scholarly journals The effect of urbanization on precipitation excess in Thi Tinh Basin

2016 ◽  
Vol 19 (2) ◽  
pp. 67-78
Author(s):  
Viet Van Luong
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Curve Number ◽  
Urban Drainage ◽  
Landsat Images ◽  
Loss Model ◽  
Remarkable Increase ◽  
Scs Curve Number ◽  
Study Results ◽  
Developing Area

Thi Tinh Basin is one of fastest developing area. The urbanization is cause of land use change, which leading the reducing of abtraction and increating of the precipitation excess. The increase of precipitation excess due to urbanization will influence on the urban drainage systems. The purpose of this paper is study of the effect of urbanization on the precipitation excess in Thi Tinh Basin, from 1989 to 2014 and masterplan to 2020. The Method used for these study is SCS Curve Number Loss Model, with landuse data were performed from Landsat Images. The study results show a remarkable increase in the precipitation excess. From 1989 to 2014, precipitation excess was increased 12,9% on the Thi Tinh Basin. On the masterplan to 2020, the accumulated precipitation excess is rather high, for the 180 minutes design hyetograph with period of 10 years repeated, it is from 66,3mm to 94,9mm on the Basin.

A GIS-Based Irregular Cellular Automata Model of Land-Use Change

2007 ◽  
Vol 34 (4) ◽  
pp. 708-724 ◽  
Author(s):  
Daniel Stevens ◽  
Suzana Dragićević
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Spatial Data ◽  
Cellular Automata Model ◽  
Population Growth Rates ◽  
Asynchronous Development ◽  
Canadian City ◽  
Ca Model ◽  
Developing Area

This study proposes an alternative cellular automata (CA) model, which relaxes the traditional CA regular square grid and synchronous growth, and is designed for representations of land-use change in rural-urban fringe settings. The model uses high-resolution spatial data in the form of irregularly sized and shaped land parcels, and incorporates synchronous and asynchronous development in order to model more realistically land-use change at the land parcel scale. The model allows urban planners and other stakeholders to evaluate how different subdivision designs will influence development under varying population growth rates and buyer preferences. A model prototype has been developed in a common desktop GIS and applied to a rapidly developing area of a midsized Canadian city.

Xinanjiang model combined with Curve Number to simulate the effect of land use change on environmental flow

2014 ◽  
Vol 519 ◽  
pp. 3142-3152 ◽  
Author(s):  
Kairong Lin ◽  
Fushui Lv ◽  
Lu Chen ◽  
Vijay P. Singh ◽  
Qiang Zhang ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Curve Number ◽  
Environmental Flow ◽  
Xinanjiang Model

scholarly journals When to Detect Changes in Object-Based Image Analysis: Before or after Classification?

2017 ◽  
Author(s):  
Kaisheng Luo ◽  
Fu-lu Tao ◽  
Juana P. Moiwo
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Change Detection ◽  
Coniferous Forest ◽  
Detection Methods ◽  
Landsat Images ◽  
Two Stage ◽  
Smoothing Effects ◽  
Stage Classification ◽  
Elevation Model

This study compared two object-oriented land use change detection methods—detection after classification (DAC) and classification after detection (CAD) —based on a digital elevation model, slope data, and multi-temporal Landsat images (TM image for 2000 and ETM image for 2010). We noted that the overall accuracy of the DAC (86.42%) was much higher than that of the CAD (71.71%). However, a slight difference between the accuracies of the two methods exists for deciduous broadleaf forest, evergreen coniferous forest, mixed wood, upland, paddy, reserved land, and settlement. Owing to substantial spectrum differences, these land use types can be extracted using spectral indexes. The accuracy of DAC was much higher than that of CAD for industrial land, traffic land, green shrub, reservoir, lake, river, and channel, all of which share similar spectrums. The discrepancy was mainly because DAC can completely utilize various forms of information apart from spectrum information during a two-stage classification. In addition, the change-area boundary was not limited at first, but was adjustable in the process of classification. DAC can overcome smoothing effects to a great extent using multi-scale segmentations and multi-characters in detection. Although DAC yielded better results, it was more time-consuming (28 days) because it uses a two-stage classification approach. Conversely, CAD consumed less time (15 days). Thus, a hybrid of the two methods is recommended for application in land use change detection.

scholarly journals ANALYSIS OF RELATIONSHIP BETWEEN URBAN HEAT ISLAND EFFECT AND LAND USE/COVER TYPE USING LANDSAT 7 ETM+ AND LANDSAT 8 OLI IMAGES

2016 ◽  
Vol XLI-B8 ◽  
pp. 821-828
Author(s):  
N. Aslan ◽  
D. Koc-San
Keyword(s):  
Land Use ◽  
Land Surface ◽  
Vegetation Index ◽  
Irrigated Agriculture ◽  
Time Interval ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Landsat Images ◽  
Study Results ◽  
Landsat 7

The main objectives of this study are (i) to calculate Land Surface Temperature (LST) from Landsat imageries, (ii) to determine the UHI effects from Landsat 7 ETM+ (June 5, 2001) and Landsat 8 OLI (June 17, 2014) imageries, (iii) to examine the relationship between LST and different Land Use/Land Cover (LU/LC) types for the years 2001 and 2014. The study is implemented in the central districts of Antalya. Initially, the brightness temperatures are retrieved and the LST values are calculated from Landsat thermal images. Then, the LU/LC maps are created from Landsat pan-sharpened images using Random Forest (RF) classifier. Normalized Difference Vegetation Index (NDVI) image, ASTER Global Digital Elevation Model (GDEM) and DMSP_OLS nighttime lights data are used as auxiliary data during the classification procedure. Finally, UHI effect is determined and the LST values are compared with LU/LC classes. The overall accuracies of RF classification results were computed higher than 88&thinsp;% for both Landsat images. During 13-year time interval, it was observed that the urban and industrial areas were increased significantly. Maximum LST values were detected for dry agriculture, urban, and bareland classes, while minimum LST values were detected for vegetation and irrigated agriculture classes. The UHI effect was computed as 5.6&thinsp;&deg;C for 2001 and 6.8&thinsp;&deg;C for 2014. The validity of the study results were assessed using MODIS/Terra LST and Emissivity data and it was found that there are high correlation between Landsat LST and MODIS LST data (r<sup>2</sup>&thinsp;=&thinsp;0.7 and r<sup>2</sup>&thinsp;=&thinsp;0.9 for 2001 and 2014, respectively).

scholarly journals Assessing the Effect of Land Use Change on Surface Runoff in a Rapidly Urbanized City: A Case Study of the Central Area of Beijing

Land ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 17 ◽  
Author(s):  
Shanshan Hu ◽  
Yunyun Fan ◽  
Tao Zhang
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Correlation Analysis ◽  
Surface Runoff ◽  
Flood Control ◽  
Central Area ◽  
Dominant Factor ◽  
Landsat Images ◽  
Rapid Urbanization ◽  
The Impact

The change in land use during the process of urbanization affects surface runoff and increases flood risk in big cities. This study investigated the impact of land use change on surface runoff in Beijing’s central area during the period of rapid urbanization from 1984 to 2019. Land use maps of 1984, 1999, 2009, and 2019 were generated by image classification of Landsat images. Surface runoffs were calculated with the Soil Conservation Service curve number (SCS-CN) model. Correlation analysis was used to identify the dominant factor of land use change affecting surface runoff. The result showed that the variation trend of surface runoff was consistent with the trend of impervious land in Beijing’s central area, which increased during 1984~2009 and decreased during 2009~2019. Correlation analysis showed that changes in surface runoff were most strongly correlated with changes in impervious surfaces when compared with the correlation of runoff with other types of land use. The results of this study may provide a reference for city flood control and urban planning in fast growing cities worldwide, especially in developing countries.

scholarly journals Spatiotemporal Dynamics of Ecosystem Service Value Determined by Land-Use Changes in the Urbanization of Anhui Province, China

2019 ◽  
Vol 16 (24) ◽  
pp. 5104 ◽  
Author(s):  
Sai Hu ◽  
Longqian Chen ◽  
Long Li ◽  
Bingyi Wang ◽  
Lina Yuan ◽  
...  
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
Ecosystem Service ◽  
Water Area ◽  
Anhui Province ◽  
Ecosystem Service Value ◽  
Service Value ◽  
Study Results ◽  
The Impact

Urbanization-induced land-use change will lead to variations in the demand and supply of ecosystem services, thus significantly affecting regional ecosystem services. The continuous degradation of ecosystem functions has become a serious problem for humanity to solve. Therefore, quantitative analysis of the corresponding impact of land-use change on ecosystem service value (ESV) is important to socio-economic development and ecological protection. The Anhui province in China has experienced rapid urbanization in recent years, and ecological environmental remediation and protection have become important goals for regional development. In this paper, the province of Anhui has been selected as a case of study, we analyzed the land-use change using Landsat images from 2000, 2005, 2010, and 2015. We then adjusted the equivalent factor of ESV per unit area and estimated the ESV of Anhui province from 2000 to 2015 to analyze the impact of land-use change on ESV. Our results show that (1) paddy field is the main land-use type in Anhui province, the built-up land area has continuously increased, and the water area has continuously decreased; (2) the total ESV of Anhui province decreased from 30,015.58 × 107 CNY in 2000 to 29,683.74 × 107 CNY in 2015 (the rate of change was −1.11%), and regulating services make the greatest contribution to ESV; and (3) land-use change has led to severe ESV variations, especially for the expansion of water area and built-up land. Our study results provide useful insights for the development of land-use management and environmental protection policies in Anhui province.

Land use change using Landsat images over 23 years in a municipality of Central Mexico

2014 ◽  
Author(s):  
Miguel Jorge Escalona Maurice ◽  
Jose Sancho Comins ◽  
Yolanda Margarita Fernandez Ordonez ◽  
Maria Josefa Jimenez Moreno ◽  
Abdul Khalil Gardezi
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Central Mexico ◽  
Landsat Images

scholarly journals Surface Runoff Responses to Suburban Growth: An Integration of Remote Sensing, GIS, and Curve Number

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 452
Author(s):  
Khurshid Jahan ◽  
Soni M. Pradhanang ◽  
Md Abul Ehsan Bhuiyan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Surface Runoff ◽  
Agricultural Land ◽  
Curve Number ◽  
Integrated Approach ◽  
Substantial Impact ◽  
Sensing Applications ◽  
Scs Cn

Suburban growth and its impacts on surface runoff were investigated using the soil conservation service curve number (SCS-CN) model, compared with the integrated advanced remote sensing and geographic information system (GIS)-based integrated approach, over South Kingston, Rhode Island, USA. This study analyzed and employed the supervised classification method on four Landsat images from 1994, 2004, 2014, and 2020 to detect land-use pattern changes through remote sensing applications. Results showed that 68.6% urban land expansion was reported from 1994 to 2020 in this suburban area. After land-use change detection, a GIS-based SCS-CN model was developed to examine suburban growth and surface runoff estimation. The developed model demonstrated the spatial distribution of runoff for each of the studied years. The results showed an increasing spatial pattern of 2% to 10% of runoff from 1994 to 2020. The correlation between runoff co-efficient and rainfall indicated the significant impact of suburban growth in surface runoff over the last 36 years in South Kingstown, RI, USA, showing a slight change of forest (8.2% area of the total area) and agricultural land (4.8% area of the total area). Suburban growth began after 2000, and within 16 years this land-use change started to show its substantial impact on surface runoff. We concluded that the proposed integrated approach could classify land-use and land cover information to understand suburban growth and its potential impact on the area.

scholarly journals Modelling forest loss and other land use change dynamics in Ashanti Region of Ghana

2015 ◽  
Vol 57 (2) ◽  
pp. 96-111 ◽  
Author(s):  
Addo Koranteng ◽  
Tomasz Zawila-Niedzwiecki
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Agricultural Land ◽  
Combination Method ◽  
Agricultural Land Use ◽  
Landsat Images ◽  
Ashanti Region ◽  
Disaster Monitoring

Abstract Forest losses amid land use dynamics have become issues of outermost concern in the light of climate change phenomenon which has captivated the world’s attention. It is imperative to monitor land use change and to forecast forms of future land use change on a temporal and spatial basis. The main thrust of this study is to assess land use change in the lower half of the Ashanti Region of Ghana within a 40 year period. The analysis of land use change uses a combination method in Remote Sensing (RS) and Geographic Information System (GIS). Cellular Automata and Markov Chain (Cellular Automata-Markov) are utilized to predict for land use land cover (LULC) change for 2020 and 2030. The processes used include: (i) a data pre-processing (geometric corrections, radiometric corrections, subset creation and image enhancement) of epoch Landsat images acquired in 1990, 2000, and Disaster Monitoring Constellation (DMC) 2010; (ii) classification of multispectral imagery (iii) Change detection mapping (iv) using Cellular Automata-Markov to generate land use change in the next 20 years. The results illustrate that in years 2020 to 2030 in the foreseeable future, there will an upsurge in built up areas, while a decline in agricultural land use is envisaged. Agricultural land use would still be the dominant land use type. Forests would be drastically reduced from close to 50% in 1990 to just fewer than 10% in 2030. Land use decision making must be very circumspect, especially in an era where Ghana has opted to take advantage of REDD+. Studies such as this provide vital pieces of information which may be used to monitor, direct and influence land use change to a more beneficial and sustainable manner

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