{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:38:17Z","timestamp":1774021097242,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,9]],"date-time":"2019-04-09T00:00:00Z","timestamp":1554768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41871278347"],"award-info":[{"award-number":["41871278347"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31570546"],"award-info":[{"award-number":["31570546"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>ICESat-2 is the new generation of NASA\u2019s ICESat (Ice, Cloud and land Elevation Satellite) mission launched in September 2018. We investigate the potential of forest parameter estimation using metrics from photon counting LiDAR data, using an integrated dataset including photon counting LiDAR data from SIMPL (the Slope Imaging Multi-polarization Photon-counting LiDAR), airborne small footprint LiDAR data from G-LiHT and a stem map in Howland Research Forest, USA. First, we propose a noise filtering method based on a local outlier factor (LOF) with elliptical search area to separate the ground and canopy surfaces from noise photons. Next, a co-registration technique based on moving profiling is applied between SIMPL and G-LiHT data to correct geolocation error. Then, we calculate height metrics from both SIMPL and G-LiHT. Finally, we investigate the relationship between the two sets of metrics, using a stem map from field measurement to validate the results. Results of the ground and canopy surface extraction show that our methods can detect the potential signal photons effectively from a quite high noise rate environment in relatively rough terrain. In addition, results from co-registration between SIMPL and G-LiHT data indicate that the moving profiling technique to correct the geolocation error between these two datasets achieves favorable results from both visual and statistical indicators validated by the stem map. Tree height retrieval using SIMPL showed error of less than 3 m. We find good consistency between the metrics derived from the photon counting LiDAR from SIMPL and airborne small footprint LiDAR from G-LiHT, especially for those metrics related to the mean tree height and forest fraction cover, with mean     R 2     value of 0.54 and 0.6 respectively. The quantitative analyses and validation with field measurements prove that these metrics can describe the relevant forest parameters and contribute to possible operational products from ICESat-2.<\/jats:p>","DOI":"10.3390\/rs11070856","type":"journal-article","created":{"date-parts":[[2019,4,10]],"date-time":"2019-04-10T03:47:36Z","timestamp":1554868056000},"page":"856","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6377-1094","authenticated-orcid":false,"given":"Bowei","family":"Chen","sequence":"first","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Global Environmental Modelling and Earth Observation (GEMEO), Department of Geography, Swansea University, Swansea SA2 8PP, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9760-6580","authenticated-orcid":false,"given":"Yong","family":"Pang","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Zengyuan","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9933-6935","authenticated-orcid":false,"given":"Peter","family":"North","sequence":"additional","affiliation":[{"name":"Global Environmental Modelling and Earth Observation (GEMEO), Department of Geography, Swansea University, Swansea SA2 8PP, UK"}]},{"given":"Jacqueline","family":"Rosette","sequence":"additional","affiliation":[{"name":"Global Environmental Modelling and Earth Observation (GEMEO), Department of Geography, Swansea University, Swansea SA2 8PP, UK"}]},{"given":"Guoqing","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA"}]},{"given":"Juan","family":"Su\u00e1rez","sequence":"additional","affiliation":[{"name":"Forest Research, Northern Research Station, Roslin, Midlothian EH25 9SY, Scotland, UK"}]},{"given":"Iain","family":"Bye","sequence":"additional","affiliation":[{"name":"Global Environmental Modelling and Earth Observation (GEMEO), Department of Geography, Swansea University, Swansea SA2 8PP, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3083-4909","authenticated-orcid":false,"given":"Hao","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shevliakova, E., Pacala, S.W., Malyshev, S., Hurtt, G.C., Milly, P., Caspersen, J.P., Sentman, L.T., Fisk, J.P., Wirth, C., and Crevoisier, C. 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