbanization in Central Asia have accelerated land use/land cover changes, which have substantial effects on ecosystem services. However, the spatiotemporal variations in ecosystem service values (ESVs) in Central Asia are not well understood. Here, based on land use products with 300-m resolution for the years 1995, 2005 and 2015 and transfer methodology, we predicted land use and land cover (LULC) for 2025 and 2035 using CA-Markov, assessed changes in ESVs in response to LULC dynamics, and explored the elasticity of the response of ESV to LULC changes. We found significant expansions of cropland (+22.10%) and urban areas (+322.40%) and shrinking of water bodies (−38.43%) and bare land (−9.42%) during 1995–2035. The combined value of ecosystem services of water bodies, cropland, and grassland accounted for over 90% of the total ESVs. Our study showed that cropland ecosystem services value increased by 93.45 billion US$ from 1995 to 2035, which was mainly caused by the expansion of cropland area. However, the area of water bodies decreased sharply during 1995–2035, causing a loss of 64.38 billion US$. Biodiversity, food production and water regulation were major ecosystem service functions, accounting for 80.52% of the total ESVs. Our results demonstrated that effective land-use policies should be made to control farmland expansion and protect water bodies, grassland and forestland for more sustainable ecosystem services.

scholarly journals Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 1132
Author(s):  
Qijiao Xie ◽  
Qi Sun
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Planning ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
The Impact

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

scholarly journals Impact of Climate and Land Use/Land Cover Change on the Water Resources of a Tropical Inland Valley Catchment in Uganda, East Africa

Climate ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 83
Author(s):  
Geofrey Gabiri ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Constanze Leemhuis ◽  
Roderick van der Linden ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Water Resources ◽  
Land Cover ◽  
Rainy Season ◽  
Hydrological Processes ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Inland Valley ◽  
Headwater Catchment

The impact of climate and land use/land cover (LULC) change continues to threaten water resources availability for the agriculturally used inland valley wetlands and their catchments in East Africa. This study assessed climate and LULC change impacts on the hydrological processes of a tropical headwater inland valley catchment in Uganda. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze climate and LULC change impacts on the hydrological processes. An ensemble of six regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment for two Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were used for climate change assessment for historical (1976–2005) and future climate (2021–2050). Four LULC scenarios defined as exploitation, total conservation, slope conservation, and protection of headwater catchment were considered. The results indicate an increase in precipitation by 7.4% and 21.8% of the annual averages in the future under RCP4.5 and RCP8.5, respectively. Future wet conditions are more pronounced in the short rainy season than in the long rainy season. Flooding intensity is likely to increase during the rainy season with low flows more pronounced in the dry season. Increases in future annual averages of water yield (29.0% and 42.7% under RCP4.5 and RCP8.5, respectively) and surface runoff (37.6% and 51.8% under RCP4.5 and RCP8.5, respectively) relative to the historical simulations are projected. LULC and climate change individually will cause changes in the inland valley hydrological processes, but more pronounced changes are expected if the drivers are combined, although LULC changes will have a dominant influence. Adoption of total conservation, slope conservation and protection of headwater catchment LULC scenarios will significantly reduce climate change impacts on water resources in the inland valley. Thus, if sustainable climate-smart management practices are adopted, the availability of water resources for human consumption and agricultural production will increase.

scholarly journals Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

2013 ◽  
Vol 8 (1) ◽  
pp. 084596 ◽  
Author(s):  
Zhongchang Sun ◽  
Xinwu Li ◽  
Wenxue Fu ◽  
Yingkui Li ◽  
Dongsheng Tang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Surface Runoff ◽  
Urban Areas ◽  
Land Use Land Cover ◽  
Long Term Effects ◽  
Effects Of Land Use ◽  
Beijing China
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