Effects of Rural Land Tenure System on Mangroves Management in Corentyne, Guyana

Mangrove forests in Guyana are recognized as the most important soft-engineering structure that protects the low-lying coastal areas against wave and wind actions. However, this vegetation has become severely degraded along some sections of the coast as a result of excessive exploitation and the dynamic nature of the coastline. In an attempt to protect and manage the mangrove ecosystem, the Government of Guyana has instituted a number of mechanisms, including the Guyana Mangrove Restoration Project (GMRP). However, the effectiveness of these instruments has been impaired by the different types of land tenure systems. The study aimed at exploring the inter-relationships between land use and tenure issues, and the sustainable management of mangroves in selected villages in Corentyne, Guyana with a view in determining plausible remedies. The study used a mixed-methods approach, involving Google Earth technology, observation, in-depth interviews, and questionnaire surveys. The results showed that while land use has not changed significantly over the past decade, the advancement and proliferation of mangroves on privately owned lands were quite noticeable. This has given rise to a new area of conflict between managers of coastal mangrove forests and land owners and small-scale traditional users, signifying an urgent need for policy reform

DETEKSI PERUBAHAN LUASAN MANGROVE MENGGUNAKAN CITRA LANDSAT BERDASARKAN METODE OBIA DI TELUK VALENTINE PULAU BUANO

Kurangnya informasi dan perhatian terhadap kawasan mangrove di Teluk Valentine menjadikan penelitian ini penting dilakukan. Seri Landsat 7 ETM + tahun 2003, dan 2015 digunakan sebagai data perekaman untuk memetakan mangrove dan melihat perubahan di wilayah ini. Penelitian ini bertujuan untuk memetakan perubahan ekosistem mangrove antara tahun 2003 dan 2015, dengan menggunakan citra Landsat berdasarkan metode OBIA dan membandingkan keakuratan metode OBIA dan piksel. Metode analis basis objek atau sering disebut klasifikasi berbasis objek digunakan untuk menganalisis sejauh mana perubahan tutupan mangrove. Hasil penelitian menunjukkan bahwa dengan menggunakan klasifikasi berbasis objek, tutupan hutan bakau sangat baik terdeteksi dengan akurasi 85-88%. Penerapan analisis ini relatif stabil pada periode pengamatan, kawasan ini telah mengalami perubahan dari tahun 2003 ke 2015 sebesar 1.2%, namun perubahan tersebut dimaksudkan penambahan mangrove alami. Perhatian pemerintah daerah diperlukan untuk melestarikan kawasan sebagai kawasan konservasi atau laboratorium alam mengingat kawasannya masih sangat bagus dan tidak dieksploitasi secara berlebihan oleh masyarakat sekitar kawasan Teluk Valentine.Limited information and attention to the mangrove areas in the Valentine Bay makes this research is very important. Series Landsat 7 ETM + in 2003, and 2015 are used as recording data to map the mangrove and to see the changes in the region. This study aims to determine changes in mangrove ecosystem between 2003 and 2015, using Landsat imagery based on the OBIA method and to compare the accuracy between OBIA and pixel method. Object base analyst method or often called object-based classification is used to analyze the extent of mangrove cover changes. The results showed that by using an object-based classification, the mangrove forest cover very well detected at the level of 85-88% accuracy. The application of this analysis is were relatively stable in the period of observation, this region has changed from 2003 to 2015 by 1.2%, but the change is meant the addition of natural mangrove. Local government attention is needed to conserve the area and as an conservation area or a natural laboratory considering that the region is still very good and not overdone exploited by people around the region of Valentine

Perbandingan Klasifikasi SVM dan Decision Tree untuk Pemetaan Mangrove Berbasis Objek Menggunakan Citra Satelit Sentinel-2B di Gili Sulat, Lombok Timur

Mangrove is one of the most important objects in wetland ecosystems. Mangrove research has been done, one of them is using remote sensing technology. This study aims to assess accuracy of object based image analysis (OBIA) approach on both Support Vector Machine (SVM) and Decision Tree classification methods to classify mangrove and estimate mangrove area in the field study. We selected Kawasan Konservasi Laut Daerah (KKLD) Gili Sulat as a research site. This research used Sentinel-2B satellite imagery. We took field data using stratified random sampling and the amount of the data we collected were 121 points. The classification analysis result with object based showed that SVM had an overall accuracy of 95 % (kappa = 0.86) and Decision Tree classification had an overall accuracy of  93 % (kappa = 0.82). It is caused SVM can reduce the error of classification than Decision Tree. Estimation result based on assessment showed that mangrove using SVM had 634.62 Ha while using Decision Tree had 590.47 H

Perspectives and Application of Land Use Management Strategies to Address Mangrove Ecosystem Degradation in Guyana: A Case Study of Mon Repos

Destruction and threats to coastal mangrove ecosystems have been a perennial problem for policy-makers in Guyana. The problem is due in part to the erosion cycles, spontaneous infrastructure development and environmental degradation. To address these multiple issues, the National Mangrove Project Office employed several different strategies, including public awareness programmes. Despite the efforts, the issues continue to plague the country. The aim of this paper was to illustrate the efficacy of zoning and regionalization for combating the problems associated with mangrove ecosystem degradation at Mon Repos, East Coast Demerara. A survey of the literature and analysis of selected documents were done and ArcGIS Pro and remote sensing were applied to the case study. The results showed that while efforts could undoubtedly have a positive impact on mangroves at Mon Repos in terms of sustaining ecosystem services, facilitating livelihood opportunities and addressing the waste management issue, the effectiveness of such actions is likely to be impeded by the lack of real-time data. To adequately address these issues, the collection and use of more accurate and up-to-date scientific from the application of Geographic Information System and Remote Sensing and implementation of a multiple-use conservation zoning plan are among the strategies recommended for implementation

Monitoring Islamic Archaeological Landscapes in Ethiopia Using Open Source Satellite Imagery

This is the final version. Available on open access from Maney Publishing via the DOI in this recordThe African landscape is set to change dramatically in the coming years, and will have a detrimental impact on the inherent archaeological and cultural heritage elements if not monitored adequately. This paper explores how satellite imagery, in particular open source imagery (Google Earth, multispectral satellite imagery from Landsat and Sentinel-2), can be utilized to monitor and protect sites that are already known with particular reference to Islamic archaeological sites in Ethiopia. The four sites used are in different geographic and geomorphological areas: three on the Somali Plateau (Harlaa, Harar, and Sheikh Hussein), and one on the edge of the Afar Depression (Nora), and have varied histories. The results indicate that open source satellite imagery offers a mechanism for evaluating site status and conservation over time at a large scale, and can be used on data from other areas of Africa by heritage professionals in the African continent at no cost.European Union Horizon 202

Investigating the decline of ecosystem services in a production mangrove forest using Landsat and object-based image analysis

The Matang Mangrove Forest Reserve is widely recognised as a sustainably managed mangrove forest. However, recently evidence of multiple ecosystem services decline has emerged. The primary objective of this study was to apply remote sensing techniques to assess the impact of the silviculture in the mangrove forest reserve on the provision of ecosystem services. It applied an object-based approach to classify multi-temporal Landsat imagery. The classified images enabled the study to characterise and analyse the spatiotemporal changes in the distribution of stand age composition and structure over a 35 year period. Links were established between the classified images and the ecosystem services assessment based on the assumption that the classification results provided a reliable proxy for an indirect analysis on the temporal and spatial distribution of aboveground biomass of the mangrove forest reserve. The relationship between the potential impacts of the observed changes derived from the classified images with the data obtained from the ecosystem services assessment were analysed. The analysis showed that the fluctuation in greenwood yield was affected by varying rates of regeneration, exposure to excessive thinning and delays in harvesting. The production of blood cockles around the mudflats of the mangrove forest reserve was determined to be influenced by both timber extraction and natural coastal erosion. An undetected ecological change in the late eighties and anthropogenic disturbances were possible key factors behind the decline in the population of the Milky Stork and migratory shorebirds. The study highlights the importance of understanding and managing the trade-offs between wood production and ecosystem services in a managed mangrove forest and provides an important reference for the future management of the Matang Forest Reserve and other multiple-use wetland forests

Mangrove Mapping And Change Detection In Ca Mau Peninsula, Vietnam, Using Landsat Data And Object-Based Image Analysis

Mangrove forests provide important ecosystem goods and services for human society. Extensive coastal development in many developing countries has converted mangrove forests to other land uses without regard to their ecosystem service values; thus, the ecosystem state of mangrove forests is critical for officials to evaluate sustainable coastal management strategies. The objective of this study is to investigate the multidecadal change in mangrove forests in Ca Mau peninsula, South Vietnam, based on Landsat data from 1979 to 2013. The data were processed through four main steps: 1) data preprocessing; 2) image processing using the object-based image analysis (OBIA); 3) accuracy assessment; and 4) multitemporal change detection and spatial analysis of mangrove forests. The classification maps compared with the ground reference data showed the satisfactory agreement with the overall accuracy higher than 82%. From 1979 to 2013, the area of mangrove forests in the study region had decreased by 74%, mainly due to the boom of local aquaculture industry in the study region. Given that mangrove reforestation and afforestation only contributed about 13.2% during the last three decades, advanced mangrove management strategies are in an acute need for promoting environmental sustainability in the future

Mangrove Mapping and Change Detection in Ca Mau Peninsula, Vietnam, Using Landsat Data and Object-Based Image Analysis

Mangrove forests provide important ecosystem goods and services for human society. Extensive coastal development in many developing countries has converted mangrove forests to other land uses without regard to their ecosystem service values; thus, the ecosystem state of mangrove forests is critical for officials to evaluate sustainable coastal management strategies. The objective of this study is to investigate the multidecadal change in mangrove forests in Ca Mau peninsula, South Vietnam, based on Landsat data from 1979 to 2013. The data were processed through four main steps: 1) data preprocessing; 2) image processing using the object-based image analysis (OBIA); 3) accuracy assessment; and 4) multitemporal change detection and spatial analysis of mangrove forests. The classification maps compared with the ground reference data showed the satisfactory agreement with the overall accuracy higher than 82%. From 1979 to 2013, the area of mangrove forests in the study region had decreased by 74%, mainly due to the boom of local aquaculture industry in the study region. Given that mangrove reforestation and afforestation only contributed about 13.2% during the last three decades, advanced mangrove management strategies are in an acute need for promoting environmental sustainability in the future