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This paper discusses the evaluation of a state-of-the-art Ka-band (35.7GHz) single-pass interferometric synthetic aperture radar (InSAR) for snow-depth mapping during the NASA SnowEx experiment. The use of InSAR for this application presents a new approach and potential alternate technology to lidar with the advantage of wide-swath operation that is not hampered by cloud cover. We discuss the plans...
Although traditional remote sensing systems based on spectral reflectance can already provide estimates of the “potential” photosynthetic activity of terrestrial vegetation through the quantification of total canopy chlorophyll content or absorbed photosynthetic radiation, the determination of the “actual” photosynthetic activity of terrestrial vegetation requires information about how the absorbed...
Self-Dual Attribute Profiles (SDAPs) have proven to be an effective method for extracting spatial features able to improve scene classification of remote sensing images with very high spatial resolution. An SDAP is a multilevel decomposition of an image obtained with a sequence of transformations performed by attribute filters over the Tree of Shapes (ToS). One of the main issues with this technique...
Individual tree-based species maps are valuable for sustainable forest practices from both economic and ecological perspectives. Recent advances in high spatial resolution remote sensing provide the opportunity to map trees species with greater resolution and accuracy. This study aims to classify tree species at the individual tree level by using multi-seasonal WorldView-3 images. Our study site is...
This paper proposed a deep convolutional neural network (DCNN) based framework for large-scale oil palm tree detection using high-resolution remote sensing images in Malaysia. Different from the previous palm tree or tree crown detection studies, the palm trees in our study area are very crowded and their crowns often overlap. Moreover, there are various land cover types in our study area, e.g. impervious,...
Airborne P-band differential interferometric (DInSAR) and X-band single-pass data were acquired from August 2015 until July 2016, along 240km downstream from Santo Antônio Energia dam in Madeira River (Amazon Basin). The objective is to measure and monitor erosions along the river banks, in the Amazon basin. The river banks are densed vegetated. We present our processing methodology, which includes...
This paper compares the classification capability of data acquired in hybrid and dual linear polarization mode over the Chelmsford area, United Kingdom, from RISAT-1 C-band satellite. Support vector machine based supervised classification is used in the study and accuracy is assessed over the validation pixels. The hybrid-pol RH/RV combination shows better classification accuracy over linear pol HH/HV...
Normalized Difference Vegetation Index (NDVI) time series is used to study different land cover dynamics such as change, compare vegetation dynamics between years and analyze intra-annual components. A nonlinear cosine model of the NDVI time series with a constant frequency is used to account for the time-varying nature of the land cover parameters due to seasonality or change. The Extended Kalman...
Discriminating human-induced vegetation change is essential for sustainable managements of arid and semi-arid ecosystems. Residual Trends method (RESTREND), an effective quantitative method, has been widely used to discriminate human-induced vegetation changes in specific arid and semi-arid ecosystems. However, how to define homogeneous spatial neighborhood to determine reference pixel for estimating...
Disturbance and regrowth are vital processes in determining the roles of forest ecosystem in carbon and biogeochemical cycles. The vegetation change tracker (VCT) algorithm derives the spectral disturbance magnitude based on the time series observations. While these spectral disturbance magnitudes are indicative of physical changes in tree cover or biomass, their quantitative relationships have yet...
We have been engaged in Numerical Solutions of Maxwell equations (NMM3D) for more than fifteen years [1-2]. In this paper, we report on the recent progress of NMM3D on random rough surfaces and discrete random media and their applications in active and passive microwave remote sensing. The random rough surface models were applied to soil surfaces and ocean surfaces. The discrete random media models...
Canopy radiation and scattering signal contains abundant vegetation information. One can quantitatively retrieve the biophysical parameters by building canopy radiation and scattering models and inverting them. Joint simulation of the three-dimensional (3D) models for multiband may combine the advantages of different spectral (frequency) domains. It is also a useful tool for validation in remote sesnsing...
This paper introduces a methodology for predicting the year of plantation (YOP) from remote sensing data. The application has important implications in forestry management and inventorying. We exploit hyperspectral and LiDAR data in combination with state-of-the-art machine learning classifiers. In particular, we present a complete processing chain to extract spectral, textural and morphological features...
Decomposition is performed for the 4×4 SMAP radar channel covariance matrix and the correlation between resulting components, surface soil moisture and vegetation is examined. Globally, the first principal component is the most dominant and the correlation coefficients with respect to soil mortise is highest (R2 ≥ 0.8) in regions with fractional ground cover and sufficient temporal dynamics of soil...
Crack detection is crucial for maintaining the structural health and safety of concrete bridges. Previous studies mainly focus on the detection of thick and conspicuous cracks on bridge deck using high resolution images. However, it's difficult to obtain accurate crack detection results on the underside of bridges due to the fainter and thinner appearance and lower contrast of cracks to their background...
Time series PALSAR-2/ScanSAR data and Landsat data were used for examining the differences in detection timing of deforestation. Optical sensor-based (Landsat) deforestation information taken about every 16 days and SAR data taken about every 1.5 months were used, and the temporal change of L-band γ0 was examined for the deforestation areas. The γ0HH value increased by 1.2 dB on average for areas...
Airborne Light Detection and Ranging (LIDAR) remote sensing based forest inventory at the individual tree level is a valuable and effective alternative to manual inventory, due to factors such as higher accuracy, easy repeatability of sampling, and economic benefits. However, individual tree detection in multi-storied forests is challenging due to high tree proximity and forest structure complexity...
Airborne lidar is the tool best suited to provide timely updated maps for monitoring forest change in both horizontal and vertical dimensions. Still, it has been little used due to the scarcity of long-term time-series of lidar measurements. The NASA Jet Propulsion Laboratory Airborne Snow Observatory (ASO) is a landscape-level monitoring system that provides ongoing remote sensing measurements with...
Forest stands are a basic unit of analysis for forest inventory and mapping. Stands are defined as large forested areas of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red and visible images. This task is tedious, highly time consuming, and needs to be automated for scalability...
NEON conducts annual LiDAR flights over several ecologically unique sites within the continental United States. One of the products derived from the LiDAR acquisitions is a canopy height model (CHM), required to make inferences about vegetation structure and annual changes in growth. It is hypothesized that the flight acquisition parameters are sufficient to allow NEON's CHMs to detect inter-annual...
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