scholarly journals Estimation of ecosystem services value based on land use and cover change information derived from remote sensing data

2020 ◽  
Vol 198 ◽  
pp. 04026
Author(s):  
Liyan Wang ◽  
Chao Chen ◽  
Kai Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Ecosystem Services ◽  
Quantitative Estimation ◽  
Research Area ◽  
Cultivated Land ◽  
Land Area ◽  
Construction Land ◽  
Ecosystem Services Value ◽  
Land Use And Cover

It is an effective method to study the value change of ecological services based on land use and cover change information. This paper analyzed the land use and cover change information in the research area, which is based on the remote sensing images and social statistics data of 2005, 2010, and 2015, and then, quantitative estimation of the ecosystem service value was performed. Yangtze-Huaihe river basin, China is a fragile ecological area, which is selected as the research area. During 2005-2015, the area of cultivated land and construction land was the main land use types in the study area, the land use and cover change in the study area were obvious, which was characterized by the increasing of construction land area and the decreasing of cultivated land area, and the total ecosystem services value in the research area has been decreasing continuously, the value from 34.376 billion yuan in 2005 to 26.161 billion yuan in 2015.

scholarly journals Correlation Studies between Land Cover Change and Baidu Index: A Case Study of Hubei Province

2020 ◽  
Vol 9 (4) ◽  
pp. 232 ◽  
Author(s):  
Yongqing Zhao ◽  
Rendong Li ◽  
Mingquan Wu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Driving Forces ◽  
Research Area ◽  
Hubei Province ◽  
Cultivated Land ◽  
Land Occupation ◽  
Construction Land ◽  
The Impact

Current land cover research focuses primarily on spatial changes in land cover and the driving forces behind these changes. Among such forces is the influence of policy, which has proven difficult to measure, and no quantitative research has been conducted. On the basis of previous studies, we took Hubei Province as the research area, using remote sensing (RS) images to extract land cover change data using a single land use dynamic degree and a comprehensive land use dynamic degree to study land cover changes from 2000 to 2015. Then, after introducing the Baidu Index (BDI), we explored its relationship with land cover change and built a tool to quantitatively measure the impact of changes in land cover. The research shows that the key search terms in the BDI are ‘cultivated land occupation tax’ and ‘construction land planning permit’, which are closely related to changes in cultivated land and construction land, respectively. Cultivated land and construction land in all regions of Hubei Province are affected by policy measures with the effects of policy decreasing the greater the distance from Wuhan, while Wuhan is the least affected region.

scholarly journals Simulation of Land Use Pattern Evolution from a Multi-Scenario Perspective: A Case Study of Suzhou City in Anhui Province, China

2021 ◽  
Vol 18 (3) ◽  
pp. 921
Author(s):  
Rongtian Zhang ◽  
Jianfei Lu
Keyword(s):  
Land Use ◽  
Thematic Mapper ◽  
Anhui Province ◽  
Landscape Patterns ◽  
Cultivated Land ◽  
Land Area ◽  
Construction Land ◽  
Ecological Protection ◽  
Suzhou City ◽  
S Model

Land use/land cover change is a frontier issue in the field of geography research. Taking Suzhou City in Anhui Province as the research case, based on thematic mapper /enhanced thematic mapper+ (TM/ETM+) remote sensing data from 1998 to 2018, through the transfer matrix model and modified conversion of land use and its effects at small region extent (CLUE-S) model, the simulation of the land use landscape pattern evolution was studied from a multi-scenario perspective. The results showed that in the past 20 years, landscape patterns have undergone spatial–temporal conversion, which was mainly manifested as the evolution from a cultivated land landscape and other agricultural land to construction land, and there was some transformation between other landscape types, but the transformation degree was not significant. The spatial autocorrelation factor was introduced to correct the CLUE-S model, and the Kappa index reached 0.83, indicating that the modified CLUE-S model had a good simulation accuracy. (I) In the cultivated land protection scenario, limiting the conversion of basic farmland use, and by 2028, the proportion of cultivated land increased by 5.23%, distributed in eastern Suzhou City; (II) in the economic development scenario, by 2028, the construction land area increased by 14.58%, and was distributed in the surrounding regions of the built-up areas; and (III) in the ecological protection scenario, by 2028, wood land, water, and other ecological protection land area increased, and were distributed in the central and eastern part of Suzhou City. Research can provide useful decision-making support for land use optimization and remediation.

Profit and Loss Analysis on Ecosystem Services Value Based on Land Use Change along Expressway

2015 ◽  
Vol 744-746 ◽  
pp. 2386-2390
Author(s):  
Xiu Mei Tang ◽  
Yan Min Ren ◽  
Yu Liu ◽  
Yu Chun Pan
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
Structure Change ◽  
Cultivated Land ◽  
Loss Analysis ◽  
Ecosystem Services Value ◽  
Agricultural Structure ◽  
Land Use Types ◽  
Garden Plot

Taking the area within 10 km along Beijing section of Jingcheng expressway as study area, this paper calculates the area changes and conversions of landuse types based on the land use map derived from TM images of 1995, 2004 and 2009, and analyze the variation of ecosystem services value of landuse types. The following results are gotten:(1) the construction of the expressway hadadramatic influence to the land use types along and the agricultural structure change obviously; (2) The total value is 20.77×108Yuan in 1995, and increased to 20.96×108 Yuan in 2004, then decreased to20.78×108 Yuan in 2009; (3)The reduction of cultivated land and the increase of construction land were the most important reason for the loss of the ecosystem services value, but because of the increase of garden plot, the total ecosystem services value was stable and increased a littlefrom 1995 to 2009.

Suzhou Urban Land-Use Change and its Prediction Analysis

2012 ◽  
Vol 174-177 ◽  
pp. 3539-3542 ◽  
Author(s):  
Gang Fang ◽  
Juan Yang ◽  
Qi Li
Keyword(s):  
Land Use ◽  
Markov Model ◽  
Water Body ◽  
Dynamic Change ◽  
Urban Land ◽  
Urban Land Use ◽  
Cultivated Land ◽  
Land Area ◽  
Body Area ◽  
Construction Land

Based on the 2000 ETM+ and 2009 TM images, the Suzhou urban district as the research object, supported by the remote sensing software, using the support vector machine (SVM) classification to extract the urban landscape types in 2000-2009, analyzing the land-use dynamic change and mutual transformation in Suzhou urbanization process from the land-use type transition matrix, dynamic degree, development degree and consumption reduction degree, and using the Markov model to forecast the Suzhou urban land-use dynamic change trend in 2009, 2018, 2027 and 2036, for the future Suzhou land-use dynamic monitoring, land-use planning and adjustment, ecological environment regulation and restoration, and land resource sustainable utilization to provide the theoretical basis. The results show that Suzhou urban land-use occurred to a large changes from 2000 to 2009, the construction land area increased significantly, the cultivated land area reduced sharply, the wood land and water body area slightly increased. According to the Markov model prediction results from 2009 to 2036, the cultivated land and wood land area will continue to reduce, the construction land and water body area will continue to increase, which makes the contradiction between the cultivated land protection and the urban expansion will become more prominent.

scholarly journals Evaluation of the status of land use/land cover change using remote sensing and GIS in Jewha Watershed, Northeastern Ethiopia

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Dereje Gebrie Habte ◽  
Satishkumar Belliethathan ◽  
Tenalem Ayenew
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Catchment Area ◽  
Environmental Conservation ◽  
Land Use Land Cover ◽  
Cultivated Land ◽  
Plantation Forest ◽  
Bare Land

AbstractEvaluation of land use/land cover (LULC) status of watersheds is vital to environmental management. This study was carried out in Jewha watershed, which is found in the upper Awash River basin of central Ethiopia. The total catchment area is 502 km2. All climatic zones of Ethiopia, including lowland arid (‘Kola’), midland semi-arid (‘Woinadega’), humid highland (Dega) and afro alpine (‘Wurch’) can be found in the watershed. The study focused on LULC classification and change detection using GIS and remote sensing techniques by analyzing satellite images. The data preprocessing and post-process was done using multi-temporal spectral satellite data. The images were used to evaluate the temporal trends of the LULC class by considering the years 1984, 1995, 2005 and 2015. Accuracy assessment and change detection of the classification were undertaken by accounting these four years images. The land use types in the study area were categorized into six classes: natural forest, plantation forest, cultivated land, shrub land, grass land and bare land. The result shows the cover classes which has high environmental role such as forest and shrub has decreased dramatically through time with cultivated land increasing during the same period in the watershed. The forest cover in 1984 was about 6.5% of the total catchment area, and it had decreased to 4.2% in 2015. In contrast, cultivated land increased from 38.7% in 1984 to 51% in 2015. Shrub land decreased from 28 to 18% in the same period. Bare land increased due to high gully formation in the catchment. In 1984, it was 1.8% which turned to 0.6% in 1995 then increased in 2015 to 2.7%. Plantation forest was not detected in 1984. In 1995, it covers 1.5% which turned to be the same in 2015. The study clearly demonstrated that there are significant changes of land use and land cover in the catchment. The findings will allow making informed decision which will allow better land use management and environmental conservation interventions.

scholarly journals Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

2019 ◽  
Vol 8 (10) ◽  
pp. 454 ◽  
Author(s):  
Junfeng Kang ◽  
Lei Fang ◽  
Shuang Li ◽  
Xiangrong Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Markov Model ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing Images ◽  
Mapreduce Framework ◽  
Construction Land ◽  
Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

scholarly journals Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2757 ◽  
Author(s):  
Kongming Li ◽  
Mingming Feng ◽  
Asim Biswas ◽  
Haohai Su ◽  
Yalin Niu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Satellite Remote Sensing ◽  
Gansu Province ◽  
Driving Factors ◽  
Driving Mechanism ◽  
Second Stage ◽  
Arid And Semiarid ◽  
Land Use And Cover

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

Sign in / Sign up

Export Citation Format

Share Document