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Fusing Digital Elevation Models to Improve Hydrological Interpretations

Journal of Geographic Information System 2017年第5期9卷 558-575页

作者： shane furze Jae Ogilvie Paul A. Arp Forest Watershed Research Center University of New Brunswick Fredericton Canada

Improving the accuracy of digital elevation is essential for reducing hydro-topographic derivation errors pertaining to, e.g., flow direction, basin borders, channel networks, depressions, flood forecasting, and soil drainage. This article demonstrates how a gain in this accuracy is improved through digital elevation model (DEM) fusion, and using LiDAR-derived elevation layers for conformance testing and validation. This demonstration is done for the Province of New Brunswick (NB, Canada), using five province-wide DEM sources (SRTM 90 m;SRTM 30 m;ASTER 30 m;CDED 22 m;NB-DEM 10 m) and a five-stage process that guides the re-projection of these DEMs while minimizing their elevational differences relative to LiDAR-captured bare-earth DEMs, through calibration and validation. This effort decreased the resulting non-LiDAR to LiDAR elevation differences by a factor of two, reduced the minimum distance conformance between the non-LiDAR and LiDAR-derived flow channels to ± 10 m at 8.5 times out of 10, and dropped the non-LiDAR wet-area percentages of false positives from 59% to 49%, and of false negatives from 14% to 7%. While these reductions are modest, they are nevertheless not only consistent with already existing hydrographic data layers informing about stream and wet-area locations, they also extend these data layers across the province by comprehensively locating previously unmapped flow channels and wet areas.

关键词： DEM Fusion LiDAR-Based Calibration Hydrographic Interpretations Stream Network Wet-Areas Mapping

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Cold-Weather Crop Suitability Modelling

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Open Journal of Soil Science 2023年第10期13卷 431-455页

作者： Kamille Lemieux Nana-Agyei O. Afriyie shane furze Patrick Toner Paul A. Arp Faculty of Forestry & Env. Management University of New Brunswick Fredericton Canada NB Dept. Agriculture & Aquaculture Hugh John Flemming Forestry Centre Fredericton Canada

This article presents ArcGIS Pro workflow results aimed at rating and mapping cold-weather crop suitability from 0% to 100% at 1-m elevation resolution for the Province of New Brunswick (NB). This rating accounts for variations by soil conditions (texture, coarse fragments, depth, calcareousness, drainage, slope), growing degree days (GDD) and frost-free days (FFD) from within fields to across regions. The ratings so produced reflect a significant part of farm and farm/woodlot property assessment values as these also vary by area and building footprint. While the soil properties for texture, coarse fragments, depth, and calcareousness vary by NB soil association mapping units, within-field suitabilities also vary by slope from flat to steep and by drainage as it correlates across the terrain by depth-to-water (DTW) from very poor to poor, imperfect, moderate, well and excessive. Areas marked by 1.5 10% have low to no suitability because of slope-increased soil erosion and trafficability risks. The number of growing-degree and frost-free days across NB were rated to be sufficient for cold weather cropping, except marginally so at the high-elevation locations.

关键词： Crop Suitability Rating Topography Climate Soil Properties Property Values Regression Analysis

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Assessing Soil-Related Black Spruce and White Spruce Plantation Productivity

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Open Journal of Forestry 2017年第2期7卷 209-227页

作者： shane furze Mark Castonguay Jae Ogilvie Mina Nasr Pierre Cormier Rolland Gagnon Greg Adams Paul A. Arp Forest Watershed Research Center UNB Faculty of Forestry and Environmental Management Fredericton Canada J.D. Irving Ltd. Sussex Canada

This article focuses on modelling and mapping the productivity of black (Picea mariana) and white spruce (Picea glauca) plantations across the Black Brook forest management area in northwestern New Brunswick, Canada, encompassing about 200,000 ha. This effort involved establishing 3500 50 m2 survey plots, each informing about: plantation age (15 to 43 years), planted species type, stem count, tree height, basal area, and wood volume. All of this was supplemented with location-specific productivity predictors, i.e., xy location and specifications pertaining to soil type, soil drainage (established through digital elevation modelling by way of the depth-to-water index DTW), and years since thinning (pre-commercial and commercial), and. The DTW index, as it emulates the elevation rise away from open water features such as streams, rivers and lakes, allowed the re-mapping of existing soil borders by topographic position and drainage association. Non-linear regression analysis revealed that plantation height, basal area and volume all increased with plantation age, as to be expected. Pre-commercial thinning in plantations <30 years old had a positive while the more recent commercial thinning still had the negative effect on standing wood volume and mean annual volume increment (MAI). White spruce MAI generally exceeded black spruce (MAI) by a factor of 1.25. Poor and excessive soil drainage reduced MAI. Best growth performances occurred on plantations established on well-drained calcareous soils. The best-fitted results so obtained allowed for generating black and white spruce MAI maps across the forest management area by ridge-to-valley soil and DTW location at 10 m resolution. These maps were subsequently used for site-by-site silvicultural evaluation and ranking purposes.

关键词： Forest Plantation Productivity Mapping Black Spruce White Spruce Soil Type & Drainage Digital Terrain Modelling

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