[HTML][HTML] Remote sensing techniques: Mapping and monitoring of mangrove ecosystem—A review
K Maurya, S Mahajan, N Chaube - Complex & Intelligent Systems, 2021 - Springer
Mangrove forests are considered to be the most productive ecosystem yet vanishing rapidly
over the world. They are mostly found in the intertidal zone and sheltered by the seacoast …
over the world. They are mostly found in the intertidal zone and sheltered by the seacoast …
[HTML][HTML] Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery
P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform
Due to rapid losses of mangrove forests caused by anthropogenic disturbances and climate
change, accurate and contemporary maps of mangrove forests are needed to understand …
change, accurate and contemporary maps of mangrove forests are needed to understand …
[HTML][HTML] Estimation of biomass in wheat using random forest regression algorithm and remote sensing data
X Zhou, X Zhu, Z Dong, W Guo - The Crop Journal, 2016 - Elsevier
Wheat biomass can be estimated using appropriate spectral vegetation indices. However,
the accuracy of estimation should be further improved for on-farm crop management …
the accuracy of estimation should be further improved for on-farm crop management …
A review of the application of multispectral remote sensing in the study of mangrove ecosystems with special emphasis on image processing techniques
Much progress has been made since the first published report on application of remote
sensing in mangrove mapping nearly 40 years ago. Remote sensing is now a widely used …
sensing in mangrove mapping nearly 40 years ago. Remote sensing is now a widely used …
Drought monitoring and prediction using SPI, SPEI, and random forest model in various climates of Iran
M Lotfirad, H Esmaeili-Gisavandani… - Journal of Water and …, 2022 - iwaponline.com
The aim of this study is to select the best model (combination of different lag times) for
predicting the standardized precipitation index (SPI) and the standardized precipitation and …
predicting the standardized precipitation index (SPI) and the standardized precipitation and …
[HTML][HTML] Integration of sentinel-1 and sentinel-2 for classification and LULC mapping in the urban area of Belém, eastern Brazilian Amazon
In tropical regions, such as in the Amazon, the use of optical sensors is limited by high cloud
coverage throughout the year. As an alternative, Synthetic Aperture Radar (SAR) products …
coverage throughout the year. As an alternative, Synthetic Aperture Radar (SAR) products …
[HTML][HTML] Combined Landsat and L-band SAR data improves land cover classification and change detection in dynamic tropical landscapes
Robust quantitative estimates of land use and land cover change are necessary to develop
policy solutions and interventions aimed towards sustainable land management. Here, we …
policy solutions and interventions aimed towards sustainable land management. Here, we …
[HTML][HTML] Mapping the land cover of Africa at 10 m resolution from multi-source remote sensing data with Google Earth Engine
The remote sensing based mapping of land cover at extensive scales, eg, of whole
continents, is still a challenging task because of the need for sophisticated pipelines that …
continents, is still a challenging task because of the need for sophisticated pipelines that …
[HTML][HTML] Large-scale high-resolution coastal mangrove forests mapping across West Africa with machine learning ensemble and satellite big data
Coastal mangrove forests provide important ecosystem goods and services, including
carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are …
carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are …