{"title":"评估孟加拉国和印度孙德尔本斯红树林的土地覆盖、NDVI 和 LST 变化:地理信息系统和遥感方法","authors":"Kingsley Kanjin, Bhuiyan Monwar Alam","doi":"10.1016/j.rsase.2024.101289","DOIUrl":null,"url":null,"abstract":"<div><p>Mangrove ecosystems, although limited in diversity and area compared to tropical forests, provide essential ecological and economic services, such as carbon sequestration and coastal protection. The Sundarbans mangrove forest, shared by Bangladesh and India, is one of the largest mangrove ecosystems in the world and is crucial for biodiversity, economy, and climate regulation. Unfortunately, this ecosystem has been under severe stress over the years, with alarming rates of deforestation leading to habitat loss and a decline in ecosystem services. This study analyzes the spatiotemporal changes in the Sundarbans mangrove forest coverage from 1973 to 2023 using supervised image classification on Landsat images. It also assesses the relationship between the Normalized Difference Vegetation Index and Land Surface Temperature in the Sundarbans using MODIS data which were extracted in Google Earth Engine. It finds that, despite the loss of denser mangrove areas, an improvement in overall vegetation health is visible, which suggests a natural resilience within the Sundarbans mangrove forest. The Land Surface Temperature result shows a weak but statistically significant negative correlation with the Normalized Difference Vegetation Index, indicating that the depletion of the Sundarbans mangrove forest could have an impact on the area’s surface temperature. As such, the study regressed the Normalized Difference Vegetation Index on Land Surface Temperature. The results confirm that although the Normalized Difference Vegetation Index has a statistically significant negative impact on Land Surface Temperature, the Coefficient of Determination is low. This suggests that other factors such as water bodies that intersect with the mangrove forest in the area may play an important role in influencing Land Surface Temperature. The paper reveals a nuanced picture of the Sundarbans’ ecological state, with both declining mangrove densities and signs of vegetation recovery. It highlights the need for comprehensive conservation strategies to mitigate further ecosystem degradation.</p></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101289"},"PeriodicalIF":3.8000,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352938524001538/pdfft?md5=72f71d063ef3ad7c929b702ac878e92f&pid=1-s2.0-S2352938524001538-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Assessing Changes in Land Cover, NDVI, and LST in the Sundarbans Mangrove Forest in Bangladesh and India: A GIS and Remote Sensing Approach\",\"authors\":\"Kingsley Kanjin, Bhuiyan Monwar Alam\",\"doi\":\"10.1016/j.rsase.2024.101289\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mangrove ecosystems, although limited in diversity and area compared to tropical forests, provide essential ecological and economic services, such as carbon sequestration and coastal protection. The Sundarbans mangrove forest, shared by Bangladesh and India, is one of the largest mangrove ecosystems in the world and is crucial for biodiversity, economy, and climate regulation. Unfortunately, this ecosystem has been under severe stress over the years, with alarming rates of deforestation leading to habitat loss and a decline in ecosystem services. This study analyzes the spatiotemporal changes in the Sundarbans mangrove forest coverage from 1973 to 2023 using supervised image classification on Landsat images. It also assesses the relationship between the Normalized Difference Vegetation Index and Land Surface Temperature in the Sundarbans using MODIS data which were extracted in Google Earth Engine. It finds that, despite the loss of denser mangrove areas, an improvement in overall vegetation health is visible, which suggests a natural resilience within the Sundarbans mangrove forest. The Land Surface Temperature result shows a weak but statistically significant negative correlation with the Normalized Difference Vegetation Index, indicating that the depletion of the Sundarbans mangrove forest could have an impact on the area’s surface temperature. As such, the study regressed the Normalized Difference Vegetation Index on Land Surface Temperature. The results confirm that although the Normalized Difference Vegetation Index has a statistically significant negative impact on Land Surface Temperature, the Coefficient of Determination is low. This suggests that other factors such as water bodies that intersect with the mangrove forest in the area may play an important role in influencing Land Surface Temperature. The paper reveals a nuanced picture of the Sundarbans’ ecological state, with both declining mangrove densities and signs of vegetation recovery. 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引用次数: 0
摘要
与热带森林相比,红树林生态系统虽然在多样性和面积上都很有限,但却能提供重要的生态和经济服务,例如碳固存和海岸保护。孟加拉国和印度共有的孙德尔本斯红树林是世界上最大的红树林生态系统之一,对生物多样性、经济和气候调节至关重要。不幸的是,多年来这一生态系统受到严重压力,惊人的森林砍伐率导致栖息地丧失,生态系统服务功能下降。本研究利用 Landsat 图像上的监督图像分类,分析了 1973 年至 2023 年期间孙德尔本斯红树林覆盖率的时空变化。研究还利用在谷歌地球引擎中提取的 MODIS 数据,评估了孙德尔本斯归一化差异植被指数与地表温度之间的关系。研究发现,尽管密集的红树林区域有所减少,但整体植被健康状况明显改善,这表明孙德尔本斯红树林具有自然恢复能力。地表温度结果显示,归一化差异植被指数与地表温度呈微弱但具有统计意义的负相关,表明孙德尔本斯红树林的枯竭可能会对该地区的地表温度产生影响。因此,研究将归一化差异植被指数与地表温度进行了回归。结果证实,尽管归一化植被指数对地表温度有显著的负面影响,但其决定系数较低。这表明,与该地区红树林相交的水体等其他因素可能在影响地表温度方面发挥着重要作用。论文揭示了孙德尔本斯生态状况的细微差别,既有红树林密度下降的情况,也有植被恢复的迹象。它强调了全面保护战略的必要性,以缓解生态系统的进一步退化。
Assessing Changes in Land Cover, NDVI, and LST in the Sundarbans Mangrove Forest in Bangladesh and India: A GIS and Remote Sensing Approach
Mangrove ecosystems, although limited in diversity and area compared to tropical forests, provide essential ecological and economic services, such as carbon sequestration and coastal protection. The Sundarbans mangrove forest, shared by Bangladesh and India, is one of the largest mangrove ecosystems in the world and is crucial for biodiversity, economy, and climate regulation. Unfortunately, this ecosystem has been under severe stress over the years, with alarming rates of deforestation leading to habitat loss and a decline in ecosystem services. This study analyzes the spatiotemporal changes in the Sundarbans mangrove forest coverage from 1973 to 2023 using supervised image classification on Landsat images. It also assesses the relationship between the Normalized Difference Vegetation Index and Land Surface Temperature in the Sundarbans using MODIS data which were extracted in Google Earth Engine. It finds that, despite the loss of denser mangrove areas, an improvement in overall vegetation health is visible, which suggests a natural resilience within the Sundarbans mangrove forest. The Land Surface Temperature result shows a weak but statistically significant negative correlation with the Normalized Difference Vegetation Index, indicating that the depletion of the Sundarbans mangrove forest could have an impact on the area’s surface temperature. As such, the study regressed the Normalized Difference Vegetation Index on Land Surface Temperature. The results confirm that although the Normalized Difference Vegetation Index has a statistically significant negative impact on Land Surface Temperature, the Coefficient of Determination is low. This suggests that other factors such as water bodies that intersect with the mangrove forest in the area may play an important role in influencing Land Surface Temperature. The paper reveals a nuanced picture of the Sundarbans’ ecological state, with both declining mangrove densities and signs of vegetation recovery. It highlights the need for comprehensive conservation strategies to mitigate further ecosystem degradation.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems