The impact of subsurface conceptualization on land energy fluxes

There is a significant body of work demonstrating the importance of hydrologic control on land energy feedbacks. Yet, quantitative data on aquifer conductivity can be difficult to assemble. Furthermore, how subsurface uncertainty propagates into land-surface processes is not well understood. This study analyzes the impact of aquifer characterization on land energy fluxes, using a coupled hydrology–land-surface model. Four gridded subsurface conductivity fields are developed for the Upper Klamath basin using two data sources and different levels of imposed heterogeneity. Each model is forced with the same transient, observed meteorology for 3 years prior to the final year presented here. Results are analyzed to quantify the impact of subsurface heterogeneity on groundwater surface water interactions and spatial patterns in hydrologic variables. Analysis shows that heterogeneity does not fundamentally alter the connection between groundwater and land surface processes. However, differences between scenarios impact the extent and location of the critical zone.     

Predicting Diel,Diurnal and Nocturnal Dynamics of Dissolved Oxygen and Chlorophyll‐a Using Regression Models and Neural Networks

Human‐induced and natural interruptions with continuous streams of observational data necessitate the development of gap‐filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non‐linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll‐a (chl‐a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO ($r_{{\rm adj}}^{2} = 68.8\%$ ). The ANN‐based predictions had a higher predictive power than the MNLR‐based predictions for both chl‐a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl‐a, generalized feedforward (GFF) for diurnal and nocturnal chl‐a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.     

基于LiDAR的解析空中三角测量像控点提取研究

提出了一种利用雷达数据解算航空影像的方法,即在航空摄影测量过程中用规则建筑物顶面中心作为控制点,代替传统摄影测量中的像控点。LiDAR数据中导出的中心点相当于一个带有3维坐标的单个点,能够用于空中三角测量系统,从而省去外业像控测量的步骤。利用LiDAR数据作为地面控制点进行空中三角测量的控制点加密,验证了方法的可行性,证明了LiDAR参考系中规则顶面中心点作为控制点进行空三加密可以满足丘陵地区1∶5 000比例尺成图要求。     

基于VRML的层状地质体3维建模

为了形象地表现层状地质体形态,本文利用VRML在虚拟环境中建立了3维地质体。根据层状地质体的实际情况,本文利用VRML中的几何形体建模节点ElevationGrid和IndexedFaceSet创建了3维地质体的虚拟现实模型。该方法利用钻孔数据获取层面数据,使用Surfer软件进行数据插值,得到网格化数据文件,用网格化文件与ElevationGrid节点相结合,模拟地质体上下表面,用IndexedFaceSet节点建立两层表面边界,从而构成一个视觉上闭合的3维实体。最后用此方法建立了层状地质体的虚拟现实模型实例。     

Modeling the morphology of gully cross sections in the Yuanmou Dry-hot Valley

Abstract

Characterizing gully cross sections (GCs) is essential for calculating the volume and erosion rate of the gully. However, little research has focused on modeling the morphology of GCs. This study investigated 456 GCs with a laser distance meter located at the mouth, middle, and head of 152 gullies in the Yuanmou Dry-hot Valley of China; mapped them with AutoCAD software; fitted them with 2nd–6th degree polynomial functions, and discussed the correlation between the coefficients and the morphology of GCs. The results showed that: (1) using a 2nd-degree polynomial function (y = ax² + bx + c) to describe the morphology of GCs produced a better result than other polynomial functions; (2) the coefficient a of 2nd-degree polynomial function was correlated with depth (r = ?0.226, p < 0.01), gradient (r = 0.545, p < 0.01), and activities; and (3) the symmetry axis (?b/2a) of 2nd-degree polynomial function increased with gully change from left-deflection to right-skewed, and the absolute value showed the asymmetrical degree (r = 0.216, p < 0.01). This study will not only help to understand the morphology and evolution of gullies, but will also provide a scientific basis for prevention of gully erosion.     

Cartographically Wordy but not Necessarily Worthy

Abstract

A novel method called multidirectional visibility index (MVI) has been developed and verified. The MVI improves standard cartographic analytical shading with a number of enhancements to topographic detail and prominent structures, i.e. the portrayal of flat areas in lighter tones, the accentuation of morphologic edges, and the multiscale visualisation of morphologic terrain features. The procedure requires a digital elevation model (DEM) and involves the following steps: visibility mask computation; the respective multidirectional altering of the azimuth and elevation angle; the generation of continuous grid MVIs that indicate upper/lower views, quasi-slope, and relative relief; and an appropriate visualisation of the relevant MVI as a standalone technique or in combination with standard hill-shaded relief. The modelling parameters are robust and therefore highly adaptive to different landforms.     

A novel approach to estimate canopy height using ICESat/GLAS data: A case study in the New Forest National Park,UK

The Geoscience Laser Altimeter System (GLAS) aboard Ice, Cloud and land Elevation Satellite (ICESat) is a spaceborne LiDAR sensor. It is the first LiDAR instrument which can digitize the backscattered waveform and offer near global coverage. Among others, scientific objectives of the mission include precise measurement of vegetation canopy heights. Existing approaches of waveform processing for canopy height estimation suggest Gaussian decomposition of the waveform which has the limitation to properly characterize significant peaks and results in discrepant information. Moreover, in most cases, Digital Terrain Models (DTMs) are required for canopy height estimation. This paper presents a new automated method of GLAS waveform processing for extracting vegetation canopy height in the absence of a DTM. Canopy heights retrieved from GLAS waveforms were validated with field measured heights. The newly proposed method was able to explain 79% of variation in canopy heights with an RMSE of 3.18 m, in the study area. The unexplained variation in canopy heights retrieved from GLAS data can be due to errors introduced by footprint eccentricity, decay of energy between emitted and received signals, uncertainty in the field measurements and limited number of sampled footprints.Results achieved with the newly proposed method were encouraging and demonstrated its potential of processing full-waveform LiDAR data for estimating forest canopy height. The study also had implications on future full-waveform spaceborne missions and their utility in vegetation studies.     

Backscattering of individual LiDAR pulses from forest canopies explained by photogrammetrically derived vegetation structure

In recent years, airborne LiDAR sensors have shown remarkable performance in the mapping of forest vegetation. This experimental study looks at LiDAR data at the scale of individual pulses to elucidate the sources behind interpulse variation in backscattering. Close-range photogrammetry was used for obtaining the canopy reference measurements at the ratio scale. The experiments illustrated different orientation techniques in the field, LiDAR acquisitions and photogrammetry in both leaf-on and leaf-off conditions, and two-waveform recording LiDAR sensors. The intrafootprint branch silhouettes in zenith-looking images, in which the camera, footprint, and LiDAR sensor were collinear, were extracted and contrasted with LiDAR backscattering. An enhanced planimetric match (refinement of strip matching) was achieved by shifting the pulses in a strip and searching for the maximal correlation between the silhouette and LiDAR intensity. The relative silhouette explained up to 80–90% of the interpulse variation. We tested whether accounting for the Gaussian spread of intrafootprint irradiance would improve the correlations, but the effect was blurred by small-scale geometric noise. Accounting for receiver gain variations in the Leica ALS60 sensor data strengthened the dependences. The size of the vegetation objects required for triggering a LiDAR observation was analyzed. We demonstrated the use of LiDAR pulses adjacent to canopy vegetation, which did not trigger a canopy echo, for canopy mapping. Pulses not triggering an echo constitute the complement to the actual canopy. We conclude that field photogrammetry is a useful tool for mapping forest canopies from below and that quantitative analysis is feasible even at the scale of single pulses for enhanced understanding of LiDAR observations from vegetation.