the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Sep 2024
Degradation of Commercially Available Digital Camera Images due to Variation of Rainfall Intensity in Outdoor Conditions
Abstract. Camera-based rainfall observation is a useful technology that contributes to the densification of rainfall observation networks because it can measure rainfall with high spatio-temporal resolution and low cost. To verify the applicability of existing theories, such as computer vision and meteorological studies, to static weather effects caused by rainfall in outdoor photography systems, this study proposed relational equations representing the relationship between image information, rainfall intensity, and scene depth by linking the theoretically derived rainfall intensity with a technique proposed in the computer vision field for removing static weather effects. This study also proposed a method for estimating rainfall intensity from images using those relational equations. Since the method only uses the camera image taken of the background over a certain distance and background scene depth information, it is a highly versatile and accessible method. The proposed equations and the method for estimating rainfall intensity from images were applied to outdoor images taken by commercial interval cameras at the observation site in a mountainous watershed in Japan. As a result, it was confirmed that transmission calculated from the image information decreases exponentially according to the increase in rainfall intensity and scene depth, as assumed in the proposed equations. On the other hand, the calculated extinction coefficient tended to be overestimated at small scene depth. Although there are issues at present that need to be resolved for the technology proposed in this study, this technology has the potential to help the development of a camera-based rainfall observation technology that is accurate, robust, versatile, and accessible.
- Preprint
(5159 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-2394', Anonymous Referee #1, 14 Oct 2024
I've read the manuscript "Degradation of commercially available digital camera images due to variation of rainfall intensity in outdoor conditions" with interest. I find it an in-depth study that is well written. I do have a couple of suggestions though to improve (the readability) of the manuscript.
- In my opinion, the title sounds a bit negative and not entirely fits the purpose of this manuscript. I suggest to rewrite the title emphasizing rainfall intensity estimation from the degradation of camera images.
- Introduction: I think this method can be considered opportunistic sensing, which includes crowdsourcing, but the term crowdsourcing seems a bit too specific, since it does not really involve the crowd. I suggest to use the term opportunistic sensing, and to use it consistently throughout the introduction.
- L. 50: rainfall estimation employing commercial microwave links does not use "cellular phones", although the network is used by these phones. So, remove "of cellular phones".
- Introduction: Give a (more) clear definition of static and dynamic weather effects. In L. 99 rain streaks may appear as fog, but the process itself is still dynamic, but considered static. This can be explained a bit more.
- L. 100: define the background. Should this be seen as those cameras capturing a relatively "undisturbed" 2D image? E.g., without persons, animals and traffic moving around? So, just the river, scenery, trees? So the background is just the quite static image that is captured.
- Section 2: despite attempts to explain "direct attenuation" and "airlight", it would help to visualize these two effects or explain them more clearly. The first seems to suggest the light going from the background to the camera, whereas the second seems direct & diffuse radiation from the sun interacting with the atmosphere (but not the background) before reaching the lens.
- L. 196: replace "chapters" by "sections".
- Section 3.1: what is the typical temporal resolution, or feasible temporal resolution, especially given rainfall retrieval processing time?
- L. 210: this is an important limitation that should be mentioned in the outlook part of the conclusions.
- L. 233: why not the entire image is used, as can also be seen in Figure 2?
- Figure 3 is really helpful in clarifying and summarizing the processing chain.
- L. 269: how do you recognize the "sky background"?
- L. 275: "rainfall intensity and rainfall intensity" seems a typo.
- Caption Figures 4-7: mention that rainfall intensity is observed by a rain gauge.
- Figures 4, 5, 7 & Table 2: this is a lot of information and I find the figures quite difficult to read. Perhaps the figures could be enlarged and put on two pages per figure (and perhaps move to an appendix).
- Figures 4 - 7: what classes do the rainfall intensity values on the horizontal axis represent? E.g., 0.2 is 0 - 0.2 mm/min? And do higher values than 0.8 mm/min not occur (since the scale ends at 0.8 mm/min). In Figure 11 the scale ends at 1 mm/min.
- Figure 11: using square plots would make it easier to spot correspondence and deviation between estimated and observed rainfall intensity.
- Adding a scatter density plot with metrics, or tables with metrics, such as relative bias in the mean and Pearson correlation coefficient (e.g., by expanding Table 4), would provide more insight into the performance of camera-based rainfall estimation. A lot of time and figures are spend on the underlying relationships (e.g., Figures 4-7), and relatively little space is reserved for the evaluation of the ultimate goal: rainfall estimation.
- Table 4 and discussion of other studies: are metrics computed in the same way across all these studies, i.e., with the same or no threshold? And are there differences in climatology that may lead to differences between studies?
- Table 4: From the data size I conclude that your study encompasses a much longer dataset. That could be emphasized in the introduction, since this stands out.
- Table 4: You honestly describe that you selected the values for the path with the lowest MAPE for each camera. What is the performance when the MAPE values over all patches are used? You could, e.g., provide the median and mean values found for MAPE, or just compute the MAPE over all patches. And did the other studies also select the patches with the highest performance?
- Particle size distribution is known to vary between rainfall types, and hence between climates. How representative is the used distribution for your study? What do you expect from the suitability of your method for other climates, e.g., tropical climates in the Global South, where often few ground-based observations are available?
- L. 613: How to select an appropriate background in urban areas? Any suggestions, e.g., buildings?
- L. 670: Would this method be generally applicable to the abundant webcam or video images around the globe? Would it in principle be possible to obtain all the necessary data by simply downloading images from public websites? And could this technique potentially become a gap filler for (tropical) areas in the Global South lacking surface rainfall observations?
- L. 670 & L. 678: what is the difference between "a single static image" and "a single individual image"? I find it a bit confusing to read that the method cannot be applied to a single individual image, but is applied to a single static image. Do you mean that the method can be applied to a single image, but that a sequence of images is needed to perform all necessary processing?
- What about dew formation (could be due to fog) and rain drops on the camera lens itself? Couldn't this cause significant blurriness, which could be interpreted as extinction? Or is the lens protected to rain drops by some cover above the lens? This could be mentioned around L. 677 or discussed in the Discussion section.
- You end the conclusions with the prospect of upscaling this technique. Would privacy issues, e.g., persons on the image, pose an obstacle for this rainfall estimation technique?
- What are the prospects for differentiating between precipitation types (e.g., rain, snow) and fog? This entails knowing which precipitation type (or fog) occurs, which can be highly relevant for early warnings (i.e., not focussed on intensity but only on type), but also improving rainfall estimates, by not taking into account other precipitation types and fog.Citation: https://doi.org/10.5194/egusphere-2024-2394-RC1 -
RC2: 'Comment on egusphere-2024-2394', Anonymous Referee #2, 18 Oct 2024
The manuscript addresses commercial camera-based rainfall observation is a useful technology that contributes to the densification of rainfall observation networks. The study investigates the main and interactional effects of different commercial interval cameras (outdoor images) and rainfall intensity, which is interesting for measuring rainfall with high spatiotemporal resolution and low cost. The topic is important, and manuscript fits with the scope of the journal. but it has some weaknesses associated with the presented data and discussion have shortcomings as discussed below. Therefore, the current version of the manuscript needs major revision to be published in (HESS Journal). There are several issues must be addressed.
Minor comments
1. Regarding the title of manuscript, the title should show the novelty of the research and tell the main finding of the study. The title explains the problem... For example, you could write a title like this: “The effect of fluctuation and change in rainfall intensity when using commercial cameras on the accuracy of rainfall measurement”
Major comments
2. For all tables and figures, no SD or SE. How the statistical analysis has been done with replicates. How many replicates are used for each camera? Please describe it in materials and methods section.
3. The experiment has been conducted at outdoor sitting using three commercial camera, which are the brand type and specifications of each camera separately (country of origin and description number of the device) such as “the UV visible spectrophotometer (model T80 × UVNIS Spectrometer PG Instruments Ltd, England)”. This must be included in the material section. And what is the camera's shooting range (km)?
4. Details about the monthly meteorological data (wind speed, relative humidity, max and min temperature) for the experiment period are missing. Please describe it in figure…
5. As for the figures (4,5,7) and the table (2), there is very dense data in them. Please simplify the presentation of the results in a way that makes it easy for the reader to understand and grasp the information easily and without feeling any distraction.
6. As for the results section... it shows very valuable and very important results, so it needs to be written in more detail and more clarity.
7. The discussion section needs work. There are no comparisons with other studies. The discussion section must be rewritten in-depth highlighting the limitations of the present study.
8. The research is based on how commercial cameras are used to measure rainfall and the effect of this rainfall on the measurement accuracy of each type of camera separately.... But how can we overcome the problem of the inefficiency of commercial cameras in measuring rainfall with high accuracy... Can the efficiency of the camera be improved... What is the best type of the three camera ... How can we help stakeholders in manufacturing a high-resolution surveillance camera at a low price... Please explain this
9. How to solve the problem of commercial cameras deteriorating due to increased rainfall.... please explain
10. Can farmers use a rainfall monitoring camera on their farmland to track rainfall and calculate irrigation rates efficiently.... Or will it be too expensive for them? Please clarify.
11. The research compares types of commercial cameras... please clarify which categories can benefit most from these results and apply the research results on a practical and realworld scale.
12. Please clarify at the end of the discussion section what are the weaknesses and future studies that should be conducted for improvement and to reach the best results that help in solving problems related to hydrology and rainfall.
13. References are generally very good, but they need to be expanded and cite recent research related to the research topic. (The references must be recent, as there are many articles related to this topic that were published during this period).
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 87 | 23 | 53 | 163 | 4 | 5 |
- HTML: 87
- PDF: 23
- XML: 53
- Total: 163
- BibTeX: 4
- EndNote: 5
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1