scholarly journals Pemanfaatan Citra Landsat 8 Multitemporal dan Model Forest Canopy Density (FCD) untuk Analisis Perubahan Kerapatan Kanopi Hutan di Kawasan Fakultas Geografi Universitas Gadjah Mada Gunung Kelud, Jawa Timur

2017 ◽  
Vol 31 (1) ◽  
pp. 65
Author(s):  
Shafira Himayah ◽  
Hartono Hartono ◽  
Projo Danoedoro
Keyword(s):  
Remote Sensing ◽  
Forest Canopy ◽  
Landsat 8 ◽  
Canopy Density ◽  
Protection Forest ◽  
Image Recording ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Before And After ◽  
Forest Canopy Density

Penginderaan jauh memiliki keunggulan dalam hal resolusi temporal yang dapat dimanfaatkan untuk meneliti perubahan suatu obyek dalam waktu yang berbeda. Hutan Gunung Kelud mengalami perubahan setelah erupsi tahun 2014. Perubahan tersebut dapat dianalisis dengan memanfaatkan teknologi penginderaan jauh melalui citra multitemporal. Penelitian ini bertujuan untuk mengkaji kemampuan citra Landsat 8 multitemporal dan Forest Canopy Density (FCD) untuk perubahan kerapatan kanopi di Hutan Lindung Gunung Kelud sebelum dan sesudah erupsi tahun 2014.Citra penginderaan jauh yang digunakan adalah citra Landsat 8 perekaman 26 Juni 2013 dan 4 September 2015. Metode yang digunakan adalah pemodelan FCD yang menghasilkan kerapatan kanopi per piksel. Hasil pemodelan FCD kemudian digunakan untuk menganalisis perubahan kerapatan kanopi setelah erupsi. Berdasarkan penelitan ini didapatkan hasil bahwa citra Landsat 8 dapat dipergunakan untuk mengetahui kerapatan kanopi Hutan Lindung Gunung Kelud sebelum dan setelah erupsi dengan masing-masing akurasi sebesar 83,73% dan 81,14%. Terjadi perubahan luas kerapatan kanopi setelah erupsi, dimana terdapat 8833,95 Ha hutan yang mengalami penurunan kerapatan kanopi, sedangkan hutan dengan kerapatan kanopi yang tetap adalah seluas 2149,38 Ha, dan hutan yang mengalami peningkatan kerapatan kanopi adalah seluas 1643,31 Ha. Remote sensing has an advantage in terms of temporal resolution that can be exploited to examine the changes of an object in different times. Gunung Kelud Forest is changing after the eruption in 2014. The changes can be analyzed by utilizing remote sensing technology through multitemporal imagery. This study aims to examine the capabilities of Landsat 8 multitemporal and Forest Canopy Density (FCD) images for changes in canopy density in Kelud Protection Forest before and after the eruption in 2014. Remote sensing imagery used is Landsat 8 image recording June 26, 2013, and September 4, 2015, The method used is FCD modeling that produces a density of the canopy per pixel. FCD modeling results are then used to analyze changes in density of the canopy after the eruption. Based on this research, it can be concluded that Landsat 8 image can be used to determine the density of canopy of Kelud Protection Forest before and after eruption with 83.73% and 81.14% accuracy respectively. There was a change in the area of the canopy density after the eruption, where there was 8833.95 ha of forest that experienced a decrease in canopy density, whereas forests with fixed canopy densities were 2149.38 Ha, and forests with an increase in canopy density were 1643.31 Ha.

scholarly journals COMPARISON OF MODEL ACCURACY IN TREE CANOPY DENSITY ESTIMATION USING SINGLE BAND, VEGETATION INDICES AND FOREST CANOPY DENSITY (FCD) BASED ON LANDSAT-8 IMAGERY (CASE STUDY: PEAT SWAMP FOREST IN RIAU PROVINCE)

2018 ◽  
Vol 15 (1) ◽  
pp. 81 ◽  
Author(s):  
Faisal Ashaari ◽  
Muhammad Kamal ◽  
Dede Dirgahayu
Keyword(s):  
Remote Sensing ◽  
Forest Canopy ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Single Band ◽  
Tree Canopy ◽  
Landsat 8 ◽  
Swamp Forest ◽  
Canopy Density ◽  
Forest Canopy Density

Identification of a tree canopy density information may use remote sensing data such as Landsat-8 imagery. Remote sensing technology such as digital image processing methods could be used to estimate the tree canopy density. The purpose of this research was to compare the results of accuracy of each method for estimating the tree canopy density and determine the best method for mapping the tree canopy density at the site of research. The methods used in the estimation of the tree canopy density are Single band (green, red, and near-infrared band), vegetation indices (NDVI, SAVI, and MSARVI), and Forest Canopy Density (FCD) model. The test results showed that the accuracy of each method: green 73.66%, red 75.63%, near-infrared 75.26%, NDVI 79.42%, SAVI 82.01%, MSARVI 82.65%, and FCD model 81.27%. Comparison of the accuracy results from the seventh methods indicated that MSARVI is the best method to estimate tree canopy density based on Landsat-8 at the site of research. Estimation tree canopy density with MSARVI method showed that the canopy density at the site of research predominantly 60-70% which spread evenly.

scholarly journals Application of Forest Canopy Density (FCD) Model for the Hotspot Monitoring of Crown Fire in Tebo, Jambi Province

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Muhammad Attorik Falensky ◽  
Anggieani Laras Sulti ◽  
Ranggas Dhuha Putra ◽  
Kuswantoro Marko
Keyword(s):  
Remote Sensing ◽  
Spatial Analysis ◽  
Forest Canopy ◽  
Remote Sensing Data ◽  
Forest Area ◽  
Landsat 8 ◽  
Crown Fire ◽  
Canopy Density ◽  
Sensing Data ◽  
Forest Canopy Density

<p><em>Indonesia is one of the owners of the 9th largest forest area in the world. Forest area in Indonesia reaches 884,950 km<sup>2</sup>. Tebo Regency is a regency in Jambi Province which has a wide forest area of 628,003 Ha. However, this forest area has been reduced due to the conversion of functions of Industrial Plantation Forests (HTI), oil palm plantations, and forest clearing activities for both settlements and plantations which led to the phenomenon of forest and land fires (karhutla). This study aims to get a better knowledge of crowns of fire potential locations in forest areas using remote sensing technology. Remote sensing data used in this study is from the satellite imagery </em><em>of </em><em>Landsat 8 OLI - TIRS in 2019. Remote sensing data is used to produce a Forest Canopy Density (FCD) model that can be overlap</em><em>ped with</em><em> a hotspot location, so the crown fire potential locations will be explored in the forest area of Tebo Regency, Jambi Province. Identification of hotspot patterns in Forest Areas was analyzed using spatial analysis. The results of this study are useful for the government as the information of the hotspot area as the cause of fires in the Forest Region of Tebo Regency Jambi Province.</em></p><strong><em>Keywords</em></strong><em>: Spatial Analysis, Forest Cover Density (FCD), Hotspots, Forest Areas, Remote Sensing</em>

scholarly journals Analysis Comparison of Algorithms for Determination Concentration of Chlorophyll-a in Traditional and Intensive Milkfish Ponds Using LANDSAT 8 Images

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Nurhadi Bashit ◽  
Abdi Sukmono ◽  
Baskoro Agum Gumelar
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Coastal Area ◽  
Average Concentration ◽  
The Body ◽  
Landsat 8 ◽  
Northern Coast ◽  
Fish Production ◽  
Remote Sensing Technology ◽  
Sensing Technology

Indonesia is an Archipelago Country because the Country of Indonesia consists of many islands stretching from Sabang in the west to the island of Merauke on the east. The Archipelago Country also comes from the old name of the Indonesian Country called Nusantara, because Nusantara is a country that consists of many islands. Indonesia is an Archipelago Country which means it has potential resources in the coastal areas, one of which is found on the northern coast of Java. The coastal area is an important area to be reviewed, one of which is the use of coastal resources by paying attention to the condition of the ecosystem that remains stable. Opportunities for coastal area utilization in the field of fisheries are in the form of fishing activities or fish farming, especially pond cultivation activities. Based on data from the Department of Marine and Fisheries of the Province of Central Java in 2010, pond cultivation is one of the potential resources on the coast. This potential is supported by the government to increase fish production in order to increase the consumption of fish in the community. Therefore, it is necessary to choose the most effective method of pond cultivation between traditional methods and intensive methods to optimize fish production. One indicator of effectiveness between the two methods can be seen from the phytoplankton distribution. Phytoplankton contains chlorophyll-a in the body and is a natural food from fish. Phytoplankton provides important ecological functions for the aquatic life cycle by serving as the basis of food webs in water. Phytoplankton also functions as the main food item in freshwater fish culture and seawater fish cultivation. Therefore, it is necessary to know the chlorophyll-a concentration in the ponds of traditional and intensive methods to determine the concentration chlorophyll-a of the two pond methods. One method used to determine the concentration of chlorophyll-a using remote sensing technology. Remote sensing technology can be used to determine the concentration of chlorophyll-a using the Wouthuyzen, Wibowo, Pentury, Much Jisin Arief and Lestari Laksmi algorithms. The results showed that the Pentury algorithm was relatively better to determine the concentration of chlorophyll-a in shallow waters (ponds). The lowest concentration of chlorophyll-a in traditional ponds is 0.47068 mg/m3, the highest concentration is 1.95017 mg/m3 and the average concentration is 1.12893 mg/m3, while in intensive ponds the lowest concentration is 0.36713 mg/m3, the concentration the highest is 3.17063 mg/m3 and the average concentration is 1.53556 mg/m3.

scholarly journals INVESTIGATION OF FOREST CANOPY DENSITY CHANGES IN HYRCANIAN FOREST RESOURCES DURING 1987 TO 2002 USING REMOTE SENSING TECHNOLOGY

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1031-1034
Author(s):  
M. Taefi Feijani ◽  
S. Azadnejad ◽  
S. Homayouni ◽  
M. Moradi
Keyword(s):  
Time Series ◽  
Forest Canopy ◽  
Spectral Band ◽  
Mixed Forest ◽  
Canopy Density ◽  
Rate Of Growth ◽  
Sensing Technology ◽  
Forest Canopy Density ◽  
Annual Time Series ◽  
Forest Lands

Abstract. Forest canopy density (FCD) of seventeen protected areas of the Caspian Hyrcanian mixed forest are studied here. A modified version of FCD mapper based on spectral band fusion and customized threshold calibration that is optimized for Hyrcanian forests is used for this purpose. In this project, the results of applying the FCD model on three time series of satellite images have been analysed. This classification is based on the FAO standard and consist of four categories such as no-forest, thin, semi-dense and dense. These images, taken with TM and ETM sensors, belong to three-time series between 1987 and 2002. The results of this study indicate that the rate of growth or destruction of forests has been investigated in the regions. Then, using tables and diagrams of variations, the rate of growth or destruction of forest lands in the corresponding period in each class is determined. The FCD model has the ability to study the canopy loading classes in the annual time series.

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

scholarly journals Forest canopy density assessment using different approaches – Review

2017 ◽  
Vol 63 (No. 3) ◽  
pp. 107-116 ◽  
Author(s):  
Abdollahnejad Azadeh ◽  
Panagiotidis Dimitrios ◽  
Surový Peter
Keyword(s):  
Remote Sensing ◽  
Cost Saving ◽  
Forest Canopy ◽  
Soil Conditions ◽  
Canopy Density ◽  
Different Types ◽  
Forest Canopy Density ◽  
Satellite Sensors ◽  
Remote Sensing Methods ◽  
Density Assessment

Crown canopy is a significant regulator of forest, affecting microclimate, soil conditions and having an undeniable role in a forest ecosystem. Among the different materials and approaches that have been used for the estimation of crown canopy, satellite based methods are among the most successful methods regarding cost-saving efforts and different kinds of options for measuring the crown canopy. Different types of satellite sensors can result in different outputs due to their various spectral and spatial resolution, even when using the same methodologies. The aim of this review is to assess different remote sensing methods for forest crown canopy density assessment.

Estimation of Sea Surface Temperature (SST) Using Split Window Methods for Monitoring Industrial Activity in Coastal Area

2017 ◽  
Vol 862 ◽  
pp. 90-95 ◽  
Author(s):  
Agung Budi Cahyono ◽  
Dian Saptarini ◽  
Cherie Bhekti Pribadi ◽  
Haryo Dwito Armono
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Brightness Temperature ◽  
Coastal Development ◽  
Sea Surface ◽  
Distribution Area ◽  
Landsat 8 ◽  
Remote Sensing Technology ◽  
Sensing Technology

The three drivers of environmental change: climate change, population growth and economic growth, result in a range of pressures on our coastal environment. Coastal development for industry and farming are a major pressure on terrestrial and environmental quality. In their process most of industry using sea water as cooling water. When water used as a coolant is returned to the natural environment at a higher temperature, the change in temperature decreases oxygen supply and affects marine ecosystem. This research is presents results from ongoing study on application of Landsat 8 for monitoring the intensity and distribution area of sea surface temperature changed by the heated effluent discharge from the power plant on Paiton coast, Probolinggo, East Java province. Remote sensing technology using a thermal band in Operational Land Imager (OLI) sensor of Landsat 8 sattelite imagery (band 10 and band 11) are used to determine the intensity and distribution of temperature changes. Estimation of sea surface temperature (SST) using remote sensing technology is applied to provide ease of marine temperature monitoring with a large area coverage. The method used in this research using the Split Window Algorithm (SWA) methods which is an algorithm with ability to perform extraction of sea surface temperature (SST) with brigthness temperature (BT) value calculation on the band 10 and band 11 of Landsat 8. Formula which was used in this area is Ts = BT10 + (2.946*(BT10 - BT11)) - 0.038 (Ts is the surface temperature value (°C), BT10 is the brightness temperature value (°C) Band 10, BT11 is the brightness temperature value (°C) Band 11. The result of this algorithm shows the good performance with Root Mean Square Error (RMSE) amount 0.406.

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