Display options:
Normal
Show Abstracts
Compact
Select/unselect all
Displaying article 1-3
p. 1-2
Received: 6 February 2009 / Published: 20 February 2009
Show/Hide Abstract
| Download PDF Full-text (20 KB) Abstract: We are so accustomed to seeing satellite pictures of the earth that it seems as if there is nothing left to be discovered. In the daily weather reports on television we regularly see images taken by geostationary satellites and with the help of web-based virtual globes we can zoom in from the full-earth disk to detailed views of any place on the earth in a matter of seconds. Yet, does this truly mean that all the secrets of the earth have now been disclosed? Can we extract all the information we need from existing earth observation data? [...]
p. 3-21
Received: 20 February 2009; in revised form: 24 March 2009 / Accepted: 25 March 2009 / Published: 27 March 2009
Show/Hide Abstract
| Download PDF Full-text (658 KB) Abstract: Satellite remote sensing observations have the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from active microwave remote sensing data are typically complex due to inherent difficulty in characterizing interactions among land surface parameters that contribute to the retrieval process. Therefore, adequate physical mathematical descriptions of microwave backscatter interaction with parameters such as land cover, vegetation density, and soil characteristics are not readily available. In such condition, non-parametric models could be used as possible alternative for better understanding the impact of variables in the retrieval process and relating it in the absence of exact formulation. In this study, non-parametric methods such as neural networks, fuzzy logic are used to retrieve soil moisture from active microwave remote sensing data. The inclusion of soil characteristics and Normalized Difference Vegetation Index (NDVI) derived from infrared and visible measurement, have significantly improved soil moisture retrievals and reduced root mean square error (RMSE) by around 30% in the retrievals. Soil moisture derived from these methods was compared with ESTAR soil moisture (RMSE ~4.0%) and field soil moisture measurements (RMSE ~6.5%). Additionally, the study showed that soil moisture retrievals from highly vegetated areas are less accurate than bare soil areas.
p. 22-35
Received: 16 January 2009; in revised form: 3 March 2009 / Accepted: 24 March 2009 / Published: 30 March 2009
Show/Hide Abstract
| Download PDF Full-text (495 KB) Abstract: People specialised in or in contact with Geographic Information Systems (GIS) at administrative or user level have been looking for economical and productive means for data acquisition tasks since the advent of GIS. Because the data acquisition constitutes major part of any GIS, scientific community, especially geodetic surveyors, have come up with a solution of real time kinematic (RTK) GPS. This paper investigates the performance (internal and external accuracy) of RTK GPS. For this purpose, two separate tests are conducted. In the first test three cases are taken in consideration for internal accuracy, namely, identical satellite configuration, different satellite configuration and different reference station. In the second test, two cases are put into study in which RTK GPS results are compared with static GPS and conventional terrestrial method. The results from all the tests have proved that this modern technique is very much suitable for data acquisition of GIS’s as well as it is efficient and economical.
Select/unselect all
Displaying article 1-3
Export citation of selected articles as:
Plain Text
BibTeX
BibTeX (without abstracts)
Endnote
Endnote (without abstracts)
Tab-delimited
PubMed XML
DOAJ XML
AGRIS XML