scholarly journals Predicting the Future Land Use and Land Cover Changes for Bhavani Basin, Tamil Nadu, India Using QGIS MOLUSCE Plugin

2021 ◽  
Author(s):  
manikandan kamaraj ◽  
Sathyanathan Rangarajan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Tamil Nadu ◽  
Land Use Changes ◽  
Significant Rise ◽  
Substantial Impact ◽  
The Road ◽  
Land Cover Dynamics ◽  
Kappa Value ◽  
Perception Model

Abstract Human population growth, movement, and demand have a substantial impact on land use and land cover dynamics. Thematic maps of land use and land cover (LULC) serve as a reference for scrutinizing, source administration, and forecasting, making it easier to establish plans that balance preservation, competing uses, and growth compressions. The objective of this study is to identify the changeover of land-use changes in the Bhavani basin for the two periods 2005 and 2015, as well as to forecast and establish potential land-use changes in the year 2025 and 2030 by using QGIS 2.18.24 version MOLUSCE plugin (ANN-Multi layer perception) model.The five criteria, such as DEM, gradient, aspect, distance from the road and river, and built-up density, are used as spatial variable maps in the processes of learning in ANN-Multi layer perception to predict their influences on LULC between 2005 and 2010 and it was found that DEM, distance from the road and river, and built-up density have significant effects. The projected and accurate LULC maps for 2015 indicate a good level of accuracy, with an overall Kappa value of 0.69 and with a percentage of the correctness 76.28 %. ANN-Multi-layer perception model is then used to forecast changes in LULC for the years 2025 and 2030 which shows significant rise in cropland and built-up areas, by 20 km2 and 10 km2 respectively. The findings assist farmers and policymakers in developing optimal land use plans and better management techniques for the long-term development of natural resources.

scholarly journals Land Use and Land Cover Dynamics Analysis of the Togodo Protected Area and Its Surroundings in Southeastern Togo, West Africa

2020 ◽  
Vol 12 (13) ◽  
pp. 5439 ◽  
Author(s):  
Amah Akodéwou ◽  
Johan Oszwald ◽  
Slim Saïdi ◽  
Laurent Gazull ◽  
Sêmihinva Akpavi ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Protected Area ◽  
Land Use Changes ◽  
Management Policy ◽  
Clear Understanding ◽  
Lulc Change ◽  
Land Cover Dynamics ◽  
Rapid Changes ◽  
Full Picture

Assessing land use and land cover (LULC) change is essential for the sustainable management of natural resources, biodiversity conservation, monitoring food security, and research related to climate change and ecology. With increasingly rapid changes in LULC in response to human population growth, a better assessment of land use changes is more necessary than ever. Although a multitude of LULC assessment methods exists, none alone provides a clear understanding of changes and their underlying factors. This study analysed historical LULC changes over a temporal extent of 42 years (1974–2016) in the Togodo Protected Area and its surroundings, in Togo, by associating intensity and trajectory analyses, that are complementary but rarely associated in the literature. Our results show that LULC change in our study site is linked to the combined effects of human activities, climate, and invasive plants, particularly Chromolaena odorata. While each type of analysis provides useful insights, neither intensity nor trajectory analysis alone provides a full picture of changes and their causes. This study highlights the usefulness of associating intensity and trajectory analyses when implementing any management policy.

scholarly journals Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand

2012 ◽  
Vol 7 (No. 1) ◽  
pp. 10-17 ◽  
Author(s):  
S. Wijitkosum
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
National Park ◽  
Land Use Changes ◽  
Influential Factors ◽  
Geographical Information ◽  
Adjacent Area ◽  
Erosion Risk ◽  
Study Results

Soil erosion has been considered as the primary cause of soil degradation since soil erosion leads to the loss of topsoil and soil organic matters which are essential for the growing of plants. Land use, which relates to land cover, is one of the influential factors that affect soil erosion. In this study, impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand, were investigated by applying remote sensing technique, geographical information system (GIS) and the Universal Soil Loss Equation (USLE). The study results revealed that land use changes in terms of area size and pattern influenced the soil erosion risk in Pa Deng in the 1990–2010 period. The area with smaller land cover obviously showed the high risk of soil erosion than the larger land cover did.

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.

Land Use and Land Cover Dynamics

2020 ◽  
pp. 39-60
Author(s):  
Bharath H. Aithal ◽  
T. V. Ramachandra ◽  
M. C. Chandan ◽  
G. Nimish ◽  
S. Vinay ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Dynamics
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