Surface Roughness Parameterization Using Land Use / Land Cover Enhanced by Lidar Point Cloud Data

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Using lidar remote sensing and support vector machines to classify fire disturbance legacies in a Florida oak scrub landscape

Background/Question/Methods

Ecologists have long emphasized the reciprocal interactions between spatial pattern and ecological processes in the creation of landscape mosaics. While an enormous amount of recent research has focused on the quantification of spatial patterns, efforts to infer process from pattern have been hindered by the presence of multi-scale, often confounding, drivers of pattern in many landscapes. At the mesoscale, Holling’s extended keystone hypothesis posits that spatially contagious disturbances such as fire are the dominant pattern-generating processes. To test this hypothesis, we used fire history data and discrete, small-footprint lidar remote sensing acquired over a 22 sq. km landscape of oak scrub in the Kennedy Space Center/Merritt Island National Wildlife Refuge area on the east-central coast of Florida. We binned the lidar return data into 1 m vertical height intervals for each 5 m x 5 m horizontal cell. Since community structure tends to recover by 7 years post-fire, we tested for significant differences between recently-burned (< 7 years) and unburned (≥ 7 years) patches with multivariate analysis of variance. To predict the burn status of each cell, we then used distribution-free, nonlinear support vector machine (SVM) classifiers, which have proven to be highly accurate for complex pattern recognition problems.

Results/Conclusions 

We detected statistically significant differences in vegetation structure between burned and unburned patches for all of the dominant land cover types (upland non-forested, upland forested, wetland hardwood forest, and non-forested wetlands) in the study area. Initially, we obtained a predicted error rate of approximately 34% from the SVM classifier; by averaging the binned lidar data over a moving window of increasing size, however, we achieved substantial reductions in the predicted error rate for the SVM classifier. The optimal window size of 100 m x 100 m yielded a predicted misclassification rate of approximately 3%, an order of magnitude lower than the error rate obtained on the same data using a logistic regression classifier. These results suggest that, as predicted by the extended keystone hypothesis, fire disturbance is a dominant pattern-generating process at the patch scale in this oak scrub landscape. Furthermore, these results indicate that it is possible to use vertical vegetation structure, as represented by the binned lidar data, to predict burn status with a high level of accuracy. While our study employed a simple binary classification scheme, future research will focus on using SVM regression techniques to predict burn status with finer-grained classes of time since fire

Use of Airborne LiDAR to Delineate Canopy Degradation and Encroachment along the Guatemala-Belize Border

Tropical rainforest clearing and degradation significantly reduces carbon sequestration and increases the rate of biodiversity loss. There has been a concerted international effort to develop remote sensing techniques to monitor broad-scale patterns of forest canopy disturbance. In addition to loss of natural resources, recent deforestation in Mesoamerica threatens historic cultural resources that for centuries lay hidden below the protective canopy. Here, we compare satellite-derived measures of canopy disturbance that occurred over a three decade period since 1980 to those derived from a 2009 airborne LiDAR campaign over the Caracol Archaeological Reserve in western Belize. Scaling up fine-resolution canopy height measures to the 30 m resolution of Landsat Thematic Mapper, we found LiDAR revealed a \u3e58% increase in the extent of canopy disturbance where there was an overlap of the remotely sensed data sources. For the entire archaeological reserve, with the addition of LiDAR, there was a 2.5% increase of degraded canopy than estimated with Landsat alone, indicating that 11.3% of the reserve has been subjected to illegal selective logging and deforestation. Incursions into the reserve from the Guatemala border, represented by LiDAR-detected canopy disturbance, extended 1 km deeper (to 3.5 km) into Belize than were derived with Landsat. Thus, while LiDAR enables a synoptic, never-seen-before, below-canopy view of the Maya city of Caracol, it also reveals the degree of canopy disturbance and potential looting of areas yet to be documented by archaeologists on the ground

Multiple source pools and dispersal barriers for Galapagos plant species distribution

We reexamined geographic factors explaining the number of plant species on islands in the Galapagos Archipelago. We hypothesized that plant species richness (S) was related to the number of source pools and that plant species dispersal preferentially followed direct, oceanic pathways. To test different dispersal pathways from multiple source pools, the total number of islands within a given dispersal radius (i) was posed as the sum of the number of line-of-sight islands (C-i) and of the number of islands without line-of-sight connection (B-i). In partial regression analyses, controlling for nearest island area (A(2)) and for recipient island elevation (E) and area (InA), C-i and C-i x E were found to be positively correlated with S in the Galapagos for nearly all dispersal ranges from 10 km to 419 km (maximum inter-island separation). In contrast, B-i x E was negatively correlated with S at the longest dispersal ranges. The connectivity index, C-i, multiplied by elevation, E, explained more variation in S in the Galapagos than prior regression models using additive forms of E, InA, A(2), and isolation from the central island. Using the variables C-i x E and InA, multiple-regression models explained \u3e 90% of the variance in both endemic and total plant species richness in the Galapagos Archipelago

Dune vegetation fertilization by nesting sea turtles

Sea turtle nesting presents a potential pathway to subsidize nutrient-poor dune ecosystems, which provide the nesting habitat for sea turtles. To assess whether this positive feedback between dune plants and turtle nests exists, we measured N concentration and delta N-15 values in dune soils, leaves from a common dune plant ( sea oats [Uniola paniculata]), and addled eggs of loggerhead (Caretta caretta) and green turtles ( Chelonia mydas) across a nesting gradient ( 200 - 1050 nests/km) along a 40.5-km stretch of beach in east central Florida, USA. The delta N-15 levels were higher in loggerhead than green turtle eggs, denoting the higher trophic level of loggerhead turtles. Soil N concentration and delta N-15 values were both positively correlated to turtle nest density. Sea oat leaf tissue delta N-15 was also positively correlated to nest density, indicating an increased use of augmented marine-based nutrient sources. Foliar N concentration was correlated with delta N-15, suggesting that increased nutrient availability from this biogenic vector may enhance the vigor of dune vegetation, promoting dune stabilization and preserving sea turtle nesting habitat

Using Lidar-Derived Vegetation Profiles to Predict Time since Fire in an Oak Scrub Landscape in East-Central Florida

Disturbance plays a fundamental role in determining the vertical structure of vegetation in many terrestrial ecosystems, and knowledge of disturbance histories is vital for developing effective management and restoration plans. In this study, we investigated the potential of using vertical vegetation profiles derived from discrete-return lidar to predict time since fire (TSF) in a landscape of oak scrub in east-central Florida. We predicted that fire influences vegetation structure at the mesoscale (i.e., spatial scales of tens of meters to kilometers). To evaluate this prediction, we binned lidar returns into 1m vertical by 5 x 5 m horizontal cells and averaged the resulting profiles over a range of horizontal window sizes (0 to 500 m on a side). We then performed a series of resampling tests to compare the performance of support vector machine (SVM), k-nearest neighbor (k-NN), logistic regression, and linear discriminant analysis (LDA) classifiers and to estimate the amount of training data necessary to achieve satisfactory performance. Our results indicate that: (1) the SVMs perform significantly better than the other classifiers, (2) SVM classifiers may require relatively small training data sets, and (3) the highest classification accuracies occur with averaging over windows representing sizes in the mesoscale range

Inferring Foraging Areas of Nesting Loggerhead Turtles Using Satellite Telemetry and Stable Isotopes

In recent years, the use of intrinsic markers such as stable isotopes to link breeding and foraging grounds of migratory species has increased. Nevertheless, several assumptions still must be tested to interpret isotopic patterns found in the marine realm. We used a combination of satellite telemetry and stable isotope analysis to (i) identify key foraging grounds used by female loggerheads nesting in Florida and (ii) examine the relationship between stable isotope ratios and post-nesting migration destinations. We collected tissue samples for stable isotope analysis from 14 females equipped with satellite tags and an additional 57 untracked nesting females. Telemetry identified three post-nesting migratory pathways and associated non-breeding foraging grounds: (1) a seasonal continental shelf-constrained migratory pattern along the northeast U. S. coastline, (2) a non-breeding residency in southern foraging areas and (3) a residency in the waters adjacent to the breeding area. Isotopic variability in both delta C-13 and delta N-15 among individuals allowed identification of three distinct foraging aggregations. We used discriminant function analysis to examine how well delta C-13 and delta N-15 predict female post-nesting migration destination. The discriminant analysis classified correctly the foraging ground used for all but one individual and was used to predict putative feeding areas of untracked turtles. We provide the first documentation that the continental shelf of the Mid-and South Atlantic Bights are prime foraging areas for a large number (61%) of adult female loggerheads from the largest loggerhead nesting population in the western hemisphere and the second largest in the world. Our findings offer insights for future management efforts and suggest that this technique can be used to infer foraging strategies and residence areas in lieu of more expensive satellite telemetry, enabling sample sizes that are more representative at the population level

Detection and Morphologic Analysis of Potential Below-Canopy Cave Openings in the Karst Landscape around the Maya Polity of Caracol using AirborneLidar

Locating caves can be difficult, as their entranceways are often obscured below vegetation. Recently, active remote-sensing technologies, in particular laser-based sensor systems (LiDARs), have demonstrated the ability to penetrate dense forest canopies to reveal the underlying ground topography. An airborne LiDAR system was used to generate a 1 m resolution, bare-earth digital elevation model (DEM) from an archaeologically- and speleologically-rich area of western Belize near the ancient Maya site of Caracol. Using a simple index to detect elevation gradients in the DEM, we identified depressions with at least a 10 m change within a circular area of no more than 25 m radius. Across 200 km 2 of the karst landscape, we located 61 depressions. Sixty of these had not been previously documented; the other was a cave opening known from a previous expedition. The morphologies of the depressions were characterized based on the LiDAR-derived DEM parameters, e.g., depth, opening area, and perimeter. We also investigated how the measurements change as a function of spatial resolution. Though there was a range of morphologies, most depressions were clustered around an average maximum depth of 21 m and average opening diameter of 15 m. Five depression sites in the general vicinity of the Caracol epicenter were visited; two of these were massive, with opening diameters of ∼50 m, two could not be explored for lack of climbing gear, and one site was a cave opening into several chambers with speleothems and Maya artifacts. Though further investigation is warranted to determine the archaeological and geological significance of the remaining depressions, the general methodology represents an important advancement in cave detection

Ancient Maya Regional Settlement and Inter-Site Analysis: The 2013 West-Central Belize LiDAR Survey

During April and May 2013, a total of 1057 km2 of LiDAR was flown by NCALM for a consortium of archaeologists working in West-central Belize, making this the largest surveyed area within the Mayan lowlands. Encompassing the Belize Valley and the Vaca Plateau, West-central Belize is one of the most actively researched parts of the Maya lowlands; however, until this effort, no comprehensive survey connecting all settlement had been conducted. Archaeological projects have investigated at least 18 different sites within this region. Thus, a large body of archaeological research provides both the temporal and spatial parameters for the varied ancient Maya centers that once occupied this area; importantly, these data can be used to help interpret the collected LiDAR data. The goal of the 2013 LiDAR campaign was to gain information on the distribution of ancient Maya settlement and sites on the landscape and, particularly, to determine how the landscape was used between known centers. The data that were acquired through the 2013 LiDAR campaign have significance for interpreting both the composition and limits of ancient Maya political units. This paper presents the initial results of these new data and suggests a developmental model for ancient Maya polities