Mark J. Chopping

Quantifying landscape structure: a review of landscape indices and their application to forested landscapes

An important assumption of many environmental decisions is that some patterns or combinations of land cover are optimal or more preferable to others. Management plans fre quently seek to change the structure of a landscape to realise particular management goals, because it is recognized that the spatial arrangement of elements in a land cover mosaic control the ecological processes which operate within it. This study reviews some of the tools available to those who need to describe and understand the spatial structure of landscapes. In particular, it examines the way in which quantitative measures, or indices, can be used and what contri bution they might make to the management of forested landscapes in the UK. The paper dis cusses the way in which the different landscape indices can be used to assess the spatial impli cations of the various design guidelines that have been proposd to promote sustainable forms of forestry. It is concluded that while progress has been made in the development of a range of landscape pattern measures, and in our understanding of the factors constraining their use, there is a pressing need for further research into the relationship between landscape pattern and ecological process.

Characterizing the urban heat island in current and future climates in New Jersey

Abstract Climate change caused by increased anthropogenic emissions of carbon dioxide (CO2) and other greenhouse gases is a long-term climate hazard with the potential to alter the intensity, temporal pattern, and spatial extent of the urban heat island (UHI) in metropolitan regions. Particular meteorological conditions—including high temperature, low cloud cover, and low average wind speed—tend to intensify the heat island effect. Analyses of existing archived climate data for the vicinities of Newark and Camden, New Jersey indicate urban to suburban/rural temperature differences over the previous half-century. Surface temperatures derived from a Landsat thermal image for each site were also analyzed for spatial patterns of heat islands. Potential interactions between the UHI effect and projected changes in temperature, wind speed, and cloud cover are then examined under a range of climate change scenarios, encompassing different greenhouse gas emissions trajectories. The scenarios include those utilized in the Metropolitan East Coast Regional Assessment of Climate Variability and Change and the A2 and B2 scenarios of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). The UHI effect was detected in Newark and Camden in both satellite surface-temperature and meteorological station airtemperature records. The average difference in urban—nonurban minimum temperatures was 3.0 °C for the Newark area and 1.5 °C for Camden. Extrapolation of current trends and the selected global climate models (GCMs) project that temperatures in the case study areas will continue to warm in the current century, as they have over the past half-century. An initial analysis of global climate scenarios shows that wind speed may decline, and that cloud cover may increase in the coming decades. These generally small countervailing tendencies suggest that urban—nonurban temperature differences may be maintained under climate change. Overall warmer conditions throughout the year may extend the spatial and temporal dimensions of the urban-suburban heat complex. The incidence of heat-related morbidity and mortality are likely to increase with interactions between the increased frequency and duration of heat waves and the UHI effect. Camden and Newark will likely be subjected to higher temperatures, and areas experiencing UHI-like conditions and temperature extremes will expand. Thus, urban heat island-related hazard potential is likely to increase in a warmer climate.

Morphological characteristics of shrub coppice dunes in desert grasslands of southern New Mexico derived from scanning LIDAR

Abstract Since the 1880s rangeland vegetation in southern New Mexico has changed dramatically over widespread areas, typically with shrublands displacing native grasslands. Coincident with these changes in vegetation dominance are increases in soil erosion, stream channel cutting, and shrub coppice dune formation on sandy soils. Where marked transitions in vegetation type from grassland to honey mesquite shrubland have occurred, the local topography has been transformed with previously flat mesa becoming rolling duneland. The size, distribution, and morphological characteristics of these dunes have an important impact on fluxes of energy and nutrients at the surface; they also render the land far less useful as grazing land for domestic livestock. These shrub coppice dunes and the mesquite shrubs that grow on them may be considered roughness elements. Quantifying their morphology is important for the calculation of aerodynamic roughness length and displacement height. This article tests the ability of active scanning laser remote sensing techniques to provide accurate estimates of the three-dimensional shapes and areal distributions of dune and interdune areas. It shows that scanning laser with a footprint diameter of 0.38 m and a sampling interval of 1.5 m to 2 m can be used to measure the morphological characteristics of shrub coppice dunes in the desert grasslands of southern New Mexico with acceptable accuracy and precision for a range of uses, including important geomorphological and hydrological applications. The use of scanning laser systems together with optical multispectral data is shown to be highly synergistic, providing information that is not easily obtainable via other surveying methods.

Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery

Abstract The surface bidirectional reflectance distribution function (BRDF) contains valuable information on canopy physiognomy for desert grassland and grass–shrub transition communities. This information may be accessed by inverting a BRDF model against sets of observations, which encompass important variations in viewing and illumination angles. This paper shows that structural canopy attributes can be derived through inversion of the Simple Geometric Model (SGM) of the BRDF developed in this paper. It is difficult to sample BRDF features from the ground because of the discontinuous nature of the canopies and long intrinsic length scales in remotely sensed spectral measures (>10 m). A multispectral digital camera was therefore used to derive spatial multiangular reflectance data sets from the air and the SGM was validated against and inverted with these. It was also validated using 3-D radiosity simulations driven with maps of field-measured plant dimensions. The interpretation of the retrieved parameter maps (shrub density, shrub width and canopy height) reveals variations in canopy structure within desert grassland and grassland–shrubland transition communities, which are clearly related to structural and optical features in high resolution panchromatic and vegetation index images. To our knowledge, this paper reports on the first attempts to acquire structural canopy attributes of desert landscapes using multiple view angle data at scales less than 1 km. The results point to further opportunities to exploit multiangular data from spaceborne sensors such as the Multiangle Imaging SpectroRadiometer (MISR) and the Compact High Resolution Imaging Spectrometer (CHRIS) on the NASA Terra and European Space Agencys PROBA satellites, respectively.

Testing a LiSK BRDF Model with in Situ Bidirectional Reflectance Factor Measurements over Semiarid Grasslands

Abstract The non-Lambertian nature of the terrestrial surface is a major source of unexplained variability in wide-swath satellite sensor data acquired in the solar reflective wavelengths, hindering quantitative analysis in the spectral, temporal, and locational domains. The interactions of light with the surface are governed by the bidirectional reflectance distribution function (BRDF), and modeling this is one of the most promising methods for describing and explaining this variability. Here the Roujean linear semiempirical kernel-driven (LiSK) model was tested against two independent bidirectional reflectance factor datasets that were acquired close to ground level over seminatural semiarid grasslands in Xilingol, Inner Mongolia (Peoples Republic of China) and in Arizona (United States). The objectives were to determine how well the model is able to describe and explain observed bidirectional reflectance factor distributions in the red and near-infrared wavelengths, to explore its utility in correcting such data for angular variations, and the likely impact of such corrections on cover-type discrimination. The sensitivity of the model to reductions in the number and angular distribution of the bidirectional reflectance observations with which it is inverted was also evaluated. The results show that the model is able to describe the observed multiangular BRFs with good accuracy and with low sensitivity to the number of angular inputs, with observations in the forward-scattering direction shown to be important in constraining inversions. The behavior of retrieved parameters indicates that one or more of the simplifying assumptions made in the model derivation is likely to be too severe for explaining BRDF in the near-infrared region; non-negligible anisotropic multiple scattering and the assumption of an optically thick medium mean that a physical interpretation of parameters is unlikely to be valid. However, the model is shown to provide an effective means of correcting for BRDF effects, allowing greater precision and consistency than hitherto possible in the retrieval of surface spectral reflectance over semiarid grasslands and concrete improvements in cover-type discrimination.

Forest Canopy Cover and Height From MISR in Topographically Complex Southwestern US Landscapes Assessed With High Quality Reference Data

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern US forests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are avail- able. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery using the CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50%, 75%, and 100% energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns of MISR 672 nm band surface reflectance (mean RMSE = 0.011, mean R2 = 0.82, N = 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid. The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with R2 of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Large-scale BRDF retrieval over New Mexico with a multiangular NOAA AVHRR dataset

Abstract In this study a number of linear semiempirical kernel-driven (LiSK) bidirectional reflectance distribution function (BRDF) models are adjusted against an extensive Advanced Very High Resolution Radiometer (AVHRR) dataset collected over a variety of semiarid cover types in the southern part of New Mexico and parts of Chihuahua, Mexico as part of the May 1997 Prototype Validation Exercise (PROVE) campaign, an activity of the NASA Earth Observing System Terra validation program. The aim is to investigate model behavior under conditions of sparse angular sampling such as that provided by the AVHRRs and MODIS over a wide variety of southwestern desert surface types. Linear semiempirical models of the type to be used in the MODIS/MISR BRDF/albedo product (MOD43) are inverted, since these are appropriate for use over large areas. The results of the inversions show that these models are able to describe BRDF for a wide variety of surfaces and provide both a means for correcting for directional phenomena in satellite data and for extracting structural information from multiangular reflectance datasets.

CANAPI: canopy analysis with panchromatic imagery

The validation of remotely sensed canopy structural parameters derived from moderate resolution imaging is a perennial problem because it is very expensive to undertake field measurements at scales of 250 m and above. High-resolution imaging and airborne light detection and ranging (lidar) systems are widely used sources of reference data, with the former used to delineate crowns and the latter to estimate tree heights and other statistics. A simple yet effective automated method that provides mapped tree crown cover, radii and height estimates from high-resolution panchromatic images of large dimensions – CANopy Analysis from Panchromatic Imagery (CANAPI) – is presented, together with comparisons with QuickBird 0.6 m spatial resolution imagery, field inventory data and lidar canopy height estimates from the NASA Laser Vegetation Imaging Sensor (LVIS) for forest sites in the Sierra National Forest in California. The method was developed as an ImageJ macro using simple image processing functions and is easily extended. It has some limitations but is likely to be useful in analysing open and semiopen forest and shrub canopies where the illumination is oblique.

Improved semi-arid community type differentiation with the NOAA AVHRR via exploitation of the directional signal

Mapping semi-arid vegetation types at the community level is extremely difficult for optical sensors with large ground footprints such as the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). Attempts to use solar wavelength AVHRR data in community type differentiation have often resulted in unacceptable classification errors which are usually attributed to noise from topographic and soil background variations, inaccurate reflectance retrieval and poor registration. One source of variation which is rarely accounted for adequately is the directional signal resulting from the combined effects of the surface bidirectional reflectance distribution function (BRDF) and the variation of viewing and illumination geometry as a function of scan angle, season, latitude and orbital overpass time. In this study, a linear semiempirical kernel-driven BRDF model is used to examine the utility:of the directional signal in community and cover type differentiation over discontinuous but statistically homogeneous semi-arid canopies in Inner Mongolia Autonomous Region, China, and New Mexico, USA. This research shows that the directional signal resulting from the physical structure of the canopy-soil complex can be retrieved to provide information which is highly complementary to that obtained in the spectral domain.

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi-arid region with MISR imagery

In this study we show that multiangle remote sensing is useful for increasing the accuracy of vegetation community type mapping in desert regions. Using images from the National Aeronautics and Space Administration (NASA) Multiangle Imaging Spectroradiometer (MISR), we compared roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with those played by topographic parameters in improving vegetation community type classifications for the Jornada Experimental Range and the Sevilleta National Wildlife Refuge in New Mexico, USA. The BRDF models used were the Rahman–Pinty–Verstraete (RPV) model and the RossThin‐LiSparseReciprocal (RTnLS) model. MISR nadir multispectral reflectance was considered as baseline because nadir observation is the most basic remote sensing observation. The BRDF model parameters and the topographic parameters were considered as additional data. The BRDF model parameters were obtained by inversion of the RPV model and the RTnLS model against the MISR multiangle reflectance data. The results of 32 classification experiments show that the BRDF model parameters are useful for vegetation mapping; they can be used to raise classification accuracies by providing information that is not available in the spectral‐nadir domain, or from ancillary topographic parameters. This study suggests that the Moderate Resolution Imaging Spectroradiometer (MODIS) and MISR BRDF model parameter data products have great potential to be used as additional information for vegetation mapping.