scholarly journals Integration of GIS and Markov chain model for land use change assessment: A case study in the upstream Ba river basin, Gia Lai province

2021 ◽  
Vol 20 (04) ◽  
pp. 69-77
Author(s):  
Huyen T. Nguyen
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Use Change ◽  
River Basin ◽  
Land Use Planning ◽  
Land Use Changes ◽  
Chain Model ◽  
Forest Land ◽  
Change Assessment ◽  
South Central

Ba river is the biggest river system in the South-Central Coast of Vietnam and plays a significant role in the socio-economic development of the region. Recently, land-use changes in Gia Lai province have been significantly transformed. Hence, to provide the information for land-use planning, there is an urgent need for land-use change assessment in the upstream Ba river basin. This study employed the Markov chain coupled with GIS to assess land-use changes between 2010 - 2015 and 2015 - 2020 periods. The results showed that during the period 2010 - 2015, there was no significant conversion of agricultural and reserve forest land. Meanwhile, a large proportion of unused (86%) and water and aquacultural land (57.5%) was converted into the other land-use types. Between 2020 and 2015, unused land decreased while the surface water and aquacultural land increased. The forest land accounted for a significant area (51.16%) during the 2015 - 2020 period. In addition, the driving forces leading to these changes were also analyzed, providing a more comprehensive of land-use change in the study area. In general, GIS and Markov were suitable for assessing land-use change. This study outcomes provide a general framework for land-use planning in Gia Lai province.

scholarly journals Analysis of Land Use Changes and Driving Forces in the Yanhe River Basin from 1980 to 2015

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhihong Yao ◽  
Bo Wang ◽  
Jie Huang ◽  
Yu Zhang ◽  
Jianchen Yang ◽  
...  
Keyword(s):  
Land Use ◽  
River Basin ◽  
Land Use Planning ◽  
Driving Forces ◽  
Land Use Changes ◽  
Urban Land ◽  
Spatial And Temporal Variation ◽  
Annual Growth Rate ◽  
Forest Land ◽  
Gis Technology

Based on the support of RS and GIS technology, this paper analyzes the spatial and temporal variation characteristics and driving forces of land use in the Yanhe River Basin through the processing and interpretation of remote sensing images in different periods from 1980 to 2015 and the methods of the land use transfer matrix and dynamic attitude. The results show that cropland, grassland, and forest land are the three types of land use with the most obvious changes, while urban land and water body have relatively small changes in the Yanhe River Basin. The transfer between cropland, forest land, and grassland and urban land is very obvious, among which the conversion rate of cropland is the highest. During the 15 years from 2000 to 2015, the land use types of the Yanhe River Basin changed by 13.17%, with an average annual growth rate of 0.88%. The implementation of ecological restoration and governance policy is the direct driving force of land use change in the Yanhe River Basin. The results obtained in this study can provide reference basis for land use planning and management and land use structure optimization in the Yanhe River Basin in the future.

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

A Spatio-Temporal Storage Method for Land-Use Change

2014 ◽  
Vol 687-691 ◽  
pp. 3078-3082
Author(s):  
Ning Pan ◽  
Ke Wang ◽  
Jing Jing Tan
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Historical Data ◽  
Land Use Changes ◽  
Storage Method ◽  
Temporal Aspect ◽  
Spatio Temporal

Frequent land-use changes might produce a large amount of historical data which are valuable for data mining and decision-making. Based on the traditional Whole-state-recording Mode, the Special-state-recording Mode was proposed, focusing on the temporal aspect. This mode could optimize the land use database and reduce redundant change record. It could also improve data rollback and historical backtracking functions. The mode was successfully applied to land use planning in Zhejiang Province.

scholarly journals Flood Risk Index for Land-Use Changes: Case Study of Pakpanang River Basin

2020 ◽  
Vol 24 (5) ◽  
pp. 25-40
Author(s):  
Chonlatid Kittikhun ◽  
Sitang Pilailar ◽  
Suwatana Chittaladakorn ◽  
Eakawat Jhonpadit
Keyword(s):  
Land Use ◽  
River Basin ◽  
Land Use Planning ◽  
Flood Risk ◽  
Urban Areas ◽  
Risk Index ◽  
Land Use Changes ◽  
Flood Depth ◽  
Arc Gis

Flood Risk Index (FRI) is the multi-criteria linked with the factors of vulnerability; exposure, susceptibility, and resilience. In order to establish local FRI, crucial local information have to be accumulated. However, under the limitation of land-use data, particular techniques were applied in this study. CA Markov model was used to analyze the past missing land-use data and, also forecast the future land-use of Pakpanang river basin under conditions of plan and without plan. The ratio changes of forest, agriculture, wetland and water, and urban areas were considered. Then, the result of LULC spatial-temporal changes was then applied to Hec-HMS and Hec-Ras , with Arc GIS extension of Hec-GeoHMS and Hec-GeoRas software, in order to evaluate the flood hydrographs and flood severity in three municipalities corresponding to 100-year return period rainfall. Afterward, the FRI of Pakpanang, Chianyai, and Hua-sai, which ranges from 0 to 1, were evaluated by using the modified FRI equations. It was found that sensitivity analysis in the area of forest on flood depth and inundation areas is incoherent. Nevertheless, without land-use planning, the changes in these three cities cause higher flood risk, where Chianyai is the riskiest as the FRIE is 0.58. Further consideration of FRIE and FRIP proportion that reveals the FRI deviation indicates that to reduce flood risk, Chianyai would need the most resources and highest effort comparison to Pakpanang and Hua-sai.

scholarly journals Combined effects of predicted climate and land use changes on future hydrological droughts in the Luanhe River basin, China

2021 ◽  
Author(s):  
Xu Chen ◽  
Ruiguang Han ◽  
Yongjie Wang
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
River Basin ◽  
Emission Scenario ◽  
Land Use Changes ◽  
Model Parameters ◽  
Baseline Scenario ◽  
Luanhe River Basin ◽  
Hydrological Droughts

Abstract Drought can be impacted by both climate change and land use change in different ways. Thus, in order to predict future drought conditions, hydrological simulations as an ideal means, can be used to account for both projected climate change and projected land use change. In this study, projected climate and land use changes were integrated with the SWAT (Soil and Water Assessment Tool) model to estimate the combined impact of climate and land use projections on hydrological droughts in the Luanhe River basin. We presented that the measured runoff and the remote sensing inversion of soil water content were simultaneously used to validate the model to ensure the reliability of model parameters. Following the calibration and validation, the SWAT model was forced with downscaled precipitation and temperature outputs from a suite of nine Global Climate Models (GCMs) based on the CMIP5, corresponding to three different representative concentration pathways (RCP 2.6, RCP 4.5 and 8.5) for three distinct time periods: 2011–2040, 2041–2070 and 2071–2100, referred to as early-century, mid-century and late-century, respectively, and the land use predicted by CA-Markov model in the same future periods. Hydrological droughts were quantified using the Standardized Runoff Index (SRI). Compared to the baseline scenario (1961–1990), mild drought occurred more frequently during the next three periods (except the 2080s under the RCP2.6 emission scenario). Under the RCP8.5 emission scenario, the probability of severe drought or above occurring in the 2080s increased, the duration prolonged and the severity increased. Under the RCP2.6 scenario, the upper central region of the Luanhe river in the 2020s and upper reaches of the Luanhe river in the 2080s, were more likely to suffer extreme drought events. And under the RCP8.5 scenario, the middle and lower Luanhe river in the 2080s, were more likely to suffer these conditions.

scholarly journals Improving land-use change modeling by integrating ANN with Cellular Automata-Markov Chain model

Heliyon ◽  
2020 ◽  
Vol 6 (9) ◽  
pp. e05092
Author(s):  
Anne Gharaibeh ◽  
Abdulrazzaq Shaamala ◽  
Rasha Obeidat ◽  
Salman Al-Kofahi
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Cellular Automata ◽  
Land Use Change ◽  
Markov Chain Model ◽  
Chain Model ◽  
Land Use Change Modeling

scholarly journals Pemodelan Perubahan Tataguna Lahan Terhadap Debit Banjir DAS Tanggul, Jember Menggunakan Model SWAT (Soil and Water Assessment Tool)

2020 ◽  
Vol 14 (2) ◽  
pp. 154-161
Author(s):  
Diah Ainunisa ◽  
◽  
Gusfan Halik ◽  
Wiwik Yunarni Widiarti ◽  
◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Rainy Season ◽  
Model Calibration ◽  
Assessment Tool ◽  
Swat Model ◽  
Land Use Changes ◽  
Forest Land ◽  
Water Assessment ◽  
Soil And Water

Population growth is one of the causes of land-use change that can increase runoff. Tanggul watershed is one of the watersheds which often overflows during the rainy season. This study purpose to analyze the effect of land-use changes on runoff in Tanggul watershed using SWAT (Soil and Water Assessment Tool) model. To make sure the performance of SWAT model calibration and classified by the value of NSE and R2. The result of calibration included in a good category and validation included in a very good category. This study was modeling forest land-use change in 2004-2017 to determine the effect of land-use change on runoff. The result in this model of forest land-use change can increase runoff.

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