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Norris Lam

Adjunkt i GIS och geomatik

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Arbetar vid Institutionen för naturgeografi
Telefon 08-674 78 69
E-post norris.lam@natgeo.su.se
Besöksadress Svante Arrhenius väg 8
Rum T 420
Postadress Inst för naturgeografi 106 91 Stockholm

Om mig

Min forskning fokuserar på tillämpning av 3D-punktmoln för att karakterisera jordens topografi. Mätteknikerna som används i min forskning inkluderar laserskanning (t.ex. terrestriska och luftburna lasersystem), akustiska Doppler strömprofiler, GNSS/GPS samt traditionella lantmätmetoder.

Undervisning

Nuvarande

Applied Remote Sensing and GIS for Landscape Analysis (GE7062)

Geographic Analysis and Visualization in GIS (GE8013)

GIS och fjärranalys (GE4012)

Geografiska informationssystem (GE4019)

Tellus II - Physical Geography (GE4023)

 

Tidigare
Information and Modeling Systems for Land and Water Resources (GE7006)

How to use Matlab to solve problems in environmental, climatological, and earth science research? (Bolin Center for Climate Research School)

GIS and remote sensing (GE4012)

Publikationer

I urval från Stockholms universitets publikationsdatabas
  • 2017. Norris Lam, Jason W. Kean, Steve W. Lyon. Hydrology Research 48 (4), 981-996

    The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.

  • 2015. Norris Lam (et al.). Journal of the American Water Resources Association 51 (5), 1211-1220

    This brief pilot study implements a camera-based laser scanning system that potentially offers a viable, cost-effective alternative to traditional terrestrial laser scanning (TLS) and LiDAR equipment. We adapted a low-cost laser ranging system (SICK LSM111) to acquire area scans of the channel and bed for a temporarily diverted stream. The 5mx2m study area was scanned at a 4mm point spacing which resulted in a point cloud density of 5,600 points/m(2). A local maxima search algorithm was applied to the point cloud and a grain size distribution of the stream bed was extracted. The 84th and 90th percentiles of this distribution, which are commonly used to characterize channel roughness, were 90mm and 109mm, respectively. Our example shows the system can resolve both large-scale geometry (e.g., bed slope and channel width) and small-scale roughness elements (e.g., grain sizes between about 30 and 255mm) in an exposed stream channel thereby providing a resolution adequate for the estimation of ecohydraulic roughness parameters such as Manning's n. While more work is necessary to refine our specific field-deployable system's design, these initial results are promising in particular for those working on a limited or fixed budget. This opens up a realm of laser scanning applications and monitoring strategies for water resources that may not have been possible previously due to cost limitations associated with traditional TLS systems.

  • 2015. Steve W. Lyon (et al.). Water 7 (4), 1324-1339

    This pilot study explores the potential of using low-resolution (0.2 points/m(2)) airborne laser scanning (ALS)-derived elevation data to model stream rating curves. Rating curves, which allow the functional translation of stream water depth into discharge, making them integral to water resource monitoring efforts, were modeled using a physics-based approach that captures basic geometric measurements to establish flow resistance due to implicit channel roughness. We tested synthetically thinned high-resolution (more than 2 points/m(2)) ALS data as a proxy for low-resolution data at a point density equivalent to that obtained within most national-scale ALS strategies. Our results show that the errors incurred due to the effect of low-resolution versus high-resolution ALS data were less than those due to flow measurement and empirical rating curve fitting uncertainties. As such, although there likely are scale and technical limitations to consider, it is theoretically possible to generate rating curves in a river network from ALS data of the resolution anticipated within national-scale ALS schemes (at least for rivers with relatively simple geometries). This is promising, since generating rating curves from ALS scans would greatly enhance our ability to monitor streamflow by simplifying the overall effort required.

  • Artikel Laser vision
    2015. A. A. Harpold (et al.). Hydrology and Earth System Sciences 19 (6), 2881-2897

    Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the 'zone of life', which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demonstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.

Visa alla publikationer av Norris Lam vid Stockholms universitet

Senast uppdaterad: 12 november 2017

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