Engineering topics

Saatchi, Sassan

Publications and source records attributed to Saatchi, Sassan.

23 records · Page 2

NASA NTRS2007

Estimation of Forest Fuel Load from Radar Remote Sensing

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar imagery acquired over a large area of the Yellowstone National Park (YNP) by the AIRSAR sensor, to estimate the distribution of forest biomass and canopy fuel loads. Semi-empirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, canopy fuel weight, canopy bulk density, and foliage moisture content. These estimates when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy, and when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R(sup 2) = 85 for the canopy fuel weight, R(sup 2)=.84 for canopy bulk density and R(sup 2) = 0.78 for the foliage biomass.

Saatchi, Sassan↗

NASA NTRS2004

Monitoring the Mesoamerican Biological Corridor: A NASA/CCAD Cooperative Research Project

To foster scientific cooperation under a Memorandum of Understanding between NASA and the Central American countries, the research project developed regional databases to monitor forest condition and environmental change throughout the region. Of particular interest is the Mesoamerican Biological Corridor (MBC), a chain of protected areas and proposed conservation areas that will link segments of natural habitats in Central America from the borders of northern Columbia to southern Mexico. The first and second year of the project focused on the development of regional satellite databases (JERS-IC, MODIS, and Landsat-TM), training of Central American cooperators and forest cover and change analysis. The three regional satellite mosaics were developed and distributed on CD-ROM to cooperators and regional outlets. Four regional remote sensing training courses were conducted in 3 countries including participants from all 7 Central American countries and Mexico. In year 3, regional forest change assessment in reference to Mesoamerican Biological Corridor was completed and land cover maps (from Landsat TM) were developed for 7 Landsat scenes and accuracy assessed. These maps are being used to support validation of MODIS forest/non forest maps and to examine forest fragmentation and forest cover change in selected study sites. A no-cost time extension (2003-2004) allowed the completion of an M.S. thesis by a Costa Rican student and preparation of manuscripts for future submission to peer-reviewed outlets. Proposals initiated at the end of the project have generated external funding from the U.S. Forest Service (to U. Maine), NASA-ESSF (Oregon State U.) and from USAID and EPA (to NASA-MSFC-GHCC) to test MODIS capabilities to detect forest change; conduct literature review on biomass estimation and carbon stocks and develop a regional remote sensing monitoring center in Central America. The success of the project has led to continued cooperation between NASA, other federal agencies, and scientists from all seven Central American Countries (see SERVIR web site for this ongoing work - servir.nsstc.nasa.gov).

Sever, Thomas↗

NASA NTRS1999

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Saatchi, Sassan↗

NASA NTRS1998

Relating Vegetation Aerodynamic Roughness Length to Interferometric SAR Measurements

In this paper, we investigate the feasibility of estimating aerodynamic roughness parameter from interferometric SAR (INSAR) measurements. The relation between the interferometric correlation and the rms height of the surface is presented analytically. Model simulations performed over realistic canopy parameters obtained from field measurements in boreal forest environment demonstrate the capability of the INSAR measurements for estimating and mapping surface roughness lengths over forests and/or other vegetation types. The procedure for estimating this parameter over boreal forests using the INSAR data is discussed and the possibility of extending the methodology over tropical forests is examined.

Saatchi, Sassan↗

NASA NTRS1995

Estimation of Boreal Forest Biomass Using Spaceborne SAR Systems

In this paper, we report on the use of a semiempirical algorithm derived from a two layer radar backscatter model for forest canopies. The model stratifies the forest canopy into crown and stem layers, separates the structural and biometric attributes of the canopy. The structural parameters are estimated by training the model with polarimetric SAR (synthetic aperture radar) data acquired over homogeneous stands with known above ground biomass. Given the structural parameters, the semi-empirical algorithm has four remaining parameters, crown biomass, stem biomass, surface soil moisture, and surface rms height that can be estimated by at least four independent SAR measurements. The algorithm has been used to generate biomass maps over the entire images acquired by JPL AIRSAR and SIR-C SAR systems. The semi-empirical algorithms are then modified to be used by single frequency radar systems such as ERS-1, JERS-1, and Radarsat. The accuracy. of biomass estimation from single channel radars is compared with the case when the channels are used together in synergism or in a polarimetric system.

Saatchi, Sassan↗