Remote Sensing Technology and Application, Volume. 40, Issue 4, 851(2025)
Remote Sensing Estimates of Terrestrial Gross Primary Production: Progress, Applications and Prospects
[1] [1] BEER C, REICHSTEIN M, TOMELLERI E,et al. Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate[J]. Science, 2010, 329(5993): 834-838. DOI: 10.1126/science.1184984
[5] [5] BALDOCCHI D D. Assessing the eddy covariance technique for evaluating carbon dioxide exchange rates of ecosystems: Past, present and future[J]. Global Change Biology, 2003, 9(4): 479-492. DOI: 10.1046/j.1365-2486.2003.00629.x
[6] [6] RUNNING S W, NEMANI R R, HEINSCH F A,et al. A continuous satellite-derived measure of global terrestrial primary production[J]. BioScience, 2004, 54(6): 547. DOI: 10.1641/0006-3568(2004)054[0547: ACSMOG]2.0.CO2
[7] [7] XIAO X M, HOLLINGER D, ABER J,et al. Satellite-based modeling of gross primary production in an evergreen needleleaf forest[J]. Remote Sensing of Environment, 2004, 89(4): 519-534. DOI: 10.1016/j.rse.2003.11.008
[8] [8] YUAN W P, LIU S G, ZHOU G S,et al. Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes[J]. Agricultural and Forest Meteorology, 2007, 143(3/4): 189-207. DOI: 10.1016/j.agrformet.2006.12.001
[9] [9] BONAN G B, LAWRENCE P J, OLESON K W,et al. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data[J]. Journal of Geophysical Research, 2011, 116(G2): G02014. DOI: 10.1029/2010jg001593
[10] [10] CHEN J M, LIU J, CIHLAR J,et al. Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications[J]. Ecological Modelling, 1999, 124(2/3): 99-119. DOI: 10.1016/S0304-3800(99)00156-8
[11] [11] WANG Y L, TIAN X J, DUAN M Z,et al. Optimal design of surface CO2 observation network to constrain China's land carbon sink[J]. Science Bulletin, 2023, 68(15): 1678-1686. DOI: 10.1016/j.scib.2023.07.010
[12] [12] ALTON P, BODIN P. A comparative study of a multilayer and a productivity (light-use) efficiency land-surface model over different temporal scales[J]. Agricultural and Forest Meteorology, 2010, 150(2): 182-195. DOI: 10.1016/j.agrformet.2009.10.001
[13] [13] LUO K W, WANG X L, DE JONG M,et al. Drought triggers and sustains overnight fires in North America[J].Nature, 2024, 627(8003): 321-327. DOI: 10.1038/s41586-024-07028-5
[14] [14] ZHAO J, YUE C, WANG J M,et al. Forest fire size amplifies postfire land surface warming[J]. Nature, 2024, 633(8031): 828-834. DOI: 10.1038/s41586-024-07918-8
[16] [16] TATEM A J, GOETZ S J, HAY S I. Fifty years of earth observation satellites: Views from above have lead to countless advances on the ground in both scientific knowledge and daily life[J]. American Scientist, 2008, 96(5): 390-398. DOI: 10.1511/2008.74.390
[17] [17] ANAV A, FRIEDLINGSTEIN P, BEER C,et al. Spatiotemporal patterns of terrestrial gross primary production: A review[J].Reviews of Geophysics, 2015, 53(3): 785-818. DOI: 10.1002/2015RG000483
[18] [18] RYU Y, BALDOCCHI D D, KOBAYASHI H,et al. Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales[J]. Global Biogeochemical Cycles, 2011, 25(4): 004053. DOI: 10.1029/2011gb 004053
[19] [19] GOWARD S N, TUCKER C J, DYE D G. North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer[J].Vegetatio, 1985, 64(1): 3-14. DOI: 10.1007/BF00033449
[20] [20] BADGLEY G, FIELD C B, BERRY J A. Canopy near-infrared reflectance and terrestrial photosynthesis[J]. Science Advances, 2017, 3(3): e1602244. DOI: 10.1126/sciadv.1602244
[21] [21] GITELSON A A, VERMA S B, VIA A,et al. Novel technique for remote estimation of CO2 flux in maize[J]. Geophysical Research Letters, 2003, 30(9): 2002GL016543. DOI: 10.1029/2002gl016543
[22] [22] SUN Y, FU R, DICKINSON R,et al. Drought onset mechanisms revealed by satellite solar-induced chlorophyll fluorescence: Insights from two contrasting extreme events[J]. Journal of Geophysical Research: Biogeosciences, 2015, 120(11): 2427-2440. DOI: 10.1002/2015jg003150
[23] [23] MOHAMMED G H, COLOMBO R, MIDDLETON E M,et al. Remote sensing of Solar-Induced chlorophyll Fluorescence (SIF) in vegetation: 50 years of progress[J]. Remote Sensing of Environment, 2019, 231: 111177. DOI: 10.1016/j.rse.2019.04.030
[24] [24] FRANKENBERG C, FISHER J B, WORDEN J,et al. New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity[J].2011, 38(17): L17706. DOI: 10.1029/2011GL048738
[25] [25] JOINER J, GUANTER L, LINDSTROT R,et al. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: Methodology, simulations, and application to GOME-2[J]. Atmospheric Measurement Techniques, 2013, 6(10): 2803-2823. DOI: 10.5194/amt-6-2803-2013
[26] [26] KEHLER P, FRANKENBERG C, MAGNEY T S,et al. Global retrievals of solar induced chlorophyll fluorescence with TROPOMI: First results and inter-sensor comparison to OCO-2[J]. Geophysical Research Letters, 2018, 45(19): 10456-10463. DOI: 10.1029/2018GL079031
[27] [27] DU S S, LIU L Y, LIU X J,et al. Retrieval of global terrestrial solar-induced chlorophyll fluorescence from TanSat satellite[J]. Science Bulletin, 2018, 63(22): 1502-1512. DOI: 10.1016/j.scib.2018.10.003
[28] [28] WIGNERON J P, CIAIS P, LI X J,et al. Global carbon balance of the forest: Satellite-based L-VOD results over the last decade[J]. Frontiers in Remote Sensing, 2024, 5: 1338618. DOI: 10.3389/frsen.2024.1338618
[29] [29] WILD B, TEUBNER I, MOESINGER L,et al. VODCA2-GPP-a new, global, long-term(1988-2020) gross primary production dataset from microwave remote sensing[J]. Earth System Science Data, 2022, 14(3): 1063-1085. DOI: 10.5194/essd-14-1063-2022
[30] [30] LIU H H, LIU Y, CHEN Y,et al. Dynamics of global dryland vegetation were more sensitive to soil moisture: Evidence from multiple vegetation indices[J]. Agricultural and Forest Meteorology, 2023, 331: 109327. DOI: 10.1016/j.agrformet.2023.109327
[31] [31] WANG S H, ZHANG Y G, JU W M,et al. Tracking the seasonal and inter-annual variations of global gross primary production during last four decades using satellite near-infrared reflectance data[J]. Science of The Total Environment, 2021, 755: 142569. DOI: 10.1016/j.scitotenv.2020.142569
[32] [32] LI X, XIAO J F. A global, 0.05-degree product of solar-induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data[J]. Remote Sensing, 2019, 11(5): 517. DOI: 10.3390/rs11050517
[33] [33] LI X, XIAO J F, HE B B. Chlorophyll fluorescence observed by OCO-2 is strongly related to gross primary productivity estimated from flux towers in temperate forests[J]. Remote Sensing of Environment, 2018, 204: 659-671. DOI: 10.1016/j.rse.2017.09.034
[34] [34] YANG F H, ICHII K, WHITE M A,et al. Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach[J]. Remote Sensing of Environment, 2007, 110(1): 109-122. DOI: 10.1016/j.rse.2007.02.016
[35] [35] JUNG M, REICHSTEIN M, MARGOLIS H A,et al. Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations[J]. Journal of Geophysical Research, 2011, 116: G00J07. DOI: 10.1029/2010jg 001566
[36] [36] JOINER J, YOSHIDA Y, ZHANG Y,et al. Estimation of terrestrial global Gross Primary Production(GPP) with satellite data-driven models and eddy covariance flux data[J]. Remote Sensing, 2018, 10(9): 1346. DOI: 10.3390/rs10091346
[37] [37] WEI S H, YI C X, FANG W,et al. A global study of GPP focusing on light-use efficiency in a random forest regression model[J].Ecosphere, 2017, 8(5): e01724. DOI: 10.1002/ecs 2.1724
[38] [38] JUNG M, SCHWALM C, MIGLIAVACCA M,et al. Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach[J].Biogeosciences, 2020, 17(5): 1343-1365. DOI: 10.5194/bg-17-1343-2020
[39] [39] NELSON J A, WALTHER S, GANS F,et al. X-base: The first terrestrial carbon and water flux products from an extended data-driven scaling framework, fluxcom-X[J].BiogeoSciences, 2024, 21: 5079-5115. DOI: 10.5194/bg-21-5079-2024
[40] [40] JOINER J, GUANTER L, LINDSTROT R,et al. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: Methodology, simulations, and application to GOME-2[J]. Atmospheric Measurement Techniques, 2013, 6(10): 2803-2823. DOI: 10.5194/amt-6-2803-2013
[41] [41] FARQUHAR G D, VON CAEMMERER S, BERRY J A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species[J].Planta, 1980, 149(1): 78-90. DOI: 10.1007/BF00386231
[42] [42] LIU Y B, XIAO J F, JU W M,et al. Satellite-derived LAI products exhibit large discrepancies and can lead to substantial uncertainty in simulated carbon and water fluxes[J]. Remote Sensing of Environment, 2018, 206: 174-188. DOI: 10.1016/j.rse.2017.12.024
[43] [43] LENG J, CHEN J M, LI W,et al. Global datasets of hourly carbon and water fluxes simulated using a satellite-based process model with dynamic parameterizations[J]. Earth System Science Data, 2024, 16(3): 1283-1300.
[44] [44] LI B L, RYU Y, JIANG C Y,et al. BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land-atmosphere fluxes[J]. Remote Sensing of Environment, 2023, 295: 113696. DOI: 10.1016/j.rse.2023.113696
[45] [45] MONTEITH J L. Solar radiation and productivity in tropical ecosystems[J]. Journal of Applied Ecology, 1972, 9(3): 747. DOI: 10.2307/2401901
[46] [46] PEI Y Y, DONG J W, ZHANG Y,et al. Performance of four state-of-the-art GPP products (VPM, MOD17, BESS and PML) for grasslands in drought years[J]. Ecological Informatics, 2020, 56: 101052. DOI: 10.1016/j.ecoinf.2020.101052
[47] [47] YUAN W P, ZHENG Y, PIAO S L,et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth[J]. Science Advances, 2019, 5(8): eaax1396. DOI: 10.1126/sciadv.aax1396
[48] [48] HUANG X J, ZHENG Y, ZHANG H,et al. High spatial resolution vegetation gross primary production product: Algorithm and validation[J]. Science of Remote Sensing, 2022, 5: 100049. DOI: 10.1016/j.srs.2022.100049
[49] [49] ZHANG Y, XIAO X M, WU X C,et al. A global moderate resolution dataset of gross primary production of vegetation for 2000~2016[J]. Scientific Data, 2017, 4: 170165. DOI: 10.1038/sdata.2017.165
[50] [50] JONES L A, KIMBALL J S, REICHLE R H,et al. The SMAP level 4 carbon product for monitoring ecosystem landatmosphere CO2 exchange[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(11): 6517-6532. DOI: 10.1109/TGRS.2017.2729343
[51] [51] ZHENG Y, SHEN R Q, WANG Y W,et al. Improved estimate of global gross primary production for reproducing its longterm variation, 1982-2017[J].Earth System Science Data, 2020, 12(4): 2725-2746. DOI: 10.5194/essd-12-2725-2020
[52] [52] LIN S R, HUANG X J, WANG C Q,et al. A 30-m gross primary production dataset from 2016 to 2020 in China[J]. Scientific Data, 2024, 11: 1065. DOI: 10.1038/s41597-024-03893-x
[53] [53] JOINER J, YOSHIDA Y. Global MODIS and FLUXNET-derived Daily Gross Primary Production, V2, ORNL DAAC, Oak Ridge, Tennessee, USA[DB].Earth Data[data set], 2021, 10.
[54] [54] PING J Y, CUI E Q, DU Y,et al. Enhanced causal effect of ecosystem photosynthesis on respiration during heatwaves[J]. Science Advances, 2023, 9(43): eadi6395. DOI: 10.1126/sciadv.adi6395
[56] [56] SIPPEL S, REICHSTEIN M, MA X L,et al. Drought, heat, and the carbon cycle: A review[J]. Current Climate Change Reports, 2018, 4(3): 266-286. DOI: 10.1007/s40641-018-0103-4
[57] [57] YUAN X, WANG Y M, JI P,et al. A global transition to flash droughts under climate change[J]. Science, 2023, 380(6641): 187-191. DOI: 10.1126/science.abn6301
[58] [58] SUNGMIN O, PARK S K. Global ecosystem responses to flash droughts are modulated by background climate and vegetation conditions[J]. Communications Earth & Environment, 2024, 5: 88. DOI: 10.1038/s43247-024-01247-4
[59] [59] YAO T T, LIU S X, HU S,et al. Response of vegetation ecosystems to flash drought with solar-induced chlorophyll fluorescence over the Hai River Basin, China during 2001-2019[J]. Journal of Environmental Management, 2022, 313: 114947. DOI: 10.1016/j.jenvman.2022.114947
[60] [60] BASTOS A, CIAIS P, FRIEDLINGSTEIN P,et al. Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity[J]. Science Advances, 2020, 6(24): eaba2724. DOI: 10.1126/sciadv.aba2724
[61] [61] XU H T, CHEN H W, CHEN D L,et al. Global patterns and drivers of post-fire vegetation productivity recovery[J].Nature Geoscience, 2024, 17(9): 874-881. DOI: 10.1038/s41561-024-01520-3
[62] [62] DUEK J, KOV H, CZERN R,et al. Influence of summer flood on the net ecosystem exchange of CO2 in a temperate sedge-grass marsh[J]. Agricultural and Forest Meteorology, 2009, 149(9): 1524-1530. DOI: 10.1016/j.agrformet.2009.04.007
[63] [63] SHEN M G, WANG S P, JIANG N,et al. Plant phenology changes and drivers on the Qinghai-Tibetan Plateau[J]. Nature Reviews Earth & Environment, 2022, 3(10): 633-651. DOI: 10.1038/s43017-022-00317-5
[64] [64] WANG L, TIAN F, HUANG K,et al. Asymmetric patterns and temporal changes in phenologybased seasonal gross carbon uptake of global terrestrial ecosystems[J]. Global Ecology and Biogeography, 2020, 29(6): 1020-1033.
[65] [65] WANG S H, JU W M, PEUELAS J,et al. Urban−rural gradients reveal joint control of elevated CO2 and temperature on extended photosynthetic seasons[J]. Nature Ecology &Evolution, 2019, 3(7): 1076-1085. DOI: 10.1038/s41559-019-0931-1
[66] [66] ZHONG Z Q, HE B, WANG Y P,et al. Disentangling the effects of vapor pressure deficit on northern terrestrial vegetation productivity[J]. Science Advances, 2023, 9(32): eadf 3166. DOI: 10.1126/sciadv.adf3166
[67] [67] WANG L X, JIAO W Z, MACBEAN N,et al. Dryland productivity under a changing climate[J]. Nature Climate Change, 2022, 12(11): 981-994. DOI: 10.1038/s41558-022-01499-y
[68] [68] JIAO W Z, WANG L X, MCCABE M F. Multi-sensor remote sensing for drought characterization: Current status, opportunities and a roadmap for the future[J]. Remote Sensing of Environment, 2021, 256: 112313. DOI: 10.1016/j.rse.2021.112313
[69] [69] YU Z, WANG J X, LIU S R,et al. Global gross primary productivity and water use efficiency changes under drought stress[J].Environmental Research Letters, 2017, 12(1): 014016. DOI: 10.1088/1748-9326/aa5258
[70] [70] LAIOLO P, GABELLANI S, CAMPO L,et al. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 48: 131-145. DOI: 10.1016/j.jag.2015.06.002
[71] [71] LPEZ LPEZ P, SUTANUDJAJA E H, SCHELLEKENS J,et al. Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products[J]. Hydrology and Earth System Sciences, 2017, 21(6): 3125-3144. DOI: 10.5194/hess-21-3125-2017
[72] [72] LI B L, RYU Y, JIANG C Y,et al. BESSv2.0: A satellite-based and coupled-process model for quantifying long-term global land-atmosphere fluxes[J]. Remote Sensing of Environment, 2023, 295: 113696. DOI: 10.1016/j.rse.2023.113696
[73] [73] ZHANG Y Q, KONG D D, GAN R,et al. Coupled estimation of 500 m and 8 day resolution global evapotranspiration and gross primary production in 2002-2017[J]. Remote Sensing of Environment, 2019, 222: 165-182. DOI: 10.1016/j.rse.2018.12.031
[74] [74] XIN Q C, BROICH M, SUYKER A E,et al. Multi-scale evaluation of light use efficiency in MODIS gross primary productivity for croplands in the Midwestern United States[J]. Agricultural and Forest Meteorology, 2015, 201: 111-119. DOI: 10.1016/j.agrformet.2014.11.004
[75] [75] DONG J, FU Y Y, WANG J J,et al. Early-season mapping of winter wheat in China based on Landsat and Sentinel images[J]. Earth System Science Data, 2020, 12(4): 3081-3095. DOI: 10.5194/essd-12-3081-2020
[76] [76] DONG J, LU H B, WANG Y W,et al. Estimating winter wheat yield based on a light use efficiency model and wheat variety data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 160: 18-32. DOI: 10.1016/j.isprsjprs. 2019.12.005
[77] [77] AVNERY S, MAUZERALL D L, LIU J F,et al. Global crop yield reductions due to surface ozone exposure: 1. Year 2000 crop production losses and economic damage[J]. Atmospheric Environment, 2011, 45(13): 2284-2296. DOI: 10.1016/j.atmosenv.2010.11.045
[78] [78] SHA Z Y, BAI Y F, LI R R,et al. The global carbon sink potential of terrestrial vegetation can be increased substantially by optimal land management[J]. Communications Earth &Environment, 2022, 3: 8. DOI: 10.1038/s43247-021-00333-1
[79] [79] LIANG W, FU B J, WANG S,et al. Quantification of the ecosystem carrying capacity on China's Loess Plateau[J].Ecological Indicators, 2019, 101: 192-202. DOI: 10.1016/j.ecolind.2019.01.020
[80] [80] YAN H M, XUE Z C, NIU Z E. Ecological restoration policy should pay more attention to the high productivity grasslands[J]. Ecological Indicators, 2021, 129: 107938. DOI: 10.1016/j.ecolind.2021.107938
[81] [81] ZHU Q A, CHEN H, PENG C H,et al. An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau[J]. Nature Communications, 2023, 14: 6406. DOI: 10.1038/s41467-023-42099-4
[84] [84] LEVIS S. Modeling vegetation and land use in models of the Earth System[J]. WIREs Climate Change, 2010, 1(6): 840-856. DOI: 10.1002/wcc.83
[85] [85] STOCKER B D, ZSCHEISCHLER J, KEENAN T F,et al. Drought impacts on terrestrial primary production underestimated by satellite monitoring[J]. Nature Geoscience, 2019, 12(4): 264-270. DOI: 10.1038/s41561-019-0318-6
[86] [86] LIN S R, HU Z M, WANG Y P,et al. Underestimated interannual variability of terrestrial vegetation production by terrestrial ecosystem models[J]. Global Biogeochemical Cycles, 2023, 37(4): e2023GB007696. DOI: 10.1029/2023GB007696
[87] [87] KOLBY SMITH W, REED S C, CLEVELAND C C,et al. Large divergence of satellite and Earth system model estimates of global terrestrial CO2 fertilization[J]. Nature Climate Change, 2015, 6(3): 306-310. DOI: 10.1038/nclimate2879
[89] [89] YUAN W P, CAI W W, XIA J Z,et al. Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database[J]. Agricultural and Forest Meteorology, 2014, 192: 108-120. DOI: 10.1016/j.agrformet.2014.03.007
[90] [90] LIN S R, LI J, LIU Q H,et al. Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type[J]. International Journal of Applied Earth Observation and Geoinformation, 2021, 100: 102328. DOI: 10.1016/j.jag.2021.102328
[91] [91] LIN S R, HUANG X J, WANG C Q,et al. A 30-m gross primary production dataset from 2016 to 2020 in China[J]. Scientific Data, 2024, 11: 1065. DOI: 10.1038/s41597-024-03893-x
[92] [92] LI X Q, PENG Q Y, ZHENG Y,et al. Incorporating environmental variables into spatiotemporal fusion model to reconstruct high-quality vegetation index data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62: 4401812.
[93] [93] DONG J Q, LI L H, LI Y Z,et al. Inter-comparisons of mean, trend and interannual variability of global terrestrial gross primary production retrieved from remote sensing approach[J]. Science of The Total Environment, 2022, 822: 153343. DOI: 10.1016/j.scitotenv.2022.153343
[94] [94] YANG R Q, WANG J, ZENG N,et al. Divergent historical GPP trends among state-of-the-art multi-model simulations and satellite-based products[J]. Earth System Dynamics, 2022, 13(2): 833-849. DOI: 10.5194/esd-13-833-2022
[95] [95] ZHANG Z Y, CESCATTI A, WANG Y P,et al. Large diurnal compensatory effects mitigate the response of Amazonian forests to atmospheric warming and drying[J]. Science Advances, 2023, 9(21): eabq4974. DOI: 10.1126/sciadv.abq4974
[96] [96] WATT M S, BUDDENBAUM H, LEONARDO E M C,et al. Monitoring biochemical limitations to photosynthesis in N and P-limited radiata pine using plant functional traits quantified from hyperspectral imagery[J]. Remote Sensing of Environment, 2020, 248: 112003. DOI: 10.1016/j.rse.2020.112003
[97] [97] FANG J C, CHEN B Z, WANG F,et al. Nitrogen, phosphorus, and potassium co-limitation in terrestrial ecosystems: A global meta-analysis[J]. Plants, People, Planet, 2024, 6(6): 1329-1340. DOI: 10.1002/ppp3.10524
[98] [98] SUN Y H, PENG D, GUAN X B,et al. Impacts of the data quality of remote sensing vegetation index on gross primary productivity estimation[J]. GIScience & Remote Sensing, 2023, 60(1): 2275421. DOI: 10.1080/15481603.2023. 2275421
[99] [99] ROBINSON N P, ALLRED B W, SMITH W K,et al. Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m[J]. Remote Sensing in Ecology and Conservation, 2018, 4(3): 264-280. DOI: 10.1002/rse2.74
[100] [100] JEONG S, RYU Y, LI X,et al. GEOSIF: A continentalscale sub-daily reconstructed solar-induced fluorescence derived from OCO-3 and GK-2A over Eastern Asia and Oceania[J]. Remote Sensing of Environment, 2024, 311: 114284. DOI: 10.1016/j.rse.2024.114284
[101] [101] ZHANG Z Y, GUANTER L, PORCAR-CASTELL A,et al. Global modeling diurnal gross primary production from OCO-3 solar-induced chlorophyll fluorescence[J]. Remote Sensing of Environment, 2023, 285: 113383. DOI: 10.1016/j.rse.2022.113383
[102] [102] LIN S R, HAO D L, ZHENG Y,et al. Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production[J]. International Journal of Applied Earth Observation and Geoinformation, 2022, 113: 102978. DOI: 10.1016/j.jag.2022.102978
[103] [103] DIERSSEN H M, GIERACH M, GUILD L S,et al. Synergies between NASA's hyperspectral aquatic missions PACE, GLIMR, and SBG: Opportunities for new science and applications[J]. Journal of Geophysical Research: Biogeosciences, 2023, 128(10): e2023JG007574. DOI: 10.1029/2023jg007574
[104] [104] WINKLER A J, MYNENI R B, HANNART A,et al. Slowdown of the greening trend in natural vegetation with further rise in atmospheric CO2[J]. Biogeosciences, 2021, 18(17): 4985-5010. DOI: 10.5194/bg-18-4985-2021
[105] [105] CORTS J, MAHECHA M D, REICHSTEIN M,et al. Where are global vegetation greening and browning trends significant?[J]. Geophysical Research Letters, 2021, 48(6): e2020GL091496. DOI: 10.1029/2020gl091496
[106] [106] CAO S, LI M Y, ZHU Z C,et al. Spatiotemporally consistent global dataset of the GIMMS Leaf Area Index(GIMMS LAI4g) from 1982 to 2020[J]. Earth System Science Data, 2023, 15(11): 4877-4899. DOI: 10.5194/essd-15-4877-2023
[107] [107] JEONG S, RYU Y, GENTINE P,et al. Persistent global greening over the last four decades using novel long-term vegetation index data with enhanced temporal consistency[J]. Remote Sensing of Environment, 2024, 311: 114282. DOI: 10.1016/j.rse.2024.114282
[108] [108] LIN S R, HU Z M, WANG Y P,et al. Underestimated interannual variability of terrestrial vegetation production by terrestrial ecosystem models[J]. Global Biogeochemical Cycles, 2023, 37(4): e2023GB007696. DOI: 10.1029/2023GB007696
[109] [109] DONG J Q, LI L H, LI Y Z,et al. Inter-comparisons of mean, trend and interannual variability of global terrestrial gross primary production retrieved from remote sensing approach[J]. Science of The Total Environment, 2022, 822: 153343. DOI: 10.1016/j.scitotenv.2022.153343
[110] [110] WANG S, FU B J, WEI F L,et al. Drylands contribute disproportionately to observed global productivity increases[J]. Science Bulletin, 2023, 68(2): 224-232. DOI: 10.1016/j.scib.2023.01.014
[111] [111] KANNENBERG S A, ANDEREGG W R L, BARNES M L,et al. Dominant role of soil moisture in mediating carbon and water fluxes in dryland ecosystems[J]. Nature Geoscience, 2024, 17(1): 38-43. DOI: 10.1038/s41561-023-01351-8
[112] [112] WANG S, FU B J, WEI F L,et al. Drylands contribute disproportionately to observed global productivity increases[J]. Science Bulletin, 2023, 68(2): 224-232. DOI: 10.1016/j.scib.2023.01.014
[113] [113] LIU L B, GUDMUNDSSON L, HAUSER M,et al. Soil moisture dominates dryness stress on ecosystem production globally[J]. Nature Communications, 2020, 11: 4892. DOI: 10.1038/s41467-020-18631-1
[114] [114] LU H B, QIN Z C, LIN S R,et al. Large influence of atmospheric vapor pressure deficit on ecosystem production efficiency[J]. Nature Communications, 2022, 13: 1653. DOI: 10.1038/s41467-022-29009-w
[115] [115] LEBAUER D S, TRESEDER K K. Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed[J]. Ecology, 2008, 89(2): 371-379. DOI: 10.1890/06-2057.1
[116] [116] ZHANG H L, BAI J, SUN R,et al. An improved light use efficiency model by considering canopy nitrogen concentrations and multiple environmental factors[J]. Agricultural and Forest Meteorology, 2023, 332: 109359. DOI: 10.1016/j.agrformet.2023.109359
[117] [117] DU E Z, TERRER C, PELLEGRINI A F A,et al. Global patterns of terrestrial nitrogen and phosphorus limitation[J].Nature Geoscience, 2020, 13(3): 221-226. DOI: 10.1038/s41561-019-0530-4
[118] [118] HOU E Q, LUO Y Q, KUANG Y W,et al. Global metaanalysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems[J]. Nature Communications, 2020, 11: 637. DOI: 10.1038/s41467-020-14492-w
[119] [119] JIANG M K, CROUS K Y, CARRILLO Y,et al. Microbial competition for phosphorus limits the CO2 response of a mature forest[J]. Nature, 2024, 630(8017): 660-665. DOI: 10.1038/s41586-024-07491-0
[120] [120] CHEN B Z, FANG J C, PIAO S L,et al. A meta-analysis highlights globally widespread potassium limitation in terrestrial ecosystems[J]. New Phytologist, 2024, 241(1): 154-165. DOI: 10.1111/nph.19294
[121] [121] WANG F, FANG J C, YAO L,et al. Applications of land surface model to economic and environmental-friendly optimization of nitrogen fertilization and irrigation[J]. Heliyon, 2024, 10(6): e27549. DOI: 10.1016/j.heliyon.2024.e27549
Get Citation
Copy Citation Text
LIN Shangrong, TAO Yuan, ZHENG Yi, LI Xing. Remote Sensing Estimates of Terrestrial Gross Primary Production: Progress, Applications and Prospects[J]. Remote Sensing Technology and Application, 2025, 40(4): 851
Received: Dec. 25, 2024
Accepted: Aug. 26, 2025
Published Online: Aug. 26, 2025
The Author Email: LI Xing (lixing58@mail.sysu.edu.cn)