Spatial and Temporal Evolution of Carbon Sink in the Three North
Forest Region Based on Remote Sensing Date
Chengxuan Jiang
College of Resources and Environment, Henan Polytechnic University, Jiaozuo 545000, China
Keywords: Remote Sensing, Casa Model, Carbon Sink, Net Primary Productivity Conversion, The Three North Region.
Abstract: The investigation is to estimate the region carbon sink in the three North areas in different time periods by
integrating forest data maps, and to further evaluate the outstanding contribution of the Three North
Shelterbelt project to forest carbon sink in recent years. The casa model is the foundation of research, using
primary quality productivity (NPP), which has a clear quantified index of forest carbon sink, to evaluate the
relationship between modern terrestrial sink for carbon and forest vegetation cover in research region.
Multiple sources of historical and existing land use, including publicly available high-resolution satellite
images and remote sensing products, statistical data from various organizations we concordance and use.
Based on the 16dMODIS data, we obtained the spatio-temporal date set and distribution of carbon sink in the
three northern shelterbelts in 2006, the NPP of the three north region range from 0 to 877.184 gC/ (m2·a),
and the vegetation coverage rate range from 0 to 80%.
1 INTRODUCTION
As the one of the most important country on earth and
the developing country with the largest carbon
emission, China has announced the climate target of
reaching the peak carbon emssions by 2030 and
achieving carbon neutrality before 2060 (Zeng et al.,
2022). The "dual carbon" action is undoubtedly a
powerful and significant measure to curb global
warming. We must act from the two directions of
carbon source and carbon sink at the same time, to
accelerate the pace of carbon neutrality. The
seemingly simple step of photosynthesis, in which
carbon is fixed and stored, plays a significant role in
ecosystems. The amount of carbon fixed by
vegetation varies widely depending on climate,
location and other reasons. Vegetation in different
regions has different characteristics, for example,
Forest is an ecosystem with a huge amount of biomass.
As a high-quality carbon sink, it can not only fix a
large amount of greenhouse gas co2, but also resist
wind sand and reduce soil erosion. An accurate
assessment of such a typical terrestrial ecosystem -
forest helps us to study the process of carbon flow and
fixation throughout the Earth system. Absorbing
about 45% of co2 emissions, the world's second
largest carbon reservoir, terrestrial ecosystems are not
only a single vegetation, but also a large number of
other types of land, such as wetlands, cultivated land
and so on. The Three-North Shelterbelt project, which
began to be built in the last century, has nearly half of
Chinese land area, and has made an indelible help and
contribution to the implementation of China's carbon
neutral plan. Due to its large area and long depth, it is
extremely difficult to assess and early warning
through field investigation and vegetation monitoring.
In 2010, China's terrestrial carbon sink was
estimated to be 198±54TgC1. From 2019 to 2021,
China's terrestrial ecosystem carbon sink is about
0.44 Pg C/ year. Various of ways serve as actual tool
to quantify carbon sink. Due to its fast and
convenient characteristics, Remote sensing
technology has long been widely and profoundly
applied in the assessment, monitoring and early
warning of afforestation management; Estimation of
vegetation biomass at the global scale; exploration
and research of the driving mechanism of carbon
sinks and the spatio-temporal differences in \regional
ecosystems.Zheng et al 2017Jiarui Dong et al
2003Bowen Pang 2024The casa model is based
on the integration of satellite images and remote
sensing data and vegetation productivity is often used
in the research of various regions, such as the spatial
Jiang, C.
Spatial and Temporal Evolution of Carbon Sink in the Three North Forest Region Based on Remote Sensing Date.
DOI: 10.5220/0013042700004601
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 1st International Conference on Innovations in Applied Mathematics, Physics and Astronomy (IAMPA 2024), pages 223-227
ISBN: 978-989-758-722-1
Proceedings Copyright © 2024 by SCITEPRESS Science and Technology Publications, Lda.
223
and temporal dynamic changes of the NPP in
grassland, Gannan; the NPP distribution of vegetation
in northern Hebei Province, and so on. casa model can
help us to carry out simple research on it
What’s more, the research has provided positive
economic and policy with influence. this including,
but not limited to assessing and evaluating forest
carbon sink and their value, and organizing the
construction and maintenance of man-made forests,
so as to achieve the co-development of man and
nature.
2 METHODOLOGY
2.1 Study Area
The Three North Shelterbelt Forest Program
construction area is located in 725 counties for 13
provinces beginning with Bin County in
Heilongjiang Province in the east, and extending to
northwest China, North China, Northeast China, and
the Xinjiang Production and Construction Corps,
west to Uzberi Pass in Xinjiang, north to the national
boundary, south along Tianjin, Fenhe River, Wei
River, Taohe River downstream, Burhanbuda
Mountain, Karakoram Mountain, 38 430-53 330N,
118 020-135 530E.(www.forestdata.cn)
Its length is 4480 kilometers from east to west,
and its width is 560 1460 kilometers in both
directions. Covering a land area totaling 4.358 million
square kilometers, which represents 45.2% of the
overall land area. The construction area of the project
from south to north across the zones of warm
temperate, temperate, and cold temperate, belongs to
the humid and semi-humid continental monsoon
climate, for the vegetation type, the construction of
farmland shelter forest as the basic framework,
multiple forest species, multiple tree species, mesh
belt, the combination of trees, agriculture, forestry
and animal husbandry inlay with each other, county
and county adjacent, mutual integration of regional
shelter forest system.
The image can help us determine the scope of the
research.
Figure1: the location of the three north region (Picture
credit: Original; Date from: Shao, Q. (2022). Three-North
Shelterbelt construction project [Data set]. National Data
Center for Ecological Sciences).
2.2 Dates
2.2.1 Data Sources
One of the primary instruments aboard the Terra
spacecraft and Aqua spacecraft is MODIS, which
stands for Moderate Resolution Imaging
Spectroradiometer. MODIS vegetation indices are
generated at various spatial resolutions at 16-day
intervals, the date on 2006s July was used in
calculatiton.
The process of data preprocessing includes
geometric correction like geolocation, image
registration, mosaic and cropping, orthographic
correction, picture fusion, cloud removal and shadow
processing, and atmospheric correction.
2.2.2 Landuse
These date comes from China's first annual land cover
product (CLCD) obtained from Landsat data. this
date is divided into several types inclouding farmland,
woodland, shrubbery, grassland, water, ice, barren,
impermeable, wetland. It selected the required date
and processed it.
These data provide an abundance of research-
useful information, allowing a thorough knowledge
of the effects of land-use change on ecosystems and
the environment. By revealing the mechanisms by
which natural and human causes influence changes in
land cover, data analysis can provide a scientific basis
for the formulation of sustainable land management
policies. Meteorological data can be used to
investigate the effects of climatic change on land use
simultaneously, and socio-economic data can be used
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to study the effects of urbanization and economic
development on land cover. These multi-perspective
analyses help us understand the complexity of land
use change more thoroughly.
2.2.3 Vegetation Carbon Sink
Aimed to estimate carbon sinkwe used the date
from governmental agencies dividing the three
north shelter forest region.
NPP refers to the remaining part of the vegetation
after photosynthesis and respiration cancel each other.
This part is very important in the ecosystem. It
indicates that the vegetation converts light energy into
chemical energy through its own reaction, and it
relate to the health and quality of the vegetation. By
quantifying NPP, we can get a better understanding
of vegetation productivity and the entire ecosystem.
According to the formula:
N
PP=GPP-Ra (1)
N
EP=NPP-Rh=GPP-Ra-Rh (2)
The terms "Ra" and "Rh" stand for autotrophic
and heterotrophic respiration, respectively. “GPP”
which means the amount of photosynthates or total
organic carbon fixed by organisms. “NEP” is net
ecosystem productivity.
There are significant differences in NEP, which
are influenced by different land cover types. From the
perspective of types of vegetation, the annual average
NEP of forest, grassland and agricultural land is
higher than that of the latter.
2.2.4 Vegetation Data Indicators
The NDVI was caculated using the equation,and The
EVI an improvement of NDVI, accounts for
atmospheric scattering and land surface reflection,
resulting in increased precision in regions with
substantial vegetation coverage.where "Red" denotes
reflectance in the red portion of the spectrum and
"NIR" denotes spectral in the near-infrared
wavelength range ‘Blue’ on behalf of the
reflectivity of the blue band in the spectrum.In view
of different environment factorthe other elements
are coefficients introduced to reflect different
environmental conditions. The computation of EVI is
outlined as follows:
aNDVI = NIR-Red/NIR+Red
(3)
EVI=G*NIR-Red/NIR+K1*Red-
K2*Blue+L
(4)
With the help of this formula, EVI can more
successfully reduce the effects of surface reflection
and atmospheric scattering, producing data on
vegetation cover that is more accurate. This
development is essential for researching the dynamics
of vegetation, evaluating the health of ecosystems,
and monitoring the environment. Beyond the
monitoring of a particular vegetation cover, EVI is
widely applied and is essential to research on global
climate change. Long-term EVI data series analysis
provides a scientific basis for managing ecosystems
and developing environmental protection policies by
highlighting regional and global trends and patterns
in changes in plant cover.
Furthermore, EVI has a great deal of application
value in forestry, land resource management, and
agriculture. It helps managers and farmers better
comprehend crop growth status, forest health, and
changes in land use, which improves resource use
efficiency and management decisions. Additionally,
as an enhanced vegetation index, EVI proves to be
very accurate and dependable across a range of
environmental circumstances, making it a crucial
instrument in the study of ecosystems and vegetation
monitoring. Its easy-to-use computation technique
and wide range of applications provide essential data
support and a scientific basis for comprehending and
safeguarding the Earth's ecology.
2.2.5 Driving Factor Analysis
Formerly known as Carnegie Ames Stanford
Approach modelthe CASA model is used for
analyzing the driving factors behind the spatio-
temporal evolution of carbon sinks in the three north
forest regions. This model is widely recognized for its
robust framework in estimating net primary
productivity (NPP) by incorporating and utilizing
remote sensing data and ecological principles. Our
study builds upon the CASA-NPP transformation
method.
In many previous studies, we have shown that the
reflection features of vegetation to infrared and near-
infrared light can effectively help us estimate
photosynthetically active radiation, and as a driving
mechanism of plant photosynthesis, it is affected by
many factors, such as the amount of biomass in the
area, the total amount of solar radiation in the field.
Moreover, the photosynthetically active radiation
also showed a good linear relationship with the
normalized vegetation difference index in a certain
range, which also proved the feasibility of the method
This is a relatively classical NPP estimation
method in the CASA model proposed by Zhu.
Spatial and Temporal Evolution of Carbon Sink in the Three North Forest Region Based on Remote Sensing Date
225
Through the measurement and calculation of NPP
data, we can effectively obtain the increment of NPP
in a large spatiotemporal range, so as to effectively
analyze the status of forest carbon sink and evaluate
the quality of the construction project of the Three-
North protective fence.
N
PP(
p
,
m
)=APAR(
p
,
m
ε(
p
,m) (5)
APAR(
p
,
m
)=SOL(
p
,m)×FPAR(
p
,m)×
k
(6)
FPAR(p,m)=(NDVI(p,m)-
NDVIi,min)/(NDVIi,max-
NDVIi,min)×(FPARmax-
FPARmin)+FPARmin
(7)
APAR is photosynthetically active radiation, ε is
solar energy utilization efficiency, FPAR is
photosynthesis radiation absorption ratio. “i” is the
sequence of vegetation species, “p” represents the
pixels, and “m” represents the months in the time
series.
3 RESULT
Initially We find the sequence occupied by
vegetation in the land use type, confirm some basic
attributes of them, deploy their static parameter files,
and import pre-treated vegetation types, ndvi time
series, climate factors, environmental factors, etc.
into the casa calculation module to obtain the original
data and import it into gis for analysing.
Then, comprehensive reclassification is carried
out on the npp results and the vegetation coverage
images at the same time, and the results are divided
into several categories according to equal proportions,
which are represented by different legends in the
images. In the vegetation coverage rate, the dark
green color indicates the high vegetation content in
the region. Similarly, in the npp results, the color can
quantitatively represent the exact npp value of the
pixel. They have a trend from fewer to more. And the
region showed an increasing from east to west.
The vegetation remote sensing image of NDVI
can reflect the change of vegetation to a certain extent,
but the image obtained by the model in this study can
more truly and effectively reflect the npp distribution
in the three northern regions combined with multi-
breadth and multi-depth influence factors
Through the comparison of forest cover and
primary quality productivity in the same year, we can
conclude that forest cover and carbon sink capacity
are highly positive correlation. That is, areas with
high forest cover usually have higher primary
productivity, which absorbs more carbon dioxide and
forms a stronger carbon sink capacity. This is a
positive and benign cycle, in which forests fix
atmospheric carbon dioxide into organic carbon
through photosynthesis. The higher the forest
coverage rate, the more obvious this carbon
fixation effect is, thus improving the regional carbon
sink capacity and making the effect of carbon
neutrality more obvious.
Figure 2: The three region vegetation coverage in 2006
(Picture credit: Original).
There are a little yellow areas or on the map,
which means there is little or no vegetation in this
region .it explains why the initial values of vegetation
coverage and NPP start at 0.
Figure 3: The Net primary productivity conversion
result
(Picture credit: Original).
At the same time, we obtained the temperature as
the most suitable growth temperature for vegetation
to fix carbon according to different time series in a
year. Finally, we lock the result between month and
July, and finally we can know the raster result.
The NPP of the three north region range from 0 to
877.184 gC/ (m2·a), and the vegetation coverage rate
range from 0 to 80%.
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4 CONCLUSION
Because of the importance of the Three Northern
regions to Chinese "dual carbon" action, it is
suggested to strengthen the continuous monitoring
and evaluation of the Three Northern shelterbelts, and
use the combination of remote sensing technology
and ground observation to obtain more detailed and
long time series data, which can also make up for the
shortcomings of the small spatiotemporal range and
fracture of the experiment, and the incomplete
accuracy of the experimental results. To study the
temporal and spatial changes of carbon sink capacity,
and actively estimate the potential of forest carbon
sink. At the same time, in forest management, the
impact of climate change should be considered, and
management action need be taken adjusting to local
natural conditions, such as disaster prevention and
mitigation, selecting drought-tolerant and water-
tolerant tree species, and avoiding planting a large
number of single tree species, so as to improve the
forest resistance and carbon sink capacity, so as to
achieve the goal of carbon neutrality as soon as
possible.
Certainly, human intervention and protective
strategies for forestry are of paramount importance.
The scenario of curbing global warming is escalating
in severity and urgency yet behavior of remnants
of deforestation and the subsequent situation of
reduction of forest carbon sinks persist. Initiatives
such as reverting cropland to forested land and
implementing stringent control measures can people
pay attention to, coupled with penalties for unchecked
deforestation, comprise various tactics aimed at
safeguarding the ecological resources within this
expansive carbon reserve. In conclusion, extensive
research underscores the indispensable and
substantial role that the Three North regions will play
in China's, and indeed the world's, future. This role is
intrinsically linked to the sustainability of human
society, economic progression, and ultimate
prosperity.
In the whole research process, the primary
productivity and vegetation coverage of the three
northern regions were analyzed from a large spatio-
temporal range by remote sensing. Compared with
the field survey, the whole result was faster and more
intuitive. However, due to the difference in data
quality and other reasons, the limitations of the
research results were also shown. The spatio-
temporal span of the results failed to clearly show the
whole change process. Secondly, only several land
cover types were used in the study, which will have
an impact on the results. Therefore, future studies can
explore the carbon sink in the three North regions in
a finer spatio-temporal range.
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