scholarly journals Predicting land use change base on GIS and remote sensing

2020 ◽  
Vol 61 (2) ◽  
pp. 106-115 ◽  
Author(s):  
Nga Thu Thi Nguyen ◽  
Hanh Thi Tong ◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Landsat Images ◽  
Rapid Urbanization ◽  
Gis And Remote Sensing ◽  
The Neural Network ◽  
Rapid Changes ◽  
Urban Planning And Development ◽  
Land Use Development

The process of urbanization in Vietnam is developing rapidly, corresponding to the rapid changes in land use. Forecasting land use development assists policymakers in making accurate decisions in urban planning and development. The objective of this paper is to forecast and analyze land use development trends based on Landsat images in 2006, 2010, and 2016 with the help of remote sensing and GIS, a case study at Gio Linh district, Quang Tri province. The analysis results show that the rapid urbanization in Gio Linh district has led to a rapid decrease in the forest area from 28.14% compared to the total area, in 2016 to 13.5%, in 2026 to 2.67% and 2036 to 0.33%. The forecast processing was done on the neural network built-in module in the Selva version of IDRISI. The accuracy achieved is 80.5%.

scholarly journals Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 12 ◽  
Author(s):  
Mohd Khairul Amri Kamarudin ◽  
Kabir Abdulkadir Gidado ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Roslan Umar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Geographical Information ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Multi Temporal ◽  
Vegetation Water

Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC found to be 100%, 88.83%, 86.15%, 81.91% in 1976, 1989, 2001 and 2016 respectively. While water body accounts for 0%, 11.17%, 12.36% and 13.62% in the years 1976, 1989, 2001 and 2016 respectively and built-up area 1.49% and 4.47 in 2001 and 2016 respectively. The predominant LC changes in the study are the water body and vegetation, the earlier increasing rapidly at the expense of the later. Therefore, proper monitoring, policies that integrate conservation of the environment are strongly recommended. 

scholarly journals Application of GIS and Remote Sensing Technique to Change Detection in Land Use/Land Cover Mapping of Igbokoda, Ondo State, Nigeria

1970 ◽  
Vol 3 (1) ◽  
Author(s):  
James R. Adewumi ◽  
James K. Akomolafe ◽  
Fidelis O. Ajibade ◽  
Blessing B. Fabeku
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Rapid Change ◽  
Land Use Land Cover ◽  
Remotely Sensed Data ◽  
Landsat Images ◽  
Annual Increment ◽  
Rapid Urbanization

This paper aims at establishing changes in land use and land cover in Igbokoda municipality using Geographic Information System and remote sensing techniques. Three satellite images for three different epochs 1986, 1999 and 2013 were used to produce a land use/land cover map classification for Igbokoda. In determining the extent of land use/land cover changes in the township from 1986 through 1999 to 2013, Landsat images of the town were downloaded from the United State Geological Survey online archive. The images were analyzed using change detection technique (NDVI differencing) along with SRTM 90m DEM of the study area to generate the extent of the changes that have occurred. Ground trotting was carried out to ascertain the accuracy of data and the major changes in the land use/land cover. Results show that vegetation has decreased from 75.04% in 1986 to 46.81% in 2013 which was due to increase in population and rapid urbanization. In 1996 the Built-up area covers 19.6321 km2 of the study area but has increased rapidly to 39.1505 km2 in the year 1999 with an average annual increment of 2.025Km2/year. By the year 2013, the built-up area has increased to 64.1520Km2. Also in the same vein, the bare surface area which was 13.28029km2 in 1986 was increased to 39.6053 and 50.240Km2 in 1999 and 2013 respectively. On the contrary, the vegetated area of Igbokoda reduced from 196.3046Km2 in 1999 to 122.4680Km2 in 2013. This study has demonstrated that remotely sensed data and GIS based approach is timely and cost effective than the conventional method of analysis, classification of land use pattern effective for planning and management. It further shows that If the rapid change in land use is not properly manage, the situation poses a serious threat to Igbokoda town by increasing surface runoff and susceptibility to flooding.

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