scholarly journals Compact Airborne Spectrographic Imager (CASI) Used for Mapping LAI of Cropland

1999 ◽  
Author(s):  
S G Leblanc ◽  
J M Chen ◽  
J R Miller ◽  
J Freemantle
Keyword(s):  
Compact Airborne Spectrographic Imager

LAI scale effect research based on compact airborne spectrographic imager data in the Heihe Oasis

2021 ◽  
Vol 18 (6) ◽  
pp. 1630-1645
Author(s):  
Xiao-ai Dai ◽  
Chao Liu ◽  
Nai-wen Li ◽  
Mei-lian Wang ◽  
Yu-wei Yang ◽  
...  
Keyword(s):  
Scale Effect ◽  
Compact Airborne Spectrographic Imager

The Bioindicators of Forest Condition Project: A physiological, remote sensing approach

2000 ◽  
Vol 76 (6) ◽  
pp. 941-952 ◽  
Author(s):  
Paul H. Sampson ◽  
Gina H. Mohammed ◽  
Thomas L. Noland ◽  
Denzil Irving ◽  
Stephen J. Colombo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Chlorophyll Fluorescence ◽  
Chlorophyll Content ◽  
Spectral Signatures ◽  
Condition Rating ◽  
Forest Condition ◽  
Operational Testing ◽  
Level Information ◽  
Intensive Sampling ◽  
Compact Airborne Spectrographic Imager

Objective measures of forest ecosystem condition are needed to gauge the effects of management activities and natural phenomena on sustainability. The Bioindicators of Forest Condition Project seeks to develop a Forest Condition Rating (FCR) system using a physiological, remote sensing approach. In particular, the goal of the project is to test whether hyperspectral remote sensing may be used to infer stand-level information about pigment concentration, chlorophyll fluorescence, and other physiological features of condition. The project spans a four-year period of intensive sampling in tolerant hardwood forests in Ontario using the Compact Airborne Spectrographic Imager (CASI). For each airborne campaign, concurrent ground-based sampling for leaf physiological features was performed. Controlled laboratory and greenhouse studies were also conducted to derive relationships between leaf-based spectral measurements and physiology in the presence of environmental stresses. The project has identified several promising bioindicators of strain that are discernible from hyperspectral images and related to ground-based physiology. The most promising remote indicator for semi-operational testing is estimation of chlorophyll content, which can be used to classify maple stands on a five-stage scale of health. Chlorophyll fluorescence has also been discerned from spectral signatures, but our studies indicate it may be confounded by chlorophyll content. The intent here is to update the forestry community on progress made, insights gained, and the practical implications of the research. Keywords: chlorophyll fluorescence, hyperspectral, indices, pigments, reflectance, tolerant hardwoods

Detection, identification and mapping of cyanobacteria — Using remote sensing to measure the optical quality of turbid inland waters

1994 ◽  
Vol 45 (5) ◽  
pp. 801 ◽  
Author(s):  
DLB Jupp ◽  
JTO Kirk ◽  
GP Harris
Keyword(s):  
Remote Sensing ◽  
Algal Species ◽  
Optical Quality ◽  
High Spectral Resolution ◽  
Turbid Waters ◽  
Eastern Australia ◽  
Processing Techniques ◽  
Compact Airborne Spectrographic Imager

The advantages of airborne scanning for the detection, identification and mapping of algal species, cyanobacteria and associated water parameters (such as turbidity) can be realized if current research outcomes are developed into operational methods based on images with high spectral resolution. Evidence for this has become available through data obtained recently in Australia from the Compact Airborne Spectrographic Imager. This paper shows how pigments associated with cyanobacteria are detectable, even in the very turbid waters typical of eastern Australia. It demonstrates how, if the waterbodies and their constituents can be characterized by a programme of field and laboratory measurement, current processing techniques and models allow the concentrations of different constituents (algae and particles) in the photic zone to be estimated and mapped. The challenge for operational remote sensing of optical water quality in Australia (and throughout the world) is seen to have two components. One is to provide an effective characterization of the target inland and adjacent coastal waters and the other is to streamline the data analysis to provide maps of water properties in the time and cost frameworks required for operational use.

Mapping macrophytic vegetation in shallow lakes using the Compact Airborne Spectrographic Imager (CASI)

2010 ◽  
Vol 20 (7) ◽  
pp. 717-727 ◽  
Author(s):  
P. D. Hunter ◽  
D. J. Gilvear ◽  
A. N. Tyler ◽  
N. J. Willby ◽  
A. Kelly
Keyword(s):  
Shallow Lakes ◽  
Compact Airborne Spectrographic Imager

Classifying Eucalyptus forests with high spatial and spectral resolution imagery: an investigation of individual species and vegetation communities

2005 ◽  
Vol 53 (4) ◽  
pp. 337 ◽  
Author(s):  
Nicholas Goodwin ◽  
Russell Turner ◽  
Ray Merton
Keyword(s):  
Tree Species ◽  
High Spatial Resolution ◽  
Species Group ◽  
Classification Performance ◽  
Individual Species ◽  
Individual Tree ◽  
Complex Species ◽  
Eucalypt Forest ◽  
Species Groups ◽  
Compact Airborne Spectrographic Imager

Mapping the spatial distribution of individual species is an important ecological and forestry issue that requires continued research to coincide with advances in remote-sensing technologies. In this study, we investigated the application of high spatial resolution (80 cm) Compact Airborne Spectrographic Imager 2 (CASI-2) data for mapping both spectrally complex species and species groups (subgenus grouping) in an Australian eucalypt forest. The relationships between spectral reflectance curves of individual tree species and identified statistical differences among species were analysed with ANOVA. Supervised maximum likelihood classifications were then performed to assess tree species separability in CASI-2 imagery. Results indicated that turpentine (Syncarpia glomulifera Smith), mesic vegetation (primarily rainforest species), and an amalgamated group of eucalypts could be readily distinguished. The discrimination of S. glomulifera was particularly robust, with consistently high classification accuracies. Eucalypt classification as a broader species group, rather than individual species, greatly improved classification performance. However, separating sunlit and shaded aspects of tree crowns did not increase classification accuracy.

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