scholarly journals National wetland mapping in China: A new product resulting from object-based and hierarchical classification of Landsat 8 OLI images

2020 ◽  
Vol 164 ◽  
pp. 11-25 ◽  
Author(s):  
Dehua Mao ◽  
Zongming Wang ◽  
Baojia Du ◽  
Lin Li ◽  
Yanlin Tian ◽  
...  
Keyword(s):  
Hierarchical Classification ◽  
New Product ◽  
Landsat 8 ◽  
Wetland Mapping ◽  
Landsat 8 Oli ◽  
Object Based

scholarly journals Analysis of the utilization of landsat 8 oli imagery for mapping the distribution of coral reefs in Pulau Weh Sabang

DEPIK ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 161-166
Author(s):  
M Taufik Rahmadi ◽  
Sugiharto Sugiharto ◽  
Mbina Pinem ◽  
Ayu Suciani
Keyword(s):  
Coral Reef ◽  
Distribution Area ◽  
Landsat 8 ◽  
Nearest Neighbour ◽  
Landsat 8 Oli ◽  
Coral Reef Ecosystem ◽  
Object Based ◽  
Coral Reef Ecosystems ◽  
Almost All ◽  
Reef Ecosystem

As one of the largest archipelagic countries globally, Indonesia has diverse natural resources, one of which is the coral reef ecosystem. Coral reef ecosystems are spread across almost all Indonesian waters, and Pulau Weh Sabang is one distribution area. This study aims to determine the distribution of coral reef ecosystems and test landsat 8 oli imagery accuracy in mapping coral reef ecosystems. The method used in this research is the nearest neighbour algorithm object-based classification method. The results showed that the coral reef ecosystem in Pulau Weh Sabang was divided into two classes: a healthy coral reef ecosystem class with 277.38 hectares and a medium condition coral reef ecosystem class with an area of 710.01 Ha.Keywords:Landsat 8 oliMappingDistributionCoral reefWeh Island 

scholarly journals Dynamique De L’occupation Du Sol Dans Les Zones Humides De La Commune D’allada Au Sud-Benin (Sites Ramsar 1017 Et 1018)

2018 ◽  
Vol 14 (12) ◽  
pp. 59
Author(s):  
L. Estelle Brun ◽  
Djego J. Gaudence ◽  
Moussa Gibigaye ◽  
Brice Tente
Keyword(s):  
Sustainable Management ◽  
Supervised Classification ◽  
Landsat 8 ◽  
Maximum Likelihood Algorithm ◽  
Landsat 8 Oli ◽  
Human Pressure ◽  
Integral Element ◽  
Benin Republic ◽  
Anthropic Pressure

The wetlands are the integral element of the natural resource of Benin Republic. However, anthropic pressure on those “fragil” environments, contribute to the reducing of their surface and accordingly, to a loss their biodiversity. The target objective is to make cartography of land units from 1990 to 2014 in order to identify the various pressures upon the wet ecosystems. A 2014 Landsat 8 OLI-TIRS image and a 1990 map of Benin land cover were used to establish the cartography. We used the Maximum likelihood algorithm to execute the supervised classification of the landsat image in ERDAS. The mapping of the land’s units in the wetlands was then carried out in ArcGIS. The results revealed that the tree savana have completely disappeared. It represents 11.47 % of the landscape in 1990 against 0 % in 2014. The mosaics of fields and fallows under palm plantations have reduced to -30.42 % in 2014. They represent 66.63 % of the landscape. The land units which progressed are the mosaic of fields and fallow (12.06 %), the swamps (10.47 %), the plantations (5.26 %) and the agglomerations (2.71 %). This shows strong human pressure exerted on the natural vegetation of the wetlands in the Allada district. These results will provide the local authorities with a tool for decision support, for an efficient use and a sustainable management of these natural wet ecosystems.

Kajian Metode Klasifikasi Citra Landsat-8 untuk Pemetaan Habitat Bentik di Kepulauan Padaido, Papua

2017 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Muhammad Hafizt ◽  
Marindah Yulia Iswari ◽  
Bayu Prayudha
Keyword(s):  
Coral Reefs ◽  
Satellite Remote Sensing ◽  
Satellite Images ◽  
Habitat Mapping ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Classification Methods ◽  
Landsat 8 Oli ◽  
Remote Sensing Technique ◽  
Object Based

<strong>Assessment of Landsat-8 Classification Method for Benthic Habitat Mapping in Padaido Islands, Papua.</strong> Indonesia is the biggest archipelagic country in the world with an area of coral reefs of 39,583 km.This area has to be managed effectively and efficiently utilizing satellite remote sensing technique capable of mapping of benthic habitat coverage, such as coral reefs, seagrasses, macroalgae, and bare substrates. The technique is supported by the availability of Landsat-8 OLI satellite images that have been recording the regions of Indonesia continuously every 16 days. This research was carried out in June 2015 in parts of Padaido Islands, Papua. This area was selected due to high coral reef damages. This study utilized Landsat-8 OLI to compare two classification methods, namely pixel based and object based methods using ‘maximum 2 likelihood’ (ML) and ‘example based feature extraction’ classifications, respectively, after water column correction (Lyzenga method).  The results showed that both methods produced benthic habitat maps with 7 class covers. The pixel-based classification resulted in a better overall accuracy (47.57%) in the mapping of benthic habitats than object-based classification approach (36.17%). Thus, the ML classification is applicable for benthic habitat mapping in Padaido Islands. However, the consistency of this method must be analyzed in many diffrent locations of Indonesian waters.

scholarly journals ANALISIS VEGETASI DI TAMAN WISATA ALAM (TWA) SUNGAI DUMAI, RIAU

2021 ◽  
Vol 16 (1) ◽  
pp. 25-36
Author(s):  
Hanifah Ikhsani
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Vegetation Density ◽  
Vegetation Analysis ◽  
Landsat 8 Oli ◽  
Density Class ◽  
Vegetation Class ◽  
Do So

TWA Sungai Dumai is a tourist forest area and ensuring the preservation of natural potential. However, there are problems that can disrupt the sustainability of it, including forest and land fires and conversion of land use to agriculture and oil palm plantations. Until now, there is no vegetation analysis using satellite imagery in TWA Sungai Dumai, so it is important to do so that can be managed sustainably. This study  classification of vegetation density classes which are presented in the form of a vegetation density class map in it. This research uses Landsat-8 OLI / TIRS images from October 2017 and October 2020 which are processed to determine density class using Normalized Difference Vegetation Index algorithm. The vegetation density class with the highest area in 2017 was the vegetation density class (2380,832 ha or 66,819% of the total area), while the lowest area was the non-vegetation class (75,737 ha or 2,126% of the total area). The vegetation density class with the highest area in 2020 in TWA Sungai Dumai is dense vegetation density class (3205,039 ha or 89,950% of the total area), while the lowest area is non-vegetation class (1,637 ha or 0.046% of the total area)

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