INDUSTRIAL IMPACTS ON VEGETATION IN THE MONCHEGORSK REGION FROM MULTISPECTRAL SPACE IMAGERY

Results are presented of analysis of Landsat MSS imagery for the purpose of assessing damage to northern taiga and tundra vegetation caused by emissions generated by nonferrous metallurgy on northwest Russia's Kola Peninsula. Unlike earlier studies, the present project attempts to provide spatially comprehensive coverage of vegetation impacts, according to a standardized methodology for their assessment. A reduction in the number of feature classes identifiable upon a change from visual interpretation to automated classification based on spectral brightness values made it necessary to test alternative classification procedures (based on brightness ratios and the normalized vegetation index).     

ECOLOGICAL-GEOGRAPHIC MAPPING: CONCEPTS,METHODS, AND TECHNOLOGY

Another paper in a series of articles on ecological-geographic mapping (see for example, Mapping Sciences and Remote Sensing, Vol. 31, No. 3, July-September 1994, pp. 185-220) focuses on outlining a concise typology of such maps and providing a brief history of their emergence during the 1970s and 1980s. A subsequent section is devoted to methods and technology used in the compilation of ecological-geographic maps, particularly the multiple variants of data organization, processing, and cartographic representation that can be factored into research design. Translated by Edward Torrey, Alexandria, VA 22308 from: Geografiya i prirodnyye resursy, 1995, No. 4, pp. 10-18.     

ECOSYSTEM MONITORING AND MAPPING IN A NATURE PRESERVE

Two specialists on the forest and wetland ecosystems of Siberia describe principles and measures employed in the establishment of a regular program of ecological mapping at Russia's Central Siberian Biosphere Preserve, as well as efforts to standardize remote-sensing-based monitoring efforts through improved procedures for selection of reference plots for ground truth determination. Issues addressed include the identification of principal ecological factors serving as landscape classification criteria, the need for better methods of interpreting an entire range of forest-wetland communities on remote sensing imagery, innovations in data gathering procedures in the field, selection of natural models [representative tracts] for monitoring in view of the technical infeasibility of monitoring the entire preserve, and selection of reference plots within each model for ground truth. Translated by Edward Torrey, Alexandria, VA 22308 from: Geografiya i prirodnyye resursy, 1996, No. 2, pp. 36-43.     

ECOLOGICAL ASSESSMENT AND MAPPING FOR BALANCED REGIONAL DEVELOPMENT

A Russian geographer summarizes the results of a comprehensive study of modern landscapes and the mapping of diverse ecological situations. The procedure involves the development of a system of criteria and indices for the assessment of the properties of the environment, which provide a sound basis for comprehensive ecological mapping. The importance of an ecological assessment in the mapping of environmental problems and situations in support of the stable and balanced development of regions is demonstrated. Translated by Edward Torrey, Alexandria, VA from: Izvestiya Akademiya Nauk, seriya geograficheskaya, 1999, No. 1, pp. 81-87.     

Field Measurements of Plant Emissivity Spectra: An Experimental Study on Remote Sensing of Vegetation in the Thermal Infrared Region

Spectral features of plant species in the visible to SWIR (0.4–2.5 μm) region have been studied extensively, but scanty attention has been given to plant thermal infrared (TIR: 4–14 μm) properties. This paper presents preliminary results of a study that was conducted first time in India to measure radiance and emissivity properties of eight plant species in TIR spectral region in the field conditions using a FTIR (Fourier Transform Infrared) field spectroradiometer working in 4–14 μm at an agriculture experimental farm. Several spectral features in the emissivity spectra of plant species were observed that are probably related to the leaf chemical constituents, such as cellulose and xylan (hemicellulose) and structural aspects of leaf surface like abundance of trichomes and texture. Observations and results from the field measurements were supported by the laboratory measurements like biochemical analysis. These preliminary field emissivity measurements of leaves in TIR show that there is useful spectral information that may be detectable by field-based instrument. More detailed field and laboratory measurements are underway to explore this research theme.     

Spatial-Correlation Based Persistent Scatterer Interferometric Study for Ground Deformation

Interferometric Synthetic Aperture Radar (InSAR), nowadays, is a precise technique for monitoring and detecting ground deformation at a millimetric level over large areas using multi-temporal SAR images. Persistent Scatterer Interferometric SAR (PSInSAR), an advanced version of InSAR, is an effective tool for measuring ground deformation using temporally stable reference points or persistent scatterers. We have applied both PSInSAR and Small Baseline Subset (SBAS) methods, based on the spatial correlation of interferometric phase, to estimate the ground deformation and time-series analysis. In this study, we select Las Vegas, Nevada, USA as our test area to detect the ground deformation along satellite line-of-sight (LOS) during November 1992–September 2000 using 44 C-band SAR images of the European Remote Sensing (ERS-1 and ERS-2) satellites. We observe the ground displacement rate of Las Vegas is in the range of ?19 to 8 mm/year in the same period. We also cross-compare PSInSAR and SBAS using mean LOS velocity and time-series. The comparison shows a correlation coefficient of 0.9467 in the case of mean LOS velocity. Along this study, we validate the ground deformation results from the satellite with the ground water depth of Las Vegas using time-series analysis, and the InSAR measurements show similar patterns with ground water data.     

A Birds Eye View of Debris-Avalanche on Miyar Glacier,Chenab Basin,India

The importance of mass wasting in glacier environments and its impacts on glacier dynamics is not fully understood. This is the first occurrence of a debris avalanche event onto a Himalayan glacier through satellite data analysis. The analysis of various factors indicates the slide was a climate-driven hill-slope event activated in 2009 masking the Miyar glacier surface up to ~1.5% including its both lateral moraines and medial moraines. Due to this addition the glacier had neither advance nor retreat from 2009 to 2014. Eventually the debris will contribute to the supraglacial and englacial debris of the glacier. This showcases the way of mass wasting an important contribution to the debris budget of the Himalayan glaciers.     

Image Pose Estimation Based on Procrustes Theory

This paper has established a high-precision hierarchical estimated pose parameters of image. Firstly, we select corresponding three image points of 3D points which constitute the largest area in image as a base, in order to estimate the depth and translate information; then based on the above method, we obtain the scale parameter of camera exterior information. And finally, the topic is transformed to a problem of estimating rotation relationship by vector, using Procrustes theory to obtain the best estimate of the angle elements of exterior parameters. The method can effectively solve problems which depth and coupling pose parameters cannot deal with. Experimental results show that this method of determining position and orientation parameter estimation model is of briefness, easy convergence and it can also achieve higher parameter estimation accuracy than the direct projection matrix factorization.     

Impact of data model and point density on aboveground forest biomass estimation from airborne LiDAR

Background

Accurate estimation of aboveground forest biomass (AGB) and its dynamics is of paramount importance in understanding the role of forest in the carbon cycle and the effective implementation of climate change mitigation policies. LiDAR is currently the most accurate technology for AGB estimation. LiDAR metrics can be derived from the 3D point cloud (echo-based) or from the canopy height model (CHM). Different sensors and survey configurations can affect the metrics derived from the LiDAR data. We evaluate the ability of the metrics derived from the echo-based and CHM data models to estimate AGB in three different biomes, as well as the impact of point density on the metrics derived from them.

Results

Our results show that differences among metrics derived at different point densities were significantly different from zero, with a larger impact on CHM-based than echo-based metrics, particularly when the point density was reduced to 1 point m^?2. Both data models-echo-based and CHM-performed similarly well in estimating AGB at the three study sites. For the temperate forest in the Sierra Nevada Mountains, California, USA, R² ranged from 0.79 to 0.8 and RMSE (relRMSE) from 69.69 (35.59%) to 70.71 (36.12%) Mg ha^?1 for the echo-based model and from 0.76 to 0.78 and 73.84 (37.72%) to 128.20 (65.49%) Mg ha^?1 for the CHM-based model. For the moist tropical forest on Barro Colorado Island, Panama, the models gave R² ranging between 0.70 and 0.71 and RMSE between 30.08 (12.36%) and 30.32 (12.46) Mg ha^?1 [between 0.69–0.70 and 30.42 (12.50%) and 61.30 (25.19%) Mg ha^?1] for the echo-based [CHM-based] models. Finally, for the Atlantic forest in the Sierra do Mar, Brazil, R² was between 0.58–0.69 and RMSE between 37.73 (8.67%) and 39.77 (9.14%) Mg ha^?1 for the echo-based model, whereas for the CHM R² was between 0.37–0.45 and RMSE between 45.43 (10.44%) and 67.23 (15.45%) Mg ha^?1.

Conclusions

Metrics derived from the CHM show a higher dependence on point density than metrics derived from the echo-based data model. Despite the median of the differences between metrics derived at different point densities differing significantly from zero, the mean change was close to zero and smaller than the standard deviation except for very low point densities (1 point m^?2). The application of calibrated models to estimate AGB on metrics derived from thinned datasets resulted in less than 5% error when metrics were derived from the echo-based model. For CHM-based metrics, the same level of error was obtained for point densities higher than 5 points m^?2. The fact that reducing point density does not introduce significant errors in AGB estimates is important for biomass monitoring and for an effective implementation of climate change mitigation policies such as REDD + due to its implications for the costs of data acquisition. Both data models showed similar capability to estimate AGB when point density was greater than or equal to 5 point m^?2.