Integrating JERS-1 imaging radar and elevation models for mapping tropical rainforest communities in far North Queensland, Australia

The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.

A comparison of SAR sensors for quantifying Melaleuca biomass on tropical floodplains in northern Australia and New Guinea

Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference

Bayesian analysis of the scatterometer wind retrieval inverse problem:Some new approaches

The retrieval of wind vectors from satellite scatterometer observations is a non-linear inverse problem. A common approach to solving inverse problems is to adopt a Bayesian framework and to infer the posterior distribution of the parameters of interest given the observations by using a likelihood model relating the observations to the parameters, and a prior distribution over the parameters. We show how Gaussian process priors can be used efficiently with a variety of likelihood models, using local forward (observation) models and direct inverse models for the scatterometer. We present an enhanced Markov chain Monte Carlo method to sample from the resulting multimodal posterior distribution. We go on to show how the computational complexity of the inference can be controlled by using a sparse, sequential Bayes algorithm for estimation with Gaussian processes. This helps to overcome the most serious barrier to the use of probabilistic, Gaussian process methods in remote sensing inverse problems, which is the prohibitively large size of the data sets. We contrast the sampling results with the approximations that are found by using the sparse, sequential Bayes algorithm.

Water resources assessment and geographic information system (GIS)-based stormwater runoff estimates for artificial recharge of freshwater aquifers in New Providence, Bahamas

The Bahamas is a small island nation that is dealing with the problem of freshwater shortage. All of the country’s freshwater is contained in shallow lens aquifers that are recharged solely by rainfall. The country has been struggling to meet the water demands by employing a combination of over-pumping of aquifers, transport of water by barge between islands, and desalination of sea water. In recent decades, new development on New Providence, where the capital city of Nassau is located, has created a large area of impervious surfaces and thereby a substantial amount of runoff with the result that several of the aquifers are not being recharged. A geodatabase was assembled to assess and estimate the quantity of runoff from these impervious surfaces and potential recharge locations were identified using a combination of Geographic Information Systems (GIS) and remote sensing. This study showed that runoff from impervious surfaces in New Providence represents a large freshwater resource that could potentially be used to recharge the lens aquifers on New Providence.

Hydrologic Dynamics of the Ground-Water-Dependent Sian Ka’an Wetlands, Mexico, Derived from InSAR and SAR Data

The 5,280 km2 Sian Ka’an Biosphere Reserve includes pristine wetlands fed by ground water from the karst aquifer of the Yucatan Peninsula, Mexico. The inflow through underground karst structures is hard to observe making it difficult to understand, quantify, and predict the wetland dynamics. Remotely sensed Synthetic Aperture Radar (SAR) amplitude and phase observations offer new opportunities to obtain information on hydrologic dynamics useful for wetland management. Backscatter amplitude of SAR data can be used to map flooding extent. Interferometric processing of the backscattered SAR phase data (InSAR) produces temporal phase-changes that can be related to relative water level changes in vegetated wetlands. We used 56 RADARSAT-1 SAR acquisitions to calculate 38 interferograms and 13 flooding maps with 24 day and 48 day time intervals covering July 2006 to March 2008. Flooding extent varied between 1,067 km2 and 2,588 km2 during the study period, and main water input was seen to take place in sloughs during October–December. We propose that main water input areas are associated with water-filled faults that transport ground water from the catchment to the wetlands. InSAR and Landsat data revealed local-scale water divides and surface water flow directions within the wetlands.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 1, Issue 1 2007

Fall 2007 Newsletter for FIU's Maps and Imagery User Services department.

MUIS News: Maps and User Imagery Services @ FIU Green Library Vol. 2, Issue 1 2008

Florida International University's Fall 2008 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 2, Issue 2 Spring 2009

Florida International University's Spring 2009 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 1 Fall 2009

Florida International University's Fall 2009 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 2 Fall 2009

Florida International University's Fall 2009 Map and User Imagery Services Newsletter; Vol. 3, issue 2.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 2, Spring 2010

Florida International University's Spring 2010 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 4, Issue 1 Fall 2012

Florida International University's Fall 2012 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 4, Issue 2 Spring/Summer 2013

Florida International University's Spring/Summer 2013 Map and User Imagery Services Newsletter.

MIUS News : Maps and Imagery User Services @ FIU Green Library: Vol. 5 Issue 1 Fall 2013

Florida International University's Fall 2013 Map and User Imagery Services Newsletter