ALOS AVNIR-2 Image Research Articles

Dark target effectiveness for dark‐object subtraction atmospheric correction method on mangrove above‐ground carbon stock mapping

One of the most effective atmospheric correction methods is dark-object subtraction (DOS) method, where the atmospheric offset can be generated from the image itself. The success of DOS strongly relies on the availability and quality of the dark target. Based on the response to the downwelling irradiances, the most effective dark target would be optically-deep water, which is not always available. It is important to assess the alternative dark targets in the absence of the ideal dark target. This research aimed at comparing the effectiveness of different dark targets for DOS method during mangrove above-ground carbon stock (AGC) mapping and comparing the accuracy with robust atmospheric correction FLAASH method. ALOS AVNIR-2 image was used as the test image, and mangrove forest of Karimunjawa and Kemujan Island was selected as the study area. The comparison covers the quality of healthy mangrove reflectance and the accuracy of vegetation indices for mangrove AGC mapping. The results of this research showed that non-ideal dark targets such as cloud-shadow pixels and the minimum value of the image can be used in the absence of ideal dark target, and DOS method is more efficient and effective than more robust atmospheric correction method.

SUITABILITY OF LOCATION FOR RESTOCKING CLAMS TRIDACNIDAE IN THE SPERMONDE ARCHIPELAGO

Efforts to protect giant clams from extinction one of them through conservation, which set a region as a restocking area. The research aimed to analyze the suitability environments with the density giant clams in the aquatic. The research conducted in September 2013-January 2014. The research site was determined by purposive sampling of middle inner zone = MIZ, middle outer zone = MOZ, and outer zone = OZ in the aquatic of Spermonde Archipelago. The research conducted was using observation method of biology, physics, and chemistry parameters of aquatic at mintakat reef flats, reef slope and reef base. Data analysis of location suitability of restocking giant clams using WSM method (and correlation analysis of giant clams density with water quality, then integrated with ALOS Avnir-2 image. The result research shows the density giant clams influenced by the physical environment parameters, mainly salinity, brightness and depth. The suitability location of restocking giant clams for class Very suitable in P. Langkadea and P. Pala (MOZ), P. Cangke (OZ), P. Tambakulu and P. Kondongbali (OZ) on mintakat reef flats. Class Very suitability on reef slope in P. Kondongbali and P. Kapoposang (OZ). Class accordance with the reef flats, there are P. Podang Podang Lompo (MOZ), P. Sarappo Keke (OZ) and P. Kapoposang (OZ). Class Appropriate to reef slope mintakat in P. Langkadea (MOZ) and P. Sarappo Keke (OZ). Determination of giant clams restocking area in nature needs considers the location suitability, primarily the quality of aquatic physics. Keywords: conservation, clam, weight sum model, ALOS Avnir-2 image

Study of coastal wetland classification based on decision rules using ALOS AVNIR-2 images and ancillary geospatial data

Wetlands play irreplaceable key roles in ecological and environmental procedures. To make effective conservation and management, it is essential to understand the wetlands’ distribution and changes. In this study, an approach based on decision rules algorithm in conjunction with maximum likelihood classification is proposed for coastal wetland mapping using multi-temporal remotely sensed imagery and ancillary geospatial data. As a case study, Multi-temporal Advanced Visible and Near Infrared Radiometer type 2 images acquired by Japanese Advanced Land Observation Satellite are analysed to investigate the seasonal change pattern of coastal wetlands in Washington State, USA. Geospatial data, including Digital Elevation Model and spatial neighbourhood knowledge, are further integrated to characterize wetland features and discriminate classes within a certain elevation ranges. The final result is a refined coastal wetland map with 15 land cover categories. Preliminary evaluation of the final result shows that the proposed approach is effective in coastal wetland mapping.

Relationship between Turbid Water and Coral Damage Distribution Using ALOS AVNIR-2 Images and Diving Survey Data Immediately after the Heavy Rain Disaster of the Amami-Oshima Island, Japan

To understand the relationship between turbid water and coral damage caused by the heavy rain disaster at the end of October 2010 in Amami-Oshima, Kagoshima Prefecture, Japan, turbid water and coral damage distribution monitoring was attempted using satellite imagery and a diving survey immediately after the disaster. ALOS AVNIR-2 images (spatial resolution: 10 m) on October 6 (before the disaster), October 24, October 30, and October 31 (after the disaster) were obtained as satellite data in 2010. The red-silt deposition index (RSI) map based on the method by Nadaoka and Tamura (1992) was also created. Moreover, a diving survey was conducted via the spot check method on December 18, 2010. As a result, comparison between the high turbidity (RSI) areas estimated using AVNIR-2 data and the coral damage areas judging from the field survey was considered relatively light. It is shown that satellite data such as AVNIR-2 can be a powerful tool to monitor damage distribution of coral reefs after heavy rain.

SPATIAL DISTRIBUTION OF SOME CHEMICAL CHARACTERISTICS OF AN ACID SULFATE SOIL-AFFECTED BRACKISHWATER PONDS IN THE COASTAL AREA OF LUWU REGENCY SOUTH SULAWESI PROVINCE

Spatial distribution of brackishwater pond soil has important role in the system of bioenvironment including brackishwater pond environment. This research was aimed to determine the spatial distribution of some chemical characteristics of an acid sulfate soil-affected brackishwater pond in coastal area of Luwu Regency South Sulawesi Province, Indonesia. ALOS AVNIR-2 images (acquisition 16 May 2008, 16 October 2008, 17 September 2009) were integrated with Indonesian Topographic maps to obtain base map. Sampling soil points were determined by simple random sampling in 104 points for two different soil depths i.e. 0-0.2 m and 0.5-0.7 m. A total of 18 soil chemical characteristics was measured in the field and analyzed in the laboratory. Geostatistic using kriging method in the ArcGIS 9.3 software was used to interpolate the data. The results of this study indicated that in general pond soil chemical characteristics in Luwu Regency could be categorized with high variability or relatively heterogenic wi th the value of var iation coefficient more than 36%. The soil characteristics that explain acidity had shown similar pattern in spatial distribution as well as other soil characteristics with soil nutrient. The high value of pH and low value of PO4 were generally found in the northern part of Luwu Regency, including East Lamasi, East Walenrang, Bua, and Ponrang Subdistricts. It is recommended that soil management in brackishwater ponds of Luwu Regency could be based on soil chemical characteristics so its could improve the production through minimizing the input, increasing carrying capacity, and avoiding environmental degradation.

SPATIAL DISTRIBUTION OF BRACKISHWATER POND SOIL CHARACTERISTICS IN PEKALONGAN CITY CENTRAL JAVA PROVINCE

Spatial distribution of brackishwater pond soil has a vital role in the system of bioenvironment including brackishwater pond environment. This research was aimed to determine the spatial distribution of brackishwater pond soil characteristics in Pekalongan City, Central Java Province. A total of 59 sampling points each with two different soil depth samplings were determined by simple random method. A total of 21 soil characteristics were measured in the field and analyzed further in the laboratory. Geostatistic with Kriging Interpolation method in the ArcGIS 9.3 software were used to depict the distribution of the data across the landscape. Furthermore, the spatial distribution was presented by using ALOS AVNIR-2 image. Research result indicates that in general, pond soil in Pekalongan City can be classified as soil with high variability or relatively heterogenic with the value of variation coefficient more than 36%. Soil characteristics which have similar pattern of spatial distribution are acid sulfate soil and soil nutrient content. High value of pH, organic matter, and total-N of soil, and on the other hand, low value of PO4 were generally found in the pond area of Krapyak Lor Village, while in Pekalongan City, it was found high clayish soil content but relatively homogenous. It is recommended that pond management must be based on soil characteristics which are different from one area to another. The soil characteristics itself can be drawn and assessed through spatial distribution.

Cloud Removal of Optical Image Using SAR Data for ALOS Applications. Experimenting on Simulated ALOS Data

Cloud is always problem of optical remote sensing data. ALOS-AVNIR2 images also will be affected. Microwave images are not affected by cloud. ALOS satellite has both optical and microwave sensor, similar resolution (~10m). Therefore, main purpose of this study is to develop a method for removing cloud in ALOS-AVNIR2 images based on ALOS-PALSAR data. This method is developed based on interpolating under cloud pixel values for ALOS-AVNIR2 images. To remove cloud, it needs to be defined. A combination method of Total Reflectance Radiance Index (TRRI) and Cloud-Soil Index (CSI) is used to define cloud. Around cloud pixels are mixture of cloud and other objects. So, that is very difficult to define. Therefore, the around cloud pixels are extended from cloud. Cloud shadow problem also is discussed in this study. Condition to apply this method is that objects in optical image and radar image change not very much. This method is experimented on simulated ALOS data from Landsat TM and JERS1-SAR images. Interpolated image is a free cloud and shadow image. Visual logic of objects is good. Original image and interpolated image is almost similar together. This method also can be applied for combination of two optical images to remove cloud if change of objects covered by cloud is not so much. Result of this study is a program with many functions like: define cloud, extend cloud, get shadow, remove cloud and so on. This is free software for every user.