waiting the answer

I follow the question.

Remote Sensing may be captivating in the generation of data, though it can be a complement to field readings and not as an alternative. It often times register technological setbacks.

Good question.

It should not be an alternative if field data is available but could be use to complement it. However, if field data is not available, then, remotely sensed data should be an option.

Oluwafemi Adeyeri

I agree with you , thanks for replying

Dickson Adom

Thanks for replying

I agree with Dr.Oluwafemi Adeyeri.

best regard

Thank you for your contribution

Remote sensing is certainly not an alternative to field investigations. As already mentioned, RS should be used to supplement & complement the field investigations. Always RS is used as a first approximation to field studies and for detailed & in-depth studies field work is carried out. Where the field area is in-accessible for field studies, then RS can be the only tool to understand the terrain properties.

N B Narasimha Prasad May be an alternative in case of inaccessibility and field sampling, thank you for your answer

While it should be considered supplementary, for inaccessible sites, it remains the only option. As such, in addition to being supplementary, it could be the only source of primary data, despite the inherent inaccuracy associated with it, due to scale considerations.

Thank you. I appreciate your interest and your answer.

I agree with many of the responses. Remote Sensing is a valuable tool for field data capable of acquiring information from small scale to large (regional or continental scales) unconstrained by inaccessible terrains and geopolitical boundaries, which the conventional method is often unable to do. While the contemporary remote sensing technologies would still require supplementary data from the conventional field data for ground truthing, I think considering the massive temporal RS data-archives and the continued advent of new high resolution remotes sensing data suggests that in many cases RS data will phase out the field data acqiusition.

An adequate answer

Thank you very much

For my thesis I worked with LIDAR, radar, and radiometers. LIDAR and radar share some characteristics in that they require backscattered information of particles moving with the wind within a sample volume, thus allowing the characterization of wind at several heights. Radiometers are passive instruments that rely on oxygen and water vapor based channels to derive temperature and moisture content. In my experience there are trade-offs. For instance, radiometers provide continuous information about temperature and moisture but are limited in that they cannot, at least with current technology, resolve the finer scale changes in the vertical structure such as inversions. I have found lidar and radars to be great tools for wind. LIDARs are less common than radars but generally agree with radars. They operate under a different wavelength, result in higher resolution along the vertical, and require less integration time. Once again, winds with radiosondes will resolve shear better but a LIDAR with 20m vertical resolution generally does a good job as well. THe lidar data I used output data every 1 second and allowed me to determine energy budgets of turbulence and wave dynamics that would be impossible to do with a radiosonde. Unfortunately, the surface layer is generally not characterized by remote sensing because the base measurements tend to be 50 m or greater. Certain LIDARs are preferable over others and it depends on what company engineered it. The famous High Resolution Doppler LIDAR (HRDL) has been around for a while and can resolve characteristics of the boundary layer quite well. Some companies, however, may produce LIDARs of lesser quality. One such example was the Vindicator lidar. I chose not to deal with that LIDAR after what I saw, but then again, it was made by a company I never heard of and haven't heard about since.

Clearly the answer to this question is no we should not replace field data of lake water quality with only remote sensing data and for best results the two types of data should be used together.

This is for a number of reasons:

1. Remotely sensed data from aircraft and satellite of water quality is usually based on the reflected and upwelling VIS/IR radiation from the waters surface. The surface layer may not be very representative of the water quality at different depths throughout the water column of the lake. There is also a significant added uncertainty in the remotely sensed data when you make the necessary conversion from radiance to water quality parameters.

2. Similarly, for the field data it is usually impossible to take in situ samples down through the water column everywhere across a lake of any appreciable size and do this repeatedly over time. As the questioner rightly states remotely sensed data has the advantage that it can give you full surface coverage at high spatial resolution over time but this does not give you the depth resolution that the field data can.

3. Working out the 3D structure throughout the lake of whatever water quality parameter you are interested in needs some sort of modelling. The combination of remotely sensed and field data would give the best results here too. It would be difficult to constrain the model without any field data at different depths throughout the water column. Using only remotely sensed data, the modelled results would therefore probably have a very large uncertainty and bear little resemblance to the real water quality situation in the lake. Using only field data would not give you the spatial coverage and repeat cycle to constrain the model over time.

4. Without field data we would have no means of validating the remotely sensed water quality products.

Of course what you are actually able to do operationally depends on data availability and how you combine the data also depends on your application's requirements, i.e. the exact water quality parameter you are interested in and what spatial, temporal, and depth resolution you need. For example for remote or extreme environments field data may be difficult to collect. In my opinion the key here is being able to calculate uncertainties for both types of data and the modelling applied to be able to quantify the confidence we have in the water quality results.

I hope this clarifies why we should not entirely replace field data of lake water quality with remotely sensed data and gives you some idea of why the combination of the two is likely to lead to the best results.

Yes, it is clear now, grateful for your interest and your answer

Edward J. Strobach Thanks for your response. Was your thesis on water quality using remote sensing, and can you provide me with some research in this field or your thesis if it concerns the study of water quality.

Very well explained by Dr. Andrew. Application of RS technique has its own advantages and limitations. Especially when it come to quality determination, field investigations and monitoring is a must (with time; space and depth). To achieve best results, integration of RS; & field studies are necessary. For futuristic predictions, as Dr. Andrew has suggested, modelling studies are necessary along with RS and field studies.

Hello Hind, in response to your additional request: my Ph.D. thesis was on the modelling and simulation of remotely sensed data and covered a number of different surface types. However, additionally I have worked for 18 years as a satellite oceanographer (ocean colour, SST, altimetry, etc.) on shallow water coastal ecosystems as well as the open ocean. For the remote sensing of water quality of inland waters if you can get your hands on the book by Mishra et al. from last year: " Bio-optical Modeling and Remote Sensing of Inland Waters" published by Elsevier that would be a good start. There are also a number of International Ocean Colour Coordinating Group reports that will give you insight into the various aspects of the remote sensing of water quality and you can download them for free at http://ioccg.org/what-we-do/ioccg-publications/ioccg-reports/. The ongoing work of the globolakes project may also be of interest to you: http://www.globolakes.ac.uk/ Good luck!

Thanks Dr. N B Narasimha Prasad for your contribution.

Andrew Clive Banks I appreciate your answer and your interest and thank you very much for the references and your kind help.

Remote sensing is a good complement especially in forestry. Sometimes we hold data we never throught to use.Old areial photos in forestry can hold a huge potential for both forestry and water quality. Past disturbance can be seen in old photos. If this information is geo reference into GIS, then the location is visited. we can find a lot of information.

What is the potential forest growth and yeild with past impacts?

If a wildfire occurs are there conditions which could lead to erosion and sediment?

The list goes on. So when you think of remote data; imagine all of the potenial sources of data that may be used. You may be able to achomplish a lot of work, with data that i scurrently held by someone else. Rather alternative than gathering new data.

James Archuleta An important point of view, thank you very much for your participation

Data are integrated for remote sensing with field data according to the research objective, in some disciplines it is good to provide both studies, and some field readings are reliable

Indeed yes, remote sensing can be used to collect data for research studies; it may on its own even be enough in some cases, however, field studies do confirm issues that may at times not be captured by remote

sensing. If means and time allow both methods could this be utilised.

Dear Hind

it depends on your purpose, but if you have good calibration, you can trust this data.

Interesting question

Following

Yes you can rely on the data and in absence of data the data obtained by remote sensing are acceptable and found trust worthy. The data predicted this way for pollution impact was found to be reliable in a study made by my one of the students.

Yes we can rely on all such data