Stream network modelling using lidar and photogrammetric digital elevation models: a comparison and field verification

Murphy, Paul; Ogilvie, Jae; Meng, Fan‐Rui; Arp, Paul A.

doi:10.1002/hyp.6770

Cited by 129 publications

(77 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…According to our field observations, these microtopographical features exert a considerable influence on downslope soil moisture distribution. Results from Murphy et al (2008) corroborate our findings by demonstrating that lidar DEMs more accurately captured the field-mapped hydrologic flow pathways than lower-resolution photogrammetric DEMs. Such micro-topographical features occur at scales much finer than 10 m-based TWIs and are therefore often not captured appropriately.…”

Section: Cell Size: 3 Vs 10 Msupporting

confidence: 84%

Evaluating topographic wetness indices across central New York agricultural landscapes

Buchanan

Fleming

Schneider

et al. 2014

Hydrol. Earth Syst. Sci.

107

View full text Add to dashboard Cite

Abstract. Accurately predicting soil moisture patterns in the landscape is a persistent challenge. In humid regions, topographic wetness indices (TWIs) are widely used to approximate relative soil moisture patterns. However, there are many ways to calculate TWIs and very few field studies have evaluated the different approaches -especially in the US. We calculated TWIs using over 400 unique formulations that considered different digital elevation model (DEM) resolutions (cell size), vertical precision of DEM, flow direction and slope algorithms, smoothing via low-pass filtering, and the inclusion of relevant soil properties. We correlated each TWI with observed patterns of soil moisture at five agricultural fields in central NY, USA, with each field visited five to eight times between August and November 2012. Using a mixed effects modeling approach, we were able to identify optimal TWI formulations applicable to moderate relief agricultural settings that may provide guidance for practitioners and future studies. Overall, TWIs were moderately well correlated with observed soil moisture patterns; in the best case the relationship between TWI and soil moisture had an average R 2 and Spearman correlation value of 0.61 and 0.78, respectively. In all cases, fine-scale (3 m) lidar-derived DEMs worked better than USGS 10 m DEMs and, in general, including soil properties improved correlations.

show abstract

Section: Cell Size: 3 Vs 10 Msupporting

confidence: 84%

Evaluating topographic wetness indices across central New York agricultural landscapes

Buchanan

Fleming

Schneider

et al. 2014

Hydrol. Earth Syst. Sci.

107

View full text Add to dashboard Cite

show abstract

“…High-resolution elevation data can present additional problems when modeling water flow because some elements, such as bridges and roads, are present in the data (Duke and Kienzle 2003, Wang and Liu 2006, Murphy et al 2008, Poppenga et al 2010. In reality, water flow is possible past these features by flowing underneath a bridge or through a culvert, but in a DEM the elevation of the road or bridge masks that and obstructs modeled flow of water.…”

Section: Creating a Hydrologically Correct Demmentioning

confidence: 99%

Land use and wetland drainage affect water levels and dynamics of remaining wetlands

et al. 2015

View full text Add to dashboard Cite

Abstract. Depressional wetlands are productive and unique ecosystems found around the world. Their value is due, in part, to their dynamic nature, in which water levels fluctuate in response to climate, occasionally drying out. However, many wetlands have been altered by consolidation drainage, where multiple, smaller wetlands are drained into fewer, larger, wetlands causing higher water levels. We evaluated whether current (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) water surface areas were greater than historical water surface areas of 141 randomly selected semipermanent and permanent wetlands across the Prairie Pothole Region of North Dakota, USA. We also evaluated whether differences between historical and current hydrology of these wetlands were attributable to consolidation drainage. For each of these wetlands, we digitized water surface areas from aerial photography during historical and current eras. Our results indicated that water surface areas are currently 86% greater in sample wetlands than they were historically and that differences can be attributed to consolidation drainage. Water surface areas of consolidated wetlands in extensively drained landscapes were 197% greater than those with no drainage and now require more extreme drought conditions to dry out. Wetlands in extensively drained catchments were larger, dry out less frequently, and have more surface-water connections to other wetlands via ditches. These factors make conditions more favorable for the presence of fish that decrease abundances of aquatic invertebrates and reduce the productivity and quality of these wetlands for many species. Our results support the idea that intact wetlands serve an important role in water storage and groundwater recharge and reduce down-stream runoff.

show abstract

“…Over the past decade, improvements in global positioning systems (GPS), inertial navigation systems (INS), computer hardware, LiDAR processing software, and reduced acquisition costs have promoted many of these applications from research to operational status in several jurisdictions (Naesset 2004, Evans et al 2006, Stephens et al 2007). Examples include predictive hydrology modeling (Murphy et al 2008, Mandlburger et al 2009), road location optimization and construction (Akay et al 2004, Aruga et al 2005, White et al 2010, harvest block engineering (Chung et al 2004), habitat definition (Clawges et al 2008, Hinsley et al 2008, and timber quantification (Holmgren and Jonsson 2004, Naesset 2004, Parker and Evans 2007. Research conducted specifically in Ontario has focused on estimating forest inventory and biophysical variables for tolerant northern hardwoods (Lim et al 2001(Lim et al , 2002(Lim et al , 2003Todd et al 2003;Lim and Treitz 2004;Woods et al 2008), boreal mixedwoods (Thomas et al 2006(Thomas et al , 2008 and conifer plantations (Chasmer et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Operational implementation of a LiDAR inventory in Boreal Ontario

Woods

Pitt

Penner

et al. 2011

The Forestry Chronicle

128

View full text Add to dashboard Cite

An existing Light Detection and Ranging (LiDAR) data set captured on the Romeo Malette Forest near Timmins, Ontario, was used to explore and demonstrate the feasibility of such data to enrich existing strategic forest-level resource inventory data. Despite suboptimal calibration data, stand inventory variables such as top height, average height, basal area, gross total volume, gross merchantable volume, and above-ground biomass were estimated from 136 calibration plots and validated on 138 independent plots, with root mean square errors generally less than 20% of mean values. Stand densities (trees per ha) were estimated with less precision (30%). These relationships were used as regression estimators to predict the suite of variables for each 400-m 2 tile on the 630 000-ha forest, with predictions capable of being aggregated in any user-defined manner-for a stand, block, or forest-with appropriate estimates of statistical precision. This pilot study demonstrated that LiDAR data may satisfy growing needs for inventory data to scale operational/tactical, through strategic needs, as well as provide spatial detail for planning and the optimization of forest management activities.Key words: forest inventory, Light Detection and Ranging (LiDAR), models, Seemingly Unrelated Regression RÉSUMÉ Un ensemble de données LiDAR (télédétection par laser) recueillies pour la Forêt Roméo Malette près de Timmins en Ontario, a été utilisé pour étudier et démontrer la possibilité d'utiliser ces données pour enrichir les données existantes d'inventaire des ressources forestières de premier plan. Malgré une calibration des données inférieure à ce qui était souhaité, les variables d'inventaire des peuplements comme la hauteur moyenne supérieure, la hauteur moyenne, la surface terrière, le volume brut total, le volume marchand total et la biomasse au-dessus du sol ont été estimées à partir de 136 parcelles de calibration et validées pour 138 parcelles indépendantes, avec une erreur quadratique moyenne géné-ralement inférieure à 20 % des valeurs moyennes. La densité des peuplements (arbres par hectare) a été estimée avec moins de précision (30 %). Ces relations ont été utilisées comme estimateurs de régressions utilisées pour générer une série de variables pour chaque unité de 400 m 2 de la forêt de 630 000 ha, avec des prédictions cumulables selon la requête de l'utilisateur-pour un peuplement, pour un bloc ou pour la forêt-avec des estimations appropriées d'une précision statistique. Ce projet pilote a démontré que les données LiDAR pourraient répondre aux besoins sans cesse croissants en matière de données d'inventaire pour définir les plans opérationnels/tactiques, bien que stratégiques, ainsi que pour établir les détails spatiaux requis pour la planification et l' optimisation des activités d'aménagement forestier.

show abstract

Stream network modelling using lidar and photogrammetric digital elevation models: a comparison and field verification

Cited by 129 publications

References 24 publications

Evaluating topographic wetness indices across central New York agricultural landscapes

Evaluating topographic wetness indices across central New York agricultural landscapes

Land use and wetland drainage affect water levels and dynamics of remaining wetlands

Operational implementation of a LiDAR inventory in Boreal Ontario

Contact Info

Product

Resources

About