Greg McCarty

Lidar Intensity for Improved Detection of Inundation below the Forest Canopy

Wetland hydrology is an important factor controlling wetland function and extent, and should therefore be a vital part of any wetland mapping program. Broad-scale forested wetland hydrology has been difficult to study with conventional remote sensing methods. Airborne Light Detection and Ranging (LiDAR) is a new and rapidly developing technology. LiDAR data have mainly been used to derive information on elevation. However, the intensity (amplitude) of the signal has the potential to significantly improve the ability to remotely monitor inundation — an important component of wetland hydrology. A comparison between LiDAR intensity data collected during peak hydrologic expression and detailedin situ data from a series of forested wetlands on the eastern shore of Maryland demonstrate the strong potential of LiDAR intensity data for this application (>96% overall accuracy). The relative ability of LiDAR intensity data for forest inundation mapping was compared with that of a false color near-infrared aerial photograph collected coincident with the LiDAR intensity (70% overall accuracy; currently the most commonly used method for wetland mapping) and a wetness index map derived from a digital elevation model. The potential of LiDAR intensity data is strong for addressing issues related to the regulatory status of wetlands and measuring the delivery of ecosystem services.

Short-term effects of tillage on mineralization of nitrogen and carbon in soil

Abstract Tillage is known to decrease soil organic nitrogen (N) and carbon (C) pools with negative consequences for soil quality. This decrease is thought partly to be caused by exposure of protected organic matter to microbial degradation by the disturbance of soil structure. Little is known, however, about the short-term effects of tillage on mineralization of N and C, and microbial activity. We studied the short-term effects of two types of tillage (conventional plough- and a non-inverting-tillage) on mineralization and microbial N and C pools in a sandy loam under organic plough-tillage management. The release of active and protected (inactive) N by tillage was further studied in the laboratory by use of 15 N labelling of the active pool of soil N followed by simulation of tillage by sieving through a 2 mm sieve. Results showed that the two types of tillage as well as the simulation of tillage had very few effects on mineralization and microbial pools. The simulation of tillage caused, however, a small release of N from a pool which was otherwise protected against microbial degradation. The use of soil crushing for disruption of larger macroaggregates (>425 μm) and chloroform fumigation for perturbation of the microbial biomass increased the release from both active and protected N pools. The relative contribution from the protected N pool was, however, similar in the three treatments (22–27%), thus the pools subjected to mineralization were characterised by similar degree of protection. On the basis of isotopic composition the pools of N mineralised were indistinguishable. This suggests that the released N originated from the same pool, that is the soil microbial biomass. The study points to the microbial pool as the main source of labile N which may be released by tillage, and thus to its importance for sustained soil fertility in agricultural systems.

Relationships between total-N, biomass-N and active-N in soil under different tillage and N fertilizer treatments

Studies assessing the effects of tillage and N fertilizer treatments on relationships between different N pools in soil can provide information concerning the influence of such treatments on the distribution of N in agricultural soils. To assess the effects of treatments on relationships between total-N, biomass-N and active-N in soil, these N pools were measured in samples of soil collected at different depths (0–2.5, 2.5–7.5 and 7.5–15 cm) from long-term field experiments located in two geographic regions (piedmont and coastal plain) and containing plots under annual treatments of plow-or no-tillage and 0 or 135 kg ha−1 of fertilizer N. Results showed that whereas geographic location, N fertilization and depth generally had little influence on the slopes of regression lines describing the linear relationships between total-N, biomass-N and active-N, tillage had a marked influence on these slopes. Such results indicated that tillage may substantially influence the distribution of N among different pools within agricultural soils. The overall results for linear regressions indicated that the active-N pool, as measured by an isotope-dilution method, was very closely related (r = 0.96) to the biomass-N pool, as measured by a fumigation-incubation method, but that measurements for the active-N pool were approximately twice those for the biomass-N pool. These observations suggested that such methods may measure a common pool of soil N, but place substantially different bounds on the size of this N pool.

Topographic Metrics for Improved Mapping of Forested Wetlands

We investigated the predictive strength of forested wetland maps produced using digital elevation models (DEMs) derived from Light Detection and Ranging (LiDAR) data and multiple topographic metrics, including multiple topographic wetness indices (TWIs), a TWI enhanced to incorporate information on water outlets, normalized relief, and hybrid TWI/relief in the Coastal Plain of Maryland. LiDAR DEM based wetland maps were compared to maps of inundation and existing wetland maps. TWIs based on the most distributed FD8 (8 cells) and somewhat distributed D∞ (1–2 cells) flow routing algorithms were better correlated with inundation than a TWI based on a non-distributed D8 (1 cell) flow routing algorithm, but D∞ TWI class boundaries appeared artificial. The enhanced FD8 TWI provided good prediction of wetland location but could not predict periodicity of inundation. Normalized relief provided good prediction of inundation periodicity but was less able to map wetland boundaries. A hybrid of these metrics provided good measurement of wetland location and inundation periodicity. Wetland maps based on topographic metrics included areas of flooded forest that were similar to an aerial photography based wetland map. These results indicate that LiDAR based topographic metrics have potential to improve accuracy and automation of wetland mapping.

Water quality and conservation practice effects in the Choptank River watershed

The Choptank River is an estuary, tributary of the Chesapeake Bay, and an ecosystem in decline due partly to excessive nutrient and sediment loads from agriculture. The Conservation Effects Assessment Project for the Choptank River watershed was established to evaluate the effectiveness of conservation practices on water quality within this watershed. Several measurement frameworks are being used to assess conservation practices. Nutrients (nitrogen and phosphorus) and herbicides (atrazine and metolachlor) are monitored within 15 small, agricultural subwatersheds and periodically in the lower portions of the river estuary. Initial results indicate that land use within these subwatersheds is a major determinant of nutrient concentration in streams. In addition, the 18O isotope signature of nitrate was used to provide a landscape assessment of denitrification processes in the presence of the variable land use. Herbicide concentrations were not correlated to land use, suggesting that herbicide delivery to the streams is influenced by other factors and/or processes. Remote sensing technologies have been used to scale point measurements of best management practice effectiveness from field to subwatershed and watershed scales. Optical satellite (SPOT-5) data and ground-level measurements have been shown to be effective for monitoring nutrient uptake by winter cover crops in fields with a wide range of management practices. Synthetic Aperture Radar (RADARSAT-1) data have been shown to detect and to characterize accurately the hydrology (hydroperiod) of forested wetlands at landscape and watershed scales. These multiple approaches are providing actual data for assessment of conservation practices and to help producers, natural resource managers, and policy makers maintain agricultural production while protecting this unique estuary.

NIR-Green-Blue High-Resolution Digital Images for Assessment of Winter Cover Crop Biomass

Many small unmanned aerial systems use true-color digital cameras for remote sensing. For some cameras, only the red channel is sensitive to near-infrared (NIR) light. Given a camera with this spectral capability, we modified it to obtain NIR-green-blue images. One advantage of this low-cost system is that images can be inspected directly from the camera. This camera was flown in a Piper Cub aircraft for estimating biomass of wheat and barley planted as winter cover crops. There was much greater variation in biomass within experimental strips than among strips, so correlations were not high. This research demonstrates the need to develop better calibration methods so inexpensive camera sensors can be used in precision agriculture.

Using satellite remote sensing to estimate winter cover crop nutrient uptake efficiency

Winter cover crops are recognized as an important agricultural conservation practice for reducing nitrogen (N) losses to groundwater following the summer growing season. Accordingly, cost-share programs have been established to promote winter cover crops for water quality on farms throughout the Chesapeake Bay watershed. However, current estimates of cover crop nutrient uptake are largely calculated from plot-scale studies extrapolated to watershed-scale based solely on enrollment acreage. Remote sensing provides a tool for rapid estimation of cover crop biomass production on working farms throughout the landscape. This project combined cost-share program enrollment data with satellite imagery and on-farm sampling to evaluate cover crop N uptake on 136 fields within the Choptank River watershed, on Marylands eastern shore. The Normalized Difference Vegetation Index was a successful predictor of aboveground biomass for fields with >210 kg ha−1 (>187 lb ac−1) of vegetation (corresponding to 4.2 kg ha−1 [3.7 lb ac−1] of plant N), below which the background reflectance of soils and crop residues obstructed the cover crop signal. Cover crops planted in the two weeks prior to the regional average first frost date (October 15) exhibited average fall aboveground N uptake rates of 18, 13, and 5 kg ha−1 (16, 12, 4 lb ac−1) for rye, barley, and wheat, respectively, corresponding to 1,260, 725, and 311 kg ha−1 (1,124, 647, 277 lb ac−1) of aboveground biomass, with associated cost-share implementation costs of

Nitrate fate and transport through current and former depressional wetlands in an agricultural landscape, Choptank Watershed, Maryland, United States

5.49,

Spatial variability of soil phosphorous levels before and after poultry litter application

7.60, and

Soil physicochemical conditions, denitrification rates, and abundance in north Carolina coastal plain restored wetlands.

19.77 kg−1 N (