scholarly journals Análise da degradação da vegetação nativa em área de preservação permanente na Paraíba

2020 ◽  
Vol 13 (1) ◽  
pp. 121
Author(s):  
Viviane Farias Silva ◽  
Julia Soares Pereira ◽  
Ana Maria Ferreira Cosme ◽  
Dihego Sousa Pessoa ◽  
Wanessa Alves Martins ◽  
...  
Keyword(s):  
Environmental Education ◽  
Satellite Images ◽  
Forest Degradation ◽  
Native Vegetation ◽  
Landsat 8 ◽  
Visual Interpretation ◽  
Dense Vegetation ◽  
Spectral Changes ◽  
Negative Impacts ◽  
Landsat Satellite

A supressão da vegetação nativa para a expansão agropecuária ou para outro tipo de uso, tem agravado o processo de degradação florestal, ocasionando impactos negativos. Assim, este estudo teve como objetivo o mapeamento da vegetação da APP no Horto Florestal Olho D´água da Bica, do município de Cuité – PB, quantificando as áreas alteradas da vegetação densa, vegetação rala e o solo exposto, através das mudanças espectrais em quatro anos (2015 a 2018), visando obter maior conhecimento sobre a sua preservação. Foram utilizadas imagens de satélite Landsat 8 que possuíam menores coberturas de nuvens. A interpretação visual de imagens de satélite ocorre através da extração de padrões texturais nas bandas monocromáticas e nas composições coloridas. A partir, dos resultados observou-se que a vegetação densa sofreu uma significativa redução ao longo dos anos e que a vegetação rala e o solo exposto obtiveram um maior crescimento no período analisado.  Desta forma, conclui-se que a degradação da vegetação, ocorreu ao longo dos anos, sendo necessário uma intervenção e plano de recuperação da área.  A vegetação densa teve redução significativa, enquanto houve elevação da vegetação rala. Assim, torna necessário a aplicação de projetos de educação ambiental na comunidade para incentivar a conscientização e preservação desta APP.  Analysis of the degradation of native vegetation in a permanent preservation area in Paraíba A B S T R A C TThe removal of native vegetation to agricultural expansion or for other use, has aggravated the process of forest degradation, causing negative impacts. Thus, this study aimed to the mapping of the vegetation of the APP in the Horto Florestal Eye D ´ water da Bica, the municipality of Cuité-PB, quantifying the altered areas of dense vegetation, thin vegetation and soil exposed, through the spectral changes in four years (2015 to 2018), in order to gain greater knowledge of your preservation. Landsat satellite images were used 8 who had lower cloudiness. The visual interpretation of satellite imagery occurs through the extraction of textural patterns in monochrome and colored bands in the compositions. From the results, it was observed that the dense vegetation has suffered a significant reduction over the years and that the thin vegetation and exposed soil obtained a higher growth in the period analyzed. Thus, it is concluded that the degradation of vegetation, occurred over the years, requiring an intervention and recovery plan of the area. The dense vegetation had significant reduction, while there were thin vegetation elevation. So, makes necessary the implementation of environmental education projects in the community to encourage the awareness and preservation of this APP.Keywords: vegetation cover, permanent preservation area, environmental education. 

scholarly journals Land Use Land Cover Analysis using Geospatial Techniques

2021 ◽  
Vol 9 (8) ◽  
pp. 2561-2566
Author(s):  
Babita Singh
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Landscape Configuration ◽  
Landsat 8 ◽  
Visual Interpretation ◽  
Open Forest

Abstract: Remote sensing and Geographic information system (GIS) techniques can be used for the changing pattern of landscape. The study was conducted in Dehradun, Haridwar and Pauri Garhwal Districts of Uttarakhand State, India. In order to understand dynamics of landscape and to examine changes in the land use/cover due to anthropogenic activities, two satellite images (Landsat 5 and Landsat 8) for 1998 and 2020 were used. Google Earth Engine was used to perform supervised classification. Spectral indices (NDVI, MNDWI, SAVI, NDBI) were calculated in order to identify land cover classes. Both 1998 and 2020 satellite images were classified broadly into six classes namely agriculture, built-up, dense forest, open forest, scrub and waterbody. Using high resolution google earth satellite images and visual interpretation, overall accuracy assessment was performed. For land cover/use change analysis, these images were imported to GIS platform. Landscape configuration was observed by calculating various landscape metrices Images. It was observed that scrub land area had increased from 11 % to 14 % but a decrease in agriculture by 4.65 %. The increased value of NP, PD, PLAND, LPI and decrease in AI landscape indices shows that land fragmentation had increased since 1998. The most fragmented classes were scrub (PD - 3.32 to 5.18) and open forest (PD - 3.57 to 5.07). Decrease in AI for open forest, agriculture, built-up indicated that more fragmented patches of these classes were present. The result confirmed increase in the fragmentation of landscape from 1998 onwards. Keywords: GIS, LULC, landscape metrics, Remote Sensing

scholarly journals Visual interpretation of ASTER satellite data, Part II: Land use mapping in Mpumalanga,South Africa

2007 ◽  
Vol 26 (4) ◽  
pp. 247-264
Author(s):  
Elna Van Niekerk
Keyword(s):  
South Africa ◽  
Land Use ◽  
Land Use Change ◽  
Satellite Data ◽  
Satellite Images ◽  
Research Projects ◽  
Visual Interpretation ◽  
Landsat 7 ◽  
Landsat 5 Tm ◽  
Landsat Satellite

Since the initiation in 1960 of the era of satellite remote sensing to detect the different characteristics of the earth, a powerful tool was created to aid researchers. Many land-use studies were undertaken using Landsat MSS, Landsat TM and ETM, as well as SPOT satellite data. The application of these data to the mapping of land use and land cover at smaller scales was constrained by the limited spectral and/or spatial resolution of the data provided by these satellite sensors. In view of the relatively high cost of SPOT data, and uncertainty regarding the future continuation of the Landsat series, alternative data sources need to be investigated. In the absence of published previous research on this issue in South Africa, the purpose of this article is to investigate the value of visual interpretation of ASTER satellite images for the identification and mapping of land-use in an area in South Africa. The study area is situated in Mpumalanga, in the area of Witbank, around the Witbank and Doorndraai dams. This area is characterised by a variety of urban, rural and industrial land uses. Digital image processing of one Landsat 5 TM, one Landsat 7 ETM and one ASTER satellite image was undertaken, including atmospheric correction and georeferencing, natural colour composites, photo infrared colour composites (or false colour satellite images), band ratios, Normalised Difference Indices, as well as the Brightness, Greenness and Wetness Indices. The efficacy with which land use could be identified through the visual interpretation of the processed Landsat 5 TM, Landsat 7 TM and ASTER satellite images was compared. The published 1:50 000 topographical maps of the area were used for the purpose of initial verification. Findings of the visual interpretation process were verified by field visits to the study area. The study found that the ASTER satellite data produced clearer results and therefore have a higher mapping ability and capacity than the Landsat satellite data. Hence, it is anticipated that the use of the full range of the spectral resolution of the ASTER satellite data – which were not available for this study – in statistical pattern recognition and classification methods will enhance the value of the process. Statistical methods are often used to produce visual information which could be applied to prepare land-use change inventories. This should be addressed in future research projects. Should the Landsat programme be terminated, ASTER satellite data might provide the best alternative for a variety of research projects, but if the Landsat project is continued, the ASTER satellite data could be used very effectively in conjunction with the Landsat satellite data. Since it is foreseen that the ASTER satellite data will be available for at least the next 12 to 15 years, it will continue to provide exciting possibilities for the development of programmes to monitor land-use and land-use change. This could then be used by all three levels of government to reach their goals in terms of agricultural planning, town and regional planning and environmental management. These requirements are described in the Integrated Development Programmes (IDP) of the different local governments.

scholarly journals DYNAMICS OF GREEN SPACES IN ST. PETERSBURG ACCORDING TO REMOTE SENSING DATA

2021 ◽  
Vol 2 (6) ◽  
pp. 38-41
Author(s):  
D.K. Alexeev ◽  
◽  
A.V. Babin ◽  
V.Yu. Sargaeva
Keyword(s):  
Spatial Distribution ◽  
Quantitative Assessment ◽  
Satellite Images ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Green Spaces ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Landsat Satellite ◽  
The City

. Urban development is formulated as one of seventeen sustainable development goals for the near future. Among the whole range of environmental problems of a modern city, the issues of urban greening occupy a special place. In the course of the work, the analysis of the spatial distribution and assessment of the dynamics of green spaces on the territory of the city of St. Petersburg and its administrative-territorial units (inner-city districts) was carried out according to the data of multispectral satellite images Landsat 7 and Landsat 8 for the period 2002–2018. The normalized vegetation index (NDVI) was used for quantitative assessment. Maps of the spatial distribution of NDVI for the specified period were built. A decrease in the indicators of the provision of green spaces for the specified period for various districts of the city has been established. The obtained maps of the city’s vegetation cover, based on Landsat satellite images, provide a visual representation of the spatial distribution of landscaping indicators with the possibility of their quantitative assessment, and provide planning of landscaping facilities. The data obtained as a result of the work can supplement existing knowledge when carrying out work on process research and monitoring, as well as when making practical decisions

scholarly journals Possibility of using Landsat satellite recordings in visualization and detection of thermal islands in the area of the city Vinkovci

2020 ◽  
Vol 7 (1) ◽  
pp. 18-28
Author(s):  
Ivana Petrinjak ◽  
Nikola Kranjčić ◽  
Milan Rezo ◽  
Bojan Đurin
Keyword(s):  
Spatial Resolution ◽  
Satellite Images ◽  
Forest Cover ◽  
Quantitative Measure ◽  
Landsat 8 ◽  
The Earth ◽  
Cartesian Coordinate ◽  
Landsat Satellite ◽  
The City ◽  
Satellite Sensor

All satellite data is generated as a record of electromagnetic radiation detected on the satellite sensor. The product of collecting information in remote explorations is a digital satellite record consisting of a pixel network representing the smallest surface that a particular sensor can collect, which is also a spatial resolution of the image. The position of each pixel is determined in the Cartesian coordinate system. To allow the ability to monitor climate change or mitigate the consequences of a natural disaster, the USGS has developed the Earth Explorer tool. USGS (US Geological Institute) provides science on natural hazards endangering life and existence; water, energy, minerals and other natural resources we rely on. This analysis will highlight the ability to use and monitor satellite imagery using the Earth Explorer browser. All satellite images are processed in QGIS. The spatial resolution of the satellite index (NDVI) as a quantitative measure of the state of the vegetation cover was tested on Landsat 8 images in the area of the city of Vinkovci. Highlighted natural disasters are thermal islands, and damage to the forest cover.

scholarly journals DEFORESTATION MONITORING IN DIFFERENT BRAZILIAN BIOMES: CHALLENGES AND LESSONS

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 47-52
Author(s):  
C. A. Almeida ◽  
D. M. Valeriano ◽  
L. Maurano ◽  
L. Vinhas ◽  
L. M. G. Fonseca ◽  
...  
Keyword(s):  
Satellite Images ◽  
Computational Technique ◽  
Native Vegetation ◽  
Annual Data ◽  
Visual Interpretation ◽  
Brazilian Government ◽  
New Challenges ◽  
Amazonian Forests ◽  
Interpretation Of Satellite Images

Abstract. Monitoring the conversion of native vegetation has challenged Brazilian government and scientists since the 1980s. In the case of the Amazonian forests, the Amazon Gross Deforestation Monitoring Project - PRODES has developed an effective methodology that provides consistent annual data on deforestation areas on a scale of 1:250,000, since 1988. In this article, we present some aspects of the evolution of this methodology, the key processes to produce accurate deforestation maps during the last 30 years and the new challenges that the Project would face. A central lesson is that no computational technique has, to date, been able to achieve the quality of deforestation maps produced by visual interpretation of satellite images and manual mapping.

Multitemporal distribution analysis of Dodonaea viscosa (L.) Jacq. by remote sensing in Durango, Mexico

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Marco, A. Márquez-Linares ◽  
Jonathan G. Escobar--Flores ◽  
Sarahi Sandoval- Espinosa ◽  
Gustavo Pérez-Verdín
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Design Methodology ◽  
Supervised Classification ◽  
Satellite Images ◽  
Ground Cover ◽  
Distribution Analysis ◽  
Dodonaea Viscosa ◽  
Artificial Neural ◽  
Landsat Satellite

Objective: to determine the distribution of D. viscosa in the vicinity of the Guadalupe Victoria Dam in Durango, Mexico, for the years 1990, 2010 and 2017.Design/Methodology/Approach: Landsat satellite images were processed in order to carry out supervised classifications using an artificial neural network. Images from the years 1990, 2010 and 2017 were used to estimate ground cover of D. viscosa, pastures, crops, shrubs, and oak forest. This data was used to calculate the expansion of D. viscosa in the study area.Results/Study Limitations/Implications: the supervised classification with the artificial neural network was optimal after 400 iterations, obtaining the best overall precision of 84.5 % for 2017. This contrasted with the year 1990, when overall accuracy was low at 45 % due to less training sites (fewer than 100) recorded for each of the land cover classes.Findings/Conclusions: in 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, and based on the distribution of D. viscosa, it is likely that in a few years it will have the ability to invade half the study area, occupying agricultural, forested, and shrub areas

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

EDUCAÇÃO AMBIENTAL COMO SUBSIDIO A (RE)AVALIAÇÃO DAS FORMAS DE USO NA APA DO ESTUÁRIO DO RIO CEARÁ EM FORTALEZA

2019 ◽  
Vol 21 (2) ◽  
pp. 962-975
Author(s):  
Emerson Rodrigues Lima ◽  
Ana Carla Alves Gomes ◽  
Ícaro Paiva de Oliveira ◽  
Maria Lucia Brito da Cruz
Keyword(s):  
Data Collection ◽  
Environmental Education ◽  
Riparian Forest ◽  
Sustainable Use ◽  
Secondary Data ◽  
Field Work ◽  
Protection Area ◽  
Negative Impacts ◽  
Natural Dynamics ◽  
Del Rio

A pesquisa trata de uma análise da relação sociedade natureza no contexto da Área de Proteção Ambiental (APA) do rio Ceará e teve como objetivo principal o estudo dos impactos negativos sofridos a partir dessa interação, descrevendo os principais problemas ocasionados pela ocupação desordenada, como a intervenção nas dunas, poluição do mangue e desmatamento da mata ciliar, os quais condicionam a mudança da dinâmica natural do ambiente causando interferências paisagísticas e biológicas no local. O aporte teórico metodológico embasa-se nas teorias clássicas pertinentes, bem como levantamento de dados secundários, trabalho de campo e a técnica de geoprocessamento para a elaboração de material cartográfico. Os resultados demonstram a urgência em inserir práticas vinculadas a educação ambiental na APA, dessa forma, o trabalho visa servir de subsídio à conscientização da necessidade de preservação deste ambiente, recomendando, assim o diálogo entre a população e os órgãos responsáveis para garantir o uso sustentável da mesma.Palavras-chave: Conservação; Educação Ambiental; Análise Geoambiental. ABSTRACTThe research deals with an analysis of the relation nature-society in the context of the APA (Ambiental Protection Area) of Ceará River and it had as main objective the study of the negative impacts suffered from this interaction, describing the main problems caused by the disordered occupation, such as the intervention in the dunes, mangrove pollution and deforestation of the riparian forest, which condition the change of the natural dynamics of the environment causing landscape and biological interferences in the place. The theoretical methodological support is based on the relevant classical theories, as well as secondary data collection, field work and the geoprocessing technique for the preparation of cartographic material. The results show the urgency to insert practices related to environmental education in the APA, so this work aims to serve as a subsidy to raise awareness of the need to preserve this environment, recommending in this way the dialogue between the population and responsible bodies to ensure sustainable use of the same. Keywords: Conservation; Environmental education; Geoenvironmental Analysis. RESUMENLa investigación aborda un análisis de la relación de la sociedad de la naturaleza en el contexto del Área de Protección Ambiental (APA) del río Ceará y su objetivo principal fue el estudio de los impactos negativos sufridos por esta interacción, describiendo los principales problemas causados por la ocupación desordenada, como el intervención en las dunas, contaminación del manglar y deforestación del bosque ribereño, que condicionan el cambio de la dinámica natural del ambiente causando interferencia biológica y paisajística en el lugar. La base teórica metodológica se basa en las teorías clásicas relevantes, así como en la recolección secundaria de datos, el trabajo de campo y la técnica de geoprocesamiento para la preparación de material cartográfico. Los resultados demuestran la urgencia de insertar prácticas relacionadas con la educación ambiental en la APA, por lo tanto, el trabajo tiene como objetivo apoyar la conciencia de la necesidad de preservar este medio ambiente, recomendando así el diálogo entre la población y los organismos responsables para garantizar un uso sostenible de la misma.Palabras clave: Conservación; Educación ambiental; Análisis geoambiental.

scholarly journals Spatiotemporal Fusion of Formosat-2 and Landsat-8 Satellite Images: A Comparison of “Super Resolution-Then-Blend” and “Blend-Then-Super Resolution” Approaches

2021 ◽  
Vol 13 (4) ◽  
pp. 606
Author(s):  
Tee-Ann Teo ◽  
Yu-Ju Fu
Keyword(s):  
Satellite Images ◽  
Traditional Approach ◽  
Spectral Band ◽  
Super Resolution ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Fusion Model ◽  
Image Blending ◽  
Fine Resolution

The spatiotemporal fusion technique has the advantages of generating time-series images with high-spatial and high-temporal resolution from coarse-resolution to fine-resolution images. A hybrid fusion method that integrates image blending (i.e., spatial and temporal adaptive reflectance fusion model, STARFM) and super-resolution (i.e., very deep super resolution, VDSR) techniques for the spatiotemporal fusion of 8 m Formosat-2 and 30 m Landsat-8 satellite images is proposed. Two different fusion approaches, namely Blend-then-Super-Resolution and Super-Resolution (SR)-then-Blend, were developed to improve the results of spatiotemporal fusion. The SR-then-Blend approach performs SR before image blending. The SR refines the image resampling stage on generating the same pixel-size of coarse- and fine-resolution images. The Blend-then-SR approach is aimed at refining the spatial details after image blending. Several quality indices were used to analyze the quality of the different fusion approaches. Experimental results showed that the performance of the hybrid method is slightly better than the traditional approach. Images obtained using SR-then-Blend are more similar to the real observed images compared with images acquired using Blend-then-SR. The overall mean bias of SR-then-Blend was 4% lower than Blend-then-SR, and nearly 3% improvement for overall standard deviation in SR-B. The VDSR technique reduces the systematic deviation in spectral band between Formosat-2 and Landsat-8 satellite images. The integration of STARFM and the VDSR model is useful for improving the quality of spatiotemporal fusion.

scholarly journals Mangrove Forest Landcover Changes in Coastal Vietnam: A Case Study from 1973 to 2020 in Thanh Hoa and Nghe An Provinces

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 637
Author(s):  
Huong Thi Thuy Nguyen ◽  
Giles E. S. Hardy ◽  
Tuat Van Le ◽  
Huy Quoc Nguyen ◽  
Hoang Huy Nguyen ◽  
...  
Keyword(s):  
Mangrove Forest ◽  
Monsoon Season ◽  
Coastal Development ◽  
Northern Coast ◽  
Mangrove Forests ◽  
Visual Interpretation ◽  
Mangrove Restoration ◽  
Coast Of Vietnam ◽  
Landsat Satellite

Mangrove forests can ameliorate the impacts of typhoons and storms, but their extent is threatened by coastal development. The northern coast of Vietnam is especially vulnerable as typhoons frequently hit it during the monsoon season. However, temporal change information in mangrove cover distribution in this region is incomplete. Therefore, this study was undertaken to detect change in the spatial distribution of mangroves in Thanh Hoa and Nghe An provinces and identify reasons for the cover change. Landsat satellite images from 1973 to 2020 were analyzed using the NDVI method combined with visual interpretation to detect mangrove area change. Six LULC classes were categorized: mangrove forest, other forests, aquaculture, other land use, mudflat, and water. The mangrove cover in Nghe An province was estimated to be 66.5 ha in 1973 and increased to 323.0 ha in 2020. Mangrove cover in Thanh Hoa province was 366.1 ha in 1973, decreased to 61.7 ha in 1995, and rose to 791.1 ha in 2020. Aquaculture was the main reason for the loss of mangroves in both provinces. Overall, the percentage of mangrove loss from aquaculture was 42.5% for Nghe An province and 60.1% for Thanh Hoa province. Mangrove restoration efforts have contributed significantly to mangrove cover, with more than 1300 ha being planted by 2020. This study reveals that improving mangrove restoration success remains a challenge for these provinces, and further refinement of engineering techniques is needed to improve restoration outcomes.

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