Determination of the Change Detection in the Land Use/ Land Cover by Supervised Image Classification Technique using RS and GIS: A Case Study of Chitwan District
Authors:
✏️ Ram Kumar Adhikaria, Sagar Dhunganaa, Sudip Chauhana, Animesh Khadkab
aDepartment of Agricultural Engineering, Tribhuvan University, IOE Purwanchal Campus, Dharan, Nepal.
bGPKoirala College of Science and Technology, Purwanchal University, Gothgaun
Abstract:
Due to the increasing rate of population and unmanaged way of urbanization there arise many problems like degradation of cultivable land, deforestation and poorly maintained marginal land, landslides in Narayanghat-Mugling Highway. These problems can be managed using RS and GIS in which we analyze different land satellite images of the district for past 20 year in a interval of 10 years. After analyzing the land satellite images, we have idea to assess the pattern of changes in population, industrial development, and the area covered by agricultural and vegetation, as well as how these factors interact through time and the consequences on surface water supplies. The project's output aids in educating the public about deforested areas and in the development of the concepts of agroforestry, communal forests and managing related organization to make proper decision. After analysis it was found that between 1992 to 2002, there was a expansion of built up land and grassland from 0.74% to 1.02% and 1.16% to 2.8% followed by barren area from 0.81% to 2.67%, however forest area, crop land and water bodies shows a reduction from 66.8 % to 63.83%, 28.6% to 28.36% and 1.1% to 1.1% aerial coverage. On the other hand, in between 2002 to 2012, water bodies, forest and built up area shows increase in the aerial coverage from 1.1% to 2.7%, 63.83% to 64.9% and 1.02% to 1.6% respectively and there is decrease in cropland, barren land and grassland from 28.36% to 28.1%, 2.67% to 0.91% and 2.8% to 2.17% respectively. And at last in between 2012 to 2022, water bodies, forest and built up area shows increase in the aerial coverage from 2.7% to 4.09%, 64.9% to 67.7% and 1.6% to 3.44% respectively and there is decrease in cropland, barren land and grassland from 28.1% to 23.24%, 0.91% to 0.078% and 2.17% to 1.34% respectively The major possible driving forces for these changes were natural factors such as mostly flat slope, drought and climate change. The possible human driving factors include population growth and density, over intensification of land use, farm size, land tenure status, and policies on land use. These factors results in various forces and strong effect to change the quantity and quality of land use.
Keywords: Urbanization, Satellite images, RS, GIS,
1. Introduction:
The physical characteristics of the surface of the land, such as vegetation, water, crops, and urban infrastructure, are referred to as land cover (LC). LU is the adjustment of LC according to human needs and behaviors. The most accurate LU indicator is land cover (LC). Land use (LU) is the modification of land cover (LC) in response to human needs and actions. Land cover (LC) defines the physical properties on the surface of the land, such as forest, water, crops, and urban infrastructure. In environmental science and geography, the phrases land use and land cover (LULC) are used to refer to how people utilize and manage the land. The phrase "land use" describes the unique activities and procedures that are carried out on a given plot of land, such as farming, mining, or urban growth. The physical and biological elements that make up the land's surface, such as forests, grasslands, and water bodies, are referred to as land cover. In order to maintain biodiversity, support ecosystem services, and provide resources for human communities, LULC is a critical component of our planet's ecology. The best way to measure LU is through land cover (Mallupattu and Sreenivasula Reddy, 2013a). Changes in land use and land cover are acknowledged to be significant contributors to global environmental change and to the socioeconomic development of local communities. The term "Land Use and Land Cover" (LULC) refers to the physical and biological components of the earth's surface, such as the soil, water, plant, and man-made structures. For a variety of applications, such as environmental monitoring, natural resource management, urban planning, and disaster management, it is crucial to comprehend LULC and its changes through time (Hasen M.C, Potapov, 2013).On regional to global dimensions, changes in land use and land cover (LULC) have a significant impact on ecosystem functioning, ecosystem services, and biophysical and human factors like climate and governmental policies (Hussain et al., 2020).
LULC can be categorized and analyzed in a variety of ways, from straightforward visual interpretation of satellite imagery to sophisticated machine learning algorithms that can automatically recognize and map various land use and land cover patterns. Remote sensing, geographic information systems (GIS), and field surveys are some of the most used techniques for LULC analysis. A comprehensive overview of LULC patterns at regional or global scales can be obtained using remote sensing techniques like satellite and aerial imaging, while a more in-depth examination of LULC changes over time and space can be performed using GIS. To verify and improve the results of remote sensing and GIS, field surveys, such as vegetation sample or soil analysis, can give ground-truth data. An important technique for studying and increasing our understanding of the earth's physical processes is remote sensing. The mapping and monitoring of LULC has been made much easier thanks to remote sensing tools like satellite images and aerial photography. These methods make it possible to recognize and categorize different forms of land cover, including woods, wetlands, croplands, and urban areas, as well as to quantify changes in land use, such as logging, urbanization, and agricultural growth Utilizing the growing amount of geographic data made available by GIS in conjunction with satellite data is a recent trend in the usage of satellite data. GIS is an integrated system of computer hardware and software that can collect, store, retrieve, manipulate, analyze, and display spatially referenced information in order to support management and decision-making procedures that are geared toward advancing growth. Agriculture, the environment, and integrated eco-environment evaluation are just a few of the areas where remote sensing and GIS have a wide range of applications. Due to the negative consequences that LU/LC studies have on the local ecosystem and plants, many researchers have concentrated on them. (Mallupattu and Sreenivasula Reddy, 2013b)
Bharatpur, its largest metropolis, is one of Nepal's fastest-growing cities. The city has not been managed well as a result of this rapid population growth. There are haphazard settlements and unplanned places due to the rising rate of migration from mountainous areas, which results in the degradation of cultivable land. There are numerous rivers such the Narayani and Rapti, as well as lakes like Bishajari, Sorahajari and Nandavauju Lake. The perennial river Narayani has a lower rate of soil and water conservation, which contributes to land cutting, bank erosion, and soil erosion.
The scope and character of LULC changes in the Chitwan district throughout time have been recorded by numerous research. For instance, Paudel et al.'s (2019) analysis of LULC trends from 1990 to 2016 using remote sensing and GIS methodologies revealed that agricultural land rose by 12.9% while forest cover dropped by 26.1%. Devkota et al. (2021) examined the drivers of LULC changes in the Chitwan district and found that infrastructure development, agricultural expansion, and population growth were the key causes of these changes. Changes in land use and land cover have a substantial impact on the environment on a local, regional, and international level. Regional and worldwide loss of biodiversity, disturbances in hydrological cycles, an increase in soil erosion, and increased sediment loads are all severe effects of these changes (Mzuza et al., n.d.).It also have Chitwan National Park. The Chitwan district is mostly covered with forests, grasslands, marshes, and hilly terrain. Due to the increase in the population of the area resulting the maximum use of the forest area so there is an imbalance between the wild animals and humans, and the attacks of the wild animals have increased (Ruda et al., 2018).
2. Objectives
General objective:
To analyze the land use land cover change in the Chitwan district from 1992 to 2022.
Specific objectives:
To prepare map from satellite image using ArcGIS 10.5.
To assess the trajectory of changes in human habitation and the area used for agriculture and vegetation, as well as how these variables interact through time and what consequences there are for surface water supplies.
To make conclusions about how to manage the surface of the water resources.
To identify densely populated area and urban area.
To perform accuracy assessment of classified image
3. Significance of study
The study of the comparison provides ideas on:
Systematic planning of urban areas in an appropriate manner,
Main priority to improve in the affected areas.
Educating people about deforested areas and creating concepts for community and agroforestry
Judicious use of natural resources and management of those resources
4. Limitation of study
Some limitations are listed below:
Ground validation cannot be performed so that accuracy of change obtained is not completely accurate.
Due to more percentage of cloud cover, it is difficult to obtain clear Landsat images.
The area of different land cover classes obtained is not completely accurate because of pixel based classification system.
It is difficult to obtain Landsat data of same time period by which we cannot obtain more accurate result due to more difference in land use pattern.
5. Methodology
5.1 Study Area
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| Figure 1. Map of study area |
Using remote sensing and unique metrics approaches, data from primary and secondary sources were processed and evaluated to quantify LULC. This study, as previously stated, employs remote sensing and spatial metrics methodologies to measure land use and land cover change and patterns. Remote sensing image classification is a useful tool for determining the amount and pace of land use and land cover change, whereas spatial metrics are derived using the remote sensing image classification results to quantify land use and land cover change. Both are thought to improve understanding of land use and land cover change. The methods are also quick ways to obtain useful information when spatial data is lacking.
5.2 Research Design
 |
| Figure 2. Research Design |
6. Result
A classification system was devised for the study region based on prior knowledge of the area that dates back more than 30 years, a quick reconnaissance assessment, and additional data from earlier studies in the area. The LULC was identified by a single number under the categorization system, which provides a rather broad classification included. A computer application can compare the area of various land uses cell by cell by superimposing them on maps. Six distinct land use and land cover categories were discovered using supervised classification tools. These consist of bodies of water, forests, shrubs, cropland, and barren areas.
Table: Estimation of Landcover
7. Conclusion
This study focuses on LULC analysis of Chitwan district over the past four decades. Four-year 1992, 2002, 2012 and 2022 are taken for image analysis and the data obtained from USGS website were pre-processed and analyzed using supervised classification After the analysis of data into different land cover classes, accuracy assessment of the data was done by calculating error matrix presented above. From 1992 to 2002, there is decrease in forest from 66.8% to 63.83%, the forest area from 2002 to 2012 increases in % from 63.83 to 64.9 and trends shows there is increase in forest area from 64.9% to 67.7% in between 2012-2022. There is increase in forest area because of concept of community forest and agro- forestry especially on the northern belt of Terai areas. For water body, there is decrease in % from 1.9 to 1.1 from 1992-2002, increase in % from 1.1 to 2.67 from 2002-2012 and again increase in % from 2.67 to 4.09 from 2012 to 2022 as shown in figure above. This may be due to increase in rainfall in the northern belt according to LULC map presented above which abruptly increases level of water.
Due to the decrease in water body, there is increase in grassland from 1992-2002 from 1.16% to 2.8%, the grassland from 2002 to 2012 decreases in % from 2.8 to 2.17 and there is decrease in grassland from 2.17% to 1.34% in between 2012- 2002. Similarly for crop land, the crop land remains almost same from 1992 to 2002 and there is decrease in cropland in % from 28.36 to 28.1 in between 2002-2012. And again, there is decrease in crop land from 28.1% to 23 24%in between 2012-2022.
For built-up area, there is increase in built up area in % from 0.74 to1.02 from 1992 to 2002, again there is increase in built up area in % from 1.02 to 1.6 in between 2002-20012. And there is again increase in built up area in % from 1.6 to 3.44 in between 2012-2022. The increase in built up area because of migration of people from rural area to urban area. In Chitwan district there are two main area where the population density has increased randomly i.e Bharatpur and Ratangar. For the barren area there is increase in barren area from 0.81% to 2.67% in between 1192-2002, the barren area from 2002 to 2012 decreases in % from 2.67 to 0.91 and again there is decrease in barren area from 0.91% to 0.078% in between 2012-2022.
This change is due to agro-forestry and community forest development.
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