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

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Applications-Society and Environment Pub Date : 2024-07-04 DOI:10.1016/j.rsase.2024.101289
Kingsley Kanjin, Bhuiyan Monwar Alam
{"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,&nbsp;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,&nbsp;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\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Applications-Society and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352938524001538\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938524001538","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
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
期刊最新文献
Mapping coastal wetland changes from 1985 to 2022 in the US Atlantic and Gulf Coasts using Landsat time series and national wetland inventories Assessment of Dry Microburst Index over India derived from INSAT-3DR satellite Unveiling soil coherence patterns along Etihad Rail using Sentinel-1 and Sentinel-2 data and machine learning in arid region Analysis of radiative heat flux using ASTER thermal images: Climatological and volcanological factors on Java Island, Indonesia Hybrid Naïve Bayes Gaussian mixture models and SAR polarimetry based automatic flooded vegetation studies using PALSAR-2 data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1