sustainability

Article Temporal-Spatial Evolution of the Urban Ecological Footprint Based on Net Primary Productivity: A Case Study of Central Area, China

Yao Lu 1 , Xiaoshun Li 1,2,*, Heng Ni 1, Xin Chen 3, Chuyu Xia 4,5, Dongmei Jiang 1,2 and Huiping Fan 1

1 Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China; [email protected] (Y.L.); [email protected] (H.N.); [email protected] (D.J.); [email protected] (H.F.) 2 China Land Problem Research Center, Agricultural University, Nanjing 210095, China 3 Department of Land Resources Management, College of Land Science and Technology, China Agricultural University, Beijing 100194, China; [email protected] 4 Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China; [email protected] 5 Fenner School of Environment and Society, Australian National University, Canberra ACT 2614, Australia * Correspondence: [email protected]; Tel.: +86-0516-8359-1322

 Received: 28 November 2018; Accepted: 27 December 2018; Published: 3 January 2019 

Abstract: The urbanization process all over the world has caused serious ecological and environmental problems which have recently become a focus for study. Ecological footprint analysis, which is widely used to assess the sustainability of regional development, can quantitatively measure the human occupation of natural capital. In this study, the ecological footprint based on net primary production (EF-NPP) and MODIS data were used to measure the ecological footprint in Xuzhou central area from 2005 to 2014. The results showed that from 2005 to 2014, the per capita ecological footprint increased from 1.06 to 1.17 hm2/person; the per capita ecological capacity decreased from 0.10 to 0.09 hm2/person; the per capita ecological deficit increased from −0.96 to −1.09 hm2/person; and the ecological pressure index increased from 6.87 to 11.97. The composition of the ecological footprint showed that grassland contributed most to the ecological footprint and deficit, and cultivated land contributed most to the ecological capacity. The spatial distribution of the ecological footprint changed significantly, especially in the expansion of the area of lower value. The ecological capacity and deficit changed little. The ecological situation in Xuzhou central area was unbalanced. Based on this study, Xuzhou city was recommended to control the increase of the ecological footprint, improve the ecological capacity and balance the ecological pattern for sustainable development.

Keywords: EF-NPP; MODIS; ecological footprint; temporal variation; spatial pattern; Xuzhou

1. Introduction Since the Industrial Revolution, the rapid development of cities and countries has caused an ecological and environmental disaster that is directly threatening human survival and sustainable social development. With the rapid advancement of urbanization and the accelerated growth of urban populations per year, the demand for land and natural resources in production and life has increased rapidly, and a significant amount of cultivated land, forestland and other types of ecological land have been occupied for real estate [1,2]. The development and construction of commercial areas and industrial areas, the changes in land use, and especially the excessive spread of cities have had a

Sustainability 2019, 11, 199; doi:10.3390/su11010199 www.mdpi.com/journal/sustainability Sustainability 2019, 11, 199 2 of 21 negative impact on the ecosystem service function [3], by impacting on water [4,5], promoting urban climate change [6] and contributing to the destruction of biodiversity [7]. Urbanization has caused serious conflicts between humans and nature, and overload of the regional land ecological carrying capacity as well. Similar to in other countries, after the reform and opening up, China’s urbanization level has increased from 17.92% in 1978 to 58.52% in 2017, with an average annual growth rate of more than 1%. The gross domestic product (GDP) of China has maintained an average annual growth rate of about 10% from the early 90s to 2011 [8], and this achievement has attracted worldwide attention. However, ecological problems have increased continually during the last 30 years, accelerating the depletion of resources and the environment that China’s economy and society rely on, and seriously hindering the dream of ordinary people to pursue a beautiful and livable life [9]. The government has also realized the seriousness of the deterioration of the ecological environment [10]. Therefore, to achieve sustainable development, accurately defining the land carrying capacity, rationally using land, and easing the contradiction between people and land are essential challenges to face, and this is a notable focus of research and policy innovation at present. Compared with previous economic models, ecological footprint analysis can quantify the utilization of natural capital by human beings, evaluate the impact of human activities on the ecosystem and environment [11], and judge whether human activities are within the carrying range of the ecosystem. The higher the ecological footprint value, the more resources humans need, and the more severe impact on the environment and Earth. The ecological footprint method provides an evaluation method for the quantitative measurement of sustainable development [3]. The ecological footprint analysis method was formally proposed by Canadian eco-economist William Rees in the early 1990s, and his student Mathis Wackernagel refined the ecological footprint analysis in his following research [12,13]. By calculating the bio-productive land and water area consumption and output, ecological footprint analysis estimates the supply and demand of natural capital. Bio-productive land is the basis that provides a unified measurement for natural capital, and makes it easy to calculate the total output of different kinds of land [13]. Bio-productive land is the land or water that has biological production capacity and can be classified into six types: Cultivated land, grassland, forestland, water area, fossil energy land, and built-up land. Ecological footprint analysis has been applied by various scholars in the measurement of ecological carrying capacity and the sustainable development level because it is easy to understand and simple to calculate [14,15]. With the increase in the breadth and depth of research, scholars have improved many aspects of the traditional ecological footprint model, including its time and space scales. Scholars have also studied the temporal variation and prediction of the ecological footprint, which makes up for the shortcomings in instantaneity of traditional ecological footprint analysis [16–18]. Some scholars have proposed modified models based on the national hectare, provincial hectare and local hectare, making the ecological model present the profit or deficit more precise on medium and small scales [19,20]. In recent years, some scholars have improved the calculation method of traditional ecological footprint analysis by utilizing knowledge from other areas. Others have proposed an ecological footprint model based on emergy analysis and net primary productivity (NPP) to obtain the equivalence factors and yield factors that reflect the real consumption and production situation [21–23]. Still others have introduced footprint depth and footprint size to construct a 3D ecological footprint model [24,25]. Overall, there is a mature structure of research on ecological footprint analysis. However, current researches paid less attention to the spatial evolution and spatial pattern of the ecological footprint, and more to the temporal change of the size of the ecological footprint. With the aim of addressing limitation of ecological footprint analysis in spatial analysis, we undertook this study. In this study, in view of the characteristic ease of calculation, the ecological footprint based on net primary productivity (EF-NPP) was applied to calculate equivalence factors and yield factors. The aim of this article is to present the temporal change and spatial evolution of the ecological footprint in Sustainability 2019, 11, 199 3 of 21

XuzhouSustainability central 2019, 11 area, x FOR from PEER 2005 REVIEW to 2014, and to explore the spatial pattern of the ecological footprint3 of 21 and ecologically fragile areas, in order to optimize the spatial pattern of Xuzhou central area. 2. Study Area 2. StudyXuzhou Area city is located in Jiangsu Province, China and the latitude and longitude are 116°22′– 118°40Xuzhou′ E, 33°43 city′–34°58 is located′ N. The inarea Jiangsu of Xuzhou Province, city is China1.18 × 10 and4 km the2, and latitude the population and longitude was 8.76 are × 116106 ◦at22 the0–118 end◦40 of0 2017.E, 33◦ There430–34 are◦58 100 N. districts, The area counties of Xuzhou and county city is 1.18-level× cities104 km under2, and the the jurisdiction population of wasXuzhou 8.76 city.× 10 Xuzhou6 at the central end of 2017.area is There the center are 10 of districts, Xuzhou countiescity, which and contains county-level five districts cities under(Yunlong the jurisdictiondistrict, Gulou of Xuzhoudistrict, Quanshan city. Xuzhou , central Jiawa areang is district, the center and ofTongshan Xuzhou district), city, which covering contains an area five districtsof 3.06 × (Yunlong103 km2. Figure district, 1 shows Gulou the district, location Quanshan of the study district, area. , and ), coveringAccording an area to of the 3.06 Statistical× 103 km Bulletin2. Figure of Xuzhou1 shows City the’s location 2017 National of the Economic study area. and Social Development [26], Accordingby the end of to 2017, the theStatistical GDP of Xuzhou Bulletin was of 6.61 Xuzhou × 1011 City’s yuan, 2017and the National urbanization Economic rate was and 63.8%, Social Developmentan increase of[26 1.4%], by over the endthe ofprevious 2017, the year. GDP However, of Xuzhou the was rapid 6.61 urbanization× 1011 yuan, process and the in urbanization Xuzhou has ratealso wascaused 63.8%, some an problems, increase of such 1.4% as over the theoccupation previous of year. ecological However, land the for rapid urban urbanization constructio processn land, inthe Xuzhou contradiction has also between caused supply some problems, and demand such of as construction the occupation land, of and ecological the weakening land for of urban land constructionecological service land, functions. the contradiction These are betweenurgent problems supply andto be demand solved immediately of construction and land,in addition, and the in weakeninga resource- ofexhausted land ecological city, many service environmental functions. These problems are urgent also problems arise in to bethe solved process immediately of urban andtransformation. in addition, in a resource-exhausted city, many environmental problems also arise in the process of urban transformation.

Figure 1. Location of the study area. Figure 1. Location of the study area. 3. Data and Methods 3. Data and Methods 3.1. Data Sources and Pretreatment 3.1. Data Sources and Pretreatment 3.1.1. Data Sources

3.1.1.According Data Sources to its availability, the statistical data were obtained from the Xuzhou Statistical Yearbook from 2005 to 2014 [27], including the area, population of Xuzhou central area, and the consumption According to its availability, the statistical data were obtained from the Xuzhou Statistical and yield of bio-productive land. Yearbook from 2005 to 2014 [27], including the area, population of Xuzhou central area, and the consumption and yield of bio-productive land. There are two kinds of MODIS data used in this study: Net Primary Production (MOD17A3) and Land Cover Type (MCD12Q1). The data are from Earthdata, NASA (https://earthdata.nasa.gov/) [28]. Sustainability 2019, 11, 199 4 of 21

There are two kinds of MODIS data used in this study: Net Primary Production (MOD17A3) and Land Cover Type (MCD12Q1). The data are from Earthdata, NASA (https://earthdata.nasa.gov/) [28]. The MODIS Net Primary Productivity product (MOD17A3) defines the rate at which all plants in an ecosystem produce net useful chemical energy. The spatial resolution is 1 km × 1 km, the remote sensing parameters are from Terra satellite, and the calculation result is given in yearly production. The valid values of the MOD17A3 data range from 0 to 65500 and the scale factor is 0.0001. The MODIS Land Cover Type product contains five classification schemes, and the spatial resolution is 500 m × 500 m. In this study, the Land Cover Type 2 was selected to reclass the land use cover.

3.1.2. Data Pretreatment The software MODIS Reprojection Tool (MRT) was used to reproject the MODIS data into Albers projection. ArcGIS was used to clip the grid files by the Xuzhou central area boundary and China boundary. MOD17A3 data were processed to obtain the NPP value and MCD12Q1 data were processed to reclass the land use cover into cultivated land, forestland, grassland, water area and built-up land. Finally, MOD17A3 data and MCD12Q1 data were analyzed by the overlay analysis function in ArcGIS to obtain the spatial distribution of the ecological footprint.

3.2. Research Methods

3.2.1. Net Primary Productivity NPP is defined as the rate of atmospheric carbon uptake through the process of net photosynthesis minus dark respiration [29,30]. As the most important part of the surface carbon cycle, NPP can not only directly reflect the productivity of plant communities in the natural environment and show the quality of the terrestrial ecological system but also can define the main factor of the carbon source/sink and the process of regulating ecosystem [31]. The recent research on NPP has mainly focused on the measurement of NPP and the calculation model of NPP, and some research has undertaken the dynamic simulation of regional NPP [32].

3.2.2. Ecological Footprint Model The ecological footprint model is divided into two parts: The ecological footprint and ecological carrying capacity. The formulas are as follows [12,33]:

6 6 n ! 6 " n !# cj EF = N × e f = N × ∑(λi × AI ) = N × ∑ λi × ∑ aaj = N × ∑ λi × ∑ . (1) i=1 i=1 j=1 i=1 j=1 pj where EF is the total ecological footprint (hm2); N is the total population; ef is the per capita ecological 2 footprint (hm /person); i is the six types of bio-productive land and water area; λi is the equivalence 2 factor of i-type bio-productive land; Ai is the per capita area of i-type bio-productive land (hm ); j is 2 the type of consumption item; aaj is the per capita area of the j-th bio-productive land (hm /person), cj is the per capita annual consumption of j-th consumption item (kg/person); and pj is the average production capacity of the j-th consumption item (kg/hm2).

6 EC = N × ec = N × ∑(αi × λi × yi) (2) i=1 where EC is the total ecological carrying capacity (hm2); N is the total population; ec is the per capita 2 2 ecological carrying capacity (hm /person); ai is the per capita area of i-type bio-productive land (hm ); λi is the equivalence factor of i-type bio-productive land; and yi is the yield factor. According to the suggestion that the United Nations World Commission on Environment and Development (WCED) Sustainability 2019, 11, 199 5 of 21 proposed in the book Our Common Future, to protect biodiversity, the ultimate ecological carrying capacity should be deducted by 12% on the basis of the balanced ecological carrying capacity [34]. In comparing the ecological footprint and ecological capacity, if the ecological footprint is higher than the ecological capacity an ecological deficit is created, which means under the current technology and productivity, the area of bio-productive land cannot support human life. Otherwise, an ecological profit occurs, which means the area of bio-productive land can adequately support human life. According to the production of the study area and the availability of data, the consumption items were classified as shown in Table1.

Table 1. Consumption items of the national hectare ecological footprint model.

Bio-Productive Land Consumption Item Type cereals, beans, potatoes, cotton, oilseeds, sugar, vegetable and Cultivated land melons, hemp, tobacco Forestland silkworm cocoons, fruits, chestnuts, ginkgo Grassland pork, beef, lamb, poultry, rabbit, milk, sheep, eggs, honey Water area aquatic products Fossil energy land coal, oil, natural gas Built-up land electricity

In the calculation of the production and consumption of bio-productive land, emergy conversion coefficient was used to convert the production and consumption into emergy [35], in order to make the calculation both simple and more accurate.

3.2.3. EF-NPP After the invention of ecological footprint analysis, some scholars suggested that the consumption of natural capital in ecological footprint analysis is actually the occupation of NPP [36]. By integrating NPP into the ecological footprint framework, EF-NPP was proposed by Venetoulis and Talberth in 2008 [21]. They refined the ecological footprint by changing the equivalence factors to NPP rather than agricultural productivity in order to achieve a more precise ecological footprint. In contrast with the traditional ecological footprint, in EF-NPP, when calculating the ecological capacity, we use a deduction of 13.4% to protect biodiversity. The equivalence factor is the coefficient that converts the bio-productive land into areas with the same ecological productivity, and the yield factor is the coefficient that describes the yield difference between the study area and the nation overall. The equivalence factor and yield factor in EF-NPP can show the different productivity of different land types or different areas directly. According to earlier researches, the formulas of the equivalence factor and yield factor are as follows [36,37]:

NPP λ = i (3) i NPP where λi is the equivalence factor, NPPi is the average NPP of i-type bio-productive land in the study area, and NPP is the average NPP of all types of bio-productive land in the study area.

NPPi yi = (4) NPPi where yi is the yield factor, NPPi is the average NPP of i-type bio-productive land in the study area, and NPPI is the average NPP of i-type bio-productive land in China. Sustainability 2019, 11, 199 6 of 21

3.2.4. Ecological Pressure Index The ecological pressure index refers to the ratio of the per capita ecological footprint and the ecological capacity, which represents the pressure tolerance of the regional ecological environment [38–40]. The formula is as follows:

EF EP = (5) EC where EP is the ecological pressure index, EF is the ecological footprint, and EC is the ecological capacity. According to Zhao’s study, the ecological pressure index can be divided into six grades [38], as shown in Table2.

Table 2. Ecological pressure index.

Grade Ecological Pressure Index Token State 1 < 0.50 Very safe 2 0.51–0.80 Relatively safe 3 0.81–1.00 Slightly unsafe 4 1.01–1.50 Relatively unsafe 5 1.51–2.00 Very unsafe 6 > 2.01 Extremely unsafe

4. Results and Analysis The ecological footprint in Xuzhou central area was analyzed in two aspects: Temporal evolution and spatial evolution.

4.1. Temporal Evolution of Ecological Footprint in Xuzhou Central Area

4.1.1. Calculation of Equivalence Factors and Yield Factors To calculate the temporal evolution of the ecological footprint, first the equivalence factors and yield factors were calculated using the consumption and yield of bio-productive land, as shown in Figure2. As shown in Figure2a, the equivalence factor of cultivated land was the highest, and that of the water area was the lowest. The results mean that the bio-productive capacity of cultivated land in Xuzhou central area was the highest in the bio-productive land and that of the water area was the lowest. The equivalence factor of fossil energy land was the same as forest land because the fossil energy footprint was expressed by the area of the forest which can absorb CO2 emissions. As shown in Figure2b, the yield factor of grassland was the highest and that of forestland was the lowest. The results mean that the bio-productive capacity of cultivated land and grassland in Xuzhou central area were higher than the national average level, while the bio-productive capacity of forestland, the water area, and built-up land were lower than the national average level. There were fluctuations during the study period but the changes were small. The yield factor of fossil energy land was zero because there is no bio-production output. Sustainability 2019, 11, 199 7 of 21 Sustainability 2019, 11, x FOR PEER REVIEW 7 of 21

1.10 1.05 1.00 0.95 0.90 0.85 0.80 0.75

(a) equivalence factors (a) equivalence 0.70 0.65 0.60 2005 2007 2009 2011 2013 Year Cultivated land Forestland Grassland Water area Fossil energy land Built-up land

1.80 1.60 1.40 1.20 1.00 0.80 0.60 (b) Yield factors (b) Yield 0.40 0.20 0.00 2005 2007 2009 2011 2013 Year Cultivated land Forestland Grassland Water area Fossil energy land Built-up land

FigureFigure 2. 2.(a ()a Equivalence) Equivalence factors factors and and ((bb)) yieldyield factors of Xuzhou Xuzhou central central area area from from 2005 2005 to to2014 2014..

4.1.2. CalculationAs shown in of Figure the Ecological 2a, the equivalence Footprint andfactor Ecological of cultivated Pressure land was Index the highest, and that of the water area was the lowest. The results mean that the bio-productive capacity of cultivated land in The per capita ecological footprint, ecological capacity and ecological deficit in Xuzhou central Xuzhou central area was the highest in the bio-productive land and that of the water area was the area from 2005 to 2014 were measured as shown in Table3. lowest. The equivalence factor of fossil energy land was the same as forest land because the fossil energyTable footprint 3. Temporal was change expressed of the by per the capita area of ecological the forest footprint which can profit absorb and deficitCO2 emissions. in Xuzhou central areaAs from shown 2005 in to Figure 2014 (hm 2b,2 /person).the yield factor of grassland was the highest and that of forestland was the lowest. The results mean that the bio-productive capacity of cultivated land and grassland in Xuzhou central Yeararea were Ecological higher Footprintthan the national Ecological average Capacity level, while Ecological the bio Deficit-productive capacity of forestland, the2005 water area, 1.0617and built-up land were 0.1004 lower than the national−0.9613 average level. There were fluctuations2006 during the 0.9880 study period but the 0.1153 changes were small.−0.8728 The yield factor of fossil energy land was2007 zero because 1.0387 there is no bio-production 0.0903 output. −0.9484 2008 0.9432 0.1208 −0.8225 − 4.1.2. Calculation2009 of the Ecological 1.0809 Footprint and Ecological 0.1084 Pressure Index0.9725 2010 1.1164 0.1239 −0.9925 The per capita2011 ecological 1.1723footprint, ecological capacity 0.1132 and ecological−1.0591 deficit in Xuzhou central area from 2005 to2012 2014 were measured 1.1766 as shown in Table 0.1202 3. −1.0564 2013 1.2441 0.1157 −1.1284 2014 1.1718 0.0865 −1.0854 Sustainability 2019, 11, x FOR PEER REVIEW 8 of 21

Table 3. Temporal change of the per capita ecological footprint profit and deficit in Xuzhou central area from 2005 to 2014 (hm2/person).

Year Ecological Footprint Ecological Capacity Ecological Deficit 2005 1.0617 0.1004 −0.9613 2006 0.9880 0.1153 −0.8728 2007 1.0387 0.0903 −0.9484 2008 0.9432 0.1208 −0.8225 2009 1.0809 0.1084 −0.9725 2010 1.1164 0.1239 −0.9925 2011 1.1723 0.1132 −1.0591 2012 1.1766 0.1202 −1.0564 Sustainability2013 2019, 11, 199 1.2441 0.1157 −1.1284 8 of 21 2014 1.1718 0.0865 −1.0854

As shown in Table 3 3,, fromfrom thethe generalgeneral view,view, thethe perper capitacapita ecologicalecological footprintfootprint showedshowed aa risingrising 2 trend of 0.11010.1101 hmhm2/person. There There were were fluctuations fluctuations during during study study period period which which may may be be caused by the deduction of consumption and equivalence factors. The ecological footprint reached its highest 2 point of 1.2441 hm2/person in in 2013, 2013, and and the the equivalence equivalence factors factors of of forestland, forestland, grassland, grassland, water water area, area, fossil energy land and built built-up-up land both increased. increased. The The per per capita capita ecol ecologicalogical capacity capacity decreased decreased from 2 2 0.1004 hm2/person to to 0.0865 0.0865 hm hm2/person./person. The The per per capita capita ecological ecological profit profit and and deficit deficit presented presented as the 2 ecological deficit deficit from 2005 toto 2014,2014, whichwhich increasedincreased byby 0.12410.1241 hmhm2/person./person. The The fluctuation fluctuation trend of ecological deficit deficit is basically the same as ecological footprint. The ecological pressure index represents the pressure tolerance of the regional ecological environment. The ecological pressure index of Xuzhou central area was calculated and the results are shown in Figure 3 3..

13.00

12.00

11.00

10.00

9.00

8.00

Ecological pressure Ecological index 7.00

6.00 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year

FFigureigure 3. EcologicalEcological pressure pressure index of Xuzhou central area from 2005 to 2014.2014.

As shown in Figure 33,, thethe changechange ofof thethe ecologicalecological pressurepressure indexindex fromfrom 20052005 toto 20142014 presentedpresented with a rising rising trend, trend, although although there there were were declines declines in in2006, 2006, 2008, 2008, 2010, 2010, and and 2012. 2012. It is Itworth is worth noting noting that thethat ecological the ecological footprint footprint and and ecological ecological capacity capacity both both decreased decreased in in 2014, 2014, however however the the ecological pressure still increased. The The reason reason for this situation was that the decreasing rate of the ecological footprint was smaller and that of t thehe ecological capacity was bigger, which led to the overall increase of the ecological pressure. According According to to the the grade of the ecological pressure index, the ecological situation of Xuzhou central area was extremely unsafe fromfrom 20052005 toto 2014.2014.

4.1.34.1.3.. Composi Compositiontion of the Ecological Footprint in Xuzhou Central Area To analyze the temporal change of the ecological footprint in Xuzhou central area more accurately, we studied the composition of the ecological footprint, ecological capacity, and ecological deficit from 2005 to 2014. As shown in Figure4, the grassland ecological footprint contributed the most to the whole ecological footprint during the study period, and the proportion increased from 31% to 40%. The cultivated land ecological capacity took the largest proportion, which was over 80%. The proportion of the grassland ecological deficit which took the largest proportion, increased from 34% to 43%, while the forestland ecological deficit decreased from 16% to 7%. The ecological footprint, ecological capacity and ecological deficit of water area changed little, which meant that the humans’ impact on water were smaller. Sustainability 2019, 11, x FOR PEER REVIEW 9 of 21

To analyze the temporal change of the ecological footprint in Xuzhou central area more accurately, we studied the composition of the ecological footprint, ecological capacity, and ecological deficit from 2005 to 2014. As shown in Figure 4, the grassland ecological footprint contributed the most to the whole ecological footprint during the study period, and the proportion increased from 31% to 40%. The cultivated land ecological capacity took the largest proportion, which was over 80%. The proportion of the grassland ecological deficit which took the largest proportion, increased from 34% to 43%, while the forestland ecological deficit decreased from 16% to 7%. The ecological footprint, ecological Sustainabilitycapacity and2019 ,ecological11, 199 deficit of water area changed little, which meant that the humans’ impact9 on of 21 water were smaller.

100% 90% 80% 70% 60% 50% 40% 30%

(a) Ecological footprint (a) Ecological 20% 10% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Farmland Forestland Grassland Water area Fossil energy land Built-up land

100% 90% 80% 70% 60% 50% 40% 30%

(b) Ecological capacity (b) Ecological 20% 10% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Farmland Forestland Grassland Water area Built-up land Sustainability 2019, 11, x FOR PEER REVIEW 10 of 21

100% 90% 80% 70% 60% 50% 40% 30%

(c) Ecological (c) Ecological deficit 20% 10% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year Farmland Forestland Grassland Water area Fossil energy land Built-up land

FigureFigure 4. 4.Composition Composition ofof ((aa)) thethe ecologicalecological footprint, ( (b)) the the ecological ecological capacity capacity and and (c ()c )the the ecological ecological deficitdeficit in in Xuzhou Xuzhou central central area areafrom from 20052005 toto 2014.2014.

4.2. Spatial Evolution of Ecological Footprint in Xuzhou Central Area The spatial pattern of the ecological footprint, ecological capacity and ecological deficit in the main years during study period are shown in Figure 5. The spatial pattern of the whole study period are shown in Figure A1.

(a) Ecological footprint Sustainability 2019, 11, x FOR PEER REVIEW 10 of 21

100% 90% 80% 70% 60% 50% Sustainability 2019, 11, 199 10 of 21 40% 30%

4.2. Spatial Evolution (c) Ecological deficit 20% of Ecological Footprint in Xuzhou Central Area 10% The spatial pattern of the ecological footprint, ecological capacity and ecological deficit in the 0% main years during study2005 period2006 are shown2007 in2008 Figure20095. The2010 spatial2011 pattern2012 of2013 the whole2014 study period are shown in Figure A1. Year As shown in Figure5a,Farmland the green color representsForestland a lower ecologicalGrassland footprint value, and the red color represents a higher value. We can see that the ecological footprint values of built-up land were Water area Fossil energy land Built-up land relatively low, and the ecological footprint values of the water area were higher. It can be seen that in 2005, 2007, and 2008, the ecological footprint values of Xuzhou central area were relatively low, mainly Figure 4. Composition of (a) the ecological footprint, (b) the ecological capacity and (c) the ecological concentrated between 0.08–0.12 hm2/person, and the pattern was superior. In 2006, 2009, 2011, 2012, deficit in Xuzhou central area from 2005 to 2014. 2013, and 2014, the ecological footprint values of the central, southwestern, and northeastern parts of 4.2Xuzhou. Spatial central Evolution area wereof Ecological relatively Footprint low. The in Xuzhou low value Central area Area expanded toward the east and northeast over time. In these years, ecological footprint values between 0.12–0.18 hm2/person accounted for a largeThe proportion spatial pattern of the total. of the In ecological 2010, the overall footprint, ecological ecological footprint capacity of Xuzhou and ecological central area deficit increased, in the mainand the years pattern during deteriorated. study period From are theshown evolution in Figure of the 5. T ecologicalhe spatial footprintpattern of we the can whole find study that humans’ period areimpact shown on naturein Figure became A1. obvious and serious.

(a) Ecological footprint

Figure 5. Cont. Sustainability 2019, 11, 199 11 of 21 Sustainability 2019, 11, x FOR PEER REVIEW 11 of 21

(b) Ecological capacity

(c) Ecological deficit

FigureFigure 5. 5. SpatialSpatial evolution evolution of of (aa)) the ecological footprint, ( (b)) the ecological capacity and (c) the the ecological deficitdeficit in XuzhouXuzhou centralcentral areaarea inin thethe mainmain yearsyears duringduring thethe studystudy period.period.

As shown in in Figure Figure 5a,5b, the the green spatial color pattern represents of the ecologicala lower ecological capacity footprint changed value, little duringand the thered studycolor represents period. As a canhigher be seenvalue. from We thecan legend,see that redthe indicatesecological a footprint low ecological values carrying of built-up capacity land were and relatively low, and the ecological footprint values of the water area were higher. It can be seen that Sustainability 2019, 11, 199 12 of 21 green indicates a high ecological carrying capacity. The lower values were concentrated in the northern boundary, center, northeast and southwest parts of Xuzhou central area, and the higher values were distributed in the northwest and southeast of Xuzhou central area. The reason why the ecological capacity in the center was lower was that there was built-up land mainly and humans’ activities were more frequent. As shown in Figure5c, the spatial distribution of the ecological deficit changed little, in accordance with the ecological capacity. The values were mainly concentrated between −0.04 to 0 hm2 except in 2014, when the value was concentrated mainly between −0.08 to −0.04 hm2. The ecological deficit increased in 2014, meaning that the ecological environment deteriorated further. The higher values of the ecological deficit were distributed in the northeast and southwest of Xuzhou central area and the lower values were distributed in the northwest and southeast.

5. Discussion

5.1. EF-NPP and Traditional Ecological Footprint Analysis Recently, near real-time MODIS GPP/NPP products have been used in global or regional studies more and more [17,41]. EF-NPP is an improvement on traditional ecological footprint analysis. The main difference is the calculation method of the equivalence factors and yield factors. EF-NPP calculates the factors by the NPP of different kinds of land, while the traditional ecological footprint calculates by the consumption and yield of bio-productive land. Other than this, EF-NPP can calculate the factors of built-up land, in order to better express the productivity [22,36,37]. Compared with the study published in 2014, which also focused on the ecological footprint of Xuzhou [42], the ecological footprint and ecological capacity values of this study were relatively low, as shown in Figure6. The main reasons for the difference are the different equivalence factors and yield factors. The cultivated land and forestland equivalence and yield factors of this study were both lower, thus led to the low ecological footprint and low ecological capacity values. From both results we can see that the ecological footprint of Xuzhou increased during the study period, so it is important to establish a reasonable ecological footprint control mechanism in order to improve the ecological carrying capacity, and control and reduce the ecological deficit. As far as the composition of the ecological capacity, it is necessary to optimize the structure of the ecological capacity, and improve the grassland, forestland, and built-up land ecological capacity. Sustainability 2019, 11, x FOR PEER REVIEW 13 of 21

4

3.5 /person) 2 3

2.5

2

1.5

1

ecological (hm ecological footprint 0.5

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Per capita Year EF of Xi's study (2014) EC of Xi's study (2014) EF of this study EC of this study

FigureFigure 6. 6. TheThe comparison comparison of of ecological ecological footprint footprint in in Xuzhou Xuzhou with Xi’s study study..

Compared with the ecological footprint of the whole of China measured by EF-NPP [43], we found that the ecological footprint and ecological capacity of Xuzhou central area were both lower than the average value of China. As shown in Figure 7, the equivalence factors of cultivated land, forestland, built-up land, and fossil energy land in Xuzhou were lower than the average level of China, meaning the NPP of these bio-productive land in Xuzhou were relatively low. Additionally, the yield factors of cultivated land, forestland, built-up land, and fossil energy land in Xuzhou were lower than the average level of China, meaning the NPP of these bio-productive land did not reach the average level.

1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Cultivated Forestland Grassland Water area Built-up land Fossil land energy land

EQF of Liu's study (2014) EQF of This study YF of Liu's study (2014) YF of This study

Figure 7. The comparison of average equivalence factors and yield factors with Liu’s study.

Currently, there is still no standard framework for ecological footprint analysis, and the existing studies of ecological footprint analysis have paid less attention to the relationship between economic development and the ecological environment [44,45]. Ecological footprint analysis will be improved in the future to measure the natural capital more accurately and more comprehensive. Sustainability 2019, 11, x FOR PEER REVIEW 13 of 21

4

3.5 /person) 2 3

2.5

2

1.5

1

ecological (hm ecological footprint 0.5

0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Per capita Year EF of Xi's study (2014) EC of Xi's study (2014) EF of this study EC of this study

Sustainability 2019, 11Figure, 199 6. The comparison of ecological footprint in Xuzhou with Xi’s study. 13 of 21

Compared with the ecological footprint of the whole of China measured by EF-NPP [43], we foundCompared that the ecological with the ecological footprint footprint and ecological of the whole capacity of China of Xuzhou measured central by EF-NPParea were [43 ],both we foundlower thanthat thethe ecological average value footprint of China. and ecological As shown capacity in Figure of Xuzhou7, the equivalence central area factors were both of cultivated lower than land the, forestland,average value built of-up China. land, As and shown fossil in energy Figure 7land, the equivalencein Xuzhou were factors lower of cultivated than the land,average forestland, level of China,built-up meaning land, and the fossil NPP energy of these land bio in-productive Xuzhou were land lower in Xuzhou than the were average relatively level low. of China, Additionally, meaning the yield NPP offactors these of bio-productive cultivated land, land forestland, in Xuzhou built were-up relativelyland, and low.fossil Additionally, energy land thein Xuzhou yield factors were lowerof cultivated than the land, average forestland, level of built-up China, meaning land, and the fossil NPP energy of these land bio in-productive Xuzhou were land lower did not than reach the theaverage average level level. of China, meaning the NPP of these bio-productive land did not reach the average level.

1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 Cultivated Forestland Grassland Water area Built-up land Fossil land energy land

EQF of Liu's study (2014) EQF of This study YF of Liu's study (2014) YF of This study

FFigureigure 7. TheThe comparison comparison of of average average equivalence equivalence factors and yield factors with Liu’s study study..

CuCurrently,rrently, therethere isis still no standard framework for ecological footprint analysis, and the existing studies of ecological footprint analysis have paid less attention to the relationship between economic development andand thethe ecologicalecological environment environment [ 44[44,45].,45]. Ecological Ecological footprint footprint analysis analysis will will be be improved improved in inthe the future future to measureto measure the the natural natural capital capital more more accurately accurately and and more more comprehensive. comprehensive.

5.2. Ecological Footprint Spatial Pattern and Ecological Pressure Some researchers hold the view that the ecological footprint cannot express the true ecological pressure [45,46]. However, in this study, the ecological footprint spatial pattern was showed, from which we could find where the ecological footprint was higher and the ecological capacity was lower in Xuzhou central area. The ecological pressure can be identified by the values of the ecological footprint and ecological capacity. According to the WWF’s report about China’s ecological footprint, China’s ecological footprint depends on the urbanization level [47]. It can be seen from the results that in the southwest and center parts of Xuzhou central area, with its high urbanization level, there was high ecological pressure. From the spatial pattern of the ecological footprint, the unbalanced ecological pattern should be optimized. The ecological pressure in the southwest and center of Xuzhou central area needs to be released. However, there still remain some shortcomings in this study. Due to the availability of the MOD17A3 data, we could only measure the ecological footprint of Xuzhou central area until 2014. Additionally, the resolution of the MODIS data is relatively coarse.

6. Conclusions During the process of urbanization, it is important to measure the human occupation of nature and maintain the sustainable development of society. Using EF-NPP, this article theoretically improved Sustainability 2019, 11, 199 14 of 21 the shortcomings of the ecological footprint model in spatial analysis, quantitatively measured the temporal change of the ecological footprint and spatially located the ecologically fragile areas. The results of this article prove that the ecological footprint can be used to indicate the pressure humans put on nature, by comparing it with the ecological capacity. Based on the results we found, policy suggestions for the sustainable development and ecological civilization of Xuzhou city were proposed. The main conclusions of this article are as follows: (1) The natural capital that humans require in Xuzhou central area increased, such that the bio-productive land could not support the demand of human living and production activities, and the ecological situation became extremely unsafe. (2) The spatial pattern showed the ecologically fragile areas and the unbalanced ecological situation in Xuzhou central area. The ecological pressure was higher in the northeast and southwest of Xuzhou central area. (3) Policy measures should be adopted to promote the harmonious development of ecology and the economy. The government should control the increase of the ecological footprint and improve the ecological capacity in the center of Xuzhou to alleviate conflicts between humans and the land. The urban space in different areas should be optimized to achieve the comprehensive and coordinated development of Xuzhou central area. The government should pay attention to increasing the investment in ecological civilization construction, improving the ecological environmental protection system as soon as possible in order to coordinate the development of the social economy and ecological environment, and take the road of sustainable development. The EF-NPP could be applied in regional ecological environment monitoring, and has profound implications for ecological security and city development planning. (4) The EF-NPP model measures the equivalence factors and yield factors by NPP instead of the production and consumption, which avoids deviation in the calculation. Combining the calculation values with land use data can spatialize the ecological footprint, ecological capacity and ecological deficit, thus making up for the shortcomings in the spatial analysis of ecological footprint analysis. (5) In future studies, the accuracy of land use data needs to be improved. For example, the MODIS data could be replaced by Landsat data with a higher resolution. Furthermore, the ecological footprint model can continue to be improved to be more comprehensive.

Author Contributions: Conceptualization, Y.L.; Data Curation, Y.L.; Formal Analysis, Y.L.; Funding Acquisition, X.L.; Methodology, Y.L.; Project Administration, X.L.; Software, H.N.; Supervision, X.L. and C.X.; Visualization, H.N.; Writing-Original Draft, Y.L. and H.N.; Writing-Review & Editing, X.L., X.C., C.X., D.J. and H.F. Funding: This study was supported by National Natural Sciences Foundation of China (Grant No. 71473249, Grant No. 71704177 and Grant No. 71874192), Fundamental Research Funds for the Central Universities (2017WB05), Key Projects of Jiangsu Provincial Social Science Fund (15EYA002), Open Fund for the Key Laboratory for Coastal Zone Development and Protection of the Ministry of Land and Resources (2017CZEPK10) and National College Students Innovation Training Program (201810290034). Acknowledgments: The supports of China University of Mining and Technology and School of Environment Science and Spatial Informatics are acknowledged. Conflicts of Interest: The authors declare no conflict of interest. Sustainability 2019, 11, x FOR PEER REVIEW 15 of 21

Funding: This study was supported by National Natural Sciences Foundation of China (Grant No. 71473249, Grant No. 71704177 and Grant No. 71874192), Fundamental Research Funds for the Central Universities (2017WB05), Key Projects of Jiangsu Provincial Social Science Fund (15EYA002), Open Fund for the Key Laboratory for Coastal Zone Development and Protection of the Ministry of Land and Resources (2017CZEPK10) and National College Students Innovation Training Program (201810290034).

Acknowledgments: The supports of China University of Mining and Technology and School of Environment SustainabilityScience and 2019Spatial, 11, Informatics 199 are acknowledged. 15 of 21

Conflicts of Interest: The authors declare no conflict of interest. Appendix A Appendix A

Figure A1. Cont. Sustainability 2019, 11, 199 16 of 21 Sustainability 2019, 11, x FOR PEER REVIEW 16 of 21

(a) Ecological footprint

Figure A1. Cont. Sustainability 2019, 11, 199 17 of 21 Sustainability 2019, 11, x FOR PEER REVIEW 17 of 21

(b) Ecological capacity

Figure A1. Cont. Sustainability 2019, 11, 199 18 of 21 Sustainability 2019, 11, x FOR PEER REVIEW 18 of 21

(c) Ecological deficit

FigFigureure A1 A1.. SpatialSpatial evolution evolution of of ( (aa)) ecological ecological footprint, footprint, ( (bb)ecological)ecological capacity capacity and and ( (cc)) ecological ecological deficit deficit in Xuzhou central area from 2005 to 2014.2014.

Sustainability 2019, 11, 199 19 of 21

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