Qi Chen

Qi Chen
University of Hawaiʻi at Mānoa | UH Manoa · Department of Geography and Environment

PhD

About

108
Publications
39,955
Reads
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5,655
Citations
Additional affiliations
July 2017 - present
University of Hawaiʻi at Mānoa
Position
  • Professor (Full)

Publications

Publications (108)
Article
Remotely sensed data have been widely used in recent years for mapping and estimating biomass. However, the characterization of the uncertainty of mapped or estimated biomass in previous studies was either based on ad-hoc approaches (e.g., using model fitting statistics such root mean square errors derived from purposive samples) or mostly limited...
Article
Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences...
Article
Full-text available
Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agro...
Article
The model-assisted difference and regression estimators are increasingly used with forest inventory and remotely sensed data to increase the precision of estimates of inventory parameters. Although these estimators date back at least 50 years and appear in multiple current sampling textbooks, the associated terminology is inconsistently defined, ev...
Article
Full-text available
Estimating the aboveground biomass (AGB) at the plot level plays a major role in connecting accurate single-tree AGB measurements to relatively difficult regional AGB estimates. However, AGB estimates at the plot level suffer from many uncertainties. The goal of this study is to determine whether combining machine learning with spatial statistics r...
Article
Using remote sensing data to estimate forest aboveground biomass (FAB) is of great significance for understanding the terrestrial C dynamics and making regional policies of forest management. The vegetation type-specified approach can improve the accuracy of estimating FAB, and it is difficult to obtain enough field plots for each vegetation type t...
Article
Hyperspectral remote sensing demonstrates a great potential for identifying crops. Orbita hyperspectral image satellite (OHS) is a new hyperspectral satellite in orbit with the highest spectral and spatial resolutions and relatively short spectral range. In this study, the OHS, along with Land Remote-Sensing Satellite (System, Landsat) eight operat...
Thesis
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Marine debris is a global crisis that negatively affects human health and safety, wildlife, and coastal economies. Geospatial technology has been deployed to map, measure, and model the sources, pathways, and eventual sinks of marine debris, however data are still scarce due to the high cost of conducting fieldwork or manually labeling debris in re...
Article
Kukui was an important element to indigenous Hawaiian agroforestry and retained some of its importance throughout Hawai‘i’s history. We examine the historical ecology and trends of kukui, including a review of the ethnobotany. We use current and historical remote imagery to map kukui canopy on the five largest Hawaiian Islands. Kukui is still wides...
Article
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This article examines overtourism indicators at Kailua Beach Park in Hawaiʻi, and demonstrates a systematic approach to assessing carrying capacity by pairing descriptive indicators with more commonly used evaluative indicators. Data were obtained from an onsite survey of 452 visitors. Questionnaires with embedded photographs measured visitors’ per...
Article
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Background: The tiller number per unit area is one of the main agronomic components in determining yield. A real-time assessment of this trait could contribute to monitoring the growth of wheat populations or as a primary phenotyping indicator for the screening of cultivars for crop breeding. However, determining tiller number has been conventiona...
Article
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Non-destructive and accurate estimation of crop biomass is crucial for the quantitative diagnosis of growth status and timely prediction of grain yield. As an active remote sensing technique, terrestrial laser scanning (TLS) has become increasingly available in crop monitoring for its advantages in recording structural properties. Some researchers...
Article
Addressing the impact of vegetation architecture on shortwave radiation transfer in land surface models is important for accurate weather forecasting, carbon budget estimates, and climate predictions. This paper investigates to what extent it is possible to retrieve structural parameters of two different parameterization schemes from direct transmi...
Preprint
Full-text available
Abstract. Aboveground biomass (AGB) estimates at the plot level plays a major part in connecting accurate single-tree AGB measurements to relatively difficult regional-scale AGB estimates. However, complex and spatially heterogeneous landscapes, where multiple environmental covariates (such as longitude, latitude, and forest structure) affect the s...
Article
Tropical countries without extensive ground sampling programs often use the gain-loss approach for greenhouse gas inventories. With this approach emissions are estimated as the products of estimates of areas of land use change characterized as activity data and estimates of emissions per unit area characterized as emission factors. For the special...
Article
Plant height, as an essential phenotypic trait, is widely used in plant breeding, growth monitoring and yield forecasting. As a state-of-the-art technology for tracking diverse structural parameters non-destructively and in situ, terrestrial laser scanning (TLS) can generate three-dimensional geometric information with unprecedented accuracy, parti...
Article
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A laser is a spatially coherent light that can travel through space with very little diffraction [...]
Article
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National greenhouse gas inventories often use variations of the gain–loss approach whereby emissions are estimated as the products of estimates of areas of land-use change characterized as activity data and estimates of emissions per unit area characterized as emission factors. Although the term emissions is often intuitively understood to mean rel...
Article
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Urban planning and management need accurate three-dimensional (3D) data such as light detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up to millimeter-level accuracy and point density of a few thousand points/m2, have gained increasing attention in urban applications. Substantial research has been conducted in...
Article
Full-text available
High-precision prediction of large-scale forest aboveground biomass (AGB) is important but challenging on account of the uncertainty involved in the prediction process from various sources, especially the uncertainty due to non-representative sample units. Usually caused by inadequate sampling, non-representative sample units are common and can lea...
Article
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The stand density of trees affects stand growth and is useful for estimating other forests structure parameters. We studied tree stand density in Jiufeng National Forest Park in Beijing. The number of spectral local maxima points (NSLMP) calculated within each sample plot was extracted by the spectral maximum filtering method using QuickBird imager...
Article
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The spatiotemporal distribution pattern of the surface temperatures of urban forest canopies (STUFC) is influenced by many environmental factors, and the identification of interactions between these factors can improve simulations and predictions of spatial patterns of urban cool islands. This quantitative research uses an integrated method that co...
Article
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Published evidence shows that views to blue spaces (e.g. ocean, lake, and river) have positive effects on humans' health and mental well-beings. However, quantitative assessment of blue space visibility is challenging for large spatial areas with complex terrain or built environment. The assessment approach introduced in this study applied an innov...
Article
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To extend agricultural productivity by knowledge-based breeding and tailoring varieties to adapt to specific environmental conditions, it is imperative to improve our ability to acquire the dynamic changes of the crop's phenotype under field conditions. Canopy leaf biomass (CLB) per ground area is one of the key crop phenotypic parameters in plant...
Article
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A methods framework is presented that utilizes field plots, airborne light detection and ranging (LiDAR), and spaceborne Geoscience Laser Altimeter System (GLAS) data to estimate forest attributes over a 20 Mha area in Northern Canada. The framework was implemented to scale up forest attribute models from field data to intersecting airborne LiDAR d...
Article
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Power lines classification is important for electric power management and geographical objects extraction using LiDAR (light detection and ranging) point cloud data. Many supervised classification approaches have been introduced for the extraction of features such as ground, trees, and buildings, and several studies have been conducted to evaluate...
Article
Earth observation (EO) data, such as high-resolution satellite imagery or LiDAR, has become one primary source for forests Aboveground Biomass (AGB) mapping and estimation. However, managing and analyzing the large amount of globally or locally available EO data remains a great challenge. The Google Earth Engine (GEE), which leverages cloud-computi...
Article
The automatic classification of power lines from airborne light detection and ranging (LiDAR) data is a crucial task for power supply management. The methods for power line classification can be either supervised or unsupervised. Supervised methods might achieve high accuracy for small areas, but it is time consuming to collect training data over a...
Article
Model-based inference is an alternative to probability-based inference for small areas or remote areas for which probability sampling is difficult. Model-based mean square error estimators incorporate three components: prediction covariance, residual variance, and residual covariance. The latter two components are often considered negligible, parti...
Article
Full-text available
Remote sensing-based forest aboveground biomass (AGB) estimation has been extensively explored in the past three decades, but how to effectively combine different sensor data and modeling algorithms is still poorly understood. This research conducted a comparative analysis of different datasets (e.g., Landsat Thematic Mapper (TM), ALOS PALSAR L-ban...
Article
Full-text available
Integration of Landsat images and multisource data using spatial statistical analysis and geographical detector models can reveal the individual and interactive influences of anthropogenic activities and ecological factors on concentrations of atmospheric particulate matter less than 2.5 microns in diameter (PM2.5). This approach has been used in m...
Article
The term shelf-life is used to characterize the elapsed time beyond which a commodity loses its usefulness. The term is most often used with reference to foods and medicines, but herein it is used to characterize the elapsed time beyond which airborne laser scanning (ALS) data are no longer useful for enhancing inferences for forest inventory popul...
Article
National forest inventories routinely report estimates of parameters related to aboveground biomass (AGB), but sample sizes are often insufficient to satisfy precision guidelines and reporting requirements. Aerial photography , satellite imagery, and increasingly airborne laser scanning (ALS) data are all used as sources of auxiliary information to...
Article
Full-text available
Leaf area index (LAI) is a significant biophysical variable in the models of hydrology, climatology and crop growth. Rapid monitoring of LAI is critical in modern precision agriculture. Remote sensing (RS) on satellite, aerial and unmanned aerial vehicles (UAVs) has become a popular technique in monitoring crop LAI. Among them, UAVs are highly attr...
Article
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We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method (BEF) versus estimates obtained from a local biomass model, based on large-scale empirical field inventory sampling data. The sources and relative contributions of deviations between the two models were analyzed by the b...
Article
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there are increasing demands for afforestation and reforestation aimed at sequestering carbon (c) and conserving biodiversity. This study provides quantitative results to evaluate C storage capacity and probes the relationship between C distribution of various forest components and their floristic diversity during natural recovery processes. We stu...
Article
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Automatic extraction of power lines has become a topic of great importance in airborne LiDAR data processing for transmission line management. In this paper, we present a new, fully automated and versatile framework that consists of four steps: (i) power line candidate point filtering, (ii) neighbourhood selection, (iii) feature extraction based on...
Article
The normalized difference vegetation index (NDVI) is a commonly used index for monitoring crop growth status. Previous studies have shown that the leaf area index (LAI) estimation based on NDVI is limited by saturation that occurs under conditions of relatively dense canopies (LAI > 2 m² m–2). To reduce the saturation effect, we suggested new spect...
Article
Automatic extraction of power lines using airborne LiDAR (Light Detection and Ranging) data has been one of the most important topics for electric power management. However, this is very challenging over complex urban areas, where power lines are in close proximity to buildings and trees. In this paper, we presented a new, semi-automated and versat...
Article
Full-text available
Previous research has explored the potential to integrate lidar and optical data in aboveground biomass (AGB) estimation, but how different data sources, vegetation types, and modeling algorithms influence AGB estimation is poorly understood. This research conducts a comparative analysis of different data sources and modeling approaches in improvin...
Article
Full-text available
Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to...
Article
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps constructed with nearest neighbours techniques. The non-parametric k-nearest neighbours (k-NN) technique calculates predictions as linear combinations of observations for sample units that are nearest in a space of auxiliary variables to population units...
Article
Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how hum...
Article
Remote sensing-based methods of aboveground biomass (AGB) estimation in forest ecosystems have gained increased attention, and substantial research has been conducted in the past three decades. This paper provides a survey of current biomass estimation methods using remote sensing data and discusses four critical issues - collection of field-based...
Article
To answer new scientific and ecological questions and monitor multiple forest changes, a fine scale characterization of these ecosystems is needed, and could imply the mapping of specific species, of detailed forest types, and of functional composition. This characterization can be now provided by the novel Earth Observation tools. This study aims...
Article
Full-text available
Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we exp...
Article
Full-text available
Tropical forests are major repositories of biodiversity, but are fast disappearing as land is converted to agriculture. Decision-makers need to know which of the remaining forests to prioritize for conservation, but the only spatial information on forest biodiversity has, until recently, come from a sparse network of ground-based plots. Here we exp...