The Banepa Municipality's variations in land use and land cover are examined in this paper. In particular, it makes an effort to study the spatial pattern of land use and land cover changes over time within the municipality. The paper deals with the effects of LULC change on the local climate, the accessibility of open space, and integration with the REDD approach. The relationship between climate change and the significance of REDD implementation is well-explained in the paper. Without using a systematic model, an analysis of the growing built-up area in relation to transportation, carbon emissions, the decline of the carbon sink caused by less forest cover, and a comparison of the land cover classes over the three-decade period from 1991 to the present are presented and discussed. Use of satellite imagery in the spatial analysis to integrate land cover land use with another domain (climate) is focused in the paper.

1. ANALYSIS OF LAND USE LAND COVER CHANGE OF
BANEPA FROM REDD PERSPECTIVE
Sujan Ghimire
sujanghimire500@gmail.com
Key words: Land cover, Land use, LULCC, Climate, REDD, CBD
Abstract
The Banepa Municipality's variations in land use and land cover are examined in this paper. In
particular, it makes an effort to study the spatial pattern of land use and land cover changes over
time within the municipality. The paper deals with the effects of LULC change on the local climate,
the accessibility of open space, and integration with the REDD approach. The relationship between
climate change and the significance of REDD implementation is well-explained in the paper.
Without using a systematic model, an analysis of the growing built-up area in relation to
transportation, carbon emissions, the decline of the carbon sink caused by less forest cover, and a
comparison of the land cover classes over the three-decade period from 1991 to the present are
presented and discussed. Use of satellite imagery in the spatial analysis to integrate land cover land
use with another domain (climate) is focused in the paper.
1. Introduction
1.1 Background
By acquiring carbon credits from developing nations, the Reducing Emissions from Deforestation
and Forest Degradation (REDD) strategy enables industrialized nations to offset their emissions.
By planting more trees and expanding the carbon sink, developing nations lower their emissions.
It is a win-win concept whereby industrialized nations are expected to pay less than half the rates
of other types of carbon credits while poor nations can be rewarded for their usage of land. REDD
and land use planning work together to reduce greenhouse gas emissions. In order to ensure
socioeconomic and environmental advantages, land use planning determines the key regions for
REDD implementation where there is the most opportunity to decrease or squatter carbon
emissions. Although the keywords land cover and land use are frequently used interchangeably,
they have quite different meanings. (Nibanupudi & Shaw, 2015)The surface cover on the ground,

2. whether it is vegetation, urban infrastructure, water, bare soil, or some other, is referred to as land
cover. For global monitoring studies, resource management, and planning operations, identifying,
defining, and mapping, land cover is critical. Land cover identification creates a baseline from
which monitoring operations (change detection) can be carried out, as well as providing ground
cover data for baseline thematic maps.
The term "land use" is used to describe how people use land. It depicts the economic and cultural
activities (such as agricultural, residential, industrial, mining, and recreational uses) carried out in
a certain location (Land Use, 2021). Land use and land cover change (LULCC) refers to human
modification of the terrestrial surface of the Earth (Elis, 2006). Grazing, shifting cultivation,
deforestation, urbanization, and land degradation have all played significant roles in LUCC in the
past (Paudel, et al., 2016).
Globally, agriculture and associated land use changes have been the principal drivers of
deforestation and were responsible for 24% of global greenhouse gas (GHG) emissions in 2010.
The UN-REDD Program stands for the United Nations Collaborative Initiative on Reducing
Emissions from Deforestation and Forest Degradation (REDD) in Developing Countries. The
program was launched in September 2008 with the purpose of aiding developing countries with
the implementation of their national REDD+ programs. The purpose of REDD is to encourage
developing countries to protect, properly manage, and utilize their forest resources wisely, thereby
assisting in the global fight against climate change.
In brief and to be precise, we plan to perform geo-spatial analysis through ArcGIS on the Remote
Sensing imagery data of LULC and create maps for the change detection in a decade interval. The
maps with the help of different interpretation along with statistical table will help us detect the
change in the LULC of Banepa Municipality of Nepal. Ultimately, we will interpret the final
outcome through REDD perspective in Nepal.

3. 1.2. Objectives
Following are the objectives of our project:
• To create LULC map of Banepa
• To detect change in land-use over three decades in Banepa
• To analyze the land-use change from REDD perspective
2. Methodology
2.1 Study Area
Banepa Municipality, which is the subject of our study, is one of the eastern Bagmati region's most
dynamic commercial hubs. Our study site was the Banepa Municipality because it has historically
been a significant trading hub on the Araniko Highway-based trade route that connects Nepal and
Tibet. We choose Banepa municipality as our study area due to the municipality's rapid urban
development. In Banepa, a sizable portion of land being urbanized every year while the amount of
agricultural and forested land is rapidly declining.
Figure 1: Location map of study area

4. 2.2 Working Procedure
For the area of our interest, Earth satellite images are retrieved. Therefore, georeferencing of the
acquired imageries has been done before doing spatial analysis. The geo-referenced photos are
subjected to maximum likelihood classification, which uses trained samples and a signature file to
perform supervised classification on the data. After classification, a LULC map is produced. Then,
a LULC map for Banepa Municipality is created by extracting the necessary region of interest, in
this case, Banepa Municipality, from the raster. The LULC map of Banepa is created and examined
for the years 1991, 2001, 2011, and 2021 using a similar process.
3. Results and Analysis
LULC map of Banepa Municipality was obtained from 1991 to 2021at interval of decade.
Classification of the land use/land cover gives an insight in the information about the area of land
covered by the different classes (Forest, Agricultural Land, Barren Land and Built-up). Obtained
statistics are presented here in chart for respective year.
3.1 Analysis of LULC for 1991
Classification and analysis of the images of 1991 shows there is abundance of forest and the
agricultural land. Table 1 shows the class-wise area and percentage in 1991. It shows that among
a total of 54577239.36 m2
of the municipality, forest cover 42%, agricultural land cover 44%,
barren land cover 10% and built-up cover 4%. It shows that only the city center is somewhat
densely populated. Outer ring of the city center had a very sparse built-up. Agricultural land and
forest covered most of the area during that time. Pie chart shows the percentage-wise distribution
of the LULC classes.
Table 1: Statistical distribution of LULC classes of Banepa in 1991
S.N. Class Area (m2
) Percentage (%)
1 Forest 23056066.96 42
2 Agricultural Land 23997145.56 44
3 Barren Land 5510578.67 10
4 Built-up 2013448.17 4

5. Figure 2: Pie-chart showing percentage of LULC classes in 1991
Forest
%
42
Agricultural Land
44%
Barren Land
10%
Built-up
%
4
percentage %
Forest Agricultural Land Barren Land Built-up

6. Figure 3: LULC map of Banepa in 1991

7. 3.2 Analysis of LULC for 2001
Table 2 shows the class-wise area and percentage in 2001. It shows that among total area of the
municipality, forest cover 41%, agricultural land cover 41%, barren land cover 9% and built-up
cover 9%. It shows that the city center (CBD) is populated and very few places outside of CBD is
populated. The expansion of built-up is not seen to have followed any model. Increase in built-up
over a decade is seen very critical i.e. doubling of built-up increase is witnessed. Core city has been
compact but still Built-up is sparse and is very slowly growing far apart from the CBD. Agricultural
land and forest still covers most of the area but a slight decrease in forest area despite different
approaches of forest protection is seen. Carbon sink is not only related to but also to the green
vegetation and the agricultural land is seen to have been decreased by 4% in just a decade with a
5% increase of the built-up, which is not a good sign for REDD implementation. Pie chart shows
the percentage-wise distribution of the LULC classes.
Table 2: Statistical distribution of LULC classes of Banepa in 2001
S.N. Class Area (m2
) Percentage (%)
1 Forest 22509308.48 41
2 Agricultural Land 22477677.06 41
3 Barren Land 4769846.17 9
4 Built-up 4820407.65 9
Forest
%
41
Agricultural Land
41%
Barren Land
9%
Built-up
%
9
Percentage (%)
Forest Agricultural Land Barren Land Built-up

8. Figure 4: Pie-chart showing percentage of LULC classes in 2001
Figure 5: LULC map of Banepa in 2001

9. 3.3 Analysis of LULC for 2011
Statistics shows that the municipality is getting critical from REDD perspective. The total forest
coverage has declined to 39%, agricultural land has declined than of 1991 but slightly increased
than of 2001 although there is increase in the built-up by 3% from 2001 to 2011. It seems that the
forest area might have been encroached for the agricultural purpose. Declination of barren land by
2% is a good sign from the REDD perspective that helps increase in capacity of carbon sink but is
not capable of compensating the 3% decline of forest cover. CBD is getting more compact without
leaving any open spaces in between. This haphazard expansion of built-up, more compact builtup
obviously requires more vehicles which are responsible for increasing carbon emission and
decreasing of carbon sink. Pie chart shows the percentage-wise distribution of the LULC classes.
Table 3: Statistical distribution of LULC classes of Banepa in 2011
S.N. Class Area (m2
) Percentage (%)
1 Forest 21492196.1 39
2 Agricultural Land 23123057.49 42
3 Barren Land 3498593.25 7
4 Built-up 6463392.52 12
Forest
%
39
Agricultural Land
42%
Barren Land
7%
Built-up
%
12
Percentage (%)
Forest Agricultural Land Barren Land Built-up

10. Figure 6: Pie-chart showing percentage of LULC classes in 2011
Figure 7: LULC map of Banepa in 2011

11. 3.4 Analysis of LULC for 2021
LULC map and associated statistical attributes shows there is a declining trend in the forest cover
but a slight increase in the agricultural land. Barren land has decreased to 3%. It seems that the
barren land has been utilized for agricultural purpose but map shows the distribution of barren land
is changing from one place to other. Barren land was seen around the city center as well in prior
decades but now has been detected in peripheral region or outward from the CBD. 3% increase in
built-up is witnessed, which shows city is getting even more compact and built-up is expanding
outwards from the core city as well. Increasing built-up by decreasing forest cover and barren land
shows there is more flow of people towards the core city. Pie chart shows the percentage-wise
distribution of the LULC classes.
Table 4: Statistical distribution of LULC classes of Banepa in 2021
S.N. Class Area (m2
) Percentage (%)
1 Forest 20130152.65 37
2 Agricultural Land 24655309.76 45
3 Barren Land 1366084.68 3
4 Built-up 8425692.278 15
Forest
%
37
Agricultural Land
45%
Barren Land
3%
Built-up
15%
Percentage (%)
Forest Agricultural Land Barren Land Built-up

12. Figure 8: Pie-chart showing percentage of LULC classes in 2021
Figure 9: LULC map of Banepa in 2021

13. 4. Discussion and Conclusion
The statistical data derived from the spatial analysis and the previously presented LULC maps for
the Banepa municipality that were created by categorizing satellite images from 1991, 2001, 2011,
and 2021 show that there has been a rapid growth in the built-up (urban area) without any kind of
systematic plan or model. The forest cover has drastically decreased (5% in three decades) while
the amount of agricultural land has remained essentially steady. Maintaining the ecological balance
through regulating the carbon sink is a top concern given the increase in built-up areas of more
than 10% over the past three decades. It should not take long to deploy REDD. Monitoring methods
for forests and land should be used to evaluate their resources, producing data that will help with
Studies on drivers of deforestation and forest degradation and feasibility and sectorial studies
(including cost- benefit analysis should be done.land-use planning.
COMPARISION OF LULC IN THREE DECADES
1991 2001 2011 2021
FOREST BUILT -UP AREA AGRICULTURE BARREN LAND
Studies on drivers of deforestation and forest degradation and feasibility and sectorial studies
(including cost- benefit analysis should be done. Studies on alternative land uses and risk of land
conversion should be conducted including assessing how conversion forests and related
greenhouse gas emissions could be halted and reversed considering direct and underlying drivers
of deforestation and forest degradation. Participatory and negotiated territorial development and

14. other land-use planning approaches should be facilitated for selecting and balancing land uses, and
to enhance synergies and socio-economic benefits, while safeguarding ecosystems and
contributing to combat climate change. Climate change is linked closely to REDD perspective. It
can be concluded that climate change is a consequence of dramatic change in land-use and drastic
change of land-use too change the land-use. Carbon footprint (sum of all emissions of carbon
oxides introduced by human activities in a timeframe directly or indirectly) is one of the
influencing factor of climate change. This can be combatted only by the implementation of REDD.
No abrupt change in map is seen in land-use because the factors of change are densified within the
CBD of Banepa. But the municipality is extended to remote places as well which constitutes most
of the part of municipality. Thus, urgent action is needed in the urban region of the municipality
for planned development of the urban infrastructure ensuring sufficient open spaces and conserving
the forest cover and agricultural land at the fullest potential.
5. References
Elis, E. (2006). Land-Use and Land-Cover change. The Encyclopedia of Earth, Environmental
Information Coalition, National Council for Science and Environment. Retrieved from
http://www.aughty.org/pdf/landuse_landcover.pdf
Land Use. (2021). US EPA. Retrieved from https://www.epa.gov/report-environment/land-use
Nibanupudi, H., & Shaw, R. (2015). Mountain Hazards and Disaster Risk Reduction Springer.
Paudel, B., Zhang, Y., Li, S., Liu, L., Wu, X., & Khanal, N. (2016). Review of studies on land use
and land cover change in Nepal. Journal of Mountain Science.