scholarly journals Estimating the Characteristic Spatiotemporal Variation in Habitat Quality Using the InVEST Model—A Case Study from Guangdong–Hong Kong–Macao Greater Bay Area

2021 ◽  
Vol 13 (5) ◽  
pp. 1008
Author(s):  
Linlin Wu ◽  
Caige Sun ◽  
Fenglei Fan
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Land Use Change ◽  
Habitat Quality ◽  
Human Activity ◽  
Spatiotemporal Variation ◽  
Effect Factors ◽  
Elevation Gradients ◽  
Bay Area ◽  
Rank Correlation Method

The intensity of human activity, habitat loss and habitat degradation have significant impacts on biodiversity. Habitat quality plays an important role in spatial dynamics when evaluating fragmented landscapes and the effectiveness of biodiversity conservation. This study aimed to evaluate the status and characteristic variation in habitat quality to analyze the underlying factors affecting habitat quality in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Here, we applied Kendall’s rank correlation method to calculate the sensitivity of habitat types to threat factors for the Integrated Valuation of Ecosystem Services and Tradeoffs habitat quality (InVEST-HQ) model. The spatiotemporal variation in habitat quality of the GBA in the period 1995–2015 was estimated based on the InVEST-HQ model. We analyzed the characteristic habitat quality using different ecosystem classifications and at different elevation gradients. Fractional vegetation cover, the proportion of impervious surface, population distribution and gross domestic product were included as the effect factors for habitat quality. The correlation between the effect factors and habitat quality was analyzed using Pearson’s correlation tests. The results showed that the spatial pattern of habitat quality decreased from fringe areas to central areas in the GBA, that the forest ecosystem had the highest value of habitat quality, and that habitat quality increased with elevation. In the period from 1995 to 2015, habitat quality declined markedly and this could be related to vegetation loss, land use change and intensity of human activity. Built-up land expansion and forest land fragmentation were clear markers of land use change. This study has great significance as an operational approach to mitigating the tradeoff between natural environment conservation and rapid economic development.

scholarly journals Assessing the Effects of Land Cover Land Use Change on Precipitation Dynamics in Guangdong–Hong Kong–Macao Greater Bay Area from 2001 to 2019

2021 ◽  
Vol 13 (6) ◽  
pp. 1135
Author(s):  
Xinghan Wang ◽  
Peitong Cong ◽  
Yuhao Jin ◽  
Xichun Jia ◽  
Junshu Wang ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Hong Kong ◽  
Land Use Change ◽  
Land Cover ◽  
Temporal Distribution ◽  
Water Security ◽  
Spatial And Temporal Distribution ◽  
Construction Land ◽  
Bay Area

The change of spatial and temporal distribution of precipitation has an important impact on urban water security. The effect of land cover land use change (LCLUC) on the spatial and temporal distribution of precipitation needs to be further studied. In this study, transfer matrix, standard deviation ellipse and spatial autocorrelation analysis techniques were used. Based on the data of land cover land use and precipitation, this paper analyzed the land cover land use change and its influence on the spatial and temporal distribution pattern of precipitation in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The results showed that from 2001 to 2019, the area of cropland, water, barren, forest/grassland in the GBA decreased by 44.03%, 8.05%, 50.22%, 0.43%, respectively, and the area of construction land increased by 20.05%. The precipitation in the GBA was mainly concentrated in spring and summer, and the precipitation in spring tended to increase gradually, while the precipitation in summer tended to decrease gradually, while the precipitation in autumn and winter has no obvious change. It was found that with the change of land cover land use, the spatial distribution of precipitation also changed. Especially in the areas where the change of construction land was concentrated, the spatial distribution of precipitation changed most obviously.

scholarly journals Multi-Scenario Analysis of Habitat Quality in the Yellow River Delta by Coupling FLUS with InVEST Model

2021 ◽  
Vol 18 (5) ◽  
pp. 2389
Author(s):  
Qinglong Ding ◽  
Yang Chen ◽  
Lingtong Bu ◽  
Yanmei Ye
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Habitat Quality ◽  
Scenario Analysis ◽  
Yellow River ◽  
The Yellow River ◽  
Cultivated Land ◽  
Invest Model ◽  
Unused Land ◽  
Dongying City

The past decades were witnessing unprecedented habitat degradation across the globe. It thus is of great significance to investigate the impacts of land use change on habitat quality in the context of rapid urbanization, particularly in developing countries. However, rare studies were conducted to predict the spatiotemporal distribution of habitat quality under multiple future land use scenarios. In this paper, we established a framework by coupling the future land use simulation (FLUS) model with the Intergrated Valuation of Environmental Services and Tradeoffs (InVEST) model. We then analyzed the habitat quality change in Dongying City in 2030 under four scenarios: business as usual (BAU), fast cultivated land expansion scenario (FCLE), ecological security scenario (ES) and sustainable development scenario (SD). We found that the land use change in Dongying City, driven by urbanization and agricultural reclamation, was mainly characterized by the transfer of cultivated land, construction land and unused land; the area of unused land was significantly reduced. While the habitat quality in Dongying City showed a degradative trend from 2009 to 2017, it will be improved from 2017 to 2030 under four scenarios. The high-quality habitat will be mainly distributed in the Yellow River Estuary and coastal areas, and the areas with low-quality habitat will be concentrated in the central and southern regions. Multi-scenario analysis shows that the SD will have the highest habitat quality, while the BAU scenario will have the lowest. It is interesting that the ES scenario fails to have the highest capacity to protect habitat quality, which may be related to the excessive saline alkali land. Appropriate reclamation of the unused land is conducive to cultivated land protection and food security, but also improving the habitat quality and giving play to the versatility and multidimensional value of the agricultural landscape. This shows that the SD of comprehensive coordination of urban development, agricultural development and ecological protection is an effective way to maintain the habitat quality and biodiversity.

Future scenarios impact on land use change and habitat quality in Lithuania

2021 ◽  
pp. 111101
Author(s):  
Eduardo Gomes ◽  
Miguel Inácio ◽  
Katažyna Bogdzevič ◽  
Marius Kalinauskas ◽  
Donalda Karnauskaitė ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Habitat Quality ◽  
Future Scenarios

scholarly journals Ecosystem Services Changes on Farmland in Response to Urbanization in the Guangdong–Hong Kong–Macao Greater Bay Area of China

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 501
Author(s):  
Xuege Wang ◽  
Fengqin Yan ◽  
Yinwei Zeng ◽  
Ming Chen ◽  
Bin He ◽  
...  
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Ecosystem Services ◽  
Ecosystem Service ◽  
Food Production ◽  
Great Loss ◽  
The Past ◽  
Bay Area ◽  
Farmland Loss ◽  
The World

Extensive urbanization around the world has caused a great loss of farmland, which significantly impacts the ecosystem services provided by farmland. This study investigated the farmland loss due to urbanization in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China from 1980 to 2018 based on multiperiod datasets from the Land Use and Land Cover of China databases. Then, we calculated ecosystem service values (ESVs) of farmland using valuation methods to estimate the ecosystem service variations caused by urbanization in the study area. The results showed that 3711.3 km2 of farmland disappeared because of urbanization, and paddy fields suffered much higher losses than dry farmland. Most of the farmland was converted to urban residential land from 1980 to 2018. In the past 38 years, the ESV of farmland decreased by 5036.7 million yuan due to urbanization, with the highest loss of 2177.5 million yuan from 2000–2010. The hydrological regulation, food production and gas regulation of farmland decreased the most due to urbanization. The top five cities that had the largest total ESV loss of farmland caused by urbanization were Guangzhou, Dongguan, Foshan, Shenzhen and Huizhou. This study revealed that urbanization has increasingly become the dominant reason for farmland loss in the GBA. Our study suggests that governments should increase the construction of ecological cities and attractive countryside to protect farmland and improve the regional ESV.

scholarly journals ANALISIS PERUBAHAN PENGGUNAAN LAHAN MENJADI LAHAN TERBANGUN PASCA PERPINDAHAN IBUKOTA KABUPATEN SUKABUMI DI WILAYAH TELUK PALABUHANRATU

2019 ◽  
Vol 21 (3) ◽  
pp. 407
Author(s):  
Yuda Pringgo Bayusukmara ◽  
Baba Barus ◽  
Akhmad Fauzi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
Landsat Imagery ◽  
Beach Sand ◽  
Bay Area ◽  
Future Situation ◽  
Type Of Land Use ◽  
Key Variables ◽  
Spatial Plan

The determination of the Capital of Sukabumi Regency had implications on Palabuhanratu Bay area in terms of the physical area marked by the change of land use. This research was begun by analyzing land use change using Landsat imagery. Markov Chain and CA-Markov Chain method were used to predict land use change. Prospective Structural Analysis assume that the future is different from the past and is not imposed, but can be built. MICMAC method were used to determine key variables in influencing the change of land use into built-area. The results showed that in the period of post-relocation, the built-up area had a significant increase than the period of pre-relocation. The prediction results of 2030 indicate the type of land use which had a significant decrease from 2016-2030 were beach sand and waterbodies. The type of land use which had higher increase was built-up area and shrub. The key variables that influence the change of land use into built-up area in Palabuhanratu Bay area in the present situation are distance to the city center, Regional Spatial Plan policy, and slope. In future situation, variables such as distance to cities, Regional Spatial Plan policy, and the proportion of paddy field would be the key variables in influencing the change of land use into built-up area.

scholarly journals Estimating Changes in Habitat Quality through Land-Use Predictions: Case Study of Roe Deer (Capreolus pygargus tianschanicus) in Jeju Island

2020 ◽  
Vol 12 (23) ◽  
pp. 10123
Author(s):  
Dong-jin Lee ◽  
Seong Woo Jeon
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Protected Areas ◽  
Habitat Quality ◽  
Green Infrastructure ◽  
Roe Deer ◽  
Land Use Changes ◽  
Jeju Island ◽  
Invest Model ◽  
Integrated Valuation

This study predicts future land-use changes and the resulting changes in habitat quality, suggesting a method for establishing land-use management to ensure sustainable wildlife habitats. The conservation effects were verified in terms of wild animal habitat quality according to the designation of protected areas. Land-use change until 2050 was predicted using the Dyna-Conversion of Land Use Change and its effects (Dyna-CLUE) model for Jeju Island, Korea, and the change in the quality of roe deer habitats was predicted using the Integrated Valuation and Environmental Services and Tradeoffs (InVEST) model. Results indicate that, compared to 2030, urbanized area increased by 42.55 km2, farmland decreased by 81.36 km2, and natural area increased by 38.82 km2 by 2050. The average habitat quality on Jeju Island was predicted to decrease from 0.306 in 2030 to 0.303 in 2050. The average habitat quality ranged from 0.477 in 2030 to 0.476 in 2050 in protected areas and 0.281 in 2030 to 0.278 in 2050 outside protected areas. Habitat quality in protected areas was relatively high, and its reduction was limited. Areas with lower habitat quality need approaches such as expanding greenery and improving its quality. By establishing appropriate land-use plans by predicting habitat quality, wildlife habitats can be better maintained and protected, which is a primary goal of green infrastructure.

scholarly journals Comparison of Changes in Urban Land Use/Cover and Efficiency of Megaregions in China from 1980 to 2015

2019 ◽  
Vol 11 (15) ◽  
pp. 1834 ◽  
Author(s):  
Shu Zhang ◽  
Chuanglin Fang ◽  
Wenhui Kuang ◽  
Fengyun Sun
Keyword(s):  
Land Use ◽  
Hong Kong ◽  
Urban Expansion ◽  
Yangtze River Delta ◽  
Urban Land ◽  
Urban Land Use ◽  
Theil Index ◽  
Valuable Insight ◽  
Bay Area ◽  
Great Bay

Urban land use/cover and efficiency are important indicators of the degree of urbanization. However, research about comparing their changes at the megaregion level is relatively rare. In this study, we depicted the differences and inequalities of urban land and efficiency among megaregions in China using China’s Land Use/cover Dataset (CLUD) and China’s Urban Land Use/cover Dataset (CLUD-Urban). Furthermore, we analyzed regional inequality using the Theil index. The results indicated that the Guangdong-Hong Kong-Macao Great Bay Area had the highest proportion of urban land (8.03%), while the Chengdu-Chongqing Megaregion had the highest proportion of developed land (64.70%). The proportion of urban impervious surface area was highest in the Guangdong-Hong Kong-Macao Great Bay Area (75.16%) and lowest in the Chengdu-Chongqing Megaregion (67.19%). Furthermore, the highest urban expansion occurred in the Yangtze River Delta (260.52 km2/a), and the fastest period was 2000–2010 (298.19 km2/a). The decreasing Theil index values for the urban population and economic density were 0.305 and 1.748, respectively, in 1980–2015. This study depicted the development trajectory of different megaregions, and will expect to provide a valuable insight and new knowledge on reasonable urban growth modes and sustainable goals in urban planning and management.

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