2012 June - 17 articles
Time series of images are required to extract and separate information on vegetation change due to phenological cycles, inter-annual climatic variability, and long-term trends. While images from the Landsat Thematic Mapper (TM) sensor have the spatia...
The cost effective monitoring of habitats and their biodiversity remains a challenge to date. Earth Observation (EO) has a key role to play in mapping habitat and biodiversity in general, providing tools for the systematic collection of environmental...
A filtering algorithm is proposed that accurately extracts ground data from airborne light detection and ranging (LiDAR) measurements and generates an estimated digital terrain model (DTM). The proposed algorithm utilizes planar surface features and...
This study explores a method to classify seven tropical rainforest tree species from full-range (400–2,500 nm) hyperspectral data acquired at tissue (leaf and bark), pixel and crown scales using laboratory and airborne sensors. Metrics that respond t...
The objective of this study was to determine whether leaf area index (LAI) in temperate mixed forests is best estimated using multiple-return airborne laser scanning (lidar) data or dual-band, single-pass interferometric synthetic aperture radar data...
Individual tree species identification is important for urban forest inventory and ecology management. Recent advances in remote sensing technologies facilitate more detailed estimation of individual urban tree characteristics. This study presents an...
Unmanned Aircraft Systems (UAS) have evolved rapidly over the past decade driven primarily by military uses, and have begun finding application among civilian users for earth sensing reconnaissance and scientific data collection purposes. Among UAS,...
Advanced Land Observing Satellite (ALOS) Phased Array L-band type Synthetic Aperture Radar (PALSAR) backscatter images with 50 m pixel size (strip images) at HV-polarization were used to map clear-cuts at a regional and national level in Sweden. For...
The Ocean Color Monitor (OCM) provides radiance measurements in eight visible and near-infrared bands, similar to the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) but with higher spatial resolution. For small- to moderate-sized coastal lakes and e...
The retrieval of nutrient concentration in sugarcane through hyperspectral remote sensing is widely known to be affected by canopy architecture. The goal of this research was to develop an estimation model that could explain the nitrogen variations i...
Canopy height data collected with an airborne laser scanner (ALS) flown across unmanaged parts of Canada’s boreal forest in the summer of 2010 were used—as stand-alone data—to derive a least-squares polynomial (LSPOL) between presumed post-fire recov...
Outlining patches dominated by different plants in wetland vegetation provides information on species succession, microhabitat patterns, wetland health and ecosystem services. Aerial photogrammetry and hyperspectral imaging are the usual data acquisi...
Sensor miniaturisation, improved battery technology and the availability of low-cost yet advanced Unmanned Aerial Vehicles (UAV) have provided new opportunities for environmental remote sensing. The UAV provides a platform for close-range aerial phot...
In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel,...
Modeling sub-canopy elevation is an important step in the processing of waveform lidar data to measure three dimensional forest structure. Here, we present a methodology based on high resolution discrete-return lidar (DRL) to correct the ground eleva...
We present the development of a low-cost Unmanned Aerial Vehicle-Light Detecting and Ranging (UAV-LiDAR) system and an accompanying workflow to produce 3D point clouds. UAV systems provide an unrivalled combination of high temporal and spatial resolu...
Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial...
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