José Claudio Mura

Eucalyptus Biomass and Volume Estimation Using Interferometric and Polarimetric SAR Data

Abstract: This work aims to establish a relationship between volume and biomass with interferometric and radiometric SAR (Synthetic Aperture Radar) response from planted Eucalyptus saligna forest stands, using multi-variable regression techniques. X and P band SAR images from the airborne OrbiSAR-1 sensor, were acquired at the study area in the southeast region of Brazil. The interferometric height (Hint = difference between interferometric digital elevation model in X and P bands), contributed to the models developed due to fact that Eucalyptus forest is composed of individuals whose structure is predominantly cylindrical and vertically oriented, and whose tree heights have great correlation with volume and biomass. The volume model showed that the stand volume was highly correlated with the interferometric height logarithm (Log 10 Hint), since Eucalyptus tree volume has a linear relationship with the vegetation height. The biomass model showed that the combination of both Hint

Land Use and Land Cover Mapping in the Brazilian Amazon Using Polarimetric Airborne P-Band SAR Data

In September 2000, an airborne synthetic aperture radar (SAR) mission acquired unprecedented full polarimetric P-band data over the Tapajos National Forest (Para State), which is an area in the Brazilian Amazon which has been continuously monitored in the last three decades. Eight land use/cover classes were identified, namely, primary forest, regeneration older than 25 years, regeneration between 12 and 25 years, regeneration between 6 and 12 years, regeneration younger than six years, crops/pasture, bare soil, and floodplain (FP). The objective of this paper is to analyze the potential of full polarimetric P-band data in distinguishing different land use/cover classes with a minimum established Kappa value of 75%, using the latest development on SAR statistical characterization. The iterated conditional mode (ICM) contextual classifier was applied to amplitude, intensity images, biomass index, and some polarimetric parameters (entropy, alpha angle, and anisotropy) extracted from the polarimetric P-band data. As the accuracy obtained for eight classes was not acceptable, another two sets, with five and four classes, were formed by the combination of the previous ones. They were defined by confusion matrix analysis and by the graphical analysis of average backscatter values, entropy, [alpha] angle, and anisotropy images and by the H/alpha plans of the land use samples. The classification accuracy with four classes (three levels of biomass plus FP) was then considered acceptable with a Kappa value of 76.81%, using the ICM classification with the adequate bivariate distribution for the HV and VV channels.

Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Field work was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Mapping recent deforestation in the Brazilian Amazon using simulated L-band MAPSAR images

Brazilian Amazon Forest biomes are presently under intensive land cover conversion from natural vegetation to agriculture. Timely detection of recent deforestation through orbital remote sensing is a critical requirement for an operational land cover monitoring system in order to provide information to the regulatory systems and decision makers. Optical images present drawbacks for operation in the moist tropics and synthetic aperture radar (SAR) data are a real alternative. The feasibility of using multipolarized L‐band images simulating the Multi‐Application Purpose SAR (MAPSAR) satellite was examined for the detection of recent deforestation in the Tapajós region. The discrimination of recent deforestation from other land cover classes was evaluated through a quantitative analysis based on Jeffreys–Matusitas (JM) distances derived from training samples using amplitude values and supported by field survey. The investigation confirmed the possibility of the discrimination of recently deforested classes from other classes based on the L‐band images as proposed in the MAPSAR.

Polarimetric SAR interferometry as applied to fully polarimetric rain forest data

The scope of this paper is to establish a polarimetric SAR interferometry approach to estimate interferometrically observable forest and ground parameter. Three optimized interferometric coherences can be found through a properly weighted superimposition of all the interferometric coherences available from a fully polarimetric single baseline experimental set-up in repeat-pass mode. These proper weights can be found by solving an eigenvalue problem for each resolution cell [Cloiude and Papathanassiou 1998]. The result serves as the right hand side of a least square optimization problem which makes use of a scattering model based on a randomly oriented volume over an impenetrable surface [Treuhaft and Siqueira 2000] to estimate a set of physical forest parameters transformed through this model. A conjugate direction set iteration scheme is used to minimize the cost function of the optimization problem and to solve for the pertinent candidate parameters, which are the forest volume thickness, the volume extinction coefficient, the interferometric phase related to the underlying topography, and the effective ground-to-volume amplitude ratios of the related interferometric coherences. Due to the non-uniqueness of this inversion problem an additional constrained is introduced via a Tikhonov regularization scheme. The results of the presented schemes are shown for the first time on P-band data takes acquired over tropical rain forest in Brazil.

Detection and Monitoring of Surface Motions in Active Open Pit Iron Mine in the Amazon Region, Using Persistent Scatterer Interferometry with TerraSAR-X Satellite Data

Persistent Scatterer interferometry (PSI) represents a powerful tool for the detection and monitoring of tiny surface deformations in vast areas, allowing a better understanding of its triggering mechanisms, planning of mitigation measures, as well as to find better solutions for social and environmental issues. However, there is no record hitherto of its use in active open pit mine in tropical rainforest environment. In this paper we evaluate the use of the PSI technique for the detection and monitoring of mine slope deformations in the N4W iron mine and its surroundings, Para State, Northern Brazil. The PSI processing was performed with 18 ascending SAR scenes of the TerraSAR-X satellite acquired in the dry season of 2012. The results showed a significant number of widely distributed persistent scatterers. It was observed that most of the study area was stable during the time span. Nevertheless, high deformation rates (312 mm/year) were mapped over the mine waste piles, but do not offer any hazard, since they are expected displacements of meters in magnitude for these manmade land structures. Additionally, it was mapped tiny deformation rates in both the east and west flanks of pits 1 and 2. The main underlying reasons can be assigned to the accommodation phenomena of very poor rock masses, to the local geometric variations of the slope cuts, to the geological contact between ironstones and the country rocks, to the exploitation activities, as well as to the major geological structures. This study showed the applicability of the PSI technique using TerraSAR-X scenes in active open pit mines in tropical moist environment. However, the PSI technique is not capable in providing real-time warnings, and faces limitations due to SAR viewing geometry. In this sense, we strongly recommend the use of radar scenes acquired in both ascending and descending orbits, which would also provide a more complete understanding of the deformation patterns.

A Phase-Offset Estimation Method for InSAR DEM Generation Based on Phase-Offset Functions

This paper presents a novel method for estimating the absolute phase offset in interferometric synthetic aperture radar (SAR) measurements for digital elevation model (DEM) generation. The method is based on “phase-offset functions (POF),” relating phase offset to topographic height, and are computed for two different overlapping interferometric data acquisitions performed with considerably different incidence angles over the same area of interest. For the purpose of extended mapping, opposite viewing directions are preferred. The two “phase-offset functions” are then linearly combined, yielding a “combined phase-offset function (CPOF)”. The intersection point of several straight lines (CPOFs), corresponding to different points in the overlap area allows for solving the phase offset for both acquisitions. Aiming at increasing performance and stability, this intersection point is found by means of averaging many points and applying principal component analysis. The method is validated against traditional phase offset estimation with corner reflectors (CR) using real OrbiSAR-1 data in X- and P-band.

The use of airborne P-band radar data for land use and land cover mapping in Brazilian Amazonia

The aim of this work was to analyze the potentiality of polarimetric P-band data for land use and land cover mapping in a site of the Brazilian Amazonia. These data are the first P-band image set gathered in the Brazilian Amazonia, so they represent a unique opportunity of analyzing the potentiality of this frequency for classification purposes. The stratification of land use/land cover classes was performed using a classification system specially developed for polarimetric data. Results showed that P-band data were able to discriminate forest and regeneration areas from crop, pasture and bare soil areas. Moreover, regeneration areas (older than 12 years) were successfully distinguished from primary forest and other regeneration stages.

Parameter estimation of rain forest vegetation via polarimetric radar interferometric data

In this paper we investigate a least square algorithm to retrieve forest parameters from interferometric, fully polarimetric radar remote sensing P-band data, based on an interferometric optimization scheme which is applied to maximize the separation of scattering phase centers related to the pertinent interferometric coherences in order to obtain most accurate parameter inversion results. A recently developed approach is especially adopted to airborne P-band data, introducing a least square minimization scheme in which synthetic interferometric coherences computed from a scattering model, which is based on a randomly oriented volume over a non-penetrable ground, are compared with three interferometric coherences measured by the P-band sensor. Through fitting of the synthetic and the measured interferometric coherences, the pertinent candidate parameters of the optimization problem can be retrieved. These parameters are the forest volume thickness, the volume extinction coefficient, the interferometric phase related to the underlying topography, and the effective ground-to-volume amplitude ratios related to the interferometric coherences. Through a weighted superposition of all the interferometric coherences provided by the fully polarimetric radar sensor these coherences can be maximized and introduced as the right-hand side of the parameter optimization problem. Experimental results obtained from P-band fully polarimetric single baseline interferometric data acquired over the amazon rain forest are shown in order to demonstrate the potential of the proposed approach. Furthermore, a (chi) 2-test is performed on the data to prove the validity of the introduced scattering model for rain forest vegetation.

MAPSAR Image Simulation Based on L-band Polarimetric Data from the SAR-R99B Airborne Sensor (SIVAM System)

This paper describes the methodology applied to generate simulated multipolarized L-band SAR images of the MAPSAR (Multi-Application Purpose SAR) satellite from the airborne SAR R99B sensor (SIVAM System). MAPSAR is a feasibility study conducted by INPE (National Institute for Space Research) and DLR (German Aerospace Center) targeting a satellite L-band SAR innovative mission for assessment, management and monitoring of natural resources. Examples of simulated products and their applications are briefly discussed.