Landscapes in the Horqin Sandy Land: Patterns and Processes

Chunwei Song

, Shihui Wang and Weiyi Lu

College of Tourism and Geographical Sciences, Jilin Normal University, Siping, Jilin, China

Keywords: Sand dune pattern, Landscape evolution, Lake complex, Horqin Sandy Land

Abstract: The Horqin Sandy Land (HSL) falls in the interlocking agricultural and pastoral zones in northern China.

The sandy area experiences wind and water erosion and the evolution of lakes and landcover is closely

related to changes to the sandy land surface. This study applied geomorphological analysis and

mathematical and statistical analyses to multiple sources of remote sensing data to study the characteristics

and changes in landforms, lakes, and lan cover patterns in the area. The results showed that the area of

sandy land in the HSL has decreased over the last 40 years at an average rate of -0.31%, whereas the areas

of fixed and semi-fixed sand dunes, such as scrub dunes and parabolic dunes, are increasing. The area of

lakes and the number of patches have decreased, there was increased clustering of lakes, and the changes to

the landscape appear to be stabilizing. There was an increase in vegetation growth, with mean annual

average Normalized Difference Vegetation Index (NDVI) of between 1.42–2.06. There was an obvious

increase in NDVI, mainly in the southeastern part of the study area. The study provides a basis for the

sustainable development of the ecological environment in the HSL.

1 INTRODUCTION

Landscape evolution is an important field in

geography and ecology and refers to changes in the

structure and function of land surface processes at

various spatial and temporal scales driven by natural

and human factors (Wu, 2013; Elhag, 2017; Fan et

al., 2018). The use of remote sensing data sources

and geographic information system (GIS) spatial

analysis methods within the study of landscape

evolution can reveal the processes and patterns of

land surface evolution, which is of importance in

regional sustainable development. Many past studies

have focused on the dynamic changes in sandy land

at different spatial and temporal scales and using

different landscape classification systems (Zuo et al.,

2009; Li et al., 2008; Wu and Ci, 2001). Among

current processes driving the evolution of sandy

land, lakes play an important role in maintaining the

wind-water balance and wetland landscape ecology

(Gao et al., 2020; Zhao and Feng, 2020; Zhu et al.,

2010). Consequently, there have been studies in

China and abroad on lakes in sandy land areas,

mostly focusing on lake area dynamics, hydrological

characteristics, and the impact of climate change.

For example, a study by Bai et al. on changes to the

lake area in the Otindag Sandy Land area over the

past 45 years determined that lake shrinkage was

mostly concentrated in the sandy hinterland (Bai et

al., 2016). Dong et al. explored the underlying

mechanism of recharge of the Alashan Desert Lake

Group (Dong et al., 2016). Past studies have gained

some understanding on the coupling relationship

between wind-sand activities and vegetation

conditions, including on changes to vegetation

cover, the movement of sand grains, wind erosion

speed, and wind profile height (El-Wahab et al.,

2018; Zhang, 2012). However, there has been

relatively less focus on the relationship between the

changes in and interactions between these three

landscapes (Chen et al., 2006). Past studies on the

wind- and sand-driven landscapes in the HSL have

mostly focused on the spatial and temporal changes

to the sandy area, assessment of the degree of

desertification, the evolution of landscape patterns,

and drivers of landscape change (Li et al., 2017; Bai

et al., 2017; Duan et al., 2012; Duan et al., 2014).

Past studies of lakes in sandy areas have mostly

focused on the dynamic changes in lake numbers

and their influences on climate (Chang et al., 2013;

Jia et al., 2014). However, studies on the interactions

between sandy areas and vegetation and between

sandy areas lake based on long timeseries data

remain limited. Therefore, the current study

Song, C., Wang, S. and Lu, W.

Landscapes in the Horqin Sandy Land: Patterns and Processes.

In Proceedings of the 7th International Conference on Water Resource and Environment (WRE 2021), pages 123-127

ISBN: 978-989-758-560-9; ISSN: 1755-1315

123

conducted long-term remote sensing monitoring of

the sandy land and lake group dynamics of the HSL

based on multiple sources of satellite data. The aim

of the present study was to identify the

characteristics of the evolution of sandy land, lake

and landcover patterns in this area over the last 40

years to explore the relationships between sandy

patterns and lake and vegetation. The results of the

present study can provide a scientific basis for the

study of regional landscape responses in the context

of global environmental change.

2 OVERVIEW OF THE STUDY

AREA AND RESEARCH

METHODS

2.1 Overview of the Study Area

The HSL is located at the edge of the monsoon zone

and is a typical agro-pastoral area in northern China.

The distribution area of HSL is about 42.3 thousand

square kilometers and falls between 118°31′–

124°18′ E, 42°31′–44°50′N. The climate of the

region is characterized by a transition from the warm

temperate zone to the temperate zone and semi-

humid zone to semi-arid zone. The frost-free period

of the area is 140–160 d, the annual average

temperature is 5.2–6.4 °C, annual precipitation is

343–500 mm, annual sunshine hours are 2 900–3

100 h. The zonal soil is mainly dark brown loam,

chestnut calcium soil, and black kiln soil, whereas

the non-zonal soil is mainly sandy soil, meadow soil,

and saline-alkaline soil. The zonal vegetation

transitions from typical grassland to forest grassland.

The HSL contains sand dunes, inter-dune

depressions, and swamp bubbles. Several sand

monopolies and inter-monopoly depressions occur

from the rear banner of the left wing of the HSL to

the Changling. The inter-monopoly depressions are

distributed with ancient riverbeds, lakes or deans

running from east to west.

2.2 Data Source and Pre-processing

The multispectral remote sensing data used in the

present study included Landsat Multi-Spectral

Scanner (MSS) multispectral images (spatial

resolution of 80 m) for 1980, Landsat Thematic

Mapper (TM) multispectral images (spatial

resolution of 30 m) for 1990, 2000, 2010, and 2020,

Landsat Operational Land Imager (OLI)

multispectral images (spatial resolution of 30 m).

The topographic map and coordinates of typical

features measured by a real-time kinematic global

positioning system were used as control points to

geometrically finetune the data for each synthesis

band, and the error was minimized to within one

pixel. Histogram matching and stitching were

performed on the contemporaneous data, following

which the images were cropped according to the

boundary of the study area. The wind-driven sandy

land types were divided into nine categories: (1)

wind erosion pits; (2) scrub dunes; (3) gently

undulating dunes; (4) beam-well dunes; (5)

parabolic dunes; (6) flat dunes; (7) sand monopolies;

(8) crescent-shaped dunes and; (9) dune chains.

Lakes were divided into several categories,

including natural lakes, artificial reservoirs, and

ponds.

2.3 Research Methodology

2.3.1 Interpretation of Remote Sensing

Image Data

Manual visual interpretation for object-oriented

segmentation was used to improve the accuracy of

classification. GPS-guided field observation was

conducted to interpret areas not yet defined, and the

interpretation was verified using the random point

method with an accuracy of 91.02%.

2.3.2 Maximum Value Synthesis Method

The Maximum Value Composites (MVC) were used

to obtain the maximum monthly NDVI for the

analysis of regional vegetation cover and

spatiotemporal characteristics of NDVI variation.

The vegetation index reflects a certain period of time

within the remote sensing data under an optimal

state for interpretation, which can effectively reduce

errors resulting from aerosols, cloud shadows, and

perspective, thereby improving the precision of the

vegetation index.

2.3.3 Mean Value Method

The present study adopted the mean value method

(MVM) to statistically analyze the mean value of

NDVI in the study area. The MVM is an index

reflecting the central trend of a dataset and is used to

calculate the mean NDVI of vegetation in the study

area over a certain period. The MVM can reduce

disturbance from outliers resulting from the angle of

solar altitude and extreme climate conditions,

thereby improving the accuracy of the vegetation

index.

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3 RESULTS AND ANALYSIS

3.1 Evolution of Sandy Land in the

HSL

The wind-driven sandy land in the HSL is mainly

distributed on the alluvial plains along the dry

tributary streams of the Xiliao River. The sand dune

types of the Horqin Sand Area tend to become

simpler from west to east and from south to north.

The area of wind-driven sandy land has been

decreasing continuously over the last 40 years, with

a net decrease in the sand area of 5,194.33 km

and

an annual rate of change of −0.31%. There were

general increases in the areas of crescent-shaped

dunes and dune chains from 1980 to 2020, with a net

increase in area of 165.51 km

. There was an

average annual growth rate in the areas of crescent-

shaped dunes and dune chains of 1.47% from 1980

to 2000, followed by a declining trend from 2000 to

2020 with an average annual rate of change of

−1.17%. The area of scrub dunes showing

fluctuating increases, with a total increase in area of

331.53 km

, with most of the increases occurring

over the last 10 years at a growth rate of 0.37%. The

area of beam nest dunes continued to decrease, with

a net decrease of 5,194.43 km

. The area of flat

sandy land fluctuated, although there was a rapid

decreasing trend in the area of flat sandy land over

the last 10 years. The area of parabolic dunes

showed a fluctuating increasing trend. The areas of

gently undulating sandy land and sandy monopoly

land both showed fluctuating decreasing trends, with

net decreases of 6.35% and 11.28%, respectively.

The area of wind erosion pits did not change

significantly. In general, the area of the wind-driven

sandy land of HSL decreased over the last 40 years,

while the area of fixed and semi-fixed dunes such as

scrub dune land and parabolic dunes increased,

indicating that the mobility of the Horqin Sand Area

weakened and showed a trend of moving from

desertification to oasis.

3.2 Evolution of the Lake

The overall area of lake Complex showed a

decreasing trend over the last 40 years. The area

increased by 239.87 km

from 1980 to 1990, with an

annual rate of change of 3.91%. The area began to

decrease from 1990, decreasing by 6.78 km

2000. The area decreased by 247.99 km

from 2000

to 2010, with an annual rate of change of −3.8%.

The decreasing trend in the lakes complex gradually

stabilized from 2010 to 2020, with an annual rate of

change of −2.90%. The number of patches of lake

groups showed a continuous increasing trend from

1980 to 2000, with a total increase of 314. The

increasing trend was most significant from 1980 to

1990, with an annual rate of change of 6.62% and

reaching a maximum value of 623 in 2000.

However, the change in number of patches of lake

groups was not synchronized with the change in lake

area, indicating increased fragmentation of the lake

during this period. The change in the number of

lakes from 2000 to 2020 was consistent with the

change in area, showing a rapid decline with an

annual rate of change of −4.60%.

3.3 Evolution of the Vegetation

Landscape

The overall NDVI trend in the HSL during the

growing season from 1982 to 2020 was one of

fluctuating increase, with an increase in area of

23.05% and an average annual growth rate of 0.59%

(Figure 1). NDVI showed a fluctuating increasing

trend from 1982 to 1992, with an increase of 16.43%

and an average annual rate of increase of 1.64%.

NDVI showed a fluctuating decreasing trend from

1992 to 2007, with a decrease of 17.46% and an

average annual rate of decrease of 1.16%. A

significant increasing trend in NDVI was evident

from 2007 to 2020, with an increase of 28.31% and

an average annual rate of increase of 2.18%. NDVI

reached a maximum in 2017 of 2.0639.

Figure 1: Interannual trends of NDVI in HSL.

The NDVI during the vegetation growing season

decreased from east to west, with an annual average

exceeding 0.25 in most areas over the last 39 years

and good vegetation conditions. The annual average

NDVI in the southwestern part of the sandy area

ranged from 0.15 to 0.25, and vegetation conditions

were slightly worse. The multi-year mean NDVIs

for Shuangliao City, Kangping County, and

southeastern Horqin Left Wing Back Banner were

high, ranging from 0.35 to 0.49, whereas the multi-

year mean NDVI for Wengniut Banner and western

Landscapes in the Horqin Sandy Land: Patterns and Processes

125

Naiman Banner were relatively low, ranging from

0.15 to 0.26.

4 DISCUSSION

The changes to HSL over the last 40 years were

characterized by a decrease in the total area of the

wind-driven sandy landscape and an increase in

fixed and semi-fixed sand dunes, such as scrub

dunes. These changes are consistent with a transition

from desert toward oasis and are supported by the

findings of Yue et al. (Yue et al., 2017). Lake

complexes in sandy areas are important components

of desert ecosystems and play an important role in

maintaining ecological stability and development

(Ma et al., 2016). However, lake complexes

themselves have poor stability, and the areas and

numbers of lake complexes vary greatly on

interannual and seasonal scales due to the influences

of climate and human activities (Duan et al., 2012).

The HSL is in a dynamic equilibrium, which

maintains its developmental stability under the

interactions of wind and water erosion. Moisture is

the most dominant factor governing plant growth

and survival. Improved moisture conditions and lush

vegetation growth around the lake complex have an

important influence on the structure of the regional

sand flow field and wind-driven sand transport,

which in turn determines the evolution of the sandy

landscape within a certain buffer zone around the

lake complex (Smith et al., 2017; Bai et al., 2016).

However, such areas are also mostly surrounded by

lakes and fields, resulting in the transformation from

natural to artificial landscapes and in the shrinkage

of the lake area. In addition, the construction of

reservoirs in the upper reaches of rivers, inevitably

affect downstream runoff and change the water and

sand conditions of rivers. A reduction in river flow

can result in the river running dry and the exposure

of rocks on the riverbed. These rocks can act as

sources of sand for the development of riverbank

dunes (Liu and Coulthard; 2015). A decrease in

surface water results in a decrease in the water table.

The water table in lumps and sand swamps will also

decrease, resulting in decreases in moisture-loving

plants, the establishment of drought-tolerant plants,

the death of trees, lower vegetation cover, dune

activation, and the continued expansion of

desertification (Telfer et al., 2017). The processes

driving the evolution of both landforms and

landscape patterns can be represented by spatial

attribute information.

The overall trend of a fluctuating increase in

NDVI in the HSL during the vegetation growing

season is consistent with the results of studies on

NDVI trends at different scales, such as in eastern

China (Liu et al., 2015; Han, 2007). In particular,

NDVI showed significant increasing and decreasing

trends before and after 1992, respectively, generally

consistent with the findings of Piao et al. for the

Eurasian region (Piao et al., 2003). The vegetation

cover of the HSL showed an general increasing

trend up until 2000, after which the influences of the

national policies for returning farmland to forests

and grasses, natural forest protection, and sand

control projects, accelerated the process of a

transition from desertification to oasis.

5 CONCLUSIONS

The wind-driven sandy land area of the HSL has

experienced a decrease over the last 40 years, with a

net decrease of 5,194.33 km

and an annual rate of

change of 0.31%. The wind-driven sandy land area

decreased, the area of fixed and semi-fixed dunes

such as scrub dunes and parabolic dunes increased,

and the mobility of the sands decreased.

The area and number of lakes in the HSL showed

fluctuating and decreasing trends, decreasing by

60.05 km

and 68 individual lakes respectively. The

lake showed an overall stabilizing evolution.

However, the lake remains in a dynamic

evolutionary process and plays an important role in

the spatial and temporal evolution of the land

surface of the HSL.

The vegetation growth in the HSL showed an

overall increasing trend from 1982 to 2020 and the

multi-year mean NDVI values fluctuated between

1.4235–2.0639. There were obvious phases of

change, among which vegetation cover increased

significantly from 1985 to 1992 and from 2007 to

2019, with annual growth rates of 4.06% and 4.53%,

respectively. Although the area in which there were

increases in NDVI was large, the increase in NDVI

was small and spatially variable, with areas of high

and low NDVI mainly distributed in the southeast

and northwest, respectively.

ACKNOWLEDGMENTS

This research was funded by the National Natural

Science Foundation of China (NO.41871022).

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