{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T20:47:54Z","timestamp":1769028474025,"version":"3.49.0"},"reference-count":99,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T00:00:00Z","timestamp":1729555200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"CNPq (Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico)","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"FAPESP (Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo)","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"CAPES (Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior\u2014Brasil)","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"University of Manchester","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"University of Manchester","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"University of Manchester","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"University of Manchester","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"University of Manchester","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"University of Manchester","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"University of Manchester","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"University of Manchester","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"University of Manchester","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"University of Manchester","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"University of Manchester","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"University of Manchester","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"University of Manchester","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"National Council for Scientific and Technological Development\u2014CNPq","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"CNPq","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"CNPq","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"CNPq","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"CNPq","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"CNPq","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"CNPq","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"CNPq","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"CNPq","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"CNPq","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"CNPq","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"CNPq","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"CNPq","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"CNPq","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"CNPq","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"CNPq","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"CNPq","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"CNPq","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"CNPq","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"CNPq","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"CNPq","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"CNPq","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"CNPq","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"CNPq","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"CNPq","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"CNPq","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"CNPq","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"FAPESP ARBOLES project","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"FAPESP ARBOLES project","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"FAPESP ARBOLES project","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"FAPESP ARBOLES project","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"FAPESP ARBOLES project","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"FAPESP ARBOLES project","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"FAPESP ARBOLES project","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"FAPESP ARBOLES project","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"FAPESP ARBOLES project","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"FAPESP ARBOLES project","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"FAPESP ARBOLES project","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"FAPESP ARBOLES project","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"FAPESP ARBOLES project","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"project Environmental Satellite Monitoring in the Amazon Biome (MSA-BNDES)","award":["14209291"],"award-info":[{"award-number":["14209291"]}]},{"name":"Amazon Fund","award":["140502\/2016-5"],"award-info":[{"award-number":["140502\/2016-5"]}]},{"name":"Amazon Fund","award":["301486\/2017-4"],"award-info":[{"award-number":["301486\/2017-4"]}]},{"name":"Amazon Fund","award":["141035\/2021-8"],"award-info":[{"award-number":["141035\/2021-8"]}]},{"name":"Amazon Fund","award":["2017\/22269-2"],"award-info":[{"award-number":["2017\/22269-2"]}]},{"name":"Amazon Fund","award":["2018\/18416-2"],"award-info":[{"award-number":["2018\/18416-2"]}]},{"name":"Amazon Fund","award":["2020\/06734-0"],"award-info":[{"award-number":["2020\/06734-0"]}]},{"name":"Amazon Fund","award":["001"],"award-info":[{"award-number":["001"]}]},{"name":"Amazon Fund","award":["401741\/2023-0"],"award-info":[{"award-number":["401741\/2023-0"]}]},{"name":"Amazon Fund","award":["305054\/2016-3"],"award-info":[{"award-number":["305054\/2016-3"]}]},{"name":"Amazon Fund","award":["314416\/2020-0"],"award-info":[{"award-number":["314416\/2020-0"]}]},{"name":"Amazon Fund","award":["307792\/2021-8"],"award-info":[{"award-number":["307792\/2021-8"]}]},{"name":"Amazon Fund","award":["18\/15001-6"],"award-info":[{"award-number":["18\/15001-6"]}]},{"name":"Amazon Fund","award":["14209291"],"award-info":[{"award-number":["14209291"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Integrating Light Detection And Ranging (LiDAR) and Hyperspectral Imaging (HSI) enhances the assessment of tropical forest degradation and regeneration, which is crucial for conservation and climate mitigation strategies. This study optimized procedures using combined airborne LiDAR, HSI data, and machine learning algorithms across 12 sites in the Brazilian Amazon, covering various environmental and anthropogenic conditions. Four forest classes (undisturbed, degraded, and two stages of second-growth) were identified using Landsat time series (1984\u20132017) and auxiliary data. Metrics from 600 samples were analyzed with three classifiers: Random Forest, Stochastic Gradient Boosting, and Support Vector Machine. The combination of LiDAR and HSI data improved classification accuracy by up to 12% compared with single data sources. The most decisive metrics were LiDAR-based upper canopy cover and HSI-based absorption bands in the near-infrared and shortwave infrared. LiDAR produced significantly fewer errors for discriminating second-growth from old-growth forests, while HSI had better performance to discriminate degraded from undisturbed forests. HSI-only models performed similarly to LiDAR-only models (mean F1 of about 75% for both data sources). The results highlight the potential of integrating LiDAR and HSI data to improve our understanding of forest dynamics in the context of nature-based solutions to mitigate climate change impacts.<\/jats:p>","DOI":"10.3390\/rs16213935","type":"journal-article","created":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T11:31:57Z","timestamp":1729596717000},"page":"3935","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Advancing Forest Degradation and Regeneration Assessment Through Light Detection and Ranging and Hyperspectral Imaging Integration"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8140-2903","authenticated-orcid":false,"given":"Catherine Torres de","family":"Almeida","sequence":"first","affiliation":[{"name":"Faculty of Agricultural Sciences of Vale do Ribeira, S\u00e3o Paulo State University\u2014UNESP, Registro 11900-000, SP, Brazil"},{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8313-0497","authenticated-orcid":false,"given":"L\u00eanio Soares","family":"Galv\u00e3o","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4221-1039","authenticated-orcid":false,"given":"Jean Pierre H. B.","family":"Ometto","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2585-5198","authenticated-orcid":false,"given":"Aline Daniele","family":"Jacon","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1319-7717","authenticated-orcid":false,"given":"Francisca Rocha de Souza","family":"Pereira","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"given":"Luciane Yumie","family":"Sato","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1052-5551","authenticated-orcid":false,"given":"Celso Henrique Leite","family":"Silva-Junior","sequence":"additional","affiliation":[{"name":"Instituto de Pesquisa Ambiental da Amaz\u00f4nia (IPAM), SCN 211, Bloco B, Sala 201, Bras\u00edlia 70836-520, GO, Brazil"},{"name":"Graduate Program in Biodiversity Conservation, Federal University of Maranh\u00e3o, S\u00e3o Lu\u00eds 65080-805, MA, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8245-4062","authenticated-orcid":false,"given":"Pedro H. S.","family":"Brancalion","sequence":"additional","affiliation":[{"name":"Department of Forest Sciences, \u201cLuiz de Queiroz\u201d College of Agriculture, University of S\u00e3o Paulo, Piracicaba 13418-900, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-6708","authenticated-orcid":false,"given":"Luiz Eduardo Oliveira e Cruz de","family":"Arag\u00e3o","sequence":"additional","affiliation":[{"name":"National Institute for Space Research\u2014INPE, Caixa Postal 515, S\u00e3o Jos\u00e9 dos Campos 12227-010, SP, Brazil"},{"name":"College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11645","DOI":"10.1073\/pnas.1710465114","article-title":"Natural Climate Solutions","volume":"114","author":"Griscom","year":"2017","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1111\/1365-2664.13725","article-title":"Guidance for Successful Tree Planting Initiatives","volume":"57","author":"Brancalion","year":"2020","journal-title":"J. Appl. Ecol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"38","DOI":"10.5751\/ES-09615-220438","article-title":"Forest Ecosystem-Service Transitions: The Ecological Dimensions of the Forest Transition","volume":"22","author":"Wilson","year":"2017","journal-title":"Ecol. Soc."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Frolking, S., Palace, M.W., Clark, D.B., Chambers, J.Q., Shugart, H.H., and Hurtt, G.C. (2009). Forest Disturbance and Recovery: A General Review in the Context of Spaceborne Remote Sensing of Impacts on Aboveground Biomass and Canopy Structure. J. Geophys. Res. Biogeosci., 114.","DOI":"10.1029\/2008JG000911"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.rse.2002.09.002","article-title":"Classifying Successional Forests Using Landsat Spectral Properties and Ecological Characteristics in Eastern Amaz\u00f4nia","volume":"87","author":"Vieira","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1080\/15481603.2014.972866","article-title":"Spectral\/Textural Attributes from ALI\/EO-1 for Mapping Primary and Secondary Tropical Forests and Studying the Relationships with Biophysical Parameters","volume":"51","author":"Camila","year":"2014","journal-title":"GIScience Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1147","DOI":"10.1126\/science.228.4704.1147","article-title":"Imaging Spectrometry for Earth Remote Sensing","volume":"228","author":"Goetz","year":"1985","journal-title":"Science"},{"key":"ref_8","first-page":"8","article-title":"dos Possibilities of Discriminating Tropical Secondary Succession in Amaz\u00f4nia Using Hyperspectral and Multiangular CHRIS\/PROBA Data","volume":"11","author":"Ponzoni","year":"2009","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1109\/TGRS.2012.2199323","article-title":"Tree Species Discrimination in Tropical Forests Using Airborne Imaging Spectroscopy","volume":"51","author":"Asner","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Baldeck, C.A., Asner, G.P., Martin, R.E., Anderson, C.B., Knapp, D.E., Kellner, J.R., and Wright, S.J. (2015). Operational Tree Species Mapping in a Diverse Tropical Forest with Airborne Imaging Spectroscopy. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0118403"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.isprsjprs.2016.06.007","article-title":"Mapping of Land Cover in Northern California with Simulated Hyperspectral Satellite Imagery","volume":"119","author":"Clark","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.isprsjprs.2014.08.015","article-title":"Spectroscopic Remote Sensing of Plant Stress at Leaf and Canopy Levels Using the Chlorophyll 680nm Absorption Feature with Continuum Removal","volume":"97","author":"Sanches","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S78","DOI":"10.1016\/j.rse.2008.10.018","article-title":"Characterizing Canopy Biochemistry from Imaging Spectroscopy and Its Application to Ecosystem Studies","volume":"113","author":"Kokaly","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.3390\/rs6031803","article-title":"Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX)","volume":"6","author":"Schepers","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.isprsjprs.2017.07.006","article-title":"Spectral Analysis of Amazon Canopy Phenology during the Dry Season Using a Tower Hyperspectral Camera and Modis Observations","volume":"131","author":"Hilker","year":"2017","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2350","DOI":"10.1016\/j.rse.2011.04.035","article-title":"On Intra-Annual EVI Variability in the Dry Season of Tropical Forest: A Case Study with MODIS and Hyperspectral Data","volume":"115","author":"Roberts","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2003.11.018","article-title":"Hyperion, IKONOS, ALI, and ETM+ Sensors in the Study of African Rainforests","volume":"90","author":"Thenkabail","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1046\/j.1466-822x.2002.00303.x","article-title":"Lidar Remote Sensing of Above-Ground Biomass in Three Biomes","volume":"11","author":"Lefsky","year":"2002","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"111194","DOI":"10.1016\/j.rse.2019.05.013","article-title":"Mapping Forest Successional Stages in the Brazilian Amazon Using Forest Heights Derived from TanDEM-X SAR Interferometry","volume":"232","author":"Bispo","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.rse.2012.01.012","article-title":"LIDAR Remote Sensing for Secondary Tropical Dry Forest Identification","volume":"121","author":"Castillo","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"111323","DOI":"10.1016\/j.rse.2019.111323","article-title":"Combining LiDAR and Hyperspectral Data for Aboveground Biomass Modeling in the Brazilian Amazon Using Different Regression Algorithms","volume":"232","author":"Almeida","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_22","first-page":"101908","article-title":"Mapping Tropical Dry Forest Age Using Airborne Waveform LiDAR and Hyperspectral Metrics","volume":"83","author":"Sun","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1038\/s41893-018-0175-0","article-title":"Spatially Explicit Valuation of the Brazilian Amazon Forest\u2019s Ecosystem Services","volume":"1","author":"Strand","year":"2018","journal-title":"Nat. Sustain."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Alencar, A., Shimbo, J.Z., Lenti, F., Marques, C.B., Zimbres, B., Rosa, M., Arruda, V., Castro, I., Fernandes, M., and Alencar, I. (2020). Mapping Three Decades of Changes in the Brazilian Savanna Native Vegetation Using Landsat Data Processed in the Google Earth Engine Platform. Remote Sens., 12.","DOI":"10.3390\/rs12060924"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1386","DOI":"10.1111\/j.1523-1739.2009.01333.x","article-title":"A Contemporary Assessment of Change in Humid Tropical Forests","volume":"23","author":"Asner","year":"2009","journal-title":"Conserv. Biol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1111\/geb.12394","article-title":"Pan-Tropical Hinterland Forests: Mapping Minimally Disturbed Forests","volume":"25","author":"Tyukavina","year":"2016","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Jacon, A.D., Galv\u00e3o, L.S., Martins-Neto, R.P., Crespo-Peremarch, P., Arag\u00e3o, L.E.O.C., Ometto, J.P., Anderson, L.O., Vedovato, L.B., Silva-Junior, C.H.L., and Lopes, A.P. (2024). Characterizing Canopy Structure Variability in Amazonian Secondary Successions with Full-Waveform Airborne LiDAR. Remote Sens., 16.","DOI":"10.3390\/rs16122085"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1639","DOI":"10.1002\/2016GB005465","article-title":"Aboveground Biomass Variability across Intact and Degraded Forests in the Brazilian Amazon","volume":"30","author":"Longo","year":"2016","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4302","DOI":"10.1002\/joc.5086","article-title":"WorldClim 2: New 1-Km Spatial Resolution Climate Surfaces for Global Land Areas","volume":"37","author":"Fick","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.5194\/bg-8-1415-2011","article-title":"Soils of Amazonia with Particular Reference to the RAINFOR Sites","volume":"8","author":"Quesada","year":"2011","journal-title":"Biogeosciences"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1002\/joc.4831","article-title":"Spatiotemporal Rainfall and Temperature Trends throughout the Brazilian Legal Amazon, 1973\u20132013","volume":"37","author":"Almeida","year":"2017","journal-title":"Int. J. Climatol."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Pontes-Lopes, A., Silva, C.V.J., Barlow, J., Rinc\u00f3n, L.M., Campanharo, W.A., Nunes, C.A., de Almeida, C.T., Silva J\u00fanior, C.H.L., Cassol, H.L.G., and Dalagnol, R. (2021). Drought-Driven Wildfire Impacts on Structure and Dynamics in a Wet Central Amazonian Forest. Proc. R. Soc. B Biol. Sci., 288.","DOI":"10.1098\/rspb.2021.0094"},{"key":"ref_33","unstructured":"(2024, October 20). SFB\u2014Servi\u00e7o Florestal Brasileiro Madeflona Industrial Madeireira: Execu\u00e7\u00e3o Financeira e T\u00e9cnica Da Concess\u00e3o (Jamari\u2014UMF I), Available online: https:\/\/www.gov.br\/florestal\/pt-br\/assuntos\/concessoes-e-monitoramento\/concessoes-florestais-em-andamento\/floresta-nacional-do-jamari-ro-2\/madeflona-industrial-madeireira-execucao-tecnica-da-concessao-jamari-umf-i-2."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"eabp8622","DOI":"10.1126\/science.abp8622","article-title":"The Drivers and Impacts of Amazon Forest Degradation","volume":"379","author":"Lapola","year":"2023","journal-title":"Science"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/S0378-1127(99)00337-0","article-title":"Effects of Soil Fertility and Land-Use on Forest Succession in Amaz\u00f4nia","volume":"139","author":"Moran","year":"2000","journal-title":"For. Ecol. Manag."},{"key":"ref_36","unstructured":"Rouse, J.W. (1973, January 10\u201314). Monitoring Vegetation Systems in the Great Plains with ERTS. Proceedings of the ERTS-1 SYMPOSIUM, Washington, DC, USA."},{"key":"ref_37","unstructured":"Key, C.H., Zhu, Z., Ohlen, D., Howard, S., McKinley, R., and Benson, N. (2002, January 8\u201312). The Normalized Burn Ratio and Relationships to Burn Severity: Ecology, Remote Sensing and Implementation. Proceedings of the Ninth Forest Service Remote Sensing Applications Conference, San Diego, CA, USA."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"074028","DOI":"10.1088\/1748-9326\/aacd1c","article-title":"Ongoing Primary Forest Loss in Brazil, Democratic Republic of the Congo, and Indonesia","volume":"13","author":"Turubanova","year":"2018","journal-title":"Environ. Res. Lett."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1038\/s41597-020-00600-4","article-title":"Benchmark Maps of 33 Years of Secondary Forest Age for Brazil","volume":"7","author":"Heinrich","year":"2020","journal-title":"Sci. Data"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Tyukavina, A., Potapov, P., Hansen, M.C., Pickens, A.H., Stehman, S.V., Turubanova, S., Parker, D., Zalles, V., Lima, A., and Kommareddy, I. (2022). Global Trends of Forest Loss Due to Fire From 2001 to 2019. Front. Remote Sens., 3.","DOI":"10.3389\/frsen.2022.825190"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1093\/forestry\/cpv047","article-title":"Optimum Plot and Sample Sizes for Carbon Stock and Biodiversity Estimation in the Lowland Tropical Forests of Papua New Guinea","volume":"89","author":"Grussu","year":"2016","journal-title":"Forestry"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.rse.2012.10.017","article-title":"A Meta-Analysis of Terrestrial Aboveground Biomass Estimation Using Lidar Remote Sensing","volume":"128","author":"Zolkos","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_43","unstructured":"Ometto, J.P., Gorgens, B.G., Assis, M., Cantinho, R.Z., Pereira, F.R.d.S., and Sato, L.Y. (2024, October 20). Summary of the Airborne LiDAR Transects Collected by EBA in the Brazilian Amazon (Version 20210219) [Data Set]. Zenodo. Available online: https:\/\/zenodo.org\/records\/4552699."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"e4209","DOI":"10.1002\/ecs2.4209","article-title":"Evaluating the Sensitivity of Forest Structural Diversity Characterization to LiDAR Point Density","volume":"13","author":"LaRue","year":"2022","journal-title":"Ecosphere"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3210","DOI":"10.1109\/JSTARS.2016.2522960","article-title":"When Big Data Are Too Much: Effects of LiDAR Returns and Point Density on Estimation of Forest Biomass","volume":"9","author":"Singh","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_46","unstructured":"Isenburg, M. (2021, August 05). LAStools\u2014Efficient LiDAR Processing Software (Version 171030, Unlicensed). Available online: https:\/\/rapidlasso.de\/downloads\/."},{"key":"ref_47","unstructured":"McGaughey, R.J. (2022, July 12). FUSION\/LDV LIDAR Analysis and Visualization Software (Version 4.61). Available online: http:\/\/forsys.sefs.uw.edu\/fusion\/fusion_overview.html."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.rse.2008.09.001","article-title":"Effects of Different Sensors, Flying Altitudes, and Pulse Repetition Frequencies on Forest Canopy Metrics and Biophysical Stand Properties Derived from Small-Footprint Airborne Laser Data","volume":"113","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_49","unstructured":"Roussel, J.R., and Auty, D. (2021, August 05). lidR: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications. R Package Version 1.6.1. Available online: https:\/\/cran.r-project.org\/web\/packages\/lidR\/index.html."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1111\/j.1461-0248.2012.01864.x","article-title":"Amazon Forest Carbon Dynamics Predicted by Profiles of Canopy Leaf Area and Light Environment","volume":"15","author":"Stark","year":"2012","journal-title":"Ecol. Lett."},{"key":"ref_51","unstructured":"Magurran, A.E. (2004). Measuring Biological Diversity, Blackwell Science, Ltd."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/01490410701295962","article-title":"Multiscale Terrain Analysis of Multibeam Bathymetry Data for Habitat Mapping on the Continental Slope","volume":"30","author":"Wilson","year":"2007","journal-title":"Mar. Geod."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"6329","DOI":"10.1029\/JB089iB07p06329","article-title":"Reflectance Spectroscopy: Quantitative Analysis Techniques for Remote Sensing Applications","volume":"89","author":"Clark","year":"1984","journal-title":"J. Geophys. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1029\/2006GL026457","article-title":"Three-Band Model for Noninvasive Estimation of Chlorophyll, Carotenoids, and Anthocyanin Contents in Higher Plant Leaves","volume":"33","author":"Gitelson","year":"2006","journal-title":"Geophys. Res. Lett."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/S0034-4257(99)00082-6","article-title":"Plant Litter and Soil Reflectance","volume":"71","author":"Nagler","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3846","DOI":"10.1016\/j.rse.2008.06.005","article-title":"Calibration and Validation of Hyperspectral Indices for the Estimation of Broadleaved Forest Leaf Chlorophyll Content, Leaf Mass per Area, Leaf Area Index and Leaf Canopy Biomass","volume":"112","author":"Soudani","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1080\/01431160310001618031","article-title":"Detecting Sugarcane \u201corange Rust\u201d Disease Using EO-1 Hyperion Hyperspectral Imagery","volume":"25","author":"Apan","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the Radiometric and Biophysical Performance of the MODIS Vegetation Indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/S0034-4257(96)00072-7","article-title":"Use of a Green Channel in Remote Sensing of Global Vegetation from EOS-MODIS","volume":"58","author":"Gitelson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.rse.2004.11.012","article-title":"Discrimination of Sugarcane Varieties in Southeastern Brazil with EO-1 Hyperion Data","volume":"94","author":"Formaggio","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/S0034-4257(02)00011-1","article-title":"Remote Sensing of Nitrogen and Lignin in Mediterranean Vegetation from AVIRIS Data: Decomposing Biochemical from Structural Signals","volume":"81","author":"Serrano","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/S0034-4257(96)00067-3","article-title":"NDWI\u2014A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space","volume":"58","author":"Gao","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(92)90059-S","article-title":"A Narrow-Waveband Spectral Index That Tracks Diurnal Changes in Photosynthetic Efficiency","volume":"41","author":"Gamon","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1034\/j.1399-3054.1999.106119.x","article-title":"Non-Destructive Optical Detection of Pigment Changes during Leaf Senescence and Fruit Ripening","volume":"106","author":"Merzlyak","year":"1999","journal-title":"Physiol. Plant."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2869","DOI":"10.1080\/014311697217396","article-title":"Estimation of Plant Water Concentration by the Reflectance Water Index WI (R900\/R970)","volume":"18","author":"Ogaya","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","first-page":"279","article-title":"Utilisation de La Haute Resolution Spectrale Pour Suivre l\u2019etat Des Couverts Vegetaux","volume":"Volume 287","author":"Guyenne","year":"1988","journal-title":"Proceedings of the Spectral Signatures of Objects in Remote Sensing"},{"key":"ref_67","unstructured":"Merton, R.N. (1998, January 12\u201316). Monitoring Community Hysteresis Using Spectral Shift Analysis and the Red-Edge Vegetation Stress Index. Proceedings of the Seventh Annual JPL Airborne Earth Science Workshop, Pasadena, CA, USA."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of Leaf-Area Index from Quality of Light on the Forest Floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Gitelson, A.A., Zur, Y., Chivkunova, O.B., and Merzlyak, M.N. (2002). Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy. Photochem. Photobiol., 75.","DOI":"10.1562\/0031-8655(2002)075<0272:ACCIPL>2.0.CO;2"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1563","DOI":"10.1080\/01431169308953986","article-title":"Red Edge Spectral Measurements from Sugar Maple Leaves","volume":"14","author":"Vogelmann","year":"1993","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","unstructured":"Lehnert, L.W., Meyer, H., and Bendix, J. (2021, August 05). Hsdar: Manage, Analyse and Simulate Hyperspectral Data in R. R Package Version 0.7.1. Available online: http:\/\/cran.nexr.com\/web\/packages\/hsdar\/index.html."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"2931","DOI":"10.1016\/j.rse.2010.08.029","article-title":"Estimation of Tropical Rain Forest Aboveground Biomass with Small-Footprint Lidar and Hyperspectral Sensors","volume":"115","author":"Clark","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building Predictive Models in R Using the Caret Package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"1319","DOI":"10.2466\/pms.1976.43.3f.1319","article-title":"Robustness of the Pearson Correlation against Violations of Assumptions","volume":"43","author":"Havlicek","year":"1976","journal-title":"Percept Mot Ski."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v011.i09","article-title":"Kernlab\u2014An S4 Package for Kernel Methods in R","volume":"11","author":"Karatzoglou","year":"2004","journal-title":"J. Stat. Softw."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.ipm.2009.03.002","article-title":"A Systematic Analysis of Performance Measures for Classification Tasks","volume":"45","author":"Sokolova","year":"2009","journal-title":"Inf. Process. Manag."},{"key":"ref_77","unstructured":"Cohen, J. (1988). Statistical Power Analysis for Behavioural Sciences, Erlbaum. [2nd ed.]."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1109\/TGRS.2008.916480","article-title":"Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas","volume":"46","author":"Dalponte","year":"2008","journal-title":"Geosci. Remote Sens. IEEE Trans."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.rse.2014.07.028","article-title":"Importance of Sample Size, Data Type and Prediction Method for Remote Sensing-Based Estimations of Aboveground Forest Biomass","volume":"154","author":"Fassnacht","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.rse.2012.03.013","article-title":"Tree Species Classification in the Southern Alps Based on the Fusion of Very High Geometrical Resolution Multispectral\/Hyperspectral Images and LiDAR Data","volume":"123","author":"Dalponte","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Shoot, C., Andersen, H., Moskal, L.M., Babcock, C., Cook, B.D., and Morton, D.C. (2021). Classifying Forest Type in the National Forest Inventory Context with Airborne Hyperspectral and Lidar Data. Remote Sens., 13.","DOI":"10.3390\/rs13101863"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/S0378-1127(03)00003-3","article-title":"Classification of Successional Forest Stages in the Brazilian Amazon Basin","volume":"181","author":"Lu","year":"2003","journal-title":"For. Ecol. Manag."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"3811","DOI":"10.5194\/bg-15-3811-2018","article-title":"Estimating Aboveground Carbon Density and Its Uncertainty in Borneo\u2019s Structurally Complex Tropical Forests Using Airborne Laser Scanning","volume":"15","author":"Jucker","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Prestes, N.C.C.d.S., Massi, K.G., Silva, E.A., Nogueira, D.S., de Oliveira, E.A., Freitag, R., Marimon, B.S., Marimon-Junior, B.H., Keller, M., and Feldpausch, T.R. (2020). Fire Effects on Understory Forest Regeneration in Southern Amazonia. Front. For. Glob. Chang., 3.","DOI":"10.3389\/ffgc.2020.00010"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0378-1127(00)00535-1","article-title":"Neotropical Secondary Forest Succession: Changes in Structural and Functional Characteristics","volume":"148","author":"Guariguata","year":"2001","journal-title":"For. Ecol. Manag."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.rse.2018.11.028","article-title":"Mapping Tropical Disturbed Forests Using Multi-Decadal 30 m Optical Satellite Imagery","volume":"221","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"6039","DOI":"10.1073\/pnas.0400168101","article-title":"Drought Stress and Carbon Uptake in an Amazon Forest Measured with Spaceborne Imaging Spectroscopy","volume":"101","author":"Asner","year":"2004","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Jaroci\u0144ska, A., Kope\u0107, D., Niedzielko, J., Wylaz\u0142owska, J., Halladin-D\u0105browska, A., Charyton, J., Piernik, A., and Kami\u0144ski, D. (2023). The Utility of Airborne Hyperspectral and Satellite Multispectral Images in Identifying Natura 2000 Non-Forest Habitats for Conservation Purposes. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-31705-6"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1016\/j.rse.2007.09.009","article-title":"Integrating Waveform Lidar with Hyperspectral Imagery for Inventory of a Northern Temperate Forest","volume":"112","author":"Anderson","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"2841","DOI":"10.1016\/j.rse.2010.07.002","article-title":"Assessing the Utility of Airborne Hyperspectral and LiDAR Data for Species Distribution Mapping in the Coastal Pacific Northwest, Canada","volume":"114","author":"Jones","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1080\/01431160701281023","article-title":"Canopy Chlorophyll Concentration Estimation Using Hyperspectral and Lidar Data for a Boreal Mixedwood Forest in Northern Ontario, Canada","volume":"29","author":"Thomas","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"112582","DOI":"10.1016\/j.rse.2021.112582","article-title":"Monitoring Restored Tropical Forest Diversity and Structure through UAV-Borne Hyperspectral and Lidar Fusion","volume":"264","author":"Almeida","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1038\/s41559-018-0490-x","article-title":"The Exceptional Value of Intact Forest Ecosystems","volume":"2","author":"Watson","year":"2018","journal-title":"Nat. Ecol. Evol."},{"key":"ref_94","unstructured":"(2024, October 20). Alliance for Restoration in the Amazon Forest. Landscape Restoration in the Amazon\u2014Overview and Paths to Follow. Position Paper: 16p ISBN 978-65-00-12760-7 2020. Available online: https:\/\/aliancaamazonia.org.br\/wp-content\/uploads\/2021\/06\/PAPER_ALIANCA_EN_2020_FINAL.pdf."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"e1600821","DOI":"10.1126\/sciadv.1600821","article-title":"The Last Frontiers of Wilderness: Tracking Loss of Intact Forest Landscapes from 2000 to 2013","volume":"3","author":"Potapov","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.1098\/rstb.2007.0013","article-title":"Fire-Mediated Dieback and Compositional Cascade in an Amazonian Forest","volume":"363","author":"Barlow","year":"2008","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"3713","DOI":"10.1111\/gcb.12627","article-title":"A Large-Scale Field Assessment of Carbon Stocks in Human-Modified Tropical Forests","volume":"20","author":"Berenguer","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.foreco.2012.11.036","article-title":"Tropical Forest Degradation by Mega-Fires in the Northern Brazilian Amazon","volume":"294","author":"Xaud","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_99","unstructured":"ITTO\u2014International Tropical Timber Organization (2002). ITTO Guidelines for the Restoration, Management and Rehabilitation of Degraded and Secondary Tropical Forests, International Tropical Timber Organization."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/21\/3935\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:18:09Z","timestamp":1760113089000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/21\/3935"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,22]]},"references-count":99,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["rs16213935"],"URL":"https:\/\/doi.org\/10.3390\/rs16213935","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,22]]}}}