scholarly journals Automating Drone Image Processing to Map Coral Reef Substrates Using Google Earth Engine

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 50
Author(s):  
Mary K. Bennett ◽  
Nicolas Younes ◽  
Karen Joyce
Keyword(s):  
Image Processing ◽  
Coral Reef ◽  
High Resolution ◽  
Satellite Imagery ◽  
Coral Cover ◽  
Google Earth ◽  
Live Coral ◽  
Coral Sand ◽  
Google Earth Engine

While coral reef ecosystems hold immense biological, ecological, and economic value, frequent anthropogenic and environmental disturbances have caused these ecosystems to decline globally. Current coral reef monitoring methods include in situ surveys and analyzing remotely sensed data from satellites. However, in situ methods are often expensive and inconsistent in terms of time and space. High-resolution satellite imagery can also be expensive to acquire and subject to environmental conditions that conceal target features. High-resolution imagery gathered from remotely piloted aircraft systems (RPAS or drones) is an inexpensive alternative; however, processing drone imagery for analysis is time-consuming and complex. This study presents the first semi-automatic workflow for drone image processing with Google Earth Engine (GEE) and free and open source software (FOSS). With this workflow, we processed 230 drone images of Heron Reef, Australia and classified coral, sand, and rock/dead coral substrates with the Random Forest classifier. Our classification achieved an overall accuracy of 86% and mapped live coral cover with 92% accuracy. The presented methods enable efficient processing of drone imagery of any environment and can be useful when processing drone imagery for calibrating and validating satellite imagery.

SHALLOW WATER HABITAT MAPPING AND REEF FISH STOCK ESTIMATION USING HIGH RESOLUTION SATELLITE DATA

2013 ◽  
Vol 5 (2) ◽  
Author(s):  
Vincentius P. Siregar ◽  
Sam Wouthuyzen ◽  
Andriani Sunuddin ◽  
Ari Anggoro ◽  
Ade Ayu Mustika
Keyword(s):  
High Resolution ◽  
Reef Fish ◽  
Satellite Imagery ◽  
Field Survey ◽  
Coral Cover ◽  
Fish Density ◽  
Fish Stock ◽  
Benthic Habitat ◽  
Live Coral ◽  
Stock Estimation

Shallow marine waters comprise diverse benthic types forming habitats for reef fish community, which important for the livelihood of coastal and small island inhabitants. Satellite imagery provide synoptic map of benthic habitat and further utilized to estimate reef fish stock. The objective of this research was to estimate reef fish stock in complex coral reef of Pulau Pari, by utilizing high resolution satellite imagery of the WorldView-2 in combination with field data such as visual census of reef fish. Field survey was conducted between May-August 2013 with 160 sampling points representing four sites (north, south, west, and east). The image was analy-zed and grouped into five classes of benthic habitats i.e., live coral (LC), dead coral (DC), sand (Sa), seagrass (Sg), and mix (Mx) (combination seagrass+coral and seagrass+sand). The overall accuracy of benthic habitat map was 78%. Field survey revealed that the highest live coral cover (58%) was found at the north site with fish density 3.69 and 1.50 ind/m2at 3 and 10 m depth, respectively. Meanwhile, the lowest live coral cover (18%) was found at the south site with fish density 2.79 and 2.18  ind/m2 at 3 and 10 m depth, respectively. Interpolation on fish density data in each habitat class resulted in standing stock reef fish estimation:  LC (5,340,698 ind), DC (56,254,356 ind), Sa (13,370,154 ind), Sg (1,776,195 ind) and Mx (14,557,680 ind). Keywords: mapping, satellite imagery, benthic habitat, reef fish, stock estimation

scholarly journals SHALLOW WATER HABITAT MAPPING AND REEF FISH STOCK ESTIMATION USING HIGH RESOLUTION SATELLITE DATA

2013 ◽  
Vol 5 (2) ◽  
Author(s):  
Vincentius P. Siregar ◽  
Sam Wouthuyzen ◽  
Andriani Sunuddin ◽  
Ari Anggoro ◽  
Ade Ayu Mustika
Keyword(s):  
High Resolution ◽  
Reef Fish ◽  
Satellite Imagery ◽  
Field Survey ◽  
Coral Cover ◽  
Fish Density ◽  
Fish Stock ◽  
Benthic Habitat ◽  
Live Coral ◽  
Stock Estimation

<p>Shallow marine waters comprise diverse benthic types forming habitats for reef fish community, which important for the livelihood of coastal and small island inhabitants. Satellite imagery provide synoptic map of benthic habitat and further utilized to estimate reef fish stock. The objective of this research was to estimate reef fish stock in complex coral reef of Pulau Pari, by utilizing high resolution satellite imagery of the WorldView-2 in combination with field data such as visual census of reef fish. Field survey was conducted between May-August 2013 with 160 sampling points representing four sites (north, south, west, and east). The image was analy-zed and grouped into five classes of benthic habitats i.e., live coral (LC), dead coral (DC), sand (Sa), seagrass (Sg), and mix (Mx) (combination seagrass+coral and seagrass+sand). The overall accuracy of benthic habitat map was 78%. Field survey revealed that the highest live coral cover (58%) was found at the north site with fish density 3.69 and 1.50 ind/m<sup>2</sup>at 3 and 10 m depth, respectively. Meanwhile, the lowest live coral cover (18%) was found at the south site with fish density 2.79 and 2.18  ind/m<sup>2</sup> at 3 and 10 m depth, respectively. Interpolation on fish density data in each habitat class resulted in standing stock reef fish estimation:  LC (5,340,698 ind), DC (56,254,356 ind), Sa (13,370,154 ind), Sg (1,776,195 ind) and Mx (14,557,680 ind).</p> <p>Keywords: mapping, satellite imagery, benthic habitat, reef fish, stock estimation</p>

scholarly journals THE BOTTOM SUBSTRATE SHALLOW WATER MAPPING USING THE QUICK BIRD SATELLITE IMAGERY

2010 ◽  
Vol 2 (1) ◽  
Author(s):  
Vincentius Siregar
Keyword(s):  
High Resolution ◽  
Shallow Water ◽  
Satellite Imagery ◽  
Transformation Method ◽  
Live Coral ◽  
Bottom Substrate ◽  
Accuracy Test ◽  
Coral Sand ◽  
Water Mapping

The objective of this study was to explore the capability of high resolution satellite data of QuicBird to map the characteristics of the bottom shallow water (habitat) using the transformation method of two bands (blue and green) by implementing "depth invariant index" algorithm i.e., Y = ln Band 1 - (ki/kj) ln Band 2. The result provide more detail information on the characteristic of the bottom shallow water comparing to the used of original band (RGB). The classification of the transformed image showed 6 classes of bottom substrats i.e., Live coral, Death, Coral, Sand mix coral, Sand mix algae, andMacro algae with Sand. The accuracy test of the map derived from the classification was about 79%.Keywords: bottom shallow water, Quick Bird image, depth invariant index, classification

Coral reef condition in several dive points around Bunaken Island, North Sulawesi

2014 ◽  
pp. 44
Author(s):  
Robert Towoliu
Keyword(s):  
Coral Reef ◽  
Coral Cover ◽  
Integrated Management ◽  
Good Condition ◽  
Live Coral ◽  
Core Zone ◽  
Integrated Management System ◽  
North Sulawesi ◽  
Live Coral Cover ◽  
Reef Condition

In order to know the coral reef conditions at several diving points around Bunaken Island, three dive locations (Ron’s point, Lekuan, and Tawara) were chosen as representative locations receiving pressures from snorkeling and SCUBA diving activities, while  core zone was representative of location for  no diving and fishing activities.  Results showed that location with diving activities had live coral cover  ranging from 16.89% to 45.78% at 3 and 10m depths, with condition range of bad to moderate, while the location for no diving and fishing activities (core zone) had live coral cover of 55.03% at 3m and 58.15% at 10m, respectively,  with good condition category.  The present study indicated that the diving activities have affected the coral reef condition, so that a sustainable integrated management system is needed to use the marine ecotourism potency without degrading the coral reef condition in Bunaken Island. Untuk mengetahui kondisi terumbu karang di beberapa lokasi penyelaman di Pulau Bunaken, tiga lokasi penyelaman(Ron’s point, Lekuan, dan Tawara) dipilih mewakili lokasi dengan tekanan aktivitas penyelaman snorkeling maupun SCUBA, sedangkan satu lokasi lainnya yaitu zona inti dipilih mewakili lokasi tanpa aktivitas penyelaman maupun aktivitas penangkapan ikan.  Hasil penelitian ini memperlihatkan bahwa lokasi dengan tekanan aktivitas penyelaman memiliki prosentase tutupan karang batu/hidup berkisar antara 16,89% - 45,78% pada kedalaman 3 dan 10m, dengan kategori kondisi terumbu karang buruk sampai cukup, sedangkan pada lokasi yang tidak memiliki aktivitas penyelaman memiliki prosentase tutupan karang batu/hidup sebesar 53,03% pada 3m dan 58,15% pada 10m dengan kategori kondisi terumbu karang adalah baik.  Hasil penelitian ini mengindikasikan bahwa aktivitas penyelaman snorkeling maupun SCUBA berdampak pada kondisi terumbu karang di Pulau Bunaken, sehingga sangat diperlukan system pengelolaan yang terpadu dan berkesinambungan dalam memanfaatkan secara maksimal potensi ekowisata bahari tanpa merusak ekosistem terumbu karang di Pulau Bunaken.

An updated national-scale mangrove forest map in China Using Sentinel-1 and Sentinel-2 Time-Series Data with Google Earth Engine

2021 ◽  
Author(s):  
Luojia Hu ◽  
Wei Yao ◽  
Zhitong Yu ◽  
Yan Huang
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Mangrove Forest ◽  
Google Earth ◽  
Series Data ◽  
National Scale ◽  
Mangrove Area ◽  
Google Earth Engine ◽  
Forest Maps ◽  
Sentinel 2

&lt;p&gt;A high resolution mangrove map (e.g., 10-m), which can identify mangrove patches with small size (&lt; 1 ha), is a central component to quantify ecosystem functions and help government take effective steps to protect mangroves, because the increasing small mangrove patches, due to artificial destruction and plantation of new mangrove trees, are vulnerable to climate change and sea level rise, and important for estimating mangrove habitat connectivity with adjacent coastal ecosystems as well as reducing the uncertainty of carbon storage estimation. However, latest national scale mangrove forest maps mainly derived from Landsat imagery with 30-m resolution are relatively coarse to accurately characterize the distribution of mangrove forests, especially those of small size (area &lt; 1 ha). Sentinel imagery with 10-m resolution provide the opportunity for identifying these small mangrove patches and generating high-resolution mangrove forest maps. Here, we used spectral/backscatter-temporal variability metrics (quantiles) derived from Sentinel-1 SAR (Synthetic Aperture Radar) and sentinel-2 MSI (Multispectral Instrument) time-series imagery as input features for random forest to classify mangroves in China. We found that Sentinel-2 imagery is more effective than Sentinel-1 in mangrove extraction, and a combination of SAR and MSI imagery can get a better accuracy (F1-score of 0.94) than using them separately (F1-score of 0.88 using Sentinel-1 only and 0.895 using Sentinel-2 only). The 10-m mangrove map derived by combining SAR and MSI data identified 20,003 ha mangroves in China and the areas of small mangrove patches (&lt; 1 ha) was 1741 ha, occupying 8.7% of the whole mangrove area. The largest area (819 ha) of small mangrove patches is located in Guangdong Province, and in Fujian the percentage of small mangrove patches in total mangrove area is the highest (11.4%). A comparison with existing 30-m mangrove products showed noticeable disagreement, indicating the necessity for generating mangrove extent product with 10-m resolution. This study demonstrates the significant potential of using Sentinel-1 and Sentinel-2 images to produce an accurate and high-resolution mangrove forest map with Google Earth Engine (GEE). The mangrove forest maps are expected to provide critical information to conservation managers, scientists, and other stakeholders in monitoring the dynamics of mangrove forest.&lt;/p&gt;

scholarly journals Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data

Land ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 118 ◽  
Author(s):  
Myroslava Lesiv ◽  
Linda See ◽  
Juan Laso Bayas ◽  
Tobias Sturn ◽  
Dmitry Schepaschenko ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Reference Data ◽  
Temporal Distribution ◽  
Google Earth ◽  
Training Data ◽  
Visual Interpretation ◽  
The Usa ◽  
Very High

Very high resolution (VHR) satellite imagery from Google Earth and Microsoft Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, one use of this imagery is to create reference data sets through visual interpretation, e.g., to complement existing training data or to aid in the validation of land-cover products. Through new applications such as Collect Earth, this imagery is also being used for monitoring purposes in the form of statistical surveys obtained through visual interpretation. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global overview of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Microsoft Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India, and with clear discontinuities at political borders. We also show that the availability of VHR imagery is currently not adequate for monitoring protected areas and deforestation, but is better suited for monitoring changes in cropland or urban areas using visual interpretation.

scholarly journals CONDITION OF CORAL AND REEF FISH IN THE LOCATION OF FISH CATCHING USING DYNAMITE FISHING IN KAPOPOSANG WATER PARK AND THE SURROUNDING SEA

2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Mahmudin Mahmudin ◽  
Chair Rani ◽  
Hamzah Hamzah
Keyword(s):  
Coral Reef ◽  
Reef Fish ◽  
Coral Cover ◽  
Low Cost ◽  
Fish Abundance ◽  
Live Coral ◽  
Coral Reef Ecosystem ◽  
Control Location ◽  
Target Fish ◽  
Reef Ecosystem

Dynamite fishing is one of the causes of damage to the coral reef ecosystem in Indonesia. Fishing activities using explosives (dynamite fishing) occur because of the desire of fishermen to get a lot of catch with low cost in a short time. Kapoposang Water Park (WP) is a region rich in marine biological resources. However, dynamite fishing activities which are still found within the area have caused the coral reef ecosystem to be severely damaged. The results showed a lower difference in the percentage of live coral cover at dynamite fishing locations (DF1, DF2) compared to control locations (K1, K2). In addition, the highest average values of coral fish abundance were found at locations K1, DF1, and DF2. Conversely, the results of the analysis found the lowest fish abundance at the K2 location. Different from the average number of reef fish species that were higher at the control location (K1, K2) compared to dynamite fishing locations (DF1, DF2). For the target fish biomass there is no real difference between the control location and dynamite fishing.

scholarly journals Status of Coral Reefs in the Water of Spermonde, Makassar, South Sulawesi

2021 ◽  
Vol 324 ◽  
pp. 03007
Author(s):  
Ni Wayan Purnama Sari ◽  
Rikoh Manogar Siringoringo ◽  
Muhammad Abrar ◽  
Risandi Dwirama Putra ◽  
Raden Sutiadi ◽  
...  
Keyword(s):  
Coral Reef ◽  
Coral Reefs ◽  
Coral Cover ◽  
Public Awareness ◽  
Live Coral ◽  
Health Index ◽  
Point Count ◽  
Live Coral Cover ◽  
Reef Health ◽  
Index Value

Observations of the condition of coral reefs have been carried out in Spermonde waters from 2015 to 2018. The method used in this observation uses Underwater Photo Transect (UPT), and the data obtained is analyzed using CPCe (Coral Point Count with Excel Extensions) software. The results show that the percentage of coral cover has increased from year to year. The percentage of live coral cover in 2015 was 19.64%, 23.60 in 2016, 23.72% in 2017, and 27.83% in 2018. The increase in live coral cover from year to year is thought to occur due to the availability of nutrients. or increasing public awareness, considering this location is one of the most famous tourist attractions in Makassar. Coral reef health index values can be used to classify coral reef health. Through the analysis of the coral reef health index, an index value of 4 was obtained, which means that the condition of the coral reefs is in the “moderate” category.

scholarly journals KEPADATAN MEGABENTOS PADA EKOSISTEM TERUMBU KARANG DI PERAIRAN DESA PERLANG BANGKA TENGAH, BANGKA BELITUNG

2019 ◽  
Vol 13 (2) ◽  
pp. 173-177
Author(s):  
Arham Hafidh Akbar ◽  
Sudirman Adibrata ◽  
Wahyu Adi
Keyword(s):  
Coral Reef ◽  
Data Collection ◽  
Coral Cover ◽  
Live Coral ◽  
Coral Reef Ecosystems ◽  
Tridacna Maxima ◽  
Belt Transect ◽  
Tridacna Gigas ◽  
Drupella Cornus ◽  
Diadema Setosum

This study aims to analyze the density of megabenthos in coral reef ecosystems in the waters of Perlang Village. This research was conducted in November 2019 in the waters of Perlang Village with the megabentos data collection method using the Bentos Belt Transect (BBT) method based on COREMAP CTI LIPI (2017) with 5 data collection stations. The results found 603 individuals consisting of 9 species from 4 megabenthos families in coral reef ecosystems. Species found at the study site are Diadema setosum, Diadema antillarium (Familli Deadematidae), Drupella cornus, Drupella rugosa (Family Murcidae), Trochus sp, Trochus conus, Tectus pyramis (Family Trochidae), Tridacna gigas, and Tridacna maxima (Family Tridacnidae) . The highest attendance percentage of all stations was obtained by Diadema setosum of 47.93% (289 people). Percentage of live coral cover from 5 observation stations ranged from 57.44% - 91.78%. Observation pensions that received the highest percentage of cover values ​​were at pension 2 with 91.78% in the very good category.

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