Causes of the apparent scale independence of fractal indices associated with forest fragmentation in Bolivia

In a recent investigation, Landsat TM and ETM+ data were used to simulate different resolutions of remotely-sensed images (from 30 to 1100 m) and to analyze the effect of resolution on a range of landscape metrics associated with spatial patterns of forest fragmentation in Chapare, Bolivia since the mid-1980s. Whereas most metrics were found to be highly dependent on pixel size, several fractal metrics (DLFD, MPFD, and AWMPFD) were apparently independent of image resolution, in contradiction with a sizeable body of literature indicating that fractal dimensions of natural objects depend strongly on image characteristics. The present re-analysis of the Chapare images, using two alternative algorithms routinely used for the evaluation of fractal dimensions, shows that the values of the box-counting and information fractal dimensions are systematically larger, sometimes by as much as 85%, than the "fractal" indices DLFD, MPFD, and AWMFD for the same images. In addition, the geometrical fractal features of the forest and non-forest patches in the Chapare region strongly depend on the resolution of images used in the analysis. The largest dependency on resolution occurs for the box-counting fractal dimension in the case of the non-forest patches in 1993, where the difference between the 30 and I 100 m-resolution images corresponds to 24% of the full theoretical range (1.0 to 2.0) of the mass fractal dimension. The observation that the indices DLFD, MPFD, and AWMPFD, unlike the classical fractal dimensions, appear relatively unaffected by resolution in the case of the Chapare images seems due essentially to the fact that these indices are based on a heuristic, "non-geometric" approach to fractals. Because of their lack of a foundation in fractal geometry, nothing guarantees that these indices will be resolution-independent in general. (C) 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

Changes in the extent of glaciers in the Eastern Terskey Alatoo, the Central Tien-Shan, in response to climatic fluctuations in between the end of the 19th and the beginning of the 21st century

Changes in the extent of glaciers and rates of glacier termini retreat in the eastern Terskey-Alatoo Range, the Tien Shan Mountains, Central Asia have been evaluated using the remote sensing techniques. Changes in the extent of 335 glaciers between the end of the Little Ice Age (LIA; mid-19th century), 1990 and 2003 have been estimated through the delineation of glacier outlines and the LIA moraine positions on the Landsat TM and ASTER imagery for 1990 and 2003 respectively. By 2003, the glacier surface area had decreased by 19% of the LIA value, which constitutes a 76 km(2) reduction in glacier surface area. Mapping of 109 glaciers using the 1965 1:25,000 maps revealed that glacier surface area decreased by 12.6% of the 1965 value between 1965 and 2003. Detailed mapping of 10 glaciers using historical maps and aerial photographs from the 1943-1977 period, has enabled glacier extent variations over the 20th century to be identified with a higher temporal resolution. Glacial retreat was slow in the early 20th century but increased considerably between 1943 and 1956 and then again after 1977. The post-1990 period has been marked by the most rapid glacier retreat since the end of the LIA. The observed changes in the extent of glaciers are in line with the observed climatic warming. The regional weather stations have revealed a strong climatic warming during the ablation season since the 1950s at a rate of 0.02-0.03 degrees Ca-1. At the higher elevations in the study area represented by the Tien Shan meteorological station, the summer warming was accompanied by negative anomalies in annual precipitation in the 1990s enhancing glacier retreat. However, trends in precipitation in the post-1997 period cannot be evaluated due to the change in observational practices at this station. Neither station in the study area exhibits significant long-term trends in precipitation. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

Using the variogram to explore imagery of two different spatial resolutions

The resolution of remotely sensed data is becoming increasingly fine, and there are now many sources of data with a pixel size of 1 m x 1 m. This produces huge amounts of data that have to be stored, processed and transmitted. For environmental applications this resolution possibly provides far more data than are needed: data overload. This poses the question: how much is too much? We have explored two resolutions of data-20 in pixel SPOT data and I in pixel Computerized Airborne Multispectral Imaging System (CAMIS) data from Fort A. P. Hill (Virginia, USA), using the variogram of geostatistics. For both we used the normalized difference vegetation index (NDVI). Three scales of spatial variation were identified in both the SPOT and 1 in data: there was some overlap at the intermediate spatial scales of about 150 in and of 500 m-600 in. We subsampled the I in data and scales of variation of about 30 in and of 300 in were identified consistently until the separation between pixel centroids was 15 in (or 1 in 225pixels). At this stage, spatial scales of about 100m and 600m were described, which suggested that only now was there a real difference in the amount of spatial information available from an environmental perspective. These latter were similar spatial scales to those identified from the SPOT image. We have also analysed I in CAMIS data from Fort Story (Virginia, USA) for comparison and the outcome is similar.:From these analyses it seems that a pixel size of 20m is adequate for many environmental applications, and that if more detail is required the higher resolution data could be sub-sampled to a 10m separation between pixel centroids without any serious loss of information. This reduces significantly the amount of data that needs to be stored, transmitted and analysed and has important implications for data compression.

Spectral properties, iron oxide content and provenance of Namib dune sands

This paper applies multispectral remote sensing techniques to map the Fe-oxide content over the entire Namib sand sea. Spectrometric analysis is applied to field samples to identify the reflectance properties of the dune sands which enable remotely sensed Fe-oxide mapping. The results indicate that the pattern of dune colour in the Namib sand sea arises from the mixing of at least two distinct sources of sand; a red component of high Fe-oxide content (present as a coating on the sand grains) which derives from the inland regions, particularly from major embayments into the Southern African escarpment; and a yellow coastal component of low Fe-oxide content which is brought into the area by northward-moving aeolian transport processes. These major provenances are separated by a mixing zone between 20 kin and 90 kin from the coast throughout the entire length of the sand sea. Previous workers have also recognised a third, fluvial, provenance, but the methodology applied here is not able to map this source as a distinct spectral component. (c) 2006 Elsevier B.V. All rights reserved.

Diurnal cycle of land surface temperature in a desert encroachment zone as observed from satellites

Climate variability in the African Soudano-Sahel savanna zone has attracted much attention because of the persistence of anomalously low rainfall. Past efforts to monitor the climate of this region have focused on rainfall and vegetation conditions, while land surface temperature (LST) has received less attention. Remote sensing of LST is feasible and possible at global scale. Most remotely sensed estimates of LST are based on the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) that are limited in their ability to capture the full diurnal cycle. Although more frequent observations are available from past geostationary satellites, their spatial resolution is coarser than that of polar orbiting satellites. In this study, the improved capabilities of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the METEOSAT Second Generation (MSG) instrument are used to remotely sense the LST in the African Soudano-Sahel savanna zone at a resolution of 3 km and 15 minutes. In support of the Radiative Atmospheric Divergence using the ARM Mobile Facility (AMF), GERB and AMMA Stations (RADAGAST) project, African Monsoon Multidisciplinary Analyses (AMMA) project and the Department of Energy's Atmospheric Radiation Measurement (ARM) program, the ARM Mobile Facility was deployed during 2006 in this climatically sensitive region, thereby providing a unique opportunity to evaluate remotely sensed algorithms for deriving LST.

Estimating surface net solar radiation by use of Landsat-5 TM and digital elevation models

The ground surface net solar radiation is the energy that drives physical and chemical processes at the ground surface. In this paper, multi-spectral data from the Landsat-5 TM, topographic data from a gridded digital elevation model, field measurements, and the atmosphere model LOWTRAN 7 are used to estimate surface net solar radiation over the FIFE site. Firstly an improved method is presented and used for calculating total surface incoming radiation. Then, surface albedo is integrated from surface reflectance factors derived from remotely sensed data from Landsat-5 TM. Finally, surface net solar radiation is calculated by subtracting surface upwelling radiation from the total surface incoming radiation.

Characterising errors in airborne laser altimetry data to extract soil roughness

Airborne laser altimetry has the potential to make frequent detailed observations that are important for many aspects of studying land surface processes. However, the uncertainties inherent in airborne laser altimetry data have rarely been well measured. Uncertainty is often specified as generally as 20cm in elevation, and 40cm planimetric. To better constrain these uncertainties, we present an analysis of several datasets acquired specifically to study the temporal consistency of laser altimetry data, and thus assess its operational value. The error budget has three main components, each with a time regime. For measurements acquired less than 50ms apart, elevations have a local standard deviation in height of 3.5cm, enabling the local measurement of surface roughness of the order of 5cm. Points acquired seconds apart acquire an additional random error due to Differential Geographic Positioning System (DGPS) fluctuation. Measurements made up to an hour apart show an elevation drift of 7cm over a half hour. Over months, this drift gives rise to a random elevation offset between swathes, with an average of 6.4cm. The RMS planimetric error in point location was derived as 37.4cm. We conclude by considering the consequences of these uncertainties on the principle application of laser altimetry in the UK, intertidal zone monitoring.

Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry

Tidal channel networks play an important role in the intertidal zone, exerting substantial control over the hydrodynamics and sediment transport of the region and hence over the evolution of the salt marshes and tidal flats. The study of the morphodynamics of tidal channels is currently an active area of research, and a number of theories have been proposed which require for their validation measurement of channels over extensive areas. Remotely sensed data provide a suitable means for such channel mapping. The paper describes a technique that may be adapted to extract tidal channels from either aerial photographs or LiDAR data separately, or from both types of data used together in a fusion approach. Application of the technique to channel extraction from LiDAR data has been described previously. However, aerial photographs of intertidal zones are much more commonly available than LiDAR data, and most LiDAR flights now involve acquisition of multispectral images to complement the LiDAR data. In view of this, the paper investigates the use of multispectral data for semiautomatic identification of tidal channels, firstly from only aerial photographs or linescanner data, and secondly from fused linescanner and LiDAR data sets. A multi-level, knowledge-based approach is employed. The algorithm based on aerial photography can achieve a useful channel extraction, though may fail to detect some of the smaller channels, partly because the spectral response of parts of the non-channel areas may be similar to that of the channels. The algorithm for channel extraction from fused LiDAR and spectral data gives an increased accuracy, though only slightly higher than that obtained using LiDAR data alone. The results illustrate the difficulty of developing a fully automated method, and justify the semi-automatic approach adopted.