Unfolding the Success of Positive Human Interventions in Combating Land Degradation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.3. Sustainable Development Goal 15.3.1: Land Degradation
2.3.1. Productivity
- (a)
- Productivity Trajectory
- (b)
- Productivity State
- (c)
- Productivity performance
2.3.2. Land Cover
2.3.3. Soil Organic Carbon
2.3.4. Drivers of Ecological Restoration
3. Results
3.1. Vegetation Dynamic Trend and Driving Forces Analysis
3.2. Relationship between NDVI and Climatic Factors
3.3. Restoration Caused by Ecological Restoration Programs and Land Degradation
4. Discussion
5. Conclusions
- Desertification reversal in Mu Us is obvious as most of the land area has shown improvement in vegetation condition, soil organic carbon, and land cover transition. Despite the limited impact of climatic factors on vegetation cover change, vegetation has increased especially on the eastern side of the desert. Ecological restoration activities are found to be the key driving forces of vegetation restoration.
- The condition of land has improved significantly in regions where vegetation restoration is attributed to ecological restoration programs. 41.21% of vegetation restoration in Mu Us is accredited to ecological restoration efforts, out of which 40.42% area has shown improvement in all three sub-indicators of land degradation and the rest 0.79% of this region is stable and has no signs of land degradation.
- This study has quantified the contribution and revealed the importance of ecological restoration programs in land degradation reversal in the Mu Us desert. It can be concluded that successful restoration projects in Mu Us are a win-win strategy and a positive step toward implementing Sustainable Development Goal 15.3.1 to achieve a land degradation-neutral world.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Trajectory | State | Performance | Classes |
---|---|---|---|
Improvement | Improvement | Stable | Improvement |
Improvement | Improvement | Degradation | Improvement |
Improvement | Stable | Stable | Improvement |
Improvement | Stable | Degradation | Improvement |
Improvement | Degradation | Stable | Improvement |
Improvement | Degradation | Degradation | Degradation |
Stable | Improvement | Stable | Stable |
Stable | Improvement | Degradation | Stable |
Stable | Stable | Stable | Stable |
Stable | Stable | Degradation | Degradation |
Stable | Degradation | Stable | Degradation |
Stable | Degradation | Degradation | Degradation |
Degradation | Improvement | Stable | Degradation |
Degradation | Improvement | Degradation | Degradation |
Degradation | Stable | Stable | Degradation |
Degradation | Stable | Degradation | Degradation |
Degradation | Degradation | Stable | Degradation |
Degradation | Degradation | Degradation | Degradation |
LU Coefficients | Forest | Grasslands | Croplands | Wetlands | Artificial Areas | Bare Lands | Water Bodies |
---|---|---|---|---|---|---|---|
Forest | 1 | 1 | f | 1 | 0.1 | 0.1 | 1 |
Grasslands | 1 | 1 | f | 1 | 0.1 | 0.1 | 1 |
Croplands | 1/f | 1/f | 1 | 1/0.71 | 0.1 | 0.1 | 1 |
Wetlands | 1 | 1 | o.71 | 1 | 0.1 | 0.1 | 1 |
Artificial areas | 2 | 2 | 2 | 2 | 1 | 1 | 1 |
Bare lands | 2 | 2 | 2 | 2 | 1 | 1 | 1 |
Water bodies | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
References
- Gashu, K.; Muchie, Y. Rethink the interlink between land degradation and livelihood of rural communities in Chilga district, Northwest Ethiopia. J. Ecol. Environ. 2018, 42, 139–149. [Google Scholar] [CrossRef]
- Kang, J.; Zhang, Y.; Biswas, A. Land Degradation and Development Processes and Their Response to Climate Change and Human Activity in China from 1982 to 2015. Remote Sens. 2021, 13, 3516. [Google Scholar] [CrossRef]
- Eswaran, H.; Lal, R.; Reich, P. Land degradation: An overview. Responses to Land Degradation. In Proceedings of the 2nd International Conference on Land Degradation and Desertification, Khon Kaen, Thailand, 25–29 January 1999; Bridges, E., Hannam, I., Oldeman, L., De Vries, F.P., Scherr, S., Sompatpanit, S., Eds.; Oxford Press: New Delhi, India, 2001. [Google Scholar]
- Talukder, B.; Ganguli, N.; Matthew, R.; VanLoon, G.W.; Hipel, K.W.; Orbinski, J. Climate change-triggered land degradation and planetary health: A review. Land Degrad. Dev. 2021, 32, 4509–4522. [Google Scholar] [CrossRef]
- Mirzabaev, A.; Wu, J.; Evans, J.; Garcia-Oliva, F.; Hussein, I.; Iqbal, M.; Kimutai, J.; Knowles, T.; Meza, F.; Nedjroaoui, D. Desertification. In Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems; Shukla, P.R., Skea, J., Buendia, E.C., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D.C., Zhai, P., Slade, R., Connors, S., Van Diemen, R., et al., Eds.; IPCC: Geneva, Switzerland, 2019; in press; Available online: https://www.ipcc.ch/site/assets/uploads/sites/4/2021/07/210714-IPCCJ7230-SRCCL-Complete-BOOK-HRES.pdf (accessed on 25 January 2022).
- Da Cunha Dias, T.A.; Lora, E.E.S.; Maya, D.M.Y.; Del Olmo, O.A. Global potential assessment of available land for bioenergy projects in 2050 within food security limits. Land Use Policy 2021, 105, 105346. [Google Scholar] [CrossRef]
- Liu, Q.; Zhao, Y.; Zhang, X.; Buyantuev, A.; Niu, J.; Wang, X. Spatiotemporal patterns of desertification dynamics and desertification effects on ecosystem Services in the Mu Us Desert in China. Sustainability 2018, 10, 589. [Google Scholar] [CrossRef] [Green Version]
- Bashir, B.; Cao, C.; Naeem, S.; Zamani Joharestani, M.; Bo, X.; Afzal, H.; Jamal, K.; Mumtaz, F. Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors. Remote Sens. 2020, 12, 2612. [Google Scholar] [CrossRef]
- Sims, N.C.; England, J.R.; Newnham, G.J.; Alexander, S.; Green, C.; Minelli, S.; Held, A. Developing good practice guidance for estimating land degradation in the context of the United Nations Sustainable Development Goals. Environ. Sci. Policy 2019, 92, 349–355. [Google Scholar] [CrossRef]
- Paylore, P.; McGinnies, W. Desert Research: Selected References 1965–1968; Arizona Univ Tucson Inst of Arid Lands Research: Tucson, AZ, USA, 1969. [Google Scholar]
- Basso, F.; Bove, E.; Dumontet, S.; Ferrara, A.; Pisante, M.; Quaranta, G.; Taberner, M. Evaluating environmental sensitivity at the basin scale through the use of geographic information systems and remotely sensed data: An example covering the Agri basin (Southern Italy). Catena 2000, 40, 19–35. [Google Scholar] [CrossRef]
- Geerken, R.; Ilaiwi, M. Assessment of rangeland degradation and development of a strategy for rehabilitation. Remote Sens. Environ. 2004, 90, 490–504. [Google Scholar] [CrossRef]
- Wessels, K.J.; Van den Bergh, F.; Scholes, R. Limits to detectability of land degradation by trend analysis of vegetation index data. Remote Sens. Environ. 2012, 125, 10–22. [Google Scholar] [CrossRef]
- Tucker, C.J.; Dregne, H.E.; Newcomb, W.W. Expansion and contraction of the Sahara Desert from 1980 to 1990. Science 1991, 253, 299–300. [Google Scholar] [CrossRef]
- Wei, H.; Wang, J.; Cheng, K.; Li, G.; Ochir, A.; Davaasuren, D.; Chonokhuu, S. Desertification information extraction based on feature space combinations on the Mongolian Plateau. Remote Sens. 2018, 10, 1614. [Google Scholar] [CrossRef] [Green Version]
- Zheng, Y.; Xie, Z.; Robert, C.; Jiang, L.; Shimizu, H. Did climate drive ecosystem change and induce desertification in Otindag sandy land, China over the past 40 years? J. Arid. Environ. 2006, 64, 523–541. [Google Scholar] [CrossRef]
- Cai, B. Monitoring and Evaluating of Major Forestry Ecological Project Based on Remote Sensing—A Case Study of “Three North” Shelter Forest Project; Graduate University of Chinese Academy of Sciences: Beijing, China, 2008. (In Chinese) [Google Scholar]
- Tian, H.; Cao, C.; Chen, W.; Bao, S.; Yang, B.; Myneni, R.B. Response of vegetation activity dynamic to climatic change and ecological restoration programs in Inner Mongolia from 2000 to 2012. Ecol. Eng. 2015, 82, 276–289. [Google Scholar] [CrossRef]
- Jobbágy, E.G.; Sala, O.E.; Paruelo, J.M. Patterns and controls of primary production in the Patagonian steppe: A remote sensing approach. Ecology 2002, 83, 307–319. [Google Scholar]
- Boschetti, M.; Nutini, F.; Brivio, P.A.; Bartholomé, E.; Stroppiana, D.; Hoscilo, A. Identification of environmental anomaly hot spots in West Africa from time series of NDVI and rainfall. ISPRS J. Photogramm. Remote Sens. 2013, 78, 26–40. [Google Scholar] [CrossRef]
- Liu, J.; Diamond, J. China’s environment in a globalizing world. Nature 2005, 435, 1179–1186. [Google Scholar] [CrossRef]
- State Forestry Administration of the People’s Republic of China. A Bulletin of Status Quo of Desertification and Sandification in China; State Forestry Administration of the People’s Republic of China: Beijing, China, 2011.
- Wang, G.; Innes, J.L.; Lei, J.; Dai, S.; Wu, S.W. China’s forestry reforms. Sci. N. Y. Wash. 2007, 318, 1556. [Google Scholar] [CrossRef] [Green Version]
- Zhang, P.; Shao, G.; Zhao, G.; Le Master, D.C.; Parker, G.R.; Dunning, J.B.; Li, Q. China’s forest policy for the 21st century. Science 2000, 288, 2135–2136. [Google Scholar] [CrossRef] [Green Version]
- Uchida, E.; Xu, J.; Rozelle, S. Grain for green: Cost-effectiveness and sustainability of China’s conservation set-aside program. Land Econ. 2005, 81, 247–264. [Google Scholar] [CrossRef]
- Li, H.; Xu, F.; Li, Z.; You, N.; Zhou, H.; Zhou, Y.; Chen, B.; Qin, Y.; Xiao, X.; Dong, J. Forest Changes by Precipitation Zones in Northern China after the Three-North Shelterbelt Forest Program in China. Remote Sens. 2021, 13, 543. [Google Scholar] [CrossRef]
- Zhao, Y.; Xin, Z.; Ding, G. Spatiotemporal variation in the occurrence of sand-dust events and its influencing factors in the Beijing–Tianjin Sand Source Region, China, 1982–2013. Reg. Environ. Chang. 2018, 18, 2433–2444. [Google Scholar] [CrossRef]
- Song, X.; Peng, C.; Zhou, G.; Jiang, H.; Wang, W. Chinese Grain for Green Program led to highly increased soil organic carbon levels: A meta-analysis. Sci. Rep. 2014, 4, 4460. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, P.; He, Y.; Feng, Y.; De la Torre, R.; Jia, H.; Tang, J.; Cubbage, F. An analysis of potential investment returns of planted forests in South China. New For. 2019, 50, 943–968. [Google Scholar] [CrossRef] [Green Version]
- Cao, S.; Wang, X.; Song, Y.; Chen, L.; Feng, Q. Impacts of the Natural Forest Conservation Program on the livelihoods of residents of Northwestern China: Perceptions of residents affected by the program. Ecol. Econ. 2010, 69, 1454–1462. [Google Scholar] [CrossRef]
- Wang, H.; He, M.; Ran, N.; Xie, D.; Wang, Q.; Teng, M.; Wang, P. China’s Key Forestry Ecological Development Programs: Implementation, Environmental Impact and Challenges. Forests 2021, 12, 101. [Google Scholar] [CrossRef]
- Liu, Q.; Zhang, Q.; Yan, Y.; Zhang, X.; Niu, J.; Svenning, J.-C. Ecological restoration is the dominant driver of the recent reversal of desertification in the Mu Us Desert (China). J. Clean. Prod. 2020, 268, 122241. [Google Scholar] [CrossRef]
- Li, S.; Wang, T.; Yan, C. Assessing the role of policies on land-use/cover change from 1965 to 2015 in the Mu Us Sandy Land, northern China. Sustainability 2017, 9, 1164. [Google Scholar] [CrossRef] [Green Version]
- Jiang, H.; Xu, X.; Guan, M.; Wang, L.; Huang, Y.; Jiang, Y. Determining the contributions of climate change and human activities to vegetation dynamics in agro-pastural transitional zone of northern China from 2000 to 2015. Sci. Total Environ. 2020, 718, 134871. [Google Scholar] [CrossRef]
- Jiang, G. It is inappropriate for afforestation in the “Three North” regions. Sci. Decis. Mak. 2005, 11, 40–42. [Google Scholar]
- Cao, S. Why Large-Scale Afforestation Efforts in China Have Failed to Solve the Desertification Problem; ACS Publications: Washington, DC, USA, 2008. [Google Scholar]
- Wang, X.; Zhang, C.; Hasi, E.; Dong, Z. Has the Three Norths Forest Shelterbelt Program solved the desertification and dust storm problems in arid and semiarid China? J. Arid. Environ. 2010, 74, 13–22. [Google Scholar] [CrossRef]
- Liang, P.; Yang, X. Landscape spatial patterns in the Maowusu (Mu Us) Sandy Land, northern China and their impact factors. Catena 2016, 145, 321–333. [Google Scholar] [CrossRef]
- Didan, K. MOD13Q1: MODIS/Terra vegetation indices 16-day L3 global 250 m grid SIN V006. NASA EOSDIS Land Process. DAAC 2014, 6. [Google Scholar] [CrossRef]
- Vermote, E.F.; El Saleous, N.Z.; Justice, C.O. Atmospheric correction of MODIS data in the visible to middle infrared: First results. Remote Sens. Environ. 2002, 83, 97–111. [Google Scholar] [CrossRef]
- Trends.Earth. Conservation International. Available online: http://trends.earth (accessed on 20 June 2020).
- ESA. Land Cover CCI Product User Guide Version 2; Technical Report; ESA: Paris, France, 2017. [Google Scholar]
- Hengl, T.; Mendes de Jesus, J.; Heuvelink, G.B.; Ruiperez Gonzalez, M.; Kilibarda, M.; Blagotić, A.; Shangguan, W.; Wright, M.N.; Geng, X.; Bauer-Marschallinger, B. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 2017, 12, e0169748. [Google Scholar] [CrossRef] [Green Version]
- Sims, N.; Green, C.; Newnham, G.; England, J.; Held, A.; Wulder, M.; Herold, M.; Cox, S.; Huete, A.; Kumar, L. Good Practice Guidance. SDG Indicator 15.3.1, Proportion of Land That Is Degraded over Total Land Area; United Nations Convention to Combat Desertification (UNCCD): Bonn, Germany, 2021. [Google Scholar]
- Hwang, S.-O.; Park, J.; Kim, H.M. Effect of hydrometeor species on very-short-range simulations of precipitation using ERA5. Atmos. Res. 2019, 218, 245–256. [Google Scholar] [CrossRef]
- Hersbach, H.; Bell, B.; Berrisford, P.; Hirahara, S.; Horányi, A.; Muñoz-Sabater, J.; Nicolas, J.; Peubey, C.; Radu, R.; Schepers, D. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 2020, 146, 1999–2049. [Google Scholar] [CrossRef]
- Baboo, S.S.; Devi, M.R. An analysis of different resampling methods in Coimbatore, District. Glob. J. Comput. Sci. Technol. 2010, 10, 61–66. [Google Scholar]
- Hashimoto, H.; Nemani, R.R.; Bala, G.; Cao, L.; Michaelis, A.R.; Ganguly, S.; Wang, W.; Milesi, C.; Eastman, R.; Lee, T. Constraints to vegetation growth reduced by region-specific changes in seasonal climate. Climate 2019, 7, 27. [Google Scholar] [CrossRef] [Green Version]
- Iegorova, L.V.; Gibbs, J.P.; Mountrakis, G.; Bastille-Rousseau, G.; Paltsyn, M.Y.; Ayatkhan, A.; Baylagasov, L.V.; Robertus, Y.V.; Chelyshev, A.V. Rangeland vegetation dynamics in the Altai Mountain region of Mongolia, Russia, Kazakhstan and China: Effects of climate, topography, and socio-political context for livestock herding practices. Environ. Res. Lett. 2019, 14, 104017. [Google Scholar] [CrossRef] [Green Version]
- Gonzalez-Roglich, M.; Zvoleff, A.; Noon, M.; Liniger, H.; Fleiner, R.; Harari, N.; Garcia, C. Synergizing global tools to monitor progress towards land degradation neutrality: Trends. Earth and the World Overview of Conservation Approaches and Technologies sustainable land management database. Environ. Sci. Policy 2019, 93, 34–42. [Google Scholar] [CrossRef]
- Yengoh, G.T.; Dent, D.; Olsson, L.; Tengberg, A.E.; Tucker, C.J., III. Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: Current Status, Future Trends, and Practical Considerations; Springer: Cham, Switzerland, 2015. [Google Scholar]
- Tucker, C.J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 1979, 8, 127–150. [Google Scholar] [CrossRef] [Green Version]
- Nzabarinda, V.; Bao, A.; Xu, W.; Uwamahoro, S.; Jiang, L.; Duan, Y.; Nahayo, L.; Yu, T.; Wang, T.; Long, G. Assessment and Evaluation of the Response of Vegetation Dynamics to Climate Variability in Africa. Sustainability 2021, 13, 1234. [Google Scholar] [CrossRef]
- Raich, J.W.; Schlesinger, W.H. The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate. Tellus B 1992, 44, 81–99. [Google Scholar] [CrossRef] [Green Version]
- Duarte-Guardia, S.; Peri, P.L.; Borchard, N.; Ladd, B. Soils need to be considered when assessing the impacts of land-use change on carbon sequestration. Nat. Ecol. Evol. 2019, 3, 1642. [Google Scholar] [CrossRef]
- Mattina, D.; Erdogan, H.E.; Wheeler, I.; Crossman, N. Default Data: Methods and Interpretation; A Guidance Document for the 2018 UNCCD Reporting; United Nations Convention to Combat Desertification (UNCCD): Bonn, Germany, 2018. [Google Scholar]
- Sen, P.K. Estimates of the regression coefficient based on Kendall’s tau. J. Am. Stat. Assoc. 1968, 63, 1379–1389. [Google Scholar] [CrossRef]
- Kasimati, A.; Espejo-Garcia, B.; Vali, E.; Malounas, I.; Fountas, S. Investigating a Selection of Methods for the Prediction of Total Soluble Solids Among Wine Grape Quality Characteristics Using Normalized Difference Vegetation Index Data from Proximal and Remote Sensing. Front. Plant Sci. 2021, 12, 1118. [Google Scholar] [CrossRef]
- Ukey, R.; Rai, A.C. Impact of global warming on heating and cooling degree days in major Indian cities. Energy Build. 2021, 244, 111050. [Google Scholar] [CrossRef]
- Huang, C.; Yang, Q.; Huang, W. Analysis of the Spatial and Temporal Changes of NDVI and Its Driving Factors in the Wei and Jing River Basins. Int. J. Environ. Res. Public Health 2021, 18, 11863. [Google Scholar] [CrossRef]
- Akhtar-Schuster, M.; Stringer, L.C.; Erlewein, A.; Metternicht, G.; Minelli, S.; Safriel, U.; Sommer, S. Unpacking the concept of land degradation neutrality and addressing its operation through the Rio Conventions. J. Environ. Manag. 2017, 195, 4–15. [Google Scholar] [CrossRef]
- Orr, B.; Cowie, A.; Castillo Sanchez, V.; Chasek, P.; Crossman, N.; Erlewein, A.; Louwagie, G.; Maron, M.; Metternicht, G.; Minelli, S. Scientific Conceptual Framework for Land Degradation Neutrality. A Report of the Science-Policy Interface; United Nations Convention to Combat Desertification (UNCCD): Bonn, Germany, 2017; pp. 1–98. [Google Scholar]
- Shen, Y.; Zhang, C.; Wang, X.; Zou, X.; Kang, L. Statistical characteristics of wind erosion events in the erosion area of Northern China. Catena 2018, 167, 399–410. [Google Scholar] [CrossRef]
- Jiang, C.; Zhang, H.; Zhao, L.; Yang, Z.; Wang, X.; Yang, L.; Wen, M.; Geng, S.; Zeng, Q.; Wang, J. Unfolding the effectiveness of ecological restoration programs in combating land degradation: Achievements, causes, and implications. Sci. Total Environ. 2020, 748, 141552. [Google Scholar] [CrossRef]
- Xie, H.; Zhang, Y.; Wu, Z.; Lv, T. A bibliometric analysis on land degradation: Current status, development, and future directions. Land 2020, 9, 28. [Google Scholar] [CrossRef] [Green Version]
- Gang, C.; Zhao, W.; Zhao, T.; Zhang, Y.; Gao, X.; Wen, Z. The impacts of land conversion and management measures on the grassland net primary productivity over the Loess Plateau, Northern China. Sci. Total Environ. 2018, 645, 827–836. [Google Scholar] [CrossRef]
- Li, S.; Yan, C.; Wang, T.; Du, H. Monitoring grassland reclamation in the Mu Us Desert using remote sensing from 2010 to 2015. Environ. Earth Sci. 2019, 78, 311. [Google Scholar] [CrossRef]
- Bünemann, E.K.; Bongiorno, G.; Bai, Z.; Creamer, R.E.; De Deyn, G.; De Goede, R.; Fleskens, L.; Geissen, V.; Kuyper, T.W.; Mäder, P. Soil quality—A critical review. Soil Biol. Biochem. 2018, 120, 105–125. [Google Scholar] [CrossRef]
- Lorenz, K.; Lal, R.; Ehlers, K. Soil organic carbon stock as an indicator for monitoring land and soil degradation in relation to United Nations’ Sustainable Development Goals. Land Degrad. Dev. 2019, 30, 824–838. [Google Scholar] [CrossRef]
- Wander, M. Soil organic matter fractions and their relevance to soil function. Soil Organic Matter in Sustainable Agriculture; CRC Press: Boca Raton, FL, USA, 2004; pp. 67–102. [Google Scholar]
- Comerford, N.B.; Franzluebbers, A.J.; Stromberger, M.E.; Morris, L.; Markewitz, D.; Moore, R. Assessment and evaluation of soil ecosystem services. Soil Horiz. 2013, 54, 1–14. [Google Scholar] [CrossRef] [Green Version]
- Murphy, B. Impact of soil organic matter on soil properties—A review with emphasis on Australian soils. Soil Res. 2015, 53, 605–635. [Google Scholar] [CrossRef]
- Grilli, E.; Carvalho, S.C.; Chiti, T.; Coppola, E.; D’Ascoli, R.; La Mantia, T.; Marzaioli, R.; Mastrocicco, M.; Pulido, F.; Rutigliano, F.A. Critical range of soil organic carbon in southern Europe lands under desertification risk. J. Environ. Manag. 2021, 287, 112285. [Google Scholar] [CrossRef]
- Bao, G.; Chen, J.; Chopping, M.; Bao, Y.; Bayarsaikhan, S.; Dorjsuren, A.; Tuya, A.; Jirigala, B.; Qin, Z. Dynamics of net primary productivity on the Mongolian Plateau: Joint regulations of phenology and drought. Int. J. Appl. Earth Obs. Geoinf. 2019, 81, 85–97. [Google Scholar] [CrossRef]
- Zhang, G.; Dong, J.; Xiao, X.; Hu, Z.; Sheldon, S. Effectiveness of ecological restoration projects in Horqin Sandy Land, China based on SPOT-VGT NDVI data. Ecol. Eng. 2012, 38, 20–29. [Google Scholar] [CrossRef]
- Wang, X.; Cheng, H.; Li, H.; Lou, J.; Hua, T.; Liu, W.; Jiao, L.; Ma, W.; Li, D.; Zhu, B. Key driving forces of desertification in the Mu Us Desert, China. Sci. Rep. 2017, 7, 3933. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, X.; Chen, F.H.; Dong, Z.; Xia, D. Evolution of the southern Mu Us Desert in North China over the past 50 years: An analysis using proxies of human activity and climate parameters. Land Degrad. Dev. 2005, 16, 351–366. [Google Scholar] [CrossRef]
- Wang, T.; Xue, X.; Zhou, L.; Guo, J. Combating aeolian desertification in northern China. Land Degrad. Dev. 2015, 26, 118–132. [Google Scholar] [CrossRef]
- Zhong, D. Dynamic Evolution of Sand Deserts in China; Gansu Culture Press: Lanzhou, China, 1998; 224p. [Google Scholar]
- Tao, W.; Wei, W.; Xian, X. Time-space evolution of desertification land in northern China. J. Desert Res. 2003, 23, 230. [Google Scholar]
- Jiao, D.; Xu, N.; Yang, F.; Xu, K. Evaluation of spatial-temporal variation performance of ERA5 precipitation data in China. Sci. Rep. 2021, 11, 17956. [Google Scholar] [CrossRef]
- Oses, N.; Azpiroz, I.; Marchi, S.; Guidotti, D.; Quartulli, M.; Olaizola, I.G. Analysis of copernicus’ era5 climate reanalysis data as a replacement for weather station temperature measurements in machine learning models for olive phenology phase prediction. Sensors 2020, 20, 6381. [Google Scholar] [CrossRef]
- Guo, Q.; Fu, B.; Shi, P.; Cudahy, T.; Zhang, J.; Xu, H. Satellite monitoring the spatial-temporal dynamics of desertification in response to climate change and human activities across the Ordos Plateau, China. Remote Sens. 2017, 9, 525. [Google Scholar] [CrossRef] [Green Version]
- Tong, X.; Wang, K.; Brandt, M.; Yue, Y.; Liao, C.; Fensholt, R. Assessing future vegetation trends and restoration prospects in the karst regions of southwest China. Remote Sens. 2016, 8, 357. [Google Scholar] [CrossRef] [Green Version]
Variable | Sensor/Dataset | Temporal | Spatial |
---|---|---|---|
NDVI | MOD13Q1 | 2001–2018 | 250 m |
Land cover | ESA CCI | 2001–2018 | 300 m |
Soil taxonomic units | Soil Grids—USDA | Static | 250 m |
Carbon Stocks | Soil Grids | N/A | 250 m |
2 m Air temperature | ERA 5 | 2001–2018 | 0.25° |
Precipitation | ERA 5 | 2001–2018 | 0.25° |
Summary of SDG 15.3.1 Indicator | ||
---|---|---|
Area (km2) | Percent of Total Land Area | |
Land area improved | 97,772.30 | 84.74% |
Land area stable | 14,197.10 | 12.30% |
Land area degraded | 3354.10 | 2.91% |
Land area with no data | 58 | 0.05% |
Total land area | 115,381.5 | 100.00% |
Land cover type in naseline Year | Land Cover in Target Year | ||||||
Tree-Covered Areas | Grasslands | Croplands | Wetlands | Artificial Areas | Other Land | ||
Tree-covered areas | 17.57 | 3.79 | 0.10 | 0.00 | 0.53 | 0.00 | |
Grasslands | 0.00 | 88,266.23 | 433.77 | 0.00 | 301.75 | 386.22 | |
Croplands | 0.00 | 277.93 | 17,340.59 | 0.00 | 74.35 | 0.83 | |
Wetlands | 0.00 | 0.00 | 0.00 | 139.81 | 0.53 | 0.00 | |
Artificial areas | 0.00 | 0.00 | 0.00 | 0.00 | 54.22 | 0.00 | |
Other lands | 0.00 | 2069.15 | 3.26 | 0.00 | 9.95 | 5999.31 |
Land cover type | Net Land Productivity Dynamics | ||||||
Declining | Moderate Decline | Declined | Stable | Increasing | No Data | ||
Tree-covered areas | 0.05 | 0.00 | 3.10 | 1.79 | 12.54 | 0.10 | |
Grasslands | 215.54 | 278.95 | 1292.08 | 11,905.63 | 74,537.95 | 36.09 | |
Croplands | 83.22 | 77.39 | 15.78 | 605.73 | 16,553.75 | 4.73 | |
Wetlands | 2.62 | 1.34 | 39.37 | 45.96 | 42.73 | 7.78 | |
Artificial areas | 4.82 | 0.20 | 0.05 | 15.98 | 33.12 | 0.05 | |
Other lands | 2.25 | 7.80 | 108.83 | 1628.00 | 4250.38 | 2.05 |
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Bashir, B.; Cao, C.; Xie, B.; Chen, Y.; Huang, Z.; Lin, X.; Gul, H.N.; Mumtaz, F.; Duerler, R.S.; Ahmad, A.; et al. Unfolding the Success of Positive Human Interventions in Combating Land Degradation. Forests 2022, 13, 818. https://doi.org/10.3390/f13060818
Bashir B, Cao C, Xie B, Chen Y, Huang Z, Lin X, Gul HN, Mumtaz F, Duerler RS, Ahmad A, et al. Unfolding the Success of Positive Human Interventions in Combating Land Degradation. Forests. 2022; 13(6):818. https://doi.org/10.3390/f13060818
Chicago/Turabian StyleBashir, Barjeece, Chunxiang Cao, Bo Xie, Yiyu Chen, Zhibin Huang, Xiaojuan Lin, Hafiza Nayab Gul, Faisal Mumtaz, Robert Shea Duerler, Adeel Ahmad, and et al. 2022. "Unfolding the Success of Positive Human Interventions in Combating Land Degradation" Forests 13, no. 6: 818. https://doi.org/10.3390/f13060818