The content of this article is from the "Surveying and Mapping Bulletin", No. 4, 2021, review number: GS (2021) No. 1567
Spatial-temporal evolution trend analysis of ecosystem service functions based on multi-source remote sensing data
Sun Hao1
Hu Jiaqi1, Cui Yajing1, Yang Nan2, Cai Chuangchuang1
1. School of Geosciences and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China; 2. China Institute of Geological Environment Monitoring, Beijing 100081
Fund Projects: National Natural Science Foundation of China (41871338), Geological Survey Project (DD20190506), General Project of Key R&D Program of Ningxia Hui Autonomous Region (2018BEG03069), Yueqi Young Scholar of China University of Mining and Technology (Beijing) (CUMTB2018)
Abstract: Studying the temporal and spatial evolution trend of regional ecosystem service functions can help to reveal the impact of human activities or climate change on the ecological environment of the region, so as to provide a basis for the conservation and management of ecosystem service functions. In this paper, taking Huai'an City as the research area, the spatial-temporal evolution trend was analyzed by expanding the remote sensing index method of the assessment of the importance of ecosystem service functions in the time dimension, and the water conservation, soil and water conservation and biodiversity maintenance functions from 2000 to 2018 were calculated, and the spatio-temporal evolution trend was analyzed by using Mann-Kendall nonparametric test and Hurst trend analysis method, and the reasons for change were explored by combining medium and high resolution remote sensing data interpretation. The results show that: (1) the ecosystem service function in most areas of Huai'an City shows a significant increase trend, of which the growth trend of water conservation and biodiversity is weaker, while the growth trend of water and soil conservation is more sustained; (2) the increase in ecosystem service function mainly occurs in the vegetation cover areas such as cultivated land and woodland, and the reduction area mainly occurs in non-ecological land areas such as building land; (3) the proportion of vegetation cover areas such as cultivated land and woodland in Huai'an City is basically unchanged, and even slightly decreased with the increase of the proportion of construction land. The main reason for the increase in ecosystem service functions may lie in the enhancement of vegetation vitality, which is manifested in the increase in vegetation greenness and vegetation productivity.
Keywords: Remote sensing Ecosystem services function temporal and spatial evolution trend Hurst analyzes the Mann-Kendall test
Citation format: Sun Hao, Hu Jiaqi, Cui Yajing, et al. Spatio-temporal evolution trend of ecosystem service functions based on multi-source remote sensing data[J]. Bulletin of Surveying and Mapping, 2021(4):1-7. DOI: 10.13474/j.cnki.11-2246.2021.0101.
Read more: http://tb.sinomaps.com/article/2021/0494-0911/20210401.htm
Full text overview
Ecosystem service function refers to the natural environmental conditions and utilities created and maintained by ecosystems and ecological processes [1-2], such as soil and water conservation, soil maintenance, climate regulation, pest control, material production, etc. Ecosystem service functions are closely related to human life and are the basis for the survival and development of human society [3]. The spatio-temporal pattern of ecosystem service functions is not static, and both human activities and climate change will change ecosystem service functions to varying degrees [1]. For example, the overexploitation of natural resources by human beings, the destruction and pollution of the ecological environment, land desertification, the decline of forest cover and the extinction of species will lead to a significant decline in the function of ecosystem services, thus causing serious damage to the ecosystem and threatening human security and sustainable development. In this context, studying the spatio-temporal evolution trend of ecosystem service functions in a certain region can help reveal the impact of changes in environmental factors such as human activities or climate on the ecological environment of the region, so as to provide a basis for the conservation and management of ecosystem service functions.
In the past 30 years or so, evaluating the temporal and spatial changes in the function of ecosystem services has become one of the important research areas of environmental and ecological economics [4]. The development of remote sensing and geographic information technology and its application in ecological research provide dynamic spatial support for the integrated assessment of ecosystem services [5-6]. At present, there are still many challenges in the study of ecosystem service functions, including the improvement and standardization of evaluation methods, as well as the exploration and analysis of spatio-temporal changes in ecosystem service functions [7]. Since land use/land cover change (LUCC) can directly alter the function and structure of ecosystems, numerous studies of the relationship between LUCC and ecosystem service values (ESVs) have shown that LUCC plays a vital role in providing EVS [8-11]. Literature[12] Using remote sensing images as data sources, different types of land use areas were obtained through the interpretation of remote sensing images in Huaxi area, the value of ecosystem services in Huaxi area was evaluated, and the coupling and change relationship between land system and ecosystem was used to study the impact of LUCC on ecosystem services. However, it does not pay enough attention to factors such as spatial differences in ecosystems to fully objectively reflect the value of ecological services in certain areas. The literature [13] evaluates the temporal and spatial variations in the value of ecosystem services under LUCC, but lacks complete time series datasets. The literature [14] quantified six ecosystem service functions related to forest ecosystems in six time periods, and found that ecosystem service functions have a high degree of spatiotemporal variability. Literature[15] According to the market value method and the production cost method, the economic value of forest ecosystem service functions in Chongqing was quantitatively evaluated. However, it only evaluates the forest service function in the two periods, and cannot objectively and continuously reflect the dynamic change of service function value and the difference in temporal and spatial distribution. Literature[16] The value coefficient table of ecosystem services was obtained by using the equivalent factor method, and the spatial and temporal distribution pattern of ecosystem service value was studied using landsat imagery as the data source. However, due to the limited data acquisition, the temporal and spatial evolution of the two-phase data analysis from 2006 to 2016 is slightly insufficient, and it is impossible to explain the evolution of the value of ecological services more objectively and scientifically. Literature[17] Using land use vector data from 2000, 2005 and 2010 to calculate the value of ecosystem services, the temporal and spatial changes of ecosystem service values in Chongqing in the past 10 years were studied. However, the study's time series were short and only used a few time sections. Literature[18] Based on the data of the 2007-2016 statistical yearbook of Chongqing, the value system of farmland ecological service is constructed, and the spatio-temporal change characteristics of ecological service value in Chongqing are studied. However, the study used counties as a computational unit with poor spatial resolution and could not reflect changes in ecosystem services within the county.
In summary, most of the previous studies on the spatio-temporal evolution trend and analysis of ecosystem service functions are based on single data, and most of the study time series is short, or only uses a number of time sections, which cannot objectively and continuously reveal the evolution of ecosystem service functions. In addition, there are few quantitative studies on the past-present-future spatial pattern evolution of ecosystem service functions in different regions, and it is difficult to clarify the future spatio-temporal evolution pattern of these areas [19]. Based on this, this paper proposes to carry out the assessment of the importance of ecosystem service functions in Huai'an City from 2000 to 2018, test the trend significance of time series by using Mann-Kendall non-parametric test method, analyze the continuity of time series development trend by using the quorum of heavy scale difference, and combine multi-scale multi-source remote sensing data to deeply analyze the spatial pattern and evolution trend of ecosystem service functions in Huai'an City, aiming to more clearly understand the current status of ecosystem in Huai'an City. Provide key information for ecological environmental protection, industrial planning and policy formulation.
1 Study area and data
1.1 Introduction to the Study Area
Huai'an is located in the north-central part of Jiangsu Province, the eastern part of the Jianghuai Plain, the territory of China's fourth largest freshwater lake Hongze Lake, rivers and lakes crisscrossed, water network longitudinal, plain area accounted for 69.39% of the total area, lake area accounted for 11.39%, hilly area accounted for 18.32%. The soils in this area are mainly yellow-brown loam, paddy soil, fluvo-aquic soil, basic geotechnical soil, limestone black soil and limestone soil. The average annual temperature is 14.1 °C to 14.8 °C, which is basically distributed in the south, high and north. The annual precipitation averages between 906 and 1007 mm for many years, and its distribution is characterized by more south than north and more east than west. The spatial distribution of Huai'an city is shown in Figure 1.
Figure 1 Spatial distribution of Huai'an City
Diagram options
1.2 Data
The study used MODIS vegetation index, land cover type and net vegetation productivity data from the long-term series from 2000 to 2018, as well as high-resolution Landsat, SPOT, Pleiades and some aerial data, in addition to geographic information data such as temperature, precipitation, DEM and soil, as follows:
(1) MODIS/Terra Vegetation Indices 16-Day L3 Global 500 m SIN Grid V006 (MOD13A1)。
(2) MODIS/Aqua and TerraLand Cover Type Yearly L3 Global 500 m SIN Grid V006 (MCD12Q1)。
(3) MODIS/Terra Gross Primary Productivity 8-Day L4 Global 500 m SIN Grid V006 (MOD17A2)。
(4) 2002 Landsat 7 ETM+ data and 2006 Landsat 5 TM data.
(5) SPOT 6 multispectral imagery (6 m) and panchromatic image (1.5 m) for 2018.
(6) Pleiades multispectral imagery (2 m) and panchromatic image (0.5 m) in 2018.
(7) Aerial photographic data of the confluence of the abandoned Yellow River and the Beijing-Hangzhou Grand Canal in Huai'an City, as well as the Hongze Lake and the Northern Jiangsu Irrigation Canal, with a spatial resolution of 0.2 m.
(8) Huai'an Meteorological Station measures temperature and precipitation.
(9) 2009 ASTER digital elevation model GDEM (30 m).
(10) 1:1 million soil attribute data in 2009, downloaded from the Cold and Arid Areas Science Data Center.
2 Research methodology
The spatial pattern and evolution trend of the ecological environment in typical areas of Huai'an City were in-depth analysis using relevant remote sensing, meteorological, soil, elevation and geographic information data of the work area to calculate the importance of ecosystem service functions (water conservation function, soil conservation function and biodiversity conservation function), and the Mann-Kendall non-parametric test[20] and Hurst index [21-22] were used to deeply analyze the spatial pattern and evolution trend of the ecological environment in typical areas of Huai'an City, based on the multi-year land cover type, vegetation index and net primary productivity (NPP), High-resolution remote sensing data analyze the reasons for the change of ecosystem service functions.
The water conservation function is evaluated by the ecosystem water conservation service capacity index, and the calculation formula is:
(1)
In this formula, WR is the ecosystem water conservation service capacity index, NPPmean is the annual average of the net primary productivity of vegetation, Fsic is the soil seepage factor, Fpre is the annual average precipitation factor, and Fslo is the slope factor.
The function of soil and water conservation is assessed by the ecosystem soil and water conservation service capacity index, and the calculation formula is:
(2)
Wherein, Spro is the soil and water conservation service capacity index, NPPmean is the annual average of the net primary productivity of vegetation, Fslo is the slope factor, and K is the soil corrosion factor.
The biodiversity conservation function is based on the biodiversity conservation service capacity index as an assessment index, and the calculation formula is:
(3)
In this formula, Sbio is the biodiversity maintenance service capacity index; NPPmean is the annual average of the net primary productivity of vegetation; Fpre is the average annual precipitation; Ftem is the average annual temperature; and Falt is the elevation factor.
Among them, the average annual precipitation and annual temperature are calculated by the measured data of Huai'an Meteorological Station. Firstly, the multi-year average precipitation or temperature values of all meteorological stations in the region are calculated, and these values are connected to the site data according to the same site name, and the multi-year average precipitation or temperature raster map is obtained by kriging interpolation method.
Soil seepage factor is a raster plot of soil seepage factor by dividing the attribute values T_USDA_TEX in the soil dataset by 13. The soil corrosiibility factor refers to the degree of difficulty of soil particles being separated and transported by hydraulics, mainly related to soil texture, organic matter content, soil structure, permeability and other soil physicochemical properties, mainly using the clay particles, silty particles, sand particles and organic carbon content in the dataset to calculate, the calculation formula is as follows
(4)
(5)
Wherein, K indicates the modified soil corrosiibility factor; KEPIC represents the soil corrosiibility factor before the correction; mc, msilt, and ms are clay particles (<0.002 mm), powder particles (0.002~0.05 mm), sand particles (0.05~2 mm); Corg is the proportional content of organic carbon, in units.
3 Findings
3.1 Water conservation
According to the model, the water conservation service capacity of Huai'an City for a total of 19 years from 2000 to 2018 is calculated. Limited to space, the results are only shown in 2000, 2010, and 2018, as shown in Figure 2. It can be seen that from 2000 to 2018, the capacity of water conservation services has increased year by year. Figure 3 shows the results of the Mann-Kendall non-parametric test and the Hurst index of water conservation, which show that the change trend of water conservation in Xuyi County is very significant, lianshui county is basically unchanged, and other regions are significantly increased. The area of the area where the overall trend of change increases is larger than the area of the area of the area that is decreasing (see table 1). The Hurst index is used to characterize the continuity or anti-sustainability of the development trend of the time series, among which Xuyi County has strong sustainability, Qingjiangpu District, huaiyin District south, and Lianshui County south have weak sustainability, and other districts and counties have weak sustainability. Table 2 is the statistical result of the prediction of the change trend of water conservation in Huai'an City, which shows that the Hurst index of the overall water conservation sequence in Huai'an City is mostly located at 0.5-0.75, indicating that the growth trend of water conservation is slow and the sustainability is weak.
Figure 2 Water conservation capacity of Huai'an City
Figure 3 Variation trend of water conservation and Hurst index distribution in Huai'an City from 2000 to 2018
Table 1 Statistics on the change trend of ecosystem service functions in Huai'an City from 2000 to 2018
Table options
Table 2 Prediction results of water conservation trend in Huai'an City from 2000 to 2018
3.2 Soil and water conservation
According to the model, the water and soil conservation service capacity of Huai'an City from 2000 to 2018 is calculated, taking 2000, 2010 and 2018 as examples, and the results are shown in Figure 4. From 2000 to 2018, the service capacity of soil and water conservation has increased year by year. Figure 5 shows the results of the Mann-Kendall non-parametric test of soil and water conservation and the results of the Hurst index, which show that the overall change trend of Huai'an City is significantly increased, of which the proportion of area with a significant increase is 77.58% (see Table 1), and the Qingjiangpu District is basically unchanged. The Hurst index is used to characterize the degree of persistence or anti-sustainability of time series development trends, among which the northern part of Xuyi District and Hongze District are more persistent, and other regions are more persistent. Table 3 shows the prediction statistical results of the change trend of soil and water conservation in Huai'an City, which shows that the Hurst index of the districts and counties of Huai'an City and the overall soil and water conservation sequence is basically greater than 0.55, indicating that the growth trend of soil and water conservation is relatively persistent.
Figure 4 Soil and water conservation capacity of Huai'an City
Figure 5 The Mann-Kendall statistic and the spatial distribution of the Hurst exponent
Table 3 Prediction and statistics of soil and water conservation trends in Huai'an city from 2000 to 2018
3.3 Biodiversity
According to the model, the biodiversity service capacity of Huai'an City from 2000 to 2018 was calculated, taking 2000, 2010 and 2018 as an example, the results shown in Figure 6, and the biodiversity service capacity increased year by year from 2000 to 2018. The time-based trend significance analysis and trend change prediction of biodiversity in Huai'an City from 2001 to 2018 were shown in Figure 7. The results show that the biodiversity change in the southern region increased significantly, among which the biodiversity of Xuyi District increased significantly, Lianshui County remained basically unchanged, and other areas increased significantly, and the area of the area where the change trend increased from The statistical results of Table 1 showed that the area where the change trend increased accounted for 75.60%, indicating that the overall biodiversity of Huai'an City showed a significant upward trend.
Figure 6 Biodiversity capacity of Huai'an City
Figure 7 Mann-Kendall statistic and the spatial distribution of the Hurst exponent
The Hurst index is used to characterize the degree of persistence or anti-sustainability of the development trend of the time series, the sustainability of Huai'an District is weak, and the sustainability of other districts and counties is stronger. Table 4 shows the statistical results of biodiversity trend prediction in Huai'an City, which shows that the Overall Biodiversity Sequence Hurst Index is located at 0.55-0.75, most of which are less than 0.65, indicating that the growth trend of biodiversity is slow and the sustainability is weak.
Table 4 Prediction results of biodiversity trends in Huai'an City from 2000 to 2018
4
Discuss the analysis
The above results show that from 2000 to 2018, the ecosystem service functions in the study area showed an overall increase trend. In order to analyze the specific reasons, the following is an in-depth analysis from the perspective of ecological land types and vegetation vitality.
4.1 Types of ecological land
Based on MODIS-MCD12Q1 land cover products and Landsat data in 2002 and 2006 and SPOT data in 2018, the land cover information of Huai'an City was extracted and the proportion of ecological land was calculated. Figure 8 shows the classification results of MODIS land cover products. The results show that Huai'an City as a whole has the largest proportion of vegetation cover, and the water bodies are basically distributed in the western and eastern areas of Hongze District, as well as the southeast of Jinhu District.
Figure 8 Land cover type in Huai'an City
Figure 9 shows the results of landsat and SPOT data classification, which are basically consistent with modis data classification results. Figure 10 shows the proportion curve of ecological land use, in which the proportion of ecological land is defined by the Technical Specification for the Evaluation of Ecological Environment Status (HJ 192-2015), which refers to the proportion of green space, water wetlands and cultivated land in the evaluation area to the total area of the evaluation area. Figure 10 shows that the proportion of ecological land in Huai'an City is basically unchanged, or even slightly decreased. The proportion of vegetation cover is the highest in ecological land, followed by the proportion of water bodies. The proportion of non-ecological land such as construction land is the lowest, and its change trend is basically stable, or even slightly increased.
Figure 9 SPOT data interpretation results
Figure 10 Ecological land scale time line
In addition, the interpretation of Pleiades remote sensing data combined the obtained land cover type maps with aerial data from parts of Huai'an City to further analyze the reasons for the evolution of ecosystem service functions. Figure 11 shows the results of biodiversity comparison. The results show that a large area of construction land is distributed in areas with significant biodiversity decline, while arable land and woodland are distributed in areas with significant increase, and the comparative results of soil and water conservation and water conservation are consistent with the biodiversity results.
Figure 11 Interpretation and comparison of biodiversity and ecological land types
The above results show that non-ecological land such as building land will reduce the function of ecosystem services. In the past 20 years, there has been a slight increase in construction land in Huai'an, but the overall land occupation ratio is not high, which has not caused a decline in the overall ecosystem service function. Correspondingly, the proportion of ecological land in Huai'an city has decreased slightly in the past 20 years, but the function of ecosystem services has increased significantly, most likely because of the improvement of the quality of the ecosystem itself, rather than the increase in the area of the ecosystem. In order to demonstrate this view, the author further analyzes the changes in vegetation vitality in the study area.
4.2 Vegetation vitality
Using Mann-Kendall nonparametric test and Hurst index, the spatio-temporal trend of the enhanced vegetation index (EVI) in Huai'an was analyzed, and the results are shown in Figure 12. The results show that from the overall point of view, the EVI area of the whole Huai'an area increased significantly, and the sustained H> 0.75. Only in the central areas of Lianshui County, Qingjiangpu District, Hongze District, Xuyi County, and Jinhu County, the EVI has decreased significantly, mainly due to the increase in the area of building land. The above results show that the greenness of vegetation in most areas of Huai'an is increasing.
Figure 12 EVI change trend and Hurst index distribution in Huai'an City from 2000 to 2018
Figure 13 shows trends in vegetation net primary productivity NPP, average annual precipitation, and annual average temperature. The figure shows that the average annual precipitation of Mann-Kendall in the study area ranges from 0 to 1.60, which remains basically unchanged, and the average annual temperature of Mann-Kendall values ranges from 0 to 1.82, which remains basically unchanged; however, NPP maintains a very significant upward trend, which proves that the vegetation vitality in the study area shows an increasing trend.
Figure 13 Spatial distribution of NPP, precipitation and temperature change trends in Huai'an City from 2000 to 2018
5 Conclusion
In this paper, taking Huai'an City as the study area, the remote sensing index method of the assessment of the importance of ecosystem service functions was expanded from the time dimension, and the multi-source remote sensing data based on long-term sequences were used from the perspectives of water conservation, soil and water conservation and biodiversity maintenance, and the evolution trend of ecosystem service function importance in the study area was further evaluated and analyzed by using Mann-Kendall non-parametric test and Hurst trend analysis, and combined with medium and high resolution remote sensing data interpretation. The reasons for the change in the function of ecosystem services are explored. The results show that: (1) from 2000 to 2018, the overall ecosystem service function of Huai'an City showed an increasing trend, of which the growth trend of water conservation and biodiversity was weak, and the growth trend of water and soil conservation was strong. (2) The increase in ecosystem service functions mainly occurs in vegetation cover areas such as cultivated land and woodland, and the reduction area mainly occurs in non-ecological land areas such as building land. (3) The proportion of vegetation coverage areas such as cultivated land and woodland in Huai'an City remains basically unchanged, and even decreases slightly as the proportion of construction land increases. Therefore, the main reason for the increase in ecosystem service functions may lie in the enhancement of vegetation vitality, which is manifested in the increase in vegetation greenness and vegetation productivity.
About the Author
About author:Hao Sun (1986-), male, Ph.D., Associate Professor, Research direction is remote sensing of resources and environment.
E-mail: [email protected]
Preliminary: Yang Ruifang
Review: Song Qifan
Final Judge: Jin Jun
The Special Issue of the Journal of Surveying and Mapping called for papers | Landslide disaster monitoring and early warning
Journal of Surveying and Mapping (English Edition) (JGGS) Special Issue Call for Papers | Call for Papers: Spatial Human and Social Geographic Computing (SHGSS)
Zhilin LI et al. ：Information Theory of Cartography: An Information-theoretic Framework for Cartographic Communication
Notice of the General Office of the Ministry of Natural Resources on printing and distributing the "Key Points of the Ministry of Natural Resources' 2021 Government Affairs Openness Work"