Browsing by Author "Ashraf, Muhammad Salman"
Now showing items 1-5 of 9
-
Alternative solutions for determining the spectral band weights for the subtractive resolution merge technique
Ashraf, Muhammad Salman; Brabyn, Lars; Hicks, Brendan J. (Taylor & Francis, 2011)Data fusion using subtractive resolution merge (SRM) is limited because it currently requires fixed spectral band weights predetermined for particular sensors. This is problematic because there is an increasing availability ... -
Enhancing spatial resolution of remotely sensed data for mapping freshwater environments
Ashraf, Muhammad Salman (University of Waikato, 2011)Freshwater environments are important for ecosystem services and biodiversity. These environments are subject to many natural and anthropogenic changes, which influence their quality; therefore, regular monitoring is ... -
Evaluating remote sensing data classification techniques for mapping freshwater habitats: Trial application in the Tongariro River delta, Lake Taupo
Ashraf, Muhammad Salman; Brabyn, Lars; Hicks, Brendan J. (Centre for Biodiversity and Ecology Research, The University of Waikato, 2008-07)The overall goal of this study is to evaluate different classification techniques that can be applied to multi-source satellite remote sensing data to map different freshwater habitat zones. The Tongariro River delta at ... -
Hindcasting water clarity from Landsat satellite images of unmonitored shallow lakes in the Waikato region, New Zealand
Hicks, Brendan J.; Stichbury, Glen; Brabyn, Lars; Allan, Mathew Grant; Ashraf, Muhammad Salman (Springer, 2013)Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial ... -
Image data fusion for the remote sensing of freshwater environments
Ashraf, Muhammad Salman; Brabyn, Lars; Hicks, Brendan J. (Elsevier, 2011)Remote sensing based mapping of diverse and heterogeneous freshwater environments requires high-resolution images. Data fusion is a useful technique for producing a high-resolution multispectral image from the merging of ...