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The worst-hit areas of the 2008 Wenchuan Earthquake in southwest China were mountainous regions with high biodiversity and the impacted area is typical of other montane regions, with the need for detecting vegetation changes following the impacts of catastrophes. While the widely used remotely sensed vegetation indicator NDVI is available from various satellite data sources, these satellites are available for different monitoring periods and durations. Combining these datasets proved challenging to make a continuous characterization of vegetation change over an extended time period. In this study, compared with linear regression, multiple linear regression, and random forest, Convolutional Neural Networks (CNNs) performed best with an average R2 of 0.819 (leave-one-out cross-validation). Thus, the CNNs model was selected to establish the map of the overlapping periods of two remote-sensing products: SPOT-VGT NDVI and PROBA-V NDVI, to reconstruct a SPOT-VGT NDVI for the period from June 2014 to December 2018 in the worst-hit areas of the Wenchuan earthquake. We analyzed the original and reconstructed SPOT-VGT NDVI in the hard-hit areas of the Wenchuan earthquake from 1999 to 2018, and we concluded that NDVI showed an overall upward trend throughout the study period, but experienced a sharp decline in 2008 and reached its lowest value a year later (2009). Vegetation recovery was rapid from 2009 until 2011 after which, it returned to a pattern of slower natural growth (2012\u20132018). The Longmenshan fault zone experienced the greatest vegetation damage and initiation of recovery there has caused the overall regional average recovery to lag by 1\u20132 years. In areas where the land was denuded of vegetation (i.e., effectively all vegetation was stripped from the surface) after the earthquake, the damage exceeded what was experienced anywhere else in the entire study area, and by 2018 it remained unrestored. In the 15 years since the earthquake, the areas that were denuded were expected to recover to the level of restoration equivalent with the NDVI of 2007, as was the case in other earthquake-damaged regions. In addition to the earthquake and the immediate loss of vegetation, the Chinese government\u2019s Grain for Green Policy, the elevation ranges within the region, the forest\u2019s phenological conditions, and human activities all had an impact on vegetation recovery and restoration. The reconstructed NDVI provides a long-term continuous record, which contributes to the identifying changes that are improving predictive forest recovery models and to better vegetation management following catastrophic disturbances, such as earthquakes.<\/jats:p>","DOI":"10.3390\/rs15020299","type":"journal-article","created":{"date-parts":[[2023,1,4]],"date-time":"2023-01-04T06:33:44Z","timestamp":1672814024000},"page":"299","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Dynamic Characteristics of Vegetation Change Based on Reconstructed Heterogenous NDVI in Seismic Regions"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9376-3784","authenticated-orcid":false,"given":"Shaolin","family":"Wu","sequence":"first","affiliation":[{"name":"College of Architecture and Environment, Sichuan University, Chengdu 610065, China"},{"name":"Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9497-6658","authenticated-orcid":false,"given":"Baofeng","family":"Di","sequence":"additional","affiliation":[{"name":"Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu 610207, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8551-0461","authenticated-orcid":false,"given":"Susan L.","family":"Ustin","sequence":"additional","affiliation":[{"name":"Institute of the Environment, University of California Davis, Davis, CA 95616, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6439-6775","authenticated-orcid":false,"given":"Man Sing","family":"Wong","sequence":"additional","affiliation":[{"name":"Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China"},{"name":"Research Institute for Land and Space, The Hong Kong Polytechnic University, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8156-0875","authenticated-orcid":false,"given":"Basanta Raj","family":"Adhikari","sequence":"additional","affiliation":[{"name":"Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu 610207, China"},{"name":"Department of Civil Engineering, Pulchowk Campus, Tribhuvan University, Lalitpur 44600, Nepal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruixin","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Architecture and Environment, Sichuan University, Chengdu 610065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maoting","family":"Luo","sequence":"additional","affiliation":[{"name":"College of Architecture and Environment, Sichuan University, Chengdu 610065, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107683","DOI":"10.1016\/j.ecolind.2021.107683","article-title":"Changes in Ecosystem Services in a Montane Landscape Impacted by Major Earthquakes: A Case Study in Wenchuan Earthquake-Affected Area, China","volume":"126","author":"Duan","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Marusig, D., Petruzzellis, F., Tomasella, M., Napolitano, R., Altobelli, A., and Nardini, A. (2020). Correlation of Field-Measured and Remotely Sensed Plant Water Status as a Tool to Monitor the Risk of Drought-Induced Forest Decline. Forests, 11.","DOI":"10.3390\/f11010077"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1080\/20964471.2021.1974681","article-title":"Drying Conditions in Switzerland\u2014Indication from a 35-Year Landsat Time-Series Analysis of Vegetation Water Content Estimates to Support SDGs","volume":"5","author":"Poussin","year":"2021","journal-title":"Big Earth Data"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1007\/s11069-013-0757-0","article-title":"Revisions of the M 8.0 Wenchuan Earthquake Seismic Intensity Map Based on Co-Seismic Landslide Abundance","volume":"69","author":"Xu","year":"2013","journal-title":"Nat. Hazards"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1007\/s11069-011-0003-6","article-title":"Meta-Synthesis Pattern of Post-Disaster Recovery and Reconstruction: Based on Actual Investigation on 2008 Wenchuan Earthquake","volume":"60","author":"Xu","year":"2012","journal-title":"Nat. Hazards"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s11069-009-9392-1","article-title":"The Wenchuan Earthquake (May 12, 2008), Sichuan Province, China, and Resulting Geohazards","volume":"56","author":"Cui","year":"2011","journal-title":"Nat. Hazards"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"301","DOI":"10.3724\/SP.J.1145.2010.00301","article-title":"Reconstruction of the Wenchuan Earthquake-Damaged Ecosystems: Four Important Questions: Reconstruction of the Wenchuan Earthquake-Damaged Ecosystems: Four Important Questions","volume":"16","author":"Lu","year":"2010","journal-title":"Chin. J. Appl. Environ. Biol."},{"key":"ref_8","first-page":"617","article-title":"A discussion on the issues of the re-construction of ecological shelter zone on the upper reaches of the Yangtze River","volume":"24","author":"Pan","year":"2004","journal-title":"Acta Ecol. Sin."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2325","DOI":"10.1007\/s10346-018-1054-5","article-title":"Spatio-Temporal Evolution of Mass Wasting after the 2008 Mw 7.9 Wenchuan Earthquake Revealed by a Detailed Multi-Temporal Inventory","volume":"15","author":"Fan","year":"2018","journal-title":"Landslides"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3029","DOI":"10.1109\/JSTARS.2014.2327794","article-title":"Diagnosis of Vegetation Recovery in Mountainous Regions After the Wenchuan Earthquake","volume":"7","author":"Wang","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5785","DOI":"10.3390\/rs70505785","article-title":"Spatial Analysis of Wenchuan Earthquake-Damaged Vegetation in the Mountainous Basins and Its Applications","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_12","first-page":"71","article-title":"Vegetation index and its advances","volume":"21","author":"Guo","year":"2003","journal-title":"J. Arid Meteorol."},{"key":"ref_13","first-page":"327","article-title":"Advances in study on vegetation indices","volume":"13","author":"Tian","year":"1998","journal-title":"Adv. Earth Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/0034-4257(91)90018-2","article-title":"Relation between the Normalized Difference Vegetation Index and Ecological Variables","volume":"35","author":"Cihlar","year":"1991","journal-title":"Remote Sens. Environ."},{"key":"ref_15","first-page":"84","article-title":"Advances in Monitoring Vegetation and Land Use Dynamics in the Sahel","volume":"114","author":"Mbow","year":"2014","journal-title":"Geogr. Tidsskr. Dan. J. Geogr."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/j.tree.2005.05.011","article-title":"Using the Satellite-Derived NDVI to Assess Ecological Responses to Environmental Change","volume":"20","author":"Pettorelli","year":"2005","journal-title":"Trends Ecol. Evol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1111\/j.1365-2486.2007.01479.x","article-title":"Comparison of Phenology Trends by Land Cover Class: A Case Study in the Great Basin, USA","volume":"14","author":"Bradley","year":"2008","journal-title":"Glob. Change Biol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"28","DOI":"10.2307\/1942049","article-title":"Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types","volume":"5","author":"Gamon","year":"1995","journal-title":"Ecol. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/S0034-4257(02)00048-2","article-title":"A Generalized Soil-Adjusted Vegetation Index","volume":"82","author":"Gilabert","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.rse.2006.01.003","article-title":"Analysis of NDVI and Scaled Difference Vegetation Index Retrievals of Vegetation Fraction","volume":"101","author":"Jiang","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2691","DOI":"10.1080\/014311697217558","article-title":"Remote Estimation of Chlorophyll Content in Higher Plant Leaves","volume":"18","author":"Gitelson","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/0034-4257(94)90016-7","article-title":"On the Relationship between FAPAR and NDVI","volume":"49","author":"Myneni","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1641\/0006-3568(2004)054[0547:ACSMOG]2.0.CO;2","article-title":"A Continuous Satellite-Derived Measure of Global Terrestrial Primary Production","volume":"54","author":"Running","year":"2004","journal-title":"BioScience"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1109\/TGRS.1995.8746029","article-title":"The Interpretation of Spectral Vegetation Indexes","volume":"33","author":"Myneni","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/0273-1177(87)90291-2","article-title":"Relations between Canopy Reflectance, Photosynthesis and Transpiration: Links between Optics, Biophysics and Canopy Architecture","volume":"7","author":"Sellers","year":"1987","journal-title":"Adv. Space Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1080\/01431168508948283","article-title":"Canopy Reflectance, Photosynthesis and Transpiration","volume":"6","author":"Sellers","year":"1985","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.rse.2016.11.021","article-title":"Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function over Northern High Latitude Forests","volume":"190","author":"Jeong","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Yengoh, G.T., Dent, D., Olsson, L., Tengberg, A.E., and Tucker, C.J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: Current Status, Future Trends, and Practical Considerations, Springer.","DOI":"10.1007\/978-3-319-24112-8"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1046\/j.1365-2486.2003.00617.x","article-title":"Response of Terrestrial Carbon Uptake to Climate Interannual Variability in China","volume":"9","author":"Cao","year":"2003","journal-title":"Glob. Change Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/0034-4257(94)00066-V","article-title":"Global Net Primary Production: Combining Ecology and Remote Sensing","volume":"51","author":"Field","year":"1995","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.rse.2012.10.030","article-title":"Spatial and Temporal Variation in Primary Productivity (NDVI) of Coastal Alaskan Tundra: Decreased Vegetation Growth Following Earlier Snowmelt","volume":"129","author":"Gamon","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wang, R., Gamon, J.A., Emmerton, C.A., Li, H., Nestola, E., Pastorello, G.Z., and Menzer, O. (2016). Integrated Analysis of Productivity and Biodiversity in a Southern Alberta Prairie. Remote Sens., 8.","DOI":"10.3390\/rs8030214"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Albarakat, R., and Lakshmi, V. (2019). Comparison of Normalized Difference Vegetation Index Derived from Landsat, MODIS, and AVHRR for the Mesopotamian Marshes Between 2002 and 2018. Remote Sens., 11.","DOI":"10.3390\/rs11101245"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s42408-018-0021-9","article-title":"Examining Post-Fire Vegetation Recovery with Landsat Time Series Analysis in Three Western North American Forest Types","volume":"15","author":"Bright","year":"2019","journal-title":"Fire Ecol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1080\/01431160210144732","article-title":"Influence of Fire Severity on Plant Regeneration by Means of Remote Sensing Imagery","volume":"24","author":"Lloret","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1886","DOI":"10.1016\/j.rse.2009.04.004","article-title":"Evaluation of Earth Observation Based Long Term Vegetation Trends\u2014Intercomparing NDVI Time Series Trend Analysis Consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT Data","volume":"113","author":"Fensholt","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1175\/2009JCLI2900.1","article-title":"Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and Limitations","volume":"23","author":"Karnieli","year":"2010","journal-title":"J. Clim."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1111\/jvs.12780","article-title":"Post-fire Vegetation Recovery at Forest Sites Is Affected by Permafrost Degradation in the Da Xing\u2019an Mountains of Northern China","volume":"30","author":"Shi","year":"2019","journal-title":"J. Veg. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"7141","DOI":"10.1080\/01431160802238435","article-title":"Neutral Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS","volume":"29","author":"Brown","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.rse.2005.08.014","article-title":"Multi-Platform Comparisons of MODIS and AVHRR Normalized Difference Vegetation Index Data","volume":"99","author":"Gallo","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1080\/01431160903002409","article-title":"Comparison and Conversion of AVHRR GIMMS and SPOT VEGETATION NDVI Data in China","volume":"31","author":"Song","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.rse.2007.05.008","article-title":"Multiscale Geostatistical Analysis of AVHRR, SPOT-VGT, and MODIS Global NDVI Products","volume":"112","author":"Tarnavsky","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Ni, Z., Yang, Z., Li, W., Zhao, Y., and He, Z. (2019). Decreasing Trend of Geohazards Induced by the 2008 Wenchuan Earthquake Inferred from Time Series NDVI Data. Remote Sens., 11.","DOI":"10.3390\/rs11192192"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"111476","DOI":"10.1016\/j.rse.2019.111476","article-title":"Decadal Vegetation Succession from MODIS Reveals the Spatio-Temporal Evolution of Post-Seismic Landsliding after the 2008 Wenchuan Earthquake","volume":"236","author":"Yunus","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3495","DOI":"10.1080\/01431161003727630","article-title":"Estimating Wenchuan Earthquake Induced Landslides Based on Remote Sensing","volume":"31","author":"Zhang","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","unstructured":"Liu, X. (2015). Vegetation Indices Based on Different Sources of Remote Sensing Data Analyzed in Qinling Region. [Master\u2019s Thesis, Chang`an University]."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1007\/s11707-014-0428-9","article-title":"Trend Analysis for Evaluating the Consistency of Terra MODIS and SPOT VGT NDVI Time Series Products in China","volume":"9","author":"An","year":"2015","journal-title":"Front. Earth Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.rse.2004.03.014","article-title":"A Simple Method for Reconstructing a High-Quality NDVI Time-Series Data Set Based on the Savitzky\u2013Golay Filter","volume":"91","author":"Chen","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1627","DOI":"10.1021\/ac60214a047","article-title":"Smoothing and Differentiation of Data by Simplified Least Squares Procedures","volume":"36","author":"Savitzky","year":"1964","journal-title":"Anal. Chem."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.rse.2005.10.021","article-title":"Improved Monitoring of Vegetation Dynamics at Very High Latitudes: A New Method Using MODIS NDVI","volume":"100","author":"Beck","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1080\/014311600209814","article-title":"Reconstructing Cloudfree NDVI Composites Using Fourier Analysis of Time Series","volume":"21","author":"Roerink","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5228","DOI":"10.1109\/JSTARS.2017.2760202","article-title":"A Deep-Learning-Based Forecasting Ensemble to Predict Missing Data for Remote Sensing Analysis","volume":"10","author":"Das","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1016\/j.rse.2013.09.011","article-title":"Re-Greening Sahel: 30 Years of Remote Sensing Data and Field Observations (Mali, Niger)","volume":"140","author":"Dardel","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.rse.2005.10.002","article-title":"Multi-Sensor NDVI Data Continuity: Uncertainties and Implications for Vegetation Monitoring Applications","volume":"100","author":"Orr","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1109\/LGRS.2006.869966","article-title":"A New Method for Retrieving Band 6 of Aqua MODIS","volume":"3","author":"Wang","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1080\/15481603.2017.1382065","article-title":"Fusing MODIS with Landsat 8 Data to Downscale Weekly Normalized Difference Vegetation Index Estimates for Central Great Basin Rangelands, USA","volume":"55","author":"Boyte","year":"2018","journal-title":"GIScience Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"7126","DOI":"10.1109\/TGRS.2017.2742529","article-title":"Spatiotemporal Fusion of MODIS and Landsat-7 Reflectance Images via Compressed Sensing","volume":"55","author":"Wei","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MGRS.2015.2441912","article-title":"Missing Information Reconstruction of Remote Sensing Data: A Technical Review","volume":"3","author":"Shen","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_59","first-page":"102640","article-title":"High-Quality Vegetation Index Product Generation: A Review of NDVI Time Series Reconstruction Techniques","volume":"105","author":"Li","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"4274","DOI":"10.1109\/TGRS.2018.2810208","article-title":"Missing Data Reconstruction in Remote Sensing Image with a Unified Spatial\u2013Temporal\u2013Spectral Deep Convolutional Neural Network","volume":"56","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.isprsjprs.2020.02.008","article-title":"Thick Cloud and Cloud Shadow Removal in Multitemporal Imagery Using Progressively Spatio-Temporal Patch Group Deep Learning","volume":"162","author":"Zhang","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_62","first-page":"39","article-title":"Evaluation on sensibility of soil erosion of harder-hit area of Wenchuan Earthquake","volume":"1","author":"Xu","year":"2011","journal-title":"Soil Water Conserv. China"},{"key":"ref_63","unstructured":"Wolters, E., Dierckx, W., Iordache, M.-D., and Swinnen, E. PROBA-V Products User Manual v3.01."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1309","DOI":"10.1007\/s11069-013-0875-8","article-title":"Assessment of Spatio-Temporal Variations in Vegetation Recovery after the Wenchuan Earthquake Using Landsat Data","volume":"70","author":"Jiao","year":"2014","journal-title":"Nat. Hazards"},{"key":"ref_65","first-page":"1570","article-title":"Vegetation Change of Yamzho Yumco Basin in Southern Tibet Based on SPOT-VGT NDVI","volume":"30","author":"Yu","year":"2010","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_66","unstructured":"Sun, J. (2007). 1982~2000 Vegetation Change in China and Response of Typical Areas with Climatic Factors. [Master\u2019s Thesis, Nanjing University of Information Science & Technology]."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"111716","DOI":"10.1016\/j.rse.2020.111716","article-title":"Deep Learning in Environmental Remote Sensing: Achievements and Challenges","volume":"241","author":"Yuan","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.neucom.2017.04.083","article-title":"Early Fire Detection Using Convolutional Neural Networks during Surveillance for Effective Disaster Management","volume":"288","author":"Muhammad","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.rse.2018.04.050","article-title":"Urban Land-Use Mapping Using a Deep Convolutional Neural Network with High Spatial Resolution Multispectral Remote Sensing Imagery","volume":"214","author":"Huang","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Shimobaba, T., Kakue, T., and Ito, T. (2018, January 13\u201315). Convolutional Neural Network-Based Regression for Depth Prediction in Digital Holography. Proceedings of the 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), Cairns, Qld, Australia.","DOI":"10.1109\/ISIE.2018.8433651"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1016\/j.envpol.2018.09.052","article-title":"A Nonparametric Approach to Filling Gaps in Satellite-Retrieved Aerosol Optical Depth for Estimating Ambient PM2.5 Levels","volume":"243","author":"Zhang","year":"2018","journal-title":"Environ. Pollut."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1080\/0143116021000020144","article-title":"Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the 1990s","volume":"24","author":"Stow","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/S0034-4257(00)00150-4","article-title":"Optical\u2013Biophysical Relationships of Vegetation Spectra without Background Contamination","volume":"74","author":"Gao","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_74","unstructured":"Wan, X. (2003). Vegetation Restoration and Its Effects on Soil after Converting Agricultural Lands to Forest. [Master\u2019s Thesis, Sichuan Agricultural University]."},{"key":"ref_75","first-page":"1","article-title":"Relationship Between Land Use and Soil Erosion in Karst Area-A Case Study of Bijie Experimental Area","volume":"24","author":"Xie","year":"2017","journal-title":"Res. Soil Water Conserv."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.rse.2015.03.031","article-title":"Evaluating Temporal Consistency of Long-Term Global NDVI Datasets for Trend Analysis","volume":"163","author":"Tian","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_77","first-page":"64","article-title":"Temporal and Spatial Variation Characteristics of Vegetation Restoration Based on MODIS-NDVI Wenchuan Earthquake Region in Ten Years","volume":"19","author":"Hong","year":"2019","journal-title":"Sci. Technol. Eng."},{"key":"ref_78","first-page":"3479","article-title":"Spatial-temporal process and characteristics of vegetation recovery after Wenchuan earthquake: A case study in Longxi River basin of Dujiangyan, China","volume":"27","author":"Li","year":"2016","journal-title":"Chin. J. Appl. Ecol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1507","DOI":"10.1007\/s11629-014-3080-7","article-title":"Combined Impacts of Antecedent Earthquakes and Droughts on Disastrous Debris Flows","volume":"11","author":"Chen","year":"2014","journal-title":"J. Mt. Sci."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"12532","DOI":"10.1038\/s41598-019-48986-5","article-title":"Assessing Susceptibility of Debris Flow in Southwest China Using Gradient Boosting Machine","volume":"9","author":"Di","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"8757","DOI":"10.3390\/rs70708757","article-title":"Evaluating the Vegetation Recovery in the Damage Area of Wenchuan Earthquake Using MODIS Data","volume":"7","author":"Jiang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_82","unstructured":"Cui, P. (2014). Atlas of Mountain Hazards and Soil Erosion in the Upper Yangtze, Science Press."},{"key":"ref_83","first-page":"18","article-title":"Detailed Inventory of Landslides Triggered by the 2008 Wenchuan Earthquake and Its Comparison with Other Earthquake Events in the World","volume":"30","author":"Xu","year":"2012","journal-title":"Sci. Technol. Rev."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1007\/s11069-010-9511-z","article-title":"Evaluating the Vegetation Destruction and Recovery of Wenchuan Earthquake Using MODIS Data","volume":"54","author":"Liu","year":"2010","journal-title":"Nat. Hazards"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.ecoleng.2012.03.012","article-title":"Destruction of Vegetation Due to Geo-Hazards and Its Environmental Impacts in the Wenchuan Earthquake Areas","volume":"44","author":"Cui","year":"2012","journal-title":"Ecol. Eng."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.ecolind.2017.12.006","article-title":"Decreased Post-Seismic Landslides Linked to Vegetation Recovery after the 2008 Wenchuan Earthquake","volume":"89","author":"Yang","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"107317","DOI":"10.1016\/j.geomorph.2020.107317","article-title":"The Long-Term Evolution of Landslide Activity near the Epicentral Area of the 2008 Wenchuan Earthquake in China","volume":"367","author":"Chen","year":"2020","journal-title":"Geomorphology"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Zhong, C., Li, C., Gao, P., and Li, H. (2021). Discovering Vegetation Recovery and Landslide Activities in the Wenchuan Earthquake Area with Landsat Imagery. Sensors, 21.","DOI":"10.3390\/s21155243"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"5397","DOI":"10.3390\/s8095397","article-title":"Long-Term Satellite NDVI Data Sets: Evaluating Their Ability to Detect Ecosystem Functional Changes in South America","volume":"8","author":"Baldi","year":"2008","journal-title":"Sensors"},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"106989","DOI":"10.1016\/j.geomorph.2019.106989","article-title":"Declining Geohazard Activity with Vegetation Recovery during First Ten Years after the 2008 Wenchuan Earthquake","volume":"352","author":"Shen","year":"2020","journal-title":"Geomorphology"},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.1007\/s11629-017-4375-1","article-title":"Debris Flow Susceptibility Analysis Based on the Combined Impacts of Antecedent Earthquakes and Droughts: A Case Study for Cascade Hydropower Stations in the Upper Yangtze River, China","volume":"14","author":"Hu","year":"2017","journal-title":"J. Mt. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/299\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:58:46Z","timestamp":1760119126000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/2\/299"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,4]]},"references-count":91,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,1]]}},"alternative-id":["rs15020299"],"URL":"https:\/\/doi.org\/10.3390\/rs15020299","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,4]]}}}