scholarly journals The Utilization of ALOS PALSAR Image to Estimate Natural Forest Biomass: Case Study at Bogani Nani Wartabone National Park

Jurnal Wasian ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 15
Author(s):  
Nurlita Indah Wahyuni
Keyword(s):  
Remote Sensing ◽  
National Park ◽  
Satellite Image ◽  
Forest Biomass ◽  
Research Area ◽  
Natural Forest ◽  
Alos Palsar ◽  
Remote Sensing Technology ◽  
Sensing Technology

The development of remote sensing technology makes it possible to utilize its data in many sectors including forestry. Remote sensing image has been used to map land cover and monitor deforestation. This paper presents utilization of ALOS PALSAR image to estimate and map aboveground biomass at natural forest of Bogani Nani Wartabone National Park especially SPTN II Doloduo and SPTN III Maelang. We used modeling method between biomass value from direct measurement and digital number of satellite image. There are two maps which present the distribution of biomass and carbon from ALOS PALSAR image with 50 m spatial resolution. These maps were built based on backscatter polarization of HH and HV bands. The maps indicate most research area dominated with biomass stock 0-5.000 ton/ha.

scholarly journals ABOVE GROUND TREES BIOMASS OF LORE LINDU NATIONAL PARK-CENTRAL SULAWESI : A STUDY COMBINING FIELD MEASUREMENT AND REMOTE SENSING

Agromet ◽  
2010 ◽  
Vol 24 (1) ◽  
pp. 33
Author(s):  
Naimatu Solicha ◽  
Tania June ◽  
M. Ardiansyah ◽  
Antonius B. W.
Keyword(s):  
Remote Sensing ◽  
Carbon Stock ◽  
Field Data ◽  
Forest Cover ◽  
Satellite Image ◽  
Forest Biomass ◽  
Allometric Equation ◽  
Natural Forest ◽  
Forest Cover Type ◽  
Cover Type

Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.Forests play an important role in global carbon cycling, since they hold a large pool of carbon as well as potential carbon sinks and sources to the atmosphere. Accurate estimation of forest biomass is required for greenhouse gas inventories and terrestrial carbon accounting. The information on biomass is essential to assess the total and the annual capacity of forest vigor. Estimation of aboveground biomass is necessary for studying productivity, carbon cycles, nutrient allocation, and fuel accumulation in terrestrial ecosystem. The possibility that above ground forest biomass might be determined from space is a promising alternative to ground-based methods. Remote sensing has opened an effective way to estimate forest biomass and carbon. By the combination of data field measurement and allometric equation, the above ground trees biomass possible to be estimated over the large area. The objectives of this research are: (1) To estimate the above ground tree biomass and carbon stock of forest cover in Lore Lindu National Park by combination of field data observation, allometric equation and multispectral satellite image; (2) to find the equation model between parameter that determines the biomass estimation. The analysis showed that field data observation and satellite image classification influencing much on the accuracy of trees biomass and carbon stock estimation. The forest cover type A and B (natural forest with the minor timber extraction) has the higher biomass than C and D (natural forest with the major timber extraction and agro forestry), it is about 607 ton/ha and 603 ton/ha. Forest cover type C is 457 ton/ha. Forest cover type D has the lowest biomass is about 203 ton/ha. Natural forest has high biomass, because of the tropical vegetation trees heterogeneity. Forest cover D has the lowest trees biomass because its vegetation component as secondary forest with the homogeneity of cacao plantation. The forest biomass and carbon estimation for each cover type will be useful for the further equation analysis when using the remote sensing technology for estimating the total biomass and for the economic carbon analysis.

The Technology of Remote Sensing and its Application to Terrestrial Ecosystem Restoration

2013 ◽  
Vol 748 ◽  
pp. 1176-1179
Author(s):  
Si Zhang ◽  
Chun Mei Xiong
Keyword(s):  
Remote Sensing ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Research Area ◽  
Living Environment ◽  
Human Beings ◽  
Local Conditions ◽  
Timing Accuracy ◽  
Remote Sensing Technology ◽  
Sensing Technology

Terrestrial ecosystems as the most important type of ecological system provide humanity with a main part of the living environment, food and clothing. However, many of ecological environmental have been severely damaged by human beings irrational activities, such as mining, deforestation, excavation herbs, etc. Faced with ecological and environmental protection pressure, its urgent to carry out ecological restoration projects according to the local conditions. Remote sensing technology is widely used in terrestrial ecosystems restoration because of its objectivity, real-timing, accuracy, covering a wide area and other unique advantages. This article discusses the restoration of terrestrial ecosystems based on remote sensing technology. At last, it analyses development trends of this research area.

scholarly journals STUDY OF DUST POLLUTION DETECTING ABILITY IN URBAN AREAS BY REMOTE SENSING TECHNOLOGY TO SUPPORT AIR ENVIRONMENT OBSERVATION

2012 ◽  
Vol 15 (4) ◽  
pp. 33-47
Author(s):  
Van Thi Tran ◽  
Binh Thi Trinh ◽  
Bao Duong Xuan Ha
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Satellite Image ◽  
Regression Function ◽  
Statistical Correlation ◽  
Step Test ◽  
Residential Areas ◽  
Remote Sensing Technology ◽  
Sensing Technology

This paper presents the approach towards application of remote sensing technology to monitor the air environemnt. Specific inital research is findings PM10 dust from SPOT 5 satellite image. The calculation based on reflectance value on remote sensing satellite images. The main method is to calculate statistical correlation regression between the PM10 concentration from ground station observations and reflectance value on each image band and the main components of satellite imagery in 2003 to find the best regression function, applied then to images 2011 where its radiance value was relatively normalized under atmospheric, geometric, environmental conditions of image 2003. The results showed the best correlation in nonlinear regression case. Spatial distribution of PM10 concentrations > 200μg/m3 found on most main roads, industrial parks and residential areas. This study is a first step test, but the results have demonstrated that satellite imagery can be used as a useful, effective tool, to monitor air environment in cities.

scholarly journals Prakiraan Daerah Penangkapan Ikan Di Selat Bali Berdasarkan Data Citra Satelit [Fishly Ground Area Estimation In The Bali Strait Satellite Image Database Based]

2019 ◽  
Vol 4 (1) ◽  
pp. 87
Author(s):  
Iqbal Ghazali, Abdul Manan
Keyword(s):  
Remote Sensing ◽  
Marine Ecosystem ◽  
Satellite Image ◽  
Sea Surface ◽  
Fishing Ground ◽  
Fishing Activity ◽  
Area Estimation ◽  
Remote Sensing Technology ◽  
Sensing Technology

Abstract Indonesia has a lot of potential marine ecosystem and fisheries, this condition make some many Indonesian get a occupation to be fisherman. However, that is make a problem during his fishing activity, so we have to make some sophisticated technology to support that is activity. At the time, remote sensing technology is the answer for they problem, it is because of that is technology fisherman can be improvement they catcher with more efficient. Determination of fishly ground area by remote sensing technology has some stage before arranging layout Fishly Ground Area Estimation (FGAE) map. Procedure to arranging are respectively data searching, data processing, and data analysis, and the last stage is composing of layout of FGAE map. The main purpose of this study is to know about catching area at Bali straits based on image satellite with creating layout of FGAE map. This study doing descriptive method. At the PDPI making process, the chlorophyl-a data and sea surface temperature getting important parameter, which temperature is the main to parameter to understand of front area and upwelling which is have a lot of nutrient composition. In the other hand, chlorophyl-a is also parameter to know of prosperity area. The data of current, wind speed, wave, and sea surface level are important component as supporting data that will be help to fisherman on determination of fishing ground area at helping fisherman in catching activity.

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