- 1.
Adhikari H, Heiskanen J, Maeda E E and Pellikka P K E. 2016. The effect of topographic normalization on fractional tree cover mapping in tropical mountains: an assessment based on seasonal Landsat time series. International Journal of Applied Earth Observation and Geoinformation, 52: 20-31
- 2.
Betthäuser B A, Bach-Mortensen A M and Engzell P. 2023. A systematic review and meta-analysis of the evidence on learning during the COVID-19 pandemic. Nature Human Behaviour, 7(3): 375-385
- 3.
Chi H J, Yan K, Yang K, Du S Y, Li H L, Qi J B and Zhou W. 2022. Evaluation of topographic correction models based on 3-D radiative transfer simulation. IEEE Geoscience and Remote Sensing Letters, 19: 1-5
- 4.
Dash J and Ogutu B O. 2016. Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems. Progress in Physical Geography: Earth and Environment, 40(2): 322-351
- 5.
Ding Y F, You H J, Zang H, Chen S J, Xu B and Sun T. 2018. Topographic correction method for high-resolution remote sensing images. Journal of Beijing University of Aeronautics and Astronautics, 44(1): 27-35
- 6.
Duan S B and Yan G J. 2007. A review of models for topographic correction of remotely sensed images in mountainous area. Journal of Beijing Normal University (Natural Science), 43(3): 362-366
- 7.
Dymond J R and Shepherd J D. 1999. Correction of the topographic effect in remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 37(5): 2618-2619
- 8.
Egger M, Smith G D and Phillips A N. 1997. Meta-analysis: principles and procedures. BMJ, 315(7121): 1533-1537
- 9.
Ekstrand S. 1996. Landsat TM-based forest damage assessment: correction for topographic effects. Photogrammetric Engineering and Remote Sensing, 62(2): 151-161
- 10.
Fan W L, Chen J M, Ju W M and Zhu G L. 2014a. GOST: a geometric-optical model for sloping terrains. IEEE Transactions on Geoscience and Remote Sensing, 52(9): 5469-5482
- 11.
Fan W L, Li J, Liu Q H, Zhang Q, Yin G F, Li A N, Zeng Y L, Xu B D, Xu X J, Zhou G M and Du H Q. 2018. Topographic correction of forest image data based on the canopy reflectance model for sloping terrains in multiple forward mode. Remote Sensing, 10(5): 717
- 12.
Fan Y C, Koukal T and Weisberg P J. 2014b. A sun-crown-sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 96: 94-105
- 13.
Feng R T, Du Q Y, Luo H, Shen H F, Li X H and Liu B. 2021. A registration algorithm based on optical flow modification for multi-temporal remote sensing images covering the complex-terrain region. National Remote Sensing Bulletin, 25(2): 630-640
- 14.
Field A P and Gillett R. 2010. How to do a meta‐analysis. British Journal of Mathematical and Statistical Psychology, 63(3): 665-694
- 15.
Ganguly S, Nemani R R, Zhang G, Hashimoto H, Milesi C, Michaelis A, Wang W L, Votava P, Samanta A, Melton F, Dungan J L, Vermote E, Gao F, Knyazikhin Y and Myneni R B. 2012. Generating global Leaf Area Index from Landsat: algorithm formulation and demonstration. Remote Sensing of Environment, 122: 185-202
- 16.
Gao Y N and Zhang W C. 2008. Comparison test and research progress of topographic correction on remotely sensed data. Geographical Research, 27(2): 467-477
- 17.
Gao Y N and Zhang W C. 2009. A simple empirical topographic correction method for ETM+ imagery. International Journal of Remote Sensing, 30(9): 2259-2275
- 18.
Gu D G and Gillespie A. 1998. Topographic normalization of landsat TM images of forest based on subpixel sun-canopy-sensor geometry. Remote Sensing of Environment, 64(2): 166-175
- 19.
Hantson S and Chuvieco E. 2011. Evaluation of different topographic correction methods for Landsat imagery. International Journal of Applied Earth Observation and Geoinformation, 13(5): 691-700
- 20.
Holben B N and Justice C O. 1980. The topographic effect on spectral response from nadir-pointing sensors. Photogrammetric Engineering and Remote Sensing, 46(9): 1191-1200
- 21.
Huang J L, Ju W M, Zheng G and Kang T T. 2013. Estimation of forest aboveground biomass using high spatial resolution remote sensing imagery. Acta Ecologica Sinica, 33(20): 6497-6508
- 22.
Hurni K, van den Hoek J and Fox J. 2019. Assessing the spatial, spectral, and temporal consistency of topographically corrected Landsat time series composites across the mountainous forests of Nepal. Remote Sensing of Environment, 231: 111225
- 23.
Immerzeel W W, Lutz A F, Andrade M, Bahl A, Biemans H, Bolch T, Hyde S, Brumby S, Davies B J, Elmore A C, Emmer A, Feng M, Fernández A, Haritashya U, Kargel J S, Koppes M, Kraaijenbrink P D A, Kulkarni A V, Mayewski P A, Nepal S, Pacheco P, Painter T H, Pellicciotti F, Rajaram H, Rupper S, Sinisalo A, Shrestha A B, Viviroli D, Wada Y, Xiao C, Yao T and Baillie J E M. 2020. Importance and vulnerability of the world’s water towers. Nature, 577(7790): 364-369
- 24.
Jin H A, Li A N, Xu W X, Xiao Z Q, Jiang J Y and Xue H Z. 2019. Evaluation of topographic effects on multiscale leaf area index estimation using remotely sensed observations from multiple sensors. ISPRS Journal of Photogrammetry and Remote Sensing, 154: 176-188
- 25.
Kobayashi S and Sanga-Ngoie K. 2008. The integrated radiometric correction of optical remote sensing imageries. International Journal of Remote Sensing, 29(20): 5957-5985
- 26.
Li F, Jupp D L B and Thankappan M. 2011. Using high resolution DSM data to correct the terrain illumination effect in Landsat data//Proceedings of the 19th International Congress on Modelling and Simulation. Perth: [s.n.]: 2402-2408
- 27.
Li F Q, Jupp D L B, Thankappan M, Lymburner L, Mueller N, Lewis A and Held A. 2012. A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain. Remote Sensing of Environment, 124: 756-770
- 28.
Li L, Liu Y, Zhu H H, Ying S, Luo Q Y, Luo H, Kuai X, Xia H and Shen H. 2017. A bibliometric and visual analysis of global geo-ontology research. Computers and Geosciences, 99: 1-8
- 29.
Li T, Chen T Y and Hui B H. 2022. Economic value of forest ecosystem services in Huangshan City based on meta-analysis. Scientia Geographica Sinica, 42(12): 2179-2188
- 30.
Li W J, Dong R M, Fu H H, Wang J, Yu L and Gong P. 2020. Integrating Google Earth imagery with Landsat data to improve 30-m resolution land cover mapping. Remote Sensing of Environment, 237: 111563
- 31.
Lin X W, Wen J G, Wu S B, Hao D L, Xiao Q and Liu Q H. 2020. Advances in topographic correction methods for optical remote sensing imageries. National Remote Sensing Bulletin, 24(8): 958-974
- 32.
Luisa E M, Frédéric Baret and Marie W. 2008. Slope correction for LAI estimation from gap fraction measurements. Agricultural and Forest Meteorology, 148(10): 1553-1562
- 33.
Ma L, Liu Y, Zhang X L, Ye Y X, Yin G F and Johnson B A. 2019. Deep learning in remote sensing applications: a meta-analysis and review. ISPRS Journal of Photogrammetry and Remote Sensing, 152: 166-177
- 34.
Messerli B, Viviroli D and Weingartner R. 2004. Mountains of the world: water towers for the 21st century. Ambio, 13: 29-34
- 35.
Meybeck M, Green P and Vörösmarty C. 2001. A new typology for mountains and other relief classes. Mountain Research and Development, 21(1): 34-45 [DOI: [0034:ANTFMA]2.0.CO;2]
- 36.
Myneni R B, Hoffman S, Knyazikhin Y, Privette J L, Glassy J, Tian Y, Wang Y, Song X, Zhang Y, Smith G R, Lotsch A, Friedl M, Morisette J T, Votava P, Nemani R R and Running S W. 2002. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sensing of Environment, 83(1/2): 214-231
- 37.
Nichol J, Hang L K and Sing W M. 2006. Empirical correction of low Sun angle images in steeply sloping terrain: a slope-matching technique. International Journal of Remote Sensing, 27(3): 629-635
- 38.
Pepin N, Bradley R S, Diaz H F, Baraer M, Caceres E B, Forsythe N, Fowler H, Greenwood G, Hashmi M Z, Liu X D, Miller J R, Ning L, Ohmura A, Palazzi E, Rangwala I, Schöner W, Severskiy I, Shahgedanova M, Wang M B, Williamson S N and Yang D Q. 2015. Elevation-dependent warming in mountain regions of the world. Nature Climate Change, 5: 424-430
- 39.
Proy C, Tanré D and Deschamps P Y. 1989. Evaluation of topographic effects in remotely sensed data. Remote Sensing of Environment, 30(1): 21-32
- 40.
Rahbek C, Borregaard M K, Colwell R K, Dalsgaard Bo, Holt B G, Morueta-Holme N, Nogues-Bravo D, Whittaker R J and Fjeldså J. 2019. Humboldt’s enigma: what causes global patterns of mountain biodiversity? Science, 365(6458): 1108-1113
- 41.
Reese H and Olsson H. 2011. C-correction of optical satellite data over alpine vegetation areas: a comparison of sampling strategies for determining the empirical c-parameter. Remote Sensing of Environment, 115(6): 1387-1400
- 42.
Schaaf C B, Li X W and Strahler A H. 1994. Topographic effects on bidirectional and hemispherical reflectances calculated with a geometric-optical canopy model. IEEE Transactions on Geoscience and Remote Sensing, 32(6): 1186-1193
- 43.
Schleppi P, Conedera M, Sedivy I and Thimonier A. 2007. Correcting non-linearity and slope effects in the estimation of the leaf area index of forests from hemispherical photographs. Agricultural and Forest Meteorology, 144(3/4): 236-242
- 44.
Shen H F and Zhang L P. 2023. Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems. Science China Earth Sciences, 66(3): 568-582
- 45.
Smith J A,Lin T L and Ranson K J. 1980. The lambertian assumption and Landsat data. Photogrammetric Engineering and Remote Sensing, 46(9): 1183-1189
- 46.
Soenen S A, Peddle D R and Coburn C A. 2005. SCS+C: a modified Sun-canopy-sensor topographic correction in forested terrain. IEEE Transactions on Geoscience and Remote Sensing, 43(9): 2148-2159
- 47.
Soenen S A, Peddle D R, Coburn C A, Hall R J and Hall F G. 2008. Improved topographic correction of forest image data using a 3‐D canopy reflectance model in multiple forward mode. International Journal of Remote Sensing, 29(4): 1007-1027
- 48.
Sola I, González-Audícana M and Álvarez-Mozos J. 2016. Multi-criteria evaluation of topographic correction methods. Remote Sensing of Environment, 184: 247-262
- 49.
Sola I, González-Audícana M, Álvarez-Mozos J and Torres J L. 2014. Synthetic images for evaluating topographic correction algorithms. IEEE Transactions on Geoscience and Remote Sensing, 52(3): 1799-1810
- 50.
Teillet P M, Guindon B and Goodenough D G. 1982. On the slope-aspect correction of multispectral scanner data. Canadian Journal of Remote Sensing, 8(2): 84-106
- 51.
Vögtli M, Schläpfer D, Richter R, Hueni A, Schaepman M E and Kneubühler M. 2021. About the transferability of topographic correction methods from spaceborne to airborne optical data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 1348-1362
- 52.
Wang S N and Li A N. 2012. The progress in the study of topographic radiometric correction models. Remote Sensing for Land and Resources, (2): 1-6
- 53.
Wen J G. 2008. Study on retrieval of land surface BRDF/albedo and its scale effects in complex terrain. Beijing: Institute of Remote Sensing Applications, Chinese Academy of Sciences
- 54.
Wen J G, Liu Q, Tang Y, Dou B C, You D Q, Xiao Q, Liu Q H and Li X W. 2015. Modeling land surface reflectance coupled BRDF for HJ-1/CCD data of rugged terrain in Heihe River Basin, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(4): 1506-1518
- 55.
Wen J G, Liu Q, Xiao Q, Liu Q H, You D Q, Hao D L, Wu S B and Lin X W. 2018. Characterizing land surface anisotropic reflectance over rugged terrain: a review of concepts and recent developments. Remote Sensing, 10(3): 370
- 56.
Wen J G, Liu Q H, Liu Q, Xiao Q and Li X W. 2009. Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain, China. International Journal of Remote Sensing, 30(11): 2875-2896
- 57.
Xiao J F, Chevallier F, Gomez C, Guanter L, Hicke J A, Huete A R, Ichii K, Ni W J, Pang Y, Rahman A F, Sun G Q, Yuan W P, Zhang L and Zhang X Y. 2019. Remote sensing of the terrestrial carbon cycle: a review of advances over 50 years. Remote Sensing of Environment, 233: 111383
- 58.
Xie J L, Wang C J, Ma D J, Chen R, Xie Q Y, Xu B D, Zhao W and Yin G F. 2022. Generating spatiotemporally continuous grassland aboveground biomass on the Tibetan Plateau through PROSAIL model inversion on Google Earth Engine. IEEE Transactions on Geoscience and Remote Sensing, 60: 1-10
- 59.
Yin G F, Cao B, Li J, Fan W L, Zeng Y L, Xu B D and Zhao W. 2020. Path length correction for improving leaf area index measurements over sloping terrains: a deep analysis through computer simulation. IEEE Transactions on Geoscience and Remote Sensing, 58(7): 4573-4589
- 60.
Yin G F, Li A N, Wu S B, Fan W L, Zeng Y L, Yan K, Xu B D, Li J and Liu Q H. 2018. PLC: a simple and semi-physical topographic correction method for vegetation canopies based on path length correction. Remote Sensing of Environment, 215: 184-198
- 61.
Yin G F, Li A N, Zhao W, Jin H A, Bian J H and Wu S B. 2017. Modeling canopy reflectance over sloping terrain based on path length correction. IEEE Transactions on Geoscience and Remote Sensing, 55(8): 4597-4609
- 62.
Yu W T, Li J, Liu Q H, Yin G F, Zeng Y L, Lin S R and Zhao J. 2020. A simulation-based analysis of topographic effects on lai inversion over sloped terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13: 794-806
- 63.
Zhang W C and Gao Y N. 2011. Topographic correction algorithm for remotely sensed data accounting for indirect irradiance. International Journal of Remote Sensing, 32(7): 1807-1824
- 64.
Zhang X Y and Kondragunta S. 2006. Estimating forest biomass in the USA using generalized allometric models and MODIS land products. Geophysical Research Letters, 33(9): L09402
- 65.
Zhang Y L, Li X, Wen J G, Liu Q H and Yan G J. 2015. Improved topographic normalization for Landsat TM images by introducing the MODIS surface BRDF. Remote Sensing, 7(6): 6558-6575
- 66.
Zheng D L, Rademacher J, Chen J Q, Crow T, Bresee M, Le Moine J and Ryu S R. 2004. Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA. Remote Sensing of Environment, 93(3): 402-411
- 67.
Zhu Z, Wulder M A, Roy D P, Woodcock C E, Hansen M C, Radeloff V C, Healey S P, Schaaf C, Hostert P, Strobl P, Pekel J F, Lymburner L, Pahlevan N and Scambos T A. 2019. Benefits of the free and open Landsat data policy. Remote Sensing of Environment, 224: 382-385