scholarly journals REVISITING THE DEMOCRATIC REPUBLIC OF THE CONGO STRATIFICATION MAP FOR THE YEAR 2000 USING CLOUD-BASED COMPOSITING AND OBJECT-BASED CLASSIFICATION ALGORITHMS

2021 ◽  
Vol 9 (07) ◽  
pp. 928-946
Author(s):  
Wilfred Kombe Ibey ◽  
◽  
Jean-Paul Kibambe Lubamba ◽  
◽  
Keyword(s):  
Land Cover ◽  
Democratic Republic ◽  
Object Based ◽  
Moist Forest ◽  
Republic Of The Congo ◽  
Remote Sensing Techniques ◽  
Images Processing ◽  
User Friendly ◽  
Year 2000 ◽  
Random Sampling Approach

National stratification maps are essential to improve forest management systems. For the Democratic Republic of the Congo, the existing maps derived from remote sensing techniques do not allow an optimal representation of the diverse land cover classes constituting the national stratification scheme. This situation is inherent to the cloud persistence, the seasonality effects and the spatial resolution of the input satellite imagery used that is not always adequate for the discrimination of certain land cover classes. This paper explores a cloud-based median luminance best pixel approach to obtain a cloud-free mosaic of optimal quality. The mosaic produced has necessitated nearly 2,500 Landsat scenes and a following object-based classification enabled the generation of a stratification map for the year 2000 according to the national stratification theme. A stratified random sampling approach that required 1,141 reference samples allowed estimating the map accuracy at 79.32%. Land cover classes areas computed using standard good practices recommendations to estimate land areas indicated that the dense moist forest area was about 158,810,975 ± 7,460,671 ha representing 68.40% ± 3.21% of the country area. Thanks to the free, user-friendly and cloud-based platforms for satellite images processing, the methodology implemented is easily replicable for other tropical countries.

scholarly journals Object-based image analysis for the assessment of mineral extraction in conflict regions – a case study in the Democratic Republic of the Congo

2016 ◽  
Vol XLI-B7 ◽  
pp. 891-896
Author(s):  
Olaf Kranz ◽  
Elisabeth Schoepfer ◽  
Kristin Spröhnle ◽  
Stefan Lang
Keyword(s):  
Image Analysis ◽  
Democratic Republic ◽  
Mining Industry ◽  
Remote Sensing Data ◽  
Mining Activities ◽  
Mineral Extraction ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Starting Point ◽  
Republic Of The Congo

In this study object-based image analysis (OBIA) techniques were applied to assess land cover changes related to mineral extraction in a conflict-affected area of the eastern Democratic Republic of the Congo (DRC) over a period of five years based on very high resolution (VHR) satellite data of different sensors. Object-based approaches explicitly consider spatio-temporal aspects which allow extracting important information to document mining activities. The use of remote sensing data as an independent, up-to-date and reliable data source provided hints on the general development of the mining sector in relation to socio-economic and political decisions. While in early 2010, the situation was still characterised by an intensification of mineral extraction, a mining ban between autumn 2010 and spring 2011 marked the starting point for a continuous decrease of mining activities. The latter can be substantiated through a decrease in the extend of the mining area as well as of the number of dwellings in the nearby settlement. A following demilitarisation and the mentioned need for accountability with respect to the origin of certain minerals led to organised, more industrialized exploitation. This development is likewise visible on satellite imagery as typical clearings within forested areas. The results of the continuous monitoring in turn facilitate non-governmental organisations (NGOs) to further foster the mentioned establishment of responsible supply chains by the mining industry throughout the entire period of investigation.

scholarly journals Land Cover Change Detection Using Object-Based Classification Technique: A Case Study Along The Kosi River, Bihar

2014 ◽  
Vol XL-8 ◽  
pp. 839-843 ◽  
Author(s):  
M. Modi ◽  
R. Kumar ◽  
G. Ravi Shankar ◽  
T.R. Martha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Time Series Data ◽  
Feature Space ◽  
Series Data ◽  
Land Use Land Cover ◽  
Shape Context ◽  
Object Property ◽  
Object Based ◽  
Remote Sensing Techniques

Land use/land cover (LULC) is dynamic in nature and can affect the ability of land to sustain human activities. The Indo-Gangetic plains of north Bihar in eastern India are prone to floods, which have a significant impact on land use / land cover, particularly agricultural lands and settlement areas. Satellite remote sensing techniques allow generating reliable and near-realtime information of LULC and have the potential to monitor these changes due to periodic flood. Automated methods such as object-based techniques have better potential to highlight changes through time series data analysis in comparison to pixel-based methods, since the former provides an opportunity to apply shape, context criteria in addition to spectral criteria to accurately characterise the changes. In this study, part of Kosi river flood plains in Supaul district, Bihar has been analysed to identify changes due to a flooding event in 2008. Object samples were collected from the post-flood image for a nearest neighbourhood (NN) classification in an object-based environment. Collection of sample were partially supported by the existing 2004–05 database. The feature space optimisation procedure was adopted to calculate an optimum feature combination (i.e. object property) that can provide highest classification accuracy. In the study, for classification of post-flood image, best class separation was obtained by using distance of 0.533 for 28 parameters out of 34. Results show that the Kosi flood has resulted in formation of sandy riverine areas.

scholarly journals Object-based image analysis for the assessment of mineral extraction in conflict regions – a case study in the Democratic Republic of the Congo

2016 ◽  
Vol XLI-B7 ◽  
pp. 891-896
Author(s):  
Olaf Kranz ◽  
Elisabeth Schoepfer ◽  
Kristin Spröhnle ◽  
Stefan Lang
Keyword(s):  
Image Analysis ◽  
Democratic Republic ◽  
Mining Industry ◽  
Remote Sensing Data ◽  
Mining Activities ◽  
Mineral Extraction ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Starting Point ◽  
Republic Of The Congo

In this study object-based image analysis (OBIA) techniques were applied to assess land cover changes related to mineral extraction in a conflict-affected area of the eastern Democratic Republic of the Congo (DRC) over a period of five years based on very high resolution (VHR) satellite data of different sensors. Object-based approaches explicitly consider spatio-temporal aspects which allow extracting important information to document mining activities. The use of remote sensing data as an independent, up-to-date and reliable data source provided hints on the general development of the mining sector in relation to socio-economic and political decisions. While in early 2010, the situation was still characterised by an intensification of mineral extraction, a mining ban between autumn 2010 and spring 2011 marked the starting point for a continuous decrease of mining activities. The latter can be substantiated through a decrease in the extend of the mining area as well as of the number of dwellings in the nearby settlement. A following demilitarisation and the mentioned need for accountability with respect to the origin of certain minerals led to organised, more industrialized exploitation. This development is likewise visible on satellite imagery as typical clearings within forested areas. The results of the continuous monitoring in turn facilitate non-governmental organisations (NGOs) to further foster the mentioned establishment of responsible supply chains by the mining industry throughout the entire period of investigation.

Constitutional Incorporation of the (Collective) Freedom to Govern Mineral Wealth: Comparing the Democratic Republic of the Congo and the Republic of Zambia

2020 ◽  
Vol 28 (1) ◽  
pp. 1-29
Author(s):  
Alexandra Carleton
Keyword(s):  
Natural Resources ◽  
Democratic Republic ◽  
Mineral Wealth ◽  
The People ◽  
Republic Of The Congo ◽  
The Republic

Constitutionalism may be gaining ascendancy in many countries in Africa. Yet thorough investigation of the extent to which current constitutions accord to the people their internationally recognised right to governance of their mineral wealth under Article 1(2) of the ICCPR has been lacking. Understanding the existing framework of rights which may support claims to land and natural resources is important. Constitutions of the Democratic Republic of the Congo and the Republic of Zambia demonstrate the reality of multiple, overlapping land interests and the limitations upon a people's claim to freely govern their mineral wealth.

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