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Study loss of vegetative cover and increased land surface temperature through remote sensing strategies under the inter-annual climate variability in Jinhua–Quzhou basin, China

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Abstract

The Jinhua–Quzhou basin in China is one of the most susceptible areas to drought. Due to the loss of vegetation and great fluctuations in rainfall and surface temperature, global warming occurs. Timely, accurate, and effective drought monitoring is crucial for protecting local vegetation and determining which vegetation is most vulnerable to increased LST during the period 1982–2019. It assumes a strong correlation between loss of vegetation cover, changes in monsoon climate, drought, and increases in land surface temperature (LST). Due to significantly increased in LST, low precipitation and vegetation cover, NDVI, TVDI, VCI, and NAP are useful in characterizing drought mitigation strategies. The temperature vegetation drought index (TVDI), normalized difference vegetation index (NDVI), vegetation condition index (VCI), and monthly precipitation anomaly percentage (NAP) can be helped to characterize drought reduction strategies. Monthly NDVI, NAP, VCI, TVDI, normalized vegetation supply water index (NVSWI), temperature condition index (TCI), vegetation health index (VHI), and heat map analysis indicate that the Jinhua–Quzhou basin experienced drought during 1984, 1993, 2000, and 2011. Seasonal SR, WVP, WS, NDVI, VCI, and NAP charts confirm that the Jinhua–Quzhou basin was affected by severe drought in 1984, which continued and led to severe droughts in 1993, 2000, and 2011. Regression analysis showed a significant positive correlation between NDVI, TVDI, VCI, and NAP values, while NVSWI, TVDI, and VHI showed positive signs of good drought monitoring strategies. The research results confirm the correlation between loss of vegetation cover and LST, which is one of the causes of global warming. The distribution of drought changed a trend indicating that compared with the Jinhua region; the Quzhou region has more droughts. The changing trend of drought has characteristics from 1982 to 2019, and there are significant differences in drought changing trends between different Jinhua–Quzhou basin areas. Overall, from 1982 to 2019, the frequency of drought showed a downward trend. We believe that these results will provide useful tools for drought management plans and play a relevant role in mitigating the effects of drought and protecting humanity from climate hazards.

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References

  • Abbas S, Nichol JE, Qamer FM, Xu J (2014) Characterization of drought development through remote sensing: a case study in central Yunnan, China. Remote Sens 6(6):4998–5018

    Article  Google Scholar 

  • Ali S, Tong D, Xu Z, Henchiri M, Wilson K, Siqi S, Zhang J (2019) Characterization of drought monitoring events through MODIS- and TRMM-based DSI and TVDI over South Asia during 2001–2017. Environ Sci Pollut Res 26:33568–33581

    Article  Google Scholar 

  • Alkama R, Cescatti A (2016) Biophysical climate impacts of recent changes in global forest cover. Science 351(6273):600e604. https://doi.org/10.1126/science.aac8083

    Article  CAS  Google Scholar 

  • Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Gonzalez P (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259(4):660–684. https://doi.org/10.1016/j.foreco.2009.09.001

    Article  Google Scholar 

  • Amin MO, Jan A, Mehrdada R, Ali M, Reza AS (2011) Drought monitoring methodology based on AVHRR images and SPOT vegetation maps. J Water Resour Prot 3:325–334

    Article  Google Scholar 

  • Bachelet D, Neilson R, Lenihan J, Drapek R (2001) Climate change effects on vegetation distribution and carbon budget in the United States. Ecosystems 4(3). https://doi.org/10.1007/s10021-001-0002-7

  • Carlson TN, Ripley DA (1997) On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens Environ 62(3):241–252

    Article  Google Scholar 

  • Carlson TN, Gillies RR, Perry EM (1994) A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover. Remote Sens Rev 9(1–2):161–173

    Article  Google Scholar 

  • Chen AF, He B, Wang HL, Huang L, Zhu YH, Lv AF (2015) Notable shifting in the responses of vegetation activity to climate change in China. Phys Chem Earth 87–88:60–66

    Article  Google Scholar 

  • Dhorde AG, Patel NR (2016) Spatio-temporal variation in terminal drought over western India using dryness index derived from long-term MODIS data. Eco Inform 32:28–38

    Article  Google Scholar 

  • Du W, Wang G (2013) Intra-event spatial correlations for cumulative absolute velocity, arias intensity, and spectral accelerations based on regional site conditions. Bull Seismol Soc Am 103(2A):1117–1129. https://doi.org/10.1785/0120120185

    Article  Google Scholar 

  • Du W, Wang G (2014) Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures. Earthq Eng Struct Dynam 43(5):661–679. https://doi.org/10.1002/eqe.2365

    Article  Google Scholar 

  • Du C, Bai X, Li Y, Tan Q, Zhao C, Luo G, Yang S (2024) Storage, form, and influencing factors of karst inorganic carbon in a carbonate area in China. Sci China Earth Sci. https://doi.org/10.1007/s11430-023-1249-9

    Article  Google Scholar 

  • FAO (2017) The future of food and the future of food and agriculture – variations and challenges. Rome

  • Gao J, Li F, Gao H, Zhou C, Zhang X (2017) The impact of land-use change on water-related ecosystem services: a study of the Guishui River Basin, Beijing, China. J Clean Prod 163:S148–S155. https://doi.org/10.1016/j.jclepro.2016.01.049

    Article  Google Scholar 

  • Guan H, Huang J, Li L, Li X, Miao S, Su W, Huang H (2023) Improved Gaussian mixture model to map the flooded crops of VV and VH polarization data. Remote Sens Environ 295:113714. https://doi.org/10.1016/j.rse.2023.113714

    Article  Google Scholar 

  • Haque M, Basak R (2017) Land cover change detection using GIS and remote sensing techniques: a spatiotemporal study on Tanguar Haor, Sunamganj, Bangladesh. Egypt J Remote Sens Space Sci 20(2). https://doi.org/10.1016/j.ejrs.2016.12.003

  • He M, Dong J, Jin Z, Liu C, Xiao J, Zhang F, Deng L (2021) Pedogenic processes in loess-paleosol sediments: clues from Li isotopes of leachate in Luochuan loess. Geochim Cosmochim Acta 299:151–162. https://doi.org/10.1016/j.gca.2021.02.021

    Article  CAS  Google Scholar 

  • He M, Ren T, Jin ZD, Deng L, Liu H, Cheng YY, Chang H (2023) Precise analysis of potassium isotopic composition in plant materials by multi-collector inductively coupled plasma mass spectrometry. Spectrochimica Acta Part B: Atomic Spectroscopy 106781. https://doi.org/10.1016/j.sab.2023.106781

  • Huang J, Xue Y, Sun S, Zhang J (2015) Spatial and temporal variability of drought during 1960–2012 in Inner Mongolia, north China. Quat Int 355:134–144

    Article  Google Scholar 

  • Huang H, Huang J, Wu Y, Zhuo W, Song J, Li X, Liang S (2023) The improved winter wheat yield estimation by assimilating GLASS LAI into a crop growth model with the proposed Bayesian posterior-based ensemble Kalman filter. IEEE Trans Geosci Remote Sens 61. https://doi.org/10.1109/TGRS.2023.3259742

  • IPCC (2021) Summary for Policymakers. In Climate Change 2021: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2013; Available online: https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_SPM_FINAL.pdf

  • Jackson TJ, Cosh MH, Bindlish R, Starks PJ, Bosch DD, Seyfried M, Du J (2010) Validation of advanced microwave scanning radiometer soil moisture products. IEEE Trans Geosci Remote Sens 48(12):4256–4272

    Article  Google Scholar 

  • Jain SK, Keshri R, Goswami A, Sarkar A (2010) Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India. Nat Hazards 54(3):643–656

    Article  Google Scholar 

  • Jain S, Salunke P, Mishra SK, Sahany S, Choudhary N (2019) Advantage of NEX1GDDP over CMIP5 and CORDEX data: Indian Summer Monsoon. Atmos Res 228:152–160. https://doi.org/10.1016/j.atmosres.2019.05.026

    Article  Google Scholar 

  • Jiang C, Wang Y, Yang Z, Zhao Y (2023) Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China. Environ Monit Assess 195(10):1215. https://doi.org/10.1007/s10661-023-11821-6

    Article  Google Scholar 

  • Jiang Y, Li J, Zuo R, Sun C, Zhai Y, Tian L, Zhang X (2024) The transmission of isotopic signals from precipitation to groundwater and its controls: an experimental study with soil cylinders of various soil textures and burial depths in a monsoon region. J Hydrol 631:130746. https://doi.org/10.1016/j.jhydrol.2024.130746

    Article  CAS  Google Scholar 

  • Jiapaer G, Liang SL, Yi QX, Liu JP (2015) Vegetation dynamics and responses to recent climate change in Xinjiang using leaf area index as an indicator. Ecol Indic 58:64–76

    Article  Google Scholar 

  • Kalisa W, Igbawua T, Henchiri M, Ali S, Zhang S, Bai Y, Zhang J (2019) Assessment of climate impact on vegetation dynamics over East Africa from 1982 to 2015. Sci Rep 9:16865

    Article  Google Scholar 

  • Kalisa W, Zhang J, Igbawua T, Ujoh F, Ebohon OJ, Namugiza J (2020) Spatio-temporal analysis of drought and return periods over the East African region using standardized precipitation index from 1920 to 2016. Agric Water Manag 237:106195

    Article  Google Scholar 

  • Khan R, Gilani H, Iqbal N, Shahid I (2020) Satellite-based (2000–2015) drought hazard assessment with indices, mapping, and monitoring of Potohar plateau, Punjab, Pakistan. Environ Earth Sci 79:1–19

    Article  Google Scholar 

  • Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15(11):91–100

    Article  Google Scholar 

  • Kogan FN (1998) A typical pattern of vegetation conditions in southern Africa during El Nino years detected from AVHRR data using threechannel numerical index. Inter J Remote Sens 19:3688–3694

    Article  Google Scholar 

  • Kogan FN, Yang B, Wei G, Zhiyuan P, Xianfeng J (2005) Modelling corn production in China using AVHRR-based vegetation health indices. Int J Remote Sens 26(11):2325–2336

    Article  Google Scholar 

  • Lin Y, Qiu R, Yao J, Hu X, Lin J (2019) The effects of urbanization on China’s forest loss from 2000 to 2012: evidence from a panel analysis. J Clean Prod 214:270–278. https://doi.org/10.1016/j.jclepro.2018.12.317

    Article  Google Scholar 

  • Lin X, Zhu G, Qiu D, Ye L, Liu Y, Chen L, Sun N (2023) Stable precipitation isotope records of cold wave events in Eurasia. Atmos Res 296:107070. https://doi.org/10.1016/j.atmosres.2023.107070

    Article  CAS  Google Scholar 

  • Liu XH, Zhang JH, Xu XH (2015) Drought monitoring in Xinjiang by using MODIS-TVDI. Remote Sens Infor 30(02):111–115

    Google Scholar 

  • Liu J, Heiskanen J, Aynekulu E, Maeda EE, Pellikka PK (2016) Land cover characterization in West Sudanian Savannas using seasonal features from annual Landsat time series. Remote Sens 8:365

    Article  Google Scholar 

  • Liu Q et al (2020) Monitoring drought using composite drought indices based on remote sensing. Sci Total Environ 711:134585. https://doi.org/10.1016/j.scitotenv.2019.134585

    Article  CAS  Google Scholar 

  • Lu S, Zhu G, Meng G, Lin X, Liu Y, Qiu D, Jiao Y (2024) Influence of atmospheric circulation on the stable isotope of precipitation in the monsoon margin region. Atmos Res 298:107131. https://doi.org/10.1016/j.atmosres.2023.107131

    Article  CAS  Google Scholar 

  • Ma JY, Jia X, Zha TS, Bourque CPA, Tian Y, Bai YJ, Liu P, Yang RZ, Li C, Li CY (2019) Ecosystem water use efficiency in a young plantation in Northern China and its relationship to drought. Agric for Meteorol 275:1–10

    Article  Google Scholar 

  • Maximilian S, Landmann T, Cornish N, Wetzel K, Siebert S, Franke JA (2020) Spatially transferable drought hazard and drought risk modeling approach based on remote sensing data. Remote Sens 12:237

    Article  Google Scholar 

  • Onyutha C (2017) On rigorous drought assessment using daily time scale: non-stationary frequency analyses, revisited concepts, and a new method to yield non-parametric indices. Hydrology 4:48

    Article  Google Scholar 

  • Piao SL, Wang XH, Ciais P, Zhu B, Wang T, Liu J (2011) Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Glob Chang Biol 17:3228–3239

    Article  Google Scholar 

  • Qiu ZX, Feng ZK, Song YN, Li ML, Zhang PP (2020) Carbon sequestration potential of forest vegetation in China from 2003 to 2050: predicting forest vegetation growth based on climate and the environment. J Clean Prod 252:119715

    Article  Google Scholar 

  • Qiu S, Yang H, Zhang S, Huang S, Zhao S, Xu X, Banwart SA (2023) Carbon storage in an arable soil combining field measurements, aggregate turnover modeling and climate scenarios. CATENA 220:106708. https://doi.org/10.1016/j.catena.2022.106708

    Article  CAS  Google Scholar 

  • Rahimzadeh-Bajgiran P, Berg AA, Champagne C, Omasa K (2013) Estimation of soil moisture using optical/thermal infrared remote sensing in the Canadian Prairies. ISPRS J Photogramm Remote Sens 83:94–103

    Article  Google Scholar 

  • Ren SL, Li YT, Peichl M (2020) Diverse effects of climate at different times on grassland phenology in mid-latitude of the Northern Hemisphere. Ecol Indic 113:106260

    Article  Google Scholar 

  • Sandholt I, Rasmussen K, Andersen J (2002) A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens Environ 79(2):213–224

    Article  Google Scholar 

  • Shao EY, Bing-Fang W (2010) Calculation of monthly precipitation anomaly percentage using web-serviced remote sensing data. Advanced computer control (ICACC), 2010 2nd international conference, vol 5. IEEE, pp 621–625

  • Shi H, Shao MG (2000) Soil and water loss from the Loess Plateau in China. J Arid Environ 45(1):9–20

    Article  Google Scholar 

  • Song X, Zeng X (2017) Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models. Ecol Evol 7(3):997–1008. https://doi.org/10.1002/ece3.2735

    Article  Google Scholar 

  • Song X, Li L, Fu G, Li J, Zhang A, Liu W, Zhang K (2014) Spatial–temporal variations of spring drought based on spring-composite index values for the Songnen Plain, Northeast China. Theor Appl Climatol 116(3–4):371–384

    Article  Google Scholar 

  • Trenberth KE (2011) Changes in precipitation with climate change. Clim Res 47(1–2):123–138. https://doi.org/10.3354/cr00953

    Article  Google Scholar 

  • Tucker CJ (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens Environ 8:127–150

    Article  Google Scholar 

  • Tucker CJ et al (2005) An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. Int J Remote Sens 26(20):4485–4498

    Article  Google Scholar 

  • Wang HL, Chen AF, Wang QF, He B (2015) Drought dynamics and impacts on vegetation in China from 1982 to 2011. Ecol Eng 75:303–307

    Article  Google Scholar 

  • Wang B, Xu G, Li P, Li ZB, Zhang YX, Cheng YT, Lu J, Zhang JX (2019) Vegetation dynamics and their relationships with climatic factors in the Qinling Mountains of China. Ecol Indic 108:105719

    Article  Google Scholar 

  • Wang Z, Zhan C, Ning L, Guo H (2021) Evaluation of global terrestrial evapotranspiration in CMIP6 models. Theor Appl Climatol 143:521–531. https://doi.org/10.1007/s00704-020-03437-4

    Article  Google Scholar 

  • Wang H, Wang S, Shu X, He Y, Huang J (2024) Increasing occurrence of sudden turns from drought to flood over China. J Geophys Res: Atmos 129(3):e2023JD039974. https://doi.org/10.1029/2023JD039974

    Article  Google Scholar 

  • Wu J, Chen X, Yao H, Gao L, Chen Y, Liu M (2017) Non-linear relationship of hydrological drought responding to meteorological drought and impact of a large reservoir. J Hydrol 551:495–507

    Article  Google Scholar 

  • Xie H, He Y, Xie X (2017) Exploring the factors influencing ecological land change for China’s Beijing– Tianjin-Hebei region using big data. J Clean Prod 142:677–687. https://doi.org/10.1016/j.jclepro.2016.03.064

    Article  Google Scholar 

  • Xie X, Xie B, Cheng J, Chu Q, Dooling T (2021) A simple Monte Carlo method for estimating the chance of a cyclone impact. Nat Hazards 107(3):2573–2582. https://doi.org/10.1007/s11069-021-04505-2

    Article  Google Scholar 

  • Xu Z, Li X, Li J, Xue Y, Jiang S, Liu L, Sun Q (2022b) Characteristics of source rocks and genetic origins of natural gas in deep formations, Gudian Depression, Songliao Basin, NE China. ACS Earth Space Chem 6(7):1750–1771. https://doi.org/10.1021/acsearthspacechem.2c00065

    Article  CAS  Google Scholar 

  • Xu J, Zhou G, Su S, Cao Q, Tian Z (2022) The development of a rigorous model for bathymetric mapping from multispectral satellite-images. Remote Sens 14(10). https://doi.org/10.3390/rs14102495

  • Yin L, Wang L, Li T, Lu S, Tian J, Yin Z, Zheng W (2023a) U-Net-LSTM: time series-enhanced lake boundary prediction model. Land 12(10):1859. https://doi.org/10.3390/land12101859

    Article  Google Scholar 

  • Yin L, Wang L, Li T, Lu S, Yin Z, Liu X, Zheng W (2023b) U-Net-STN: a novel end-to-end lake boundary prediction model. Land 12(8):1602. https://doi.org/10.3390/land12081602

    Article  Google Scholar 

  • Zhang J, Mu Q, Huang J (2016) Assessing the remotely sensed drought severity index for agricultural drought monitoring and impact analysis in North China. Ecol Indic 63:296–309

    Article  Google Scholar 

  • Zhang S, Bai X, Zhao C, Tan Q, Luo G, Wang J, Xi H (2021) Global CO2 consumption by silicate rock chemical weathering: its past and future. Earth’s Future 9(5):e1938E-e2020E. https://doi.org/10.1029/2020EF001938

    Article  Google Scholar 

  • Zhang T, Song B, Han G, Zhao H, Hu Q, Zhao Y, Liu H (2023) Effects of coastal wetland reclamation on soil organic carbon, total nitrogen, and total phosphorus in China: a meta-analysis. Land Degrad Dev 34(11):3340–3349. https://doi.org/10.1002/ldr.4687

    Article  Google Scholar 

  • Zhao J, Xu J, Xie X, Lu H (2016) Drought monitoring based on TIGGE and distributed hydrological model in Huaihe River Basin, China. Sci Total Environ 553:358–365

    Article  CAS  Google Scholar 

  • Zheng H, Fan X, Bo W, Yang X, Tjahjadi T, Jin S (2023) A multiscale point-supervised network for counting maize tassels in the wild. Plant Phenomics 5:100. https://doi.org/10.34133/plantphenomics.0100

    Article  Google Scholar 

  • Zhou QX (2006) Advance in the effects of climate change on environment and health. J Meteorol Environ 22:38–44

    CAS  Google Scholar 

  • Zhou WM, Wang JD, Liu JS, Yang JS (2005) Influence of different land-use to regional climate in Sanjiang Plain. J Soil Water Conserv 10:155–158

    Google Scholar 

  • Zhou L, Wu J, Mo X, Zhou H, Diao C (2017) Quantitative and detailed spatiotemporal patterns of drought in China during 2001–2013. Sci Total Environ 589(1):136–145

    CAS  Google Scholar 

  • Zhou G, Liu W, Zhu Q, Lu Y, Liu Y (2022) ECA-MobileNetV3(Large)+SegNet model for binary sugarcane classification of remotely sensed images. IEEE Trans Geosci Remote Sens 60. https://doi.org/10.1109/TGRS.2022.3215802

  • Zhou G, Tang Y, Zhang W, Liu W, Jiang Y, Gao E, Bai Y (2023) Shadow detection on high-resolution digital orthophoto map using semantic matching. IEEE Trans Geosci Remote Sens 61. https://doi.org/10.1109/TGRS.2023.3294531

  • Zhu G, Yong L, Zhao X, Liu Y, Zhang Z, Xu Y, Wang L (2022) Evaporation, infiltration and storage of soil water in different vegetation zones in the Qilian Mountains: a stable isotope perspective. Hydrol Earth Syst Sci 26(14):3771–3784. https://doi.org/10.5194/hess-26-3771-2022

    Article  CAS  Google Scholar 

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Acknowledgements

The authors acknowledge the funding from the Researchers Supporting Project number (RSPD2024R665), King Saud University, Riyadh, Saudi Arabia.

Funding

This work was supported by the basic research project of the Zhejiang Normal University (ZC304022952), China; the authors also acknowledge the funding from the Researchers Supporting Project number (RSPD2024R665), King Saud University, Riyadh, Saudi Arabia.

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Authors and Affiliations

  1. College of Life Sciences, Zhejiang Normal University, Jinhua, 321004, China

    Shahzad Ali, Muhammad Umair & Tyan Alice Makanda

  2. College of Chemistry and Material Science, Zhejiang Normal University, Jinhua, 321004, China

    Shahzad Ali

  3. School of Computer Science and Technology, Qingdao University, Qingdao, China

    Abdul Basit

  4. Department of Agriculture, Hazara University, Mansehra, 21120, Pakistan

    Sajid Ali

  5. Department of Chemistry, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia

    Mohammed Rafi Shaik & Mujeeb Khan

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Ali, S., Basit, A., Ali, S. et al. Study loss of vegetative cover and increased land surface temperature through remote sensing strategies under the inter-annual climate variability in Jinhua–Quzhou basin, China. Environ Sci Pollut Res 31, 28950–28966 (2024). https://doi.org/10.1007/s11356-024-33112-4

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