How Good is Bicycling for the Environment?

Bicycling has been promoted as a means to reduce our dependence on climate-warming fossil fuel burning, clean the air in our streets, promote personal health, and fight widespread obesity. It is often postulated that there are obvious environmental benefits associated with increasing participation in cycling as a transportation alternative, since the bicycles’ fuel is the banana and/or the muffin. This presentation will discuss why mass bicycling might not be quite as good for the environment as you may imagine – though it is still very, very good indeed

Forest structure and aboveground biomass in the southwestern United States from MODIS and MISR

Red band bidirectional reflectance factor data from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) acquired over the southwestern United States were interpreted through a simple geometric–optical (GO) canopy reflectance model to provide maps of fractional crown cover (dimensionless), mean canopy height (m), and aboveground woody biomass (Mg ha−1) on a 250 m grid. Model adjustment was performed after dynamic injection of a background contribution predicted via the kernel weights of a bidirectional reflectance distribution function (BRDF) model. Accuracy was assessed with respect to similar maps obtained with data from the NASA Multiangle Imaging Spectroradiometer (MISR) and to contemporaneous US Forest Service (USFS) maps based partly on Forest Inventory and Analysis (FIA) data. MODIS and MISR retrievals of forest fractional cover and mean height both showed compatibility with the USFS maps, with MODIS mean absolute errors (MAE) of 0.09 and 8.4 m respectively, compared with MISR MAE of 0.10 and 2.2 m, respectively. The respective MAE for aboveground woody biomass was ~10 Mg ha−1, the same as that from MISR, although the MODIS retrievals showed a much weaker correlation, noting that these statistics do not represent evaluation with respect to ground survey data. Good height retrieval accuracies with respect to averages from high resolution discrete return lidar data and matches between mean crown aspect ratio and mean crown radius maps and known vegetation type distributions both support the contention that the GO model results are not spurious when adjusted against MISR bidirectional reflectance factor data. These results highlight an alternative to empirical methods for the exploitation of moderate resolution remote sensing data in the mapping of woody plant canopies and assessment of woody biomass loss and recovery from disturbance in the southwestern United States and in parts of the world where similar environmental conditions prevail

Geometric-Optical Modeling with MISR Over the Kola Peninsula

This study presents the results of a geometric-optical canopy reflectance model inversion experiment for canopy mapping in the taiga-tundra transition landscapes of the Kola Peninsula, Russia. The approach exploits red wavelength multi-angle reflectance factor data provided by NASA\u27s Multiangle Imaging SpectroRadiometer (MISR), with its nine cameras. Results were assessed with respect to reference data for 53 sites obtained by analysis of very high resolution imagery. Crown cover was retrieved accurately (RMSE= 0.04, R 2= 0.65), with mean canopy height somewhat less so (RMSE= 1.9 m, R2= 0.54)

The Impact of the Structure and Composition of Shrub-Coppice Dune Landscapes On MASTER Reflectance Anisotropy

This study assesses the effects of physical structure and composition of shrub-coppice dune landscapes on anisotropy in the NASA MODIS-ASTER Airborne Simulator (MASTER) solar channels, and investigates the viability of simulating multi-angular data sets using off-nadir airborne imaging radiometry from a single overpass by means of data segmentation. Segmentation data are plant density and cover and spectral measures derived from high-resolution aerial photography and classified Landsat 7 Enhanced Thematic Mapper imagery. The directional signal contributes a variation of 5-10% in reflectance, necessitating angular corrections. For most areas the signal appears to differ only slightly with changes in landscape structure and composition because the view/illumination geometry is poor and reflectance is dominated by bright soils. Further work is required to determine whether simple models would be adequate for angular corrections

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

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 wave-lengths, 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 (BBDF), and modeling this is one of the most promising methods for describing and explaining this variability. Here the Roujean linear semi-empirical 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 (People\u27s 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

Comment on \u27a Simple Method to Account for Off-Nadir-Scattering in the NOAA/Nasa Pathfinder AVHRR Land Data Set\u27 by Seaquist and Olsson (1998)

A recent contribution to the Journal suggested that corrections for off-nadir scattering in NOAA-NASA Pathfinder AVHRR Land Data Set may be achieved through polynomial fitting techniques. The method developed is based on assumptions which may not be valid and provides few advantages over the widely-adopted Maximum Value Compositing procedure. While simple and expedient, the polynomial model does not adequately account for the complex surface scattering processes which result in the directional phenomena observed in AVHRR channel 1 and 2 data and does not provide consistent NDVI values

Progress in Retrieving Canopy Structure Parameters from NASA Multi-Angle Remote Sensing

All remote sensing of the Earth\u27s surface in the solar wavelengths is impacted by the Bidirectional Reflectance Distribution Function (BRDF): all Earth surfaces scatter light anisotropically. The BRDF describes the angular distribution of scattered light and is thus what most remote sensing instruments sample. The BRDF is dependent on the structural as well as the optical characteristics of surfaces and multiple samples of the BRDF may be exploited to retrieve structural parameters. It is less than seven years since instruments designed explicitly to exploit the directional signal obtained by viewing at multiple Sun and/or viewing angles have been placed in orbit. NASA\u27s flagship multi-angle imager, the Multi-angle Imaging SpectroRadiometer (MISR) flown on the Terra satellite is the first of these to image the surface with a ground resolution of less than 1 km. This review will focus on recent progress in exploiting multi-angle data from MISR and the Moderate Resolution Imaging Spectroradiometer (MODIS) to retrieve parameters providing information on canopy structure

Canapicanopy 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 highresolution 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

Testing LiSK BRDF Models over a Semi-Arid Grassland Region with Visible and Near-Infrared ATSR-2 and AVHRR Data

This paper assesses the capability of the Roujean and LiSparse-MODIS-RossThin linear semi-empirical kernel-driven (LiSK) bidirectional reflectance distribution function (BRDF) models to predict bidirectional reflectance at geometries other than those of the observations used to invert the model, when the models are inverted against a sparse set of angular samples from 21 orbits (3-19 August 1996) of the operational Advanced Very High Resolution Radiometers (AVHRRs) on NOAA TIROS series AM (morning) and PM (evening) satellites. Red (\u27visible\u27) and near-infrared (NIR) spectral reflectance estimates acquired at 4:40 GMT on 14 August 1996 by the Along-Track Scanning Radiometer-2 (ATSR-2) sensor flown on the European Space Agency\u27s ERS-2 satellite are used as reference data. The test area is a semi-arid grassland region in Inner Mongolia, P.R. China, bounded by 42.84°-44.71° N and 112.40°-116.05° E. The results show that in spite of the difficulties posed by such a task, LiSK models can be inverted against multiangular AVHRR observations to predict bidirectional reflectance at the acquisition geometry of the ATSR-2 with reasonable accuracy: The rms. error of the reflectance predictions made by both models is less than 4% for the nadir views and less than or equal to 6% in the forward views. These error values are less than one-half those provided by a 13 August 1996 AM AVHRR scene in the 0.65 μm channel and about one-seventh of those for the AVHRR scene in the 0.87 μm (NIR) channel, in both nadir and forward views