Ecological Sensitivity Assessment and Spatial Pattern Analysis of Land Resources in Tumen River Basin, China
2. Research Methodology
2.1. Overview of the Study Area and Data Sources
2.1.1. Overview of the Study Area
2.1.2. Data Sources and Preprocessing
2.2. Construction of an Ecological Sensitivity Evaluation System
2.2.1. Selection of Evaluation Factors
2.2.2. Classification of Sensitivity Levels for Each Factor
2.3. Determination of Factor Weights
- Define the objectives of the analysis, identify the various factors related to the objectives of the analysis and the correlation between the various factors, then establish a hierarchical structure model.
- Construct a judgment matrix and invite relevant experts to score each of the two factors according to their relative importance.
- Calculate the weights and maximum eigenvalue of each indicator using the sum-product method.
- Conduct a consistency test. If the consistency ratio CR < 0.10, it means that the judgment matrix passes the consistency test and the weights determined above are valid.
2.4. Comprehensive Evaluation of Ecological Sensitivity
3.1. Single Factor Analysis
3.1.1. Natural Environmental Factors
- Mean annual temperature. The mean annual temperature in the Tumen River Basin ranges from −0.9 °C to 6.7 °C, and the spatial difference is not very large. Based on the actual situation in the study area, the natural breakpoint method was used to classify the mean annual temperature sensitivity into five levels (Table 2), and the results and statistics are presented in Figure 3a and Table 4. It can be seen that the sensitivity is higher in the central and eastern parts of the Tumen River Basin, and it decreases in the west, north, and south. In general, the slightly sensitive, moderately sensitive, and highly sensitive areas are more or less evenly distributed, with a lower proportion of insensitive and extremely sensitive areas.
- Annual precipitation. The result of the annual precipitation sensitivity classification of the Tumen River Basin is shown in Figure 3b. The central region of the basin is extremely sensitive, while the sensitivity of other regions gradually decreases from the center to the periphery. The area proportion of highly sensitive areas is the highest, followed by extremely sensitive areas, and the area proportion of moderately sensitive areas, slightly sensitive areas, and insensitive areas gradually decreases.
- Elevation. The Tumen River Basin is located in the Changbai Mountain Range, with elevations ranging from 8 m to 1689 m. The elevation varies greatly and the topography is undulating. As shown in Figure 3c, the sensitivity is higher in the higher elevation areas in the south and north, and lower in the central and eastern river valley plains. The area of slightly sensitive areas and moderately sensitive areas account for a relatively large proportion of the study area, while insensitive areas and highly sensitive areas account for a relatively small proportion, and only 1.66% of region are extremely sensitive areas.
- Distance to water. Water bodies, such as rivers, lakes, and reservoirs, play an important role in maintaining the regional ecological balance. In this study, the ecological sensitivity levels were classified according to the distance from water (Table 2), and the results are shown in Figure 3d. The ecological sensitivity in the study area is closely related to the distribution of the Tumen River main stream, tributaries at all levels, lakes, reservoirs, and other water bodies. The proportion of the area of insensitive and slightly sensitive areas is relatively large, totaling 60.67%. The proportion of moderately sensitive and highly sensitive areas is relatively low, and the area of extremely sensitive areas is 1942.47 km2, which is the smallest proportion of the area.
3.1.2. Human Disturbance Factors
- Land use types. Different land use patterns make for different land cover, and differences exist in their regional ecological service functions and response to human activity disturbances. Among the various types of land use in the Tumen River Basin, the woodland is absolutely dominant, followed by cultivated land, with a relatively low proportion of construction land, grassland, and other land areas. According to the principles of classifying the sensitivity levels of land use type factors (Table 2), the result of the ecological sensitivity levels in the study area is shown in Figure 4a and Table 5. The moderately sensitive area corresponding to the woodland accounts for 84.39% of the total area, covering most of the study area, with a clear dominance. In second place is the slightly sensitive area corresponding to cultivated land distributed in the valley plains and nearby areas with low slopes, accounting for 11.38%. The least abundant area is the extremely sensitive area, with only 0.46%, where the main types of land are water or wetland.
- Distance to construction land. In general, the smaller the distance to construction land, the more frequent the human activities and the stronger the disturbance to the ecosystem (Table 2). Construction land in the Tumen River Basin is concentrated in the urban and township areas of the major cities in the study area, such as Yanji, Longjing, Tumen, and Wangqing, as well as in scattered rural settlements and industrial and mining sites. Therefore, the level of ecological sensitivity gradually decreases in these areas (Figure 4b). More than half of them are insensitive areas (57.07%). With the increase in sensitivity, the proportion of each sensitive area decreases (Table 5).
- Distance to road: Similar to the impact of construction land on ecological disturbance in the nearby area, the closer to the road, the higher the ecological sensitivity. The results are shown in Figure 4c and Table 5, based on the principle of classifying ecological sensitivity according to the distance to the road (Table 2). It is obvious that the ecological sensitivity gradually decreases with the increase in distance from the center of all kinds of roads in the study area to both sides. The areas with a clear dominance of area remain insensitive areas. The proportion of slightly sensitive, moderately sensitive, and highly sensitive areas gradually decreases, with the least extremely sensitive area accounting for only 6.88%.
3.1.3. Soil Erosion Factors
- Topographic relief. Topographic relief is an important topographic and geomorphic feature factor, which is closely related to soil erosion and ecological sensitivity. In general, the greater the relief, the higher the degree of ecological sensitivity. The Tumen River Basin is mostly mountainous and most of the areas have a large topographic relief and a high overall sensitivity. According to the results of the analysis (Figure 5a and Table 6), the study area has the largest area of highly sensitive areas, accounting for 54.87%. This is followed by moderately sensitive areas (32.01%). Slightly sensitive areas and insensitive areas account for a relatively small proportion and are mainly located in the river valley plain area. Extremely sensitive areas cover only 0.44% of the study area and are scattered throughout the areas where elevation changes are dramatic.
- Rainfall erosivity. The differences in rainfall erosivity in the Tumen River Basin are not particularly significant. Based on the results of the analysis, there are only two areas in the study area that are slightly and moderately sensitive (Figure 5b). Most of these areas are moderately sensitive (86.29%). A small number of slightly sensitive areas (13.71%) are mainly located in the mountainous areas in the northern part of the study area.
- Soil texture. The soil texture of the Tumen River Basin is dominated by clay loam and sandy loam, followed by loam and a very small amount of clay. The result of the ecological sensitivity classification of soil texture is shown in Figure 5c. Most of the study area is highly sensitive (73.94%); moderately sensitive areas are mainly located in river valleys, with an area of 26.01%; a very few slightly sensitive areas (0.06%) are mainly located near wetlands. There are no extremely sensitive areas or insensitive areas in the study area.
- Vegetation coverage. Vegetation cover is an important factor influencing the ecological sensitivity of the region . The Tumen River Basin has high forest coverage and an overall good level of ecological sensitivity (Figure 5d). Among the various levels of ecological sensitivity, the proportion of insensitive areas and mildly sensitive areas are relatively large, 70.83% and 23.95%, respectively, mainly woodland and grassland, cultivated land, and so on. The other three types of regions account for a relatively small proportion, with a total proportion of only 5.22%. The moderately sensitive and highly sensitive areas are located in scattered areas around the cities and towns. Extremely sensitive areas, with very low vegetation coverage, are located in urban construction land and areas such as rivers, lakes, and reservoirs.
3.2. Comprehensive Analysis
3.2.1. Spatial Pattern Analysis of Ecological Sensitivity
3.2.2. Ecological Sensitivity Analysis of Various Land Resources
4.1. Analysis of Results
4.2. Limitations of Work and Future Work
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
- Wang, K.; Tian, G.X.; Cui, L. Ecological Sensitivity Analysis in Tongshan Scenic Spot Based on RS and GIS. J. Northwest For. Univ. 2009, 24, 200–203, 228. (In Chinese) [Google Scholar]
- Zhou, Y.L.; Yang, Y.F.; Yuan, W.Y. Analysis and Evaluation on Ecological Sensitivity of Xiaoqinghe River Basin in Jinan Based on GIS. J. Northwest For. Univ. 2016, 31, 50–56, 62. (In Chinese) [Google Scholar]
- Pan, F.; Tian, C.; Shao, F.; Zhou, W.; Chen, F. Evaluation of Ecological Sensitivity in Karamay, Xinjiang, Northwest China. Acta Geogr. Sin. 2011, 66, 1497–1507. (In Chinese) [Google Scholar]
- Duan, X.J.; Zou, H.; Wang, L.; Chen, W.X.; Min, M. Assessing ecological sensitivity and economic potentials and regulation zoning of the riverfront development along the Yangtze River. China J. Clean. Prod. 2021, 291, 125963. [Google Scholar] [CrossRef]
- Yu, J.; Li, F.T.; Wang, Y.; Lin, Y.; Peng, Z.W.; Cheng, K. Spatiotemporal evolution of tropical forest degradation and its impact on ecological sensitivity: A case study in Jinghong, Xishuangbanna. China Sci. Total Environ. 2020, 727, 138678. [Google Scholar] [CrossRef]
- Bai, Y.J.; Guo, R. The construction of green infrastructure network in the perspectives of ecosystem services and ecological sensitivity: The case of Harbin, China. Glob. Ecol. Conserv. 2021, 27, 01534. [Google Scholar] [CrossRef]
- You, N.S.; Meng, J.J. Ecological Functions Regionalization and Ecosystem Management Based on the Ecological Sensitivity and Ecosystem Service in the Middle Reaches of the Heihe River. J. Desert Res. 2017, 37, 186–197. (In Chinese) [Google Scholar]
- Ding, Z.M.; Yao, S.B. Theoretical analysis and model design of search for ecological conservation redlines based on the sensitivity assessment of ecosystem services. Land Use Policy 2020, 97, 104745. [Google Scholar] [CrossRef]
- Guo, N.D.; Chen, Z.Y.; Li, H.Z. Ecological Sensitivity Research and Their Grey Forecast Based on Land Use Change in Pingshan County, Hebei Province. Res. Soil Water Conserv. 2016, 23, 229–234. (In Chinese) [Google Scholar]
- LI, S.C.; Wu, S.H.; Dai, E.F. Assessing the fragility of ecosystem using artificial neural network model. Acta Geogr. Sin. 2005, 25, 621–626. (In Chinese) [Google Scholar]
- Qiu, H.J.; Cao, M.M.; Liu, W.; Wang, Y.; Hao, J.; Hu, S. The Susceptibility Assessment of Landslide and Its Calibration of the Models Based on Three Different Models. Sci. Geogr. Sin. 2014, 34, 110–115. (In Chinese) [Google Scholar]
- Leman, N.; Ramli, M.F.; Khirotdin, R.P.K. GIS-based integrated evaluation of environmentally sensitive areas (ESAs) for land use planning in Langkawi, Malaysia. Ecol. Indic. 2016, 61, 293–308. [Google Scholar] [CrossRef]
- Xu, Y.; Liu, R.; Xue, C.B.; Xia, Z.H. Ecological Sensitivity Evaluation and Explanatory Power Analysis of the Giant Panda National Park in China. Ecol. Indic. 2023, 146, 109792. [Google Scholar] [CrossRef]
- Ma, Y.J.; Huang, X.J.; Xu, M.M.; Zhong, T.Y.; Du, W.X. Sensitivity Analysis of Ecosystem Service Value to Coastal Tideland Development in Jiangsu Province. China Land Sci. 2006, 20, 28–34. (In Chinese) [Google Scholar]
- Chinese Research Academy of Environmental Sciences; University of Science and Technology Beijing; University of Chinese Academy of Sciences; Institute of Geographical Sciences and Natural Resources; CAS. Interim Technical Regulations For Ecological Function Zoning [EB/OL]. 2014. Available online: https://www.mee.gov.cn/gkml/hbb/bgth/201405/t20140521_275396.htm (accessed on 18 October 2022).
- Ministry of Natural Resources of the People’s Republic of China. Technical Guidelines for the Evaluation of Resource and Environmental Carrying Capacity & Land Space Development Suitability (Trial) [EB/OL]. 2020. Available online: http://gi.mnr.gov.cn/202001/t20200121_2498502.html (accessed on 18 October 2022).
- Zhang, R.; Liu, X.; Heathman, G.C.; Yao, X.; Hu, X.; Zhang, G. Assessment of soil erosion sensitivity and analysis of sensitivity factors in the Tongbai-Dabie mountainous area of China. Catena 2013, 101, 92–98. [Google Scholar] [CrossRef]
- Xu, D.Y.; You, X.G.; Xia, C.L. Assessing the spatial-temporal pattern and evolution of areas sensitive to land desertification in North China. Ecol. Indic. 2019, 97, 150–158. [Google Scholar] [CrossRef]
- Zhang, T.Y.; Wang, L.; Han, Y.; Zhang, M. Sensitivity Evaluation of Soil Salinization in Manasi River Basin Based on GIS and RS. Soils 2017, 49, 812–818. (In Chinese) [Google Scholar]
- Yan, L.H.; Zhou, Z.F.; Xie, Y.T.; Huang, D. Analysis on spatial correlation between sensitivity of rocky desertification and macroscopic geomorphology in Guizhou Plateau. Carsol. Sin. 2018, 37, 400–407. (In Chinese) [Google Scholar]
- Du, Y.Y.; Hu, Y.N.; Yang, Y.; Peng, J. Building ecological security patterns in southwestern mountainous areas based on ecological importance and ecological sensitivity:A case study of Dali Bai Autonomous Prefecture, Yunnan Province. Acta Ecol. Sin. 2017, 37, 8241–8253. (In Chinese) [Google Scholar]
- Huang, J.; Cui, S.G.; Li, F.Y.; Qiu, Q.Y.; Ma, K.M. Ecological sensitivity of Xiamen City to land use changes. Acta Ecol. Sin. 2011, 31, 7441–7449. (In Chinese) [Google Scholar]
- Chi, Y.; Zhang, Z.W.; Gao, J.H.; Xie, Z.L.; Zhao, M.W.; Wang, E.K. Evaluating landscape ecological sensitivity of an estuarine island based on landscape pattern across temporal and spatial scales. Ecol. Indic. 2019, 101, 221–237. [Google Scholar] [CrossRef]
- Duan, Y.Q.; Zhang, L.D.; Fan, X.Y.; Hou, Q.H.; Hou, X.M. Smart city oriented Ecological Sensitivity Assessment and Service Value Computing based on Intelligent sensing data processing. Comput. Commun. 2020, 160, 263–273. [Google Scholar] [CrossRef]
- Shi, Y.S.; Li, J.Q.; Xie, M.Q. Evaluation of the ecological sensitivity and security of tidal flats in Shanghai. Ecol. Indic. 2018, 85, 729–741. [Google Scholar] [CrossRef]
- Zhang, M.W.; Jin, H.J.; Cai, D.S.; Jiang, C.B. The comparative study on the ecological sensitivity analysis in Huixian karst wetland, China. Procedia Environ. Sci. 2010, 2, 386–398. [Google Scholar]
- Wang, X.M.; Bian, Z.F. The Implications of Ecological Sensitivity on Exploitation of Unutilized Land: A Case Study in Ji’Nan City, China. Procedia Environ. Sci. 2011, 10, 275–281. [Google Scholar] [CrossRef][Green Version]
- Xu, L.L.; Yan, H.; Qian, S. Spatio-temporal change of land desertification sensitivity in Northern China from 2000 to 2018 based on MODIS-NDVI. J. Nat. Resour. 2020, 35, 925–936. (In Chinese) [Google Scholar]
- Wei, W.; Zhou, T.; Guo, Z.C.; Li, Z.Y.; Zhang, X.Y. Spatiotemporal evolution of land ecological sensitivity in arid inland river basin based on remote sensing index: A case of Wuwei City in Shiyang River Basin. Chin. J. Ecol. 2020, 39, 3068–3079. (In Chinese) [Google Scholar]
- Kosmas, C.; Kirkby, M.; Geeson, N. Manual on key indicators of desertification and mapping environmentally sensitive areas to desertification. European Commission. In European Commission, Energy, Environment and Sustainable Development, EUR 18882; European Commission: Bruxelles, Belgium, 1999; Volume 87. [Google Scholar]
- Prăvălie, R.; Patriche, C.; Tişcovschi, A.; Dumitraşcu, M.; Săvulescu, I.; Sîrodoev, I.; Bandoc, G. Recent spatio-temporal changes of land sensitivity to degradation in Romania due to climate change and human activities: An approach based on multiple environmental quality indicators. Ecol. Indic. 2020, 118, 106755. [Google Scholar] [CrossRef]
- Lee, E.J.; Piao, D.; Song, C.; Kim, J.; Lim, C.H.; Kim, E.; Moon, J.; Kafatos, M.; Lamchin, M.; Jeon, S.W.; et al. Assessing environmentally sensitive land to desertification using MEDALUS method in Mongolia. For. Sci. Technol. 2019, 15, 210–220. [Google Scholar] [CrossRef][Green Version]
- Karamesouti, M.; Panagos, P.; Kosmas, C. Model-based spatio-temporal analysis of land desertification risk in Greece. Catena 2018, 167, 266–275. [Google Scholar] [CrossRef]
- Roué-Legall, A.; Lucotte, M.; Carreau, J.; Canuel, R.; Garcia, E. Development of an ecosystem sensitivity model regarding mercury levels in fish using a preference modeling methodology: Application to the Canadian boreal system. Environ. Sci. Technol. 2005, 39, 9412–9423. [Google Scholar] [CrossRef]
- John, F.; Kurt, J.J. Assessing uncertainty in ecological systems using global sensitivity analyses: A case example of simulated wolf reintroduction effects on elk. Ecol. Model. 2005, 187, 259–280. [Google Scholar]
- Rossi, P.; Pecci, A.; Amadio, V.; Rossi, O.; Soliani, L. Coupling indicators of ecological value and ecological sensitivity with indicators of demographic pressure in the demarcation of new areas to be protected: The case of the Oltrepò Pavese and the Ligurian-Emilian Apennine area (Italy). Landsc. Urban Plan. 2008, 85, 12–26. [Google Scholar] [CrossRef]
- Janusz, A.; Robert, D. Analysis of the sensitivity of the ecological effects for the investment based on the thermal insulation of the building: A Polish case study. J. Clean. Prod. 2017, 162, 856–864. [Google Scholar]
- Wei, C.J.; Meng, J.J. Ecological sensitivity assessment and spatial pattern analysis of land resources in China. Acta Sci. Nat. Univ. Pekin. 2022, 58, 157–168. [Google Scholar]
- Saaty, T.L. The Analytic Hierarchy Process; Mc Graw-Hill Company: Landon, UK, 1980. [Google Scholar]
- Chen, X.C.; Li, F.; Li, X.Q. Mapping ecological space quality changes for ecological management: A case study in the Pearl River Delta urban agglomeration, China. J. Environ. Manag. 2020, 267, 110658. [Google Scholar] [CrossRef]
- Li, J.Y. Responses of Vegetation NDVI to Climate Change and Land Use in Ordos City, North China. Appl. Sci 2022, 12, 7288. [Google Scholar] [CrossRef]
- Shi, N.N.; Quan, Z.J.; Han, Y.; Wang, Q.; Xiao, N.; Gao, X. Analysis of Land Resources Carrying Capacity in Wuhai City Based on Ecological Sensitivity. Res. Soil Water Conserv. 2017, 24, 239–243. (In Chinese) [Google Scholar]
- Yi, D.; Zhao, X.M.; Guo, X.; Zhao, L.H.; Zhang, H.; Han, Y.; Roshan, S.; Luo, Z.J. Delimitation of urban development boundary based on ecological sensitivity evaluation and CA-Markov simulation in plain city: A case of Nanchang, Jiangxi, China. Chin. J. Appl. Ecol. 2020, 31, 208–218. (In Chinese) [Google Scholar]
- Li, Y.J. Evaluation of Eco-environmental Sensitivity of National Ecological Function Area of Dushan County in Guizhou Province. J. Northwest For. Univ. 2017, 37, 66–73. (In Chinese) [Google Scholar]
|Temperatures||Raster image||WorldClim (www.worldclim.org, accessed on 12 September 2022)||1 km||Produce a multi-year average temperature factor|
|Precipitation||Raster image||WorldClim (www.worldclim.org, accessed on 13 September 2022)||1 km||Produce a multi-year average annual precipitation factor|
|Elevation||Raster image||Geospatial Data Cloud (China, gscloud.cn, accessed on 15 September 2022)||30 m||Produce factors of elevation and topographic relief|
|Water||Vector data||National Catalogue Service For Geographic Information (China, www.webmap.cn, accessed on 8 October 2022), OSM (https://www.openstreetmap.org, accessed on 20 September 2022),||1:1,000,000||Produce factor of distance to water|
|Land use types||Raster image||GlobeLand30 (http://globallandcover.com/, accessed on 15 September 2022)||30 m||Produce factor of land use, and extract construction land data to produce factor of distance to construction land|
|Roads||Vector data||National Catalogue Service For Geographic Information (China, www.webmap.cn, accessed on 8 October 2022), OSM (https://www.openstreetmap.org, accessed on 22 September 2022),||1:1,000,000||Produce factor of distance from roads|
|Rainfall erosivity||Raster image||Earth System Science Data (China, http://www.geodata.cn/, accessed on 14 September 2022)||0.01°||Produce factor of rainfall erosivity|
|Soil texture||Raster image||Harmonized World Soil Database (www.fao.org/soils-portal/, accessed on 17 September 2022)||1 km||Produce factor of soil texture|
|Lansat-OLI remote sensing data||Remote sensing image||Geospatial Data Cloud (China, gscloud.cn, accessed on 2 October 2022)||30 m||Produce vegetation coverage factor|
|Type of Sensitivity||Sensitive Indicators||Sensitivity Classification|
|Insensitive||Slightly Sensitivity||Moderately Sensitive||Highly Sensitive||Extremely Sensitive|
|Natural environment||Mean annual temperature (°C)||<1.68||1.68–2.79||2.79–3.84||3.84–4.94||>4.94|
|Annual precipitation (mm)||<621||621–652||652–688||688–721||>721|
|Distance to water (m)||>2000||1000–2000||500–1000||200–500||<200|
|Human disturbance||Type of land use||Construction land, bare land||Cultivated land||Woodland||Grassland||Water, wetlands|
|Distance to construction land (m)||>2000||1000–2000||500–1000||200–500||<200|
|Distance to road (m)||>1000||500–1000||250–500||100–250||<100|
|Soil erosion||Topographic relief||<20||20–50||50–100||100–300||>300|
|Rainfall erosivity (MJ·mm/(hm2·h·a))||<500||500–1000||1000–1500||1500–2000||>2000|
|Soil texture||Sand||Clay (heavy), silty clay, clay||Loam, sandy clay||Clay loam, silt loam, sandy clay loam||Silt|
|Target Layer||Criterion Layer||Weights||Evaluation Indicator Layer||Weights||Weight Sort|
|Ecological sensitivity||Natural environment||0.3119||Mean annual temperature||0.0601||7|
|Distance to water||0.0377||9|
|Human disturbance||0.4905||Type of land use||0.2643||1|
|Distance to construction land||0.1458||2|
|Distance to road||0.0803||6|
|Soil erosion||0.1976||Topographic relief||0.0513||8|
|Sensitivity Level||Mean Annual |
|Annual Precipitation||Elevation||Distance to Water|
|Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)|
|Sensitivity Level||Land Use Types||Distance to Construction Land||Distance to Road|
|Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)|
|Sensitivity Level||Topographic Relief||Rainfall Erosivity||Soil Texture||Vegetation Coverage|
|Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)|
|Sensitivity Level||Area (km2)||Proportion (%)|
|Type of Land Resource||Slightly Sensitivity||Moderately Sensitive||Highly Sensitive||Total|
|Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Area (km2)||Proportion (%)||Total Area (km2)||Total Proportion (%)|
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Feng, H.; Zhang, X.; Nan, Y.; Zhang, D.; Sun, Y. Ecological Sensitivity Assessment and Spatial Pattern Analysis of Land Resources in Tumen River Basin, China. Appl. Sci. 2023, 13, 4197. https://doi.org/10.3390/app13074197
Feng H, Zhang X, Nan Y, Zhang D, Sun Y. Ecological Sensitivity Assessment and Spatial Pattern Analysis of Land Resources in Tumen River Basin, China. Applied Sciences. 2023; 13(7):4197. https://doi.org/10.3390/app13074197Chicago/Turabian Style
Feng, Hengdong, Xiaoguang Zhang, Ying Nan, Da Zhang, and Yan Sun. 2023. "Ecological Sensitivity Assessment and Spatial Pattern Analysis of Land Resources in Tumen River Basin, China" Applied Sciences 13, no. 7: 4197. https://doi.org/10.3390/app13074197