scholarly journals Monitoring Land Use Changes and Their Future Prospects Using GIS and ANN-CA for Perak River Basin, Malaysia

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2286
Author(s):  
Muhammad Talha Zeshan ◽  
Muhammad Raza Ul Mustafa ◽  
Mohammed Feras Baig
Keyword(s):  
Land Use ◽  
Information Systems ◽  
Geographic Information Systems ◽  
River Basin ◽  
Land Use Changes ◽  
Geographic Information ◽  
Kappa Coefficient ◽  
Urban Land Use ◽  
Lulc Changes ◽  
The Impact

Natural landscapes have changed significantly through anthropogenic activities, particularly in areas that are severely impacted by climate change and population expansion, such as countries in Southeast Asia. It is essential for sustainable development, particularly efficient water management practices, to know about the impact of land use and land cover (LULC) changes. Geographic information systems (GIS) and remote sensing were used for monitoring land use changes, whereas artificial neural network cellular automata (ANN-CA) modeling using quantum geographic information systems (QGIS) was performed for prediction of LULC changes. This study investigated the changes in LULC in the Perak River basin for the years 2000, 2010, and 2020. The study also provides predictions of future changes for the years 2030, 2040, and 2050. Landsat satellite images were utilized to monitor the land use changes. For the classification of Landsat images, maximum-likelihood supervised classification was implemented. The broad classification defines four main classes in the study area, including (i) waterbodies, (ii) agricultural lands, (iii) barren and urban lands, and (iv) dense forests. The outcomes revealed a considerable reduction in dense forests from the year 2000 to 2020, whereas a substantial increase in barren lands (up to 547.39 km2) had occurred by the year 2020, while urban land use has seen a rapid rise. The kappa coefficient was used to assess the validity of classified images, with an overall kappa coefficient of 0.86, 0.88, and 0.91 for the years 2000, 2010, and 2020, respectively. In addition, ANN-CA simulation results predicted that barren and urban lands will expand in the future at the expense of other classes in the years 2030, 2040, and 2050. However, a considerable decrease will occur in the area of dense forests in the simulated years. The study successfully presents LULC changes and future predictions highlighting significant pattern of land use change in the Perak River basin. This information could be helpful for land use administration and future planning in the region.

scholarly journals Pengaruh Perubahan Penggunaan Lahan Terhadap Insiden Penyakit Tuberkulosis Paru: Studi Di Provinsi Lampung

2017 ◽  
Vol 5 (1) ◽  
pp. 71
Author(s):  
Rita Rosari ◽  
Samsul Bakri ◽  
Trio Santoso ◽  
Dyah W.S.R Wardani
Keyword(s):  
Land Use ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Healthy Lifestyle ◽  
Land Use Changes ◽  
Geographic Information ◽  
Forest Plantation ◽  
Community Forest ◽  
Gis Software ◽  
Density Population

Deforestation and land conversion is one of the effects of high nativity rates and urbanizationthat affect the ecological situation.  The imbalance of ecological system become a factor ofincreasing pulmunary Tuberkulosis incidence (TB).  TB is a disease of pulmunary infectionsthat caused by the bacterium Mycobacterium tuberculosis, and it is spread directly.  Thisresearch was conducted to determine the contribution of land use changes incidence of TB inthe Lampung Province.  Land use changes be resultant through landsat imegeryinterpretation utilize Geographic Information Systems (GIS) software.  Parameter usedstatistical software, used the F test on the real level of 10%.  The result showed that therewere several factors that have real influence, namely; community forest with a coefficient of 1.0314(Pvalue=0.040), Clean and Healthy Lifestyle (PHBS) coefficient of -0.3691 (Pvalue=0.042), density population coefficient of 0.011661 (Pvalue=0.008) and the percentage of poorresident coefficient of 0.6641 (Pvalue=0.006).  While forest, plantation, developed land, healthfacility and healthy house did not have significant effect toward incidence of TB in Lampung Province.Keywords : deforestation, geographic information systems(GIS), incidence of TB, land use.

Application of Remote Sensing Technologies and Geographical Information Systems in Monitoring Environmental Degradation in the Lake Victoria Watershed, East Africa

2010 ◽  
pp. 431-455
Author(s):  
Charles K. Twesigye
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information Systems ◽  
Geographic Information Systems ◽  
River Basin ◽  
Environmental Degradation ◽  
Lake Victoria ◽  
Geographic Information ◽  
African Region ◽  
Gis And Remote Sensing

Accurate information on the state of water resources in the Lake Victoria watershed is crucial for planning and sustainable development in the East African region. This region largely depends on its natural resource-base for economic development, and therefore comprehensive information on its resources dynamics is key in implementing poverty alleviation strategies, improving human condition and preserving the biological systems upon which the region‘s population depends. This chapter focuses on key issues, which have emerged as a result of population growth and development in the region. The research on which this chapter is based aims to address the concerns on land use and settlement trends in the study sites, vulnerability of the communities to water stress and sustainability of the livelihood systems in the watersheds of Nzoia River Basin (Kenya), Nakivubo Wetland (Uganda) and Simiyu River Basin (Tanzania). These communities engage in unique land use practices that have intensified environmental degradation in recent times. The research adopts a multi-disciplinary approach in bringing to the fore the various processes affecting watershed resources use and management in the selected wetlands of the Lake Victoria Drainage Basin (LVDB). The data presented covers trends in vegetation cover loss, pesticide pollution and general water quality parameters. Geographic information systems (GIS) and remote sensing techniques were employed to unveil land use patterns that have resulted in the degradation of the watershed. Wetland degradation levels have been characterized using secondary data generated by analytical techniques. New emerging challenges of environmental degradation caused by industrial, domestic and agricultural activities are presented and discussed. The potential of the new science of hydroinformatics in integrated watershed management through mathematical modeling, geographic information systems analysis and water supply management is highlighted.

Application of Remote Sensing Technologies and Geographical Information Systems in Monitoring Environmental Degradation in the Lake Victoria Watershed, East Africa

2011 ◽  
pp. 653-677
Author(s):  
Charles K. Twesigye
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information Systems ◽  
Geographic Information Systems ◽  
River Basin ◽  
Environmental Degradation ◽  
Lake Victoria ◽  
Geographic Information ◽  
African Region ◽  
Gis And Remote Sensing

Accurate information on the state of water resources in the Lake Victoria watershed is crucial for planning and sustainable development in the East African region. This region largely depends on its natural resource-base for economic development, and therefore comprehensive information on its resources dynamics is key in implementing poverty alleviation strategies, improving human condition and preserving the biological systems upon which the region‘s population depends. This chapter focuses on key issues, which have emerged as a result of population growth and development in the region. The research on which this chapter is based aims to address the concerns on land use and settlement trends in the study sites, vulnerability of the communities to water stress and sustainability of the livelihood systems in the watersheds of Nzoia River Basin (Kenya), Nakivubo Wetland (Uganda) and Simiyu River Basin (Tanzania). These communities engage in unique land use practices that have intensified environmental degradation in recent times. The research adopts a multi-disciplinary approach in bringing to the fore the various processes affecting watershed resources use and management in the selected wetlands of the Lake Victoria Drainage Basin (LVDB). The data presented covers trends in vegetation cover loss, pesticide pollution and general water quality parameters. Geographic information systems (GIS) and remote sensing techniques were employed to unveil land use patterns that have resulted in the degradation of the watershed. Wetland degradation levels have been characterized using secondary data generated by analytical techniques. New emerging challenges of environmental degradation caused by industrial, domestic and agricultural activities are presented and discussed. The potential of the new science of hydroinformatics in integrated watershed management through mathematical modeling, geographic information systems analysis and water supply management is highlighted.

The Use of Geographic Information Systems (GIS) in Land Resources Appraisal

1994 ◽  
Vol 23 (4) ◽  
pp. 249-255 ◽  
Author(s):  
W.G. Sombroek ◽  
J. Antoine
Keyword(s):  
Land Use ◽  
Developing Countries ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Land Degradation ◽  
Geographic Information ◽  
Land Resource ◽  
Land Resources ◽  
Training Support ◽  
Village Communities

Nations, village communities and individual land users need to make choices about land use in order to support development without risk of land degradation. Computerized land information systems (LIS) based on geographic information systems (GIS) have emerged as powerful tools for generating maps and reports to inform such decisions. Recently, FAO has been developing GIS/LIS systems in linkage with its agroecological zoning (AEZ) and other models, and using them to tackle issues of land, food and people at global, national and subnational levels. They have been successfully developed for land resource management at different scales, but practical difficulties have been encountered in making them accessible to the casual user in most developing countries, due to scarcity of data and poor training support.

scholarly journals Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change

2020 ◽  
Vol 12 (7) ◽  
pp. 1186 ◽  
Author(s):  
A.-M. Olteanu-Raimond ◽  
L. See ◽  
M. Schultz ◽  
G. Foody ◽  
M. Riffler ◽  
...  
Keyword(s):  
Land Use ◽  
Change Detection ◽  
Urban Areas ◽  
Detection Algorithm ◽  
Geographic Information ◽  
Urban Land Use ◽  
Basic Knowledge ◽  
User Profiles ◽  
Local Authorities ◽  
The Impact

Land use and land cover (LULC) mapping is often undertaken by national mapping agencies, where these LULC products are used for different types of monitoring and reporting applications. Updating of LULC databases is often done on a multi-year cycle due to the high costs involved, so changes are only detected when mapping exercises are repeated. Consequently, the information on LULC can quickly become outdated and hence may be incorrect in some areas. In the current era of big data and Earth observation, change detection algorithms can be used to identify changes in urban areas, which can then be used to automatically update LULC databases on a more continuous basis. However, the change detection algorithm must be validated before the changes can be committed to authoritative databases such as those produced by national mapping agencies. This paper outlines a change detection algorithm for identifying construction sites, which represent ongoing changes in LU, developed in the framework of the LandSense project. We then use volunteered geographic information (VGI) captured through the use of mapathons from a range of different groups of contributors to validate these changes. In total, 105 contributors were involved in the mapathons, producing a total of 2778 observations. The 105 contributors were grouped according to six different user-profiles and were analyzed to understand the impact of the experience of the users on the accuracy assessment. Overall, the results show that the change detection algorithm is able to identify changes in residential land use to an adequate level of accuracy (85%) but changes in infrastructure and industrial sites had lower accuracies (57% and 75 %, respectively), requiring further improvements. In terms of user profiles, the experts in LULC from local authorities, researchers in LULC at the French national mapping agency (IGN), and first-year students with a basic knowledge of geographic information systems had the highest overall accuracies (86.2%, 93.2%, and 85.2%, respectively). Differences in how the users approach the task also emerged, e.g., local authorities used knowledge and context to try to identify types of change while those with no knowledge of LULC (i.e., normal citizens) were quicker to choose ‘Unknown’ when the visual interpretation of a class was more difficult.

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