KR101271489B1 - Satellite footage of algae farms for the detection of spectral regions of satellite imaging data extraction methods - Google Patents

Abstract

PURPOSE: A method for extracting the image data of an artificial satellite of a spectrum area for detecting a marine plant farm is provided to extract the past or present image data of the artificial satellite for detecting the marine plant farm by utilizing the image data of the artificial satellite including the marine plant farm. CONSTITUTION: A method for extracting the image data of an artificial satellite of a spectrum area for detecting a marine plant farm is as follows. A spectrum wavelength band in which a difference of the spectrum reflection of marine plants and seawater, that of the marine plants and foreshore is converted into a database. In the visible rays, near IR(Infrared Rays), and thermal IR electromagnetic wave spectrum areas with respect to the earth surface, the image data of the artificial satellite of the spectrum wavelength band in which the difference of the spectrum reflection of marine plants and seawater, that of the marine plants and foreshore is extracted from the image data of the artificial satellite of each spectrum wavelength band of blue, green, red, near IR, first short wavelength IR, thermal IR, and a second short wavelength IR as the image data for detecting a marine plant farm. [Reference numerals] (AA) Graph 1. Showing a spectrum reflection curve of a laver farm and a wavelength range corresponding to each spectrum band of a landsat TM sensor

Description

Satellite footage of algae farms for the detection of spectral regions of satellite imaging data extraction methods}

The present invention relates to a satellite image data extraction method of the spectral region for detecting the algae farm from the satellite image data to identify the algae farm in the past using a satellite image.

Satellite imagery is a very effective tool for determining the existence of facilities that have been installed in a certain area in the past. Although there are some differences depending on the types of satellites, information on the surface of the satellite is periodically collected, so that various information required for the change and prediction of the surface of the earth, past, present, and future, as well as the surface at some point in time, can be obtained.

On the other hand, the present invention is to extract the image data of the satellite spectral region to calculate the area by extracting the seaweed farms installed in a specific region in the past satellite image. Seaweeds are divided into green algae, brown algae, and red algae according to their color. Green seaweeds are green, green seaweeds are kelp, seaweed, and red seaweeds. Among these seaweeds, the seaweed farm is as follows.

The seaweed is a general name of seaweed (Porphyra) among red algae and has the widest distribution area among seaweeds due to its adaptability to salt. The farms in the sea are somewhat different depending on the region, but their feet will be installed around September and removed from April to May the following year. Since seaweed lives in water, it is affected by water temperature, especially at low tide, which directly affects laver fronds. The laver enters the growing season below 15 ℃ and grows very lush as the temperature decreases. The growth temperature of laver is 8-5 degreeC, and the minimum is 4 degreeC. And when the spring is 12 ~ 13 ℃ growth stops. Sunlight, which is essential for the growth of laver, is not only a necessary factor for photosynthesis, but also determines the vertical distribution, or habitat, of laver. The laver's habitat is relatively upper in the intertidal zone, and laver grows in a very narrow range, about 15cm up and down. Seaweed farms are widely distributed near estuaries because of the sufficient supply of nutrients by river water, the decrease of water temperature, and the formation of large tidal flats. The exposure time of gimbal has a great influence on the growth, and the exposure time is the highest when the average difference between control and digestion is about 2 hours every day, and decreases more than 4 hours.

Kim farms in Korea are largely divided into a holding type and a class type according to the structure of the Kimbal (see Fig. 1). Since holding farms raise up horses to raise seaweed, intertidal zones that can control foot exposure time are appropriate. Water temperature is more than 3 ℃ in winter, where 5 ~ 10 ℃ is maintained for more than three months. The algae are good at flow rate of 20cm / sec or more and the productivity is high in the place where the algae is fast and windy. The type of laver is a newly improved laver farming method that can not only expose the feet to the surface and expose them as a holding type, but also farm them without using items. The type of farming can be done irrespective of depth and bottom (bottom), but if the water depth is too shallow, the anchor line may be broken by the wind wave, and if it is too deep, the cost of facility will be high due to the use of large anchors and thick ropes. Considering this, the depth of the farm will be established within 4m to 50m.

Domestic Patent Publication No. 10-1050067 (2011.07.19.)

An object of the present invention is to provide a satellite image data extraction method of the spectral region for the detection of algae farms of the satellite image data to identify the algae farms that were installed in a specific region in the past using satellite images.

An object of the present invention as described above is a step of database the spectral wavelength band having a large difference in the spectral reflectance of seaweed and tidal, or seaweed and seawater;

In the visible, near-infrared, and thermal-infrared electromagnetic spectral ranges, blue (Blue, 450 nm-520 nm), green (Green, 520 nm-600 nm), red (Red, 630 nm-690 nm), near infrared Near IR, 760 nm-900 nm), first short wavelength infrared (SW IR, 1550 nm-1750 nm), thermal infrared (Thermal IR, 1040 nm-1240 nm), second short wavelength infrared (SW IR, 2080 nm-2350 (Nm) extracting the satellite image data of the satellite image data of the spectral wavelength band having a large difference in the spectral reflectances of the algae and the tidal flats or the algae and the seawater among the satellite image data of the spectral wavelength band of each spectral wavelength band;

It is achieved by a satellite image data extraction method of the spectral region for seaweed farm detection among satellite image data comprising a.

Here, when the satellite image data of each spectral wavelength band is the image data exposed to the algae farm in the algae farm, the satellite image data for extracting the algae farm, the near infrared (Near IR, the largest difference between the spectral reflectance of algae and tidal flat 760 nm-900 nm) is characterized in that the satellite image data of the spectral wavelength band.

In addition, when the satellite image data of each of the spectral wavelength band is the image data in which the seaweed farm is submerged in seawater or the top of the seaweed farm is exposed to the sea surface, the satellite image data for seaweed farm extraction is the spectral reflection of seaweed and seawater. It is characterized by the satellite image data of the spectral wavelength band of the largest green (Green, 520nm-600nm), and the blue (Blue, 450nm-520nm), red (Red, 630nm-690nm) It may also include satellite imagery in the wavelength band.

According to the present invention, satellite image data including aquatic and marine algae farms has a large difference in spectral reflectivity between seaweeds and seawater, green (520 nm-600 nm), blue (Blue, 450 nm-520 nm), It can be seen that the satellite image data of the red (Red, 630nm-690nm) spectral wavelength band can be used to extract the past or present satellite image data for seaweed farm detection.

In the case of the strut type, algae showed the highest spectral reflectance in the wavelength range corresponding to the near infrared (Near IR, 760nm-900nm) spectral wavelength band, and the difference between the spectral reflectances of the algae and the tidal flat was also the largest. It can be used to extract past or present satellite image data for seaweed farm detection.

1 is a view showing the types of structural forms of seaweed farms,
2 is a satellite image data showing (I) the surrounding waters of Gochang-gun, Jeollabuk-do, and (II) the surrounding waters of Cheongnam-gun, Jeonnam,
3 is a view showing the specifications of the GER-3700 spectroradiometer,
4 is a satellite image data showing the Jeongsanpo, Geunheung-myeon, Taean-gun, Chungnam
Figure 5 (a) is a panoramic view of the holding algae farm in the low tide during the low tide, (b) is a panoramic view of the holding algae farm in the sea at high tide,
6 is a graph showing a wavelength range corresponding to each spectral band of an algae farm spectral reflectance curve and Landsat TM sensor;
7 is a graph showing the algae farm spectral reflectance curve corresponding to each spectral bed of Landsat ™.

The present invention relates to a satellite image data extraction method of the spectral region for detecting the algae farm from the satellite image data to identify the algae farm in the past using a satellite image.

To this end, the satellite image data extraction method of the spectral region for the detection of algae aquaculture farms in the satellite image data according to the present invention comprises the steps of: database the spectral wavelength band having a large difference in the spectral reflectance of the seaweed and tidal flats;

In the visible, near-infrared, and thermal-infrared electromagnetic spectral ranges, blue (Blue, 450 nm-520 nm), green (Green, 520 nm-600 nm), red (Red, 630 nm-690 nm), near infrared Near IR, 760 nm-900 nm), first short wavelength infrared (SW IR, 1550 nm-1750 nm), thermal infrared (Thermal IR, 1040 nm-1240 nm), second short wavelength infrared (SW IR, 2080 nm-2350 (Nm) extracting satellite image data of the spectral wavelength band having a large difference in the spectral reflectance of the algae and the tidal flats or the algae and the seawater from the satellite image data of the spectral wavelength band of each spectral wavelength band; .

Here, when the satellite image data of each spectral wavelength band is the image data exposed to the algae farm in the algae farm, the satellite image data for extracting the algae farm, the near infrared (Near IR, the largest difference between the spectral reflectance of algae and tidal flat 760 nm-900 nm) is characterized in that the satellite image data of the spectral wavelength band.

In addition, when the satellite image data of each of the spectral wavelength band is the image data in which the seaweed farm is submerged in seawater or the top of the seaweed farm is exposed to the sea surface, the satellite image data for seaweed farm extraction is the spectral reflection of seaweed and seawater. It is characterized by the satellite image data of the spectral wavelength band of the largest green (Green, 520nm-600nm), and the blue (Blue, 450nm-520nm), red (Red, 630nm-690nm) It may include satellite image data in the wavelength band.

On the other hand, the satellite image data extraction method of the spectral region for the detection of seaweed farms of the satellite image data according to the present invention comprises the step of database the spectral wavelength band having a large difference in the spectral reflectance of algae or tidal flat;

In the visible, near-infrared, and thermal-infrared electromagnetic spectral ranges, blue (Blue, 450 nm-520 nm), green (Green, 520 nm-600 nm), red (Red, 630 nm-690 nm), near infrared Near IR, 760 nm-900 nm), first short wavelength infrared (SW IR, 1550 nm-1750 nm), thermal infrared (Thermal IR, 1040 nm-1240 nm), second short wavelength infrared (SW IR, 2080 nm-2350 Nm) extracting the satellite image data of the spectral wavelength band in which the spectral reflectance of the algae or the tidal flat has the highest spectral reflectance among the satellite image data of the spectral wavelength band of each of the spectral wavelength bands.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Satellite imagery is a very effective tool for determining the existence of facilities that have been installed in a certain area in the past. Although it varies slightly depending on the type of satellite, the information about the surface is collected periodically, so that not only the surface information at some point in time but also various information necessary for the change and prediction of the surface of the past, present and future can be obtained. .

An object of the present invention is to extract seaweed farms from seaweeds installed in the surrounding waters of Yeonggwang nuclear power plant in the early 1990s using Landsat ™ satellite imagery.

 The target area is about 13 km from the drainage port of Yeonggwang Nuclear Power Station to the vicinity of Gokdo-ri, Simwon-myeon, Gochang-gun, Gochang-gun, Jeollabuk-do, and about 12 km from Daegu-ri, Yeongseongpo, Yeongseong-gun, Jeollanam-do, and Daesu-ri, Baeksu-eup. (See FIG. 2).

The natural geography of the region is due to the large tidal flats, the monotonous coastline, and the diverse oceanic operations of the coast, forming vast muddy and sandy tidal flats. In the south of the research area, Baeksu intertidal zone, one of the largest tidal flats in Jeollanam-do, is located in the north, and only Gomso is located in the north.

The scope of the period was in the early 1990s, before the removal of the farm facilities due to damages caused by the Kim farm.

The satellite image data was taken from Landsat 4 and 5 SPOT 2 from 1990 to 1993 to extract seaweed farms installed in the surrounding waters of Yeonggwang nuclear power plant in the early 1990s. Data taken from October to December and January to March were reviewed by searching for Quick Look images. As a result of SPOT satellite image search, there was almost no recorded image data, and even some of the retrieved data were covered with a lot of clouds in the target area, and it was judged to be unsuitable to extract the seaweed farm. Landsat satellite image search result of Path / Row (116/35) including the surrounding waters of Yeonggwang nuclear power plant has searched a lot of satellite data, and processed four scene data that are considered suitable for the extraction of seaweed farm. 1).

Landsat 4 was launched on July 16, 1982 by Landsat 5 on March 1, 1984, and was launched by the Delta-3920 rocket. Visit. The transit time in Korea is about 10:30 am. Landsat 4 is now suspended and Landsat 5 is in service. Table 2 shows the specifications of TM sensors mounted on Landsat satellites.

<Measurement of Spectral Reflectance of Gold Farm>

In the present invention, a GER-3700 spectroradiometer was used for measuring spectroscopic reflectance of seaweed (see FIG. 3). The GER-3700 spectroradiometer is a portable type that is easy to carry and measure outdoors, and can be applied to all fields that require spectroscopic measurement as well as ground truth. And with a wide spectral range, various spectroscopic and radiative measurements are possible. The results of spectral reflectance measurements obtained through this instrument are most commonly used to prove geographic information such as geology, forests, and soil from satellite data through the Ground Truth field survey. In the case of Ground Truth, the results of the satellite data and the spectroscopic measurement of the spectroradiometer can be compared with each other to derive an evaluation suitable for the purpose of measurement and data utilization. In addition, it is an efficient equipment for mineral core analysis, growth analysis using spectral characteristics of crops, and measuring and analyzing lipid characteristics.

The spectral reflectance measurement for the seaweed farm is to select a suitable spectral band and to use it in the image processing process to effectively extract the seaweed farm from the satellite data. Currently, there are no landscaping laver farms in Yeonggwang Nuclear Power Plant, so Taean-gun, Chungnam, which is located on the west coast where similar natural environments and landscaping laver farms are installed, was selected as the target area for spectroscopic reflection. Spectral reflectance measurements were measured at a seaweed farm in Jeongsanpo (latitude: 36 ° 42′38 ″, longitude: 126 ° 09′38 ″) near Jeongjuk-ri, Geunheung-myeon, Taean-gun, Chungnam, Korea, at the time of low tide and afternoon high tide on March 23, 2004. Measurement was made (see FIG. 4).

Spectral reflectance measurements were performed on laver attached to gimbal and surrounding tidal-flats at low tide during the morning low tide, and on gimbal and surrounding seawater submerged in about 5 to 10 cm in the afternoon at high tide. See FIG. 5).

6 is a spectral reflectance curve measured at aquaculture farms located in Jeongsanpo, Jeongjuk-ri, Geunheung-myeon, Taean-gun, Chungnam, South Korea on March 23, 2004, and shows a range of wavelength bands corresponding to each spectral band of the Landsat TM sensor. The graph of FIG. 7 is a graph separately displayed for each wavelength band corresponding to each spectral band of Landsat TM in the laver spectral reflectance curve of the graph of FIG. 6.

The spectral reflectance of the seaweed was measured separately at low tide and at high tide, because the difference between tidal tide is large due to the marine environment of the west coast, so that the seaweed is exposed to tidal flats at low tide and submerged by seawater at high tide. The assumption is that each will show different spectral reflection characteristics.

Spectral reflectivity of the laver attached to the laver and surrounding tidal flats at low tide showed that the laver had the highest spectral reflectance in the wavelength region corresponding to Band 4 (760 nm to 900 nm) of the Landsat TM sensor. The difference in spectral reflectance between laver and tidal flats was also greatest. If the fish farms were photographed by Landsat satellites at low tide exposed to tidal flats, it can be seen that band farms and tidal flats are best distinguished from Band 4 among the photographs recorded at that time. As can be seen in the graph of FIG. 6, it can be seen that the overall pattern of the spectral reflectance curve measured when the steam is exposed to the tidal flat shows a pattern similar to the spectral reflectance curve measured for the living plant. In band 1 (450 nm to 520 nm), band 2 (520 nm to 600 nm), and band 3 (630 nm to 690 nm), the tidal flats showed higher reflectivity than laver as opposed to band 4 (760 nm to 900 nm). . In these wavelength ranges, the reflectance difference between laver and tidal flat is not greater than Band 4 (760nm ~ 900nm), but it can be seen that there is some difference in reflectance. In Band 5 (1550nm ~ 1750nm) and Band 7 (2080nm ~ 2350nm), most of the spectral reflectance patterns of laver and tidal flat are consistent and there is almost no difference.

Spectral reflectance of seaweed and surrounding seawater slightly submerged at high tide was found to show Band 1 (450 nm to 520 nm), Band 2 (520 nm to 600 nm), and Band 3 (630) of the Landsat TM sensor. Nm ~ 690 nm) in the wavelength range of the seawater reflectivity was higher than the seaweed submerged in the seawater. Band 2 (520nm ~ 600nm) showed the largest difference in reflectance between seawater and seaweed. In Band 4 (760nm ~ 900nm), the largest difference in reflectance between seaweed and tidal flat at low tide, no difference was observed in seaweed and seawater at high tide. In Band 5 (1550 nm to 1750 nm) and Band 7 (2080 nm to 2350 nm), there was no significant difference in reflectance as at low tide.

Based on these measurements, it is possible to know what is the spectral wavelength band with a large difference in the spectral reflectance of seaweed and tidal flats or seaweed and seawater. (Blue, 450 nm-520 nm), Green (520, 600 nm), Red (Red, 630 nm-690 nm), Near infrared (Near IR, 760 nm-900 nm), First short wavelength infrared (SW) IR, 1550 nm-1750 nm), thermal infrared rays (Thermal IR, 1040 nm-1240 nm), and the second short wavelength infrared rays (SW IR, 2080 nm-2350 nm), which are classified according to the spectral wavelengths of the satellite image data. Satellite image data of spectral wavelength bands with large differences in the spectral reflectances between and tidal flats, or seaweed and seawater can be extracted as satellite image data for seaweed farm extraction.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is evident that many alternatives, modifications, and variations will readily occur to those skilled in the art without departing from the spirit and scope of the invention. Therefore, it should be understood that the disclosed embodiments are to be considered in an illustrative rather than a restrictive sense, and that the true scope of the invention is indicated by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof, .

Claims (5)

Database spectral wavelength bands having a large difference in spectral reflectance between seaweed and tidal flats, or seaweed and seawater;
In the visible, near-infrared, and thermal-infrared electromagnetic spectral ranges, blue (Blue, 450 nm-520 nm), green (Green, 520 nm-600 nm), red (Red, 630 nm-690 nm), near infrared Near IR, 760 nm-900 nm), first short wavelength infrared (SW IR, 1550 nm-1750 nm), thermal infrared (Thermal IR, 1040 nm-1240 nm), second short wavelength infrared (SW IR, 2080 nm-2350 (Nm) extracting satellite image data of the spectral wavelength band having a large difference in the spectral reflectance between the algae and the tidal flats or the algae and the seawater among the satellite image data of the spectral wavelength band of each spectral wavelength band; ,
When the satellite image data of each spectral wavelength band is the image data exposed to the tidal flats of the algae farm,
The satellite image data for extracting the seaweed farm,
Satellite image data extraction method of spectral region for detection of algae farms among satellite image data, characterized in that the spectral reflectance of algae and tidal flat is the largest infrared ray (Near IR, 760nm-900nm) .
Database spectral wavelength bands having a large difference in spectral reflectance between seaweed and tidal flats, or seaweed and seawater;
In the visible, near-infrared, and thermal-infrared electromagnetic spectral ranges, blue (Blue, 450 nm-520 nm), green (Green, 520 nm-600 nm), red (Red, 630 nm-690 nm), near infrared Near IR, 760 nm-900 nm), first short wavelength infrared (SW IR, 1550 nm-1750 nm), thermal infrared (Thermal IR, 1040 nm-1240 nm), second short wavelength infrared (SW IR, 2080 nm-2350 (Nm) extracting satellite image data of the spectral wavelength band having a large difference in the spectral reflectance between the algae and the tidal flats or the algae and the seawater among the satellite image data of the spectral wavelength band of each spectral wavelength band; ,
When the satellite image data of each spectral wavelength band is image data in which the algae farm is submerged in seawater or the top of the algae farm is exposed to sea level,
The satellite image data for extracting the seaweed farm,
A satellite image data extraction method of a spectral region for detecting algae farms among satellite image data, characterized in that the satellite image data of the green (Green, 520 nm-600 nm) spectral reflectance of the largest difference between the spectral reflectance of seaweed and seawater.
The method of claim 2,
The satellite image data for extracting the seaweed farm,
Extraction of satellite image data of spectral regions for detecting seaweed farms among satellite image data including satellite image data of spectral wavelengths of blue (450, 450-520 nm) and red (Red, 630 nm-690 nm) Way.
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