A survey of computer vision techniques for forest characterization and carbon monitoring tasks
Estimation of terrestrial carbon balance is one of the key tasks in the understanding and
prognosis of climate change impacts and the development of tools and policies according to …
prognosis of climate change impacts and the development of tools and policies according to …
Generating annual high resolution land cover products for 28 metropolises in China based on a deep super-resolution mapping network using Landsat imagery
High resolution of global land cover dynamic is indicative for understanding the influence of
anthropogenic activity on environmental change. However, most of the land cover products …
anthropogenic activity on environmental change. However, most of the land cover products …
An overview of remote monitoring methods in biodiversity conservation
RG Kerry, FJP Montalbo, R Das, S Patra… - … Science and Pollution …, 2022 - Springer
Conservation of biodiversity is critical for the coexistence of humans and the sustenance of
other living organisms within the ecosystem. Identification and prioritization of specific …
other living organisms within the ecosystem. Identification and prioritization of specific …
Land use land cover classification with U-net: Advantages of combining sentinel-1 and sentinel-2 imagery
The U-net is nowadays among the most popular deep learning algorithms for land use/land
cover (LULC) mapping; nevertheless, it has rarely been used with synthetic aperture radar …
cover (LULC) mapping; nevertheless, it has rarely been used with synthetic aperture radar …
Deep subpixel mapping based on semantic information modulated network for urban land use mapping
Mixed pixel problem is omnipresent in remote sensing images for urban land use
interpretation due to the hardware limitations. Subpixel mapping (SPM) is a usual way to …
interpretation due to the hardware limitations. Subpixel mapping (SPM) is a usual way to …
[HTML][HTML] R Libraries for remote sensing data classification by k-means clustering and NDVI computation in Congo River Basin, DRC
P Lemenkova, O Debeir - Applied Sciences, 2022 - mdpi.com
Featured Application Libraries of the R programming language, including RStoolbox, raster
and terra, were used to classify Landsat OLI-TIRS satellite images by k-means clustering …
and terra, were used to classify Landsat OLI-TIRS satellite images by k-means clustering …
A spectral-temporal constrained deep learning method for tree species mapping of plantation forests using time series Sentinel-2 imagery
Plantation forests provide critical ecosystem services and have experienced worldwide
expansion during the past few decades. Accurate mapping of tree species through remote …
expansion during the past few decades. Accurate mapping of tree species through remote …
Construction of multidimensional features to identify tea plantations using multisource remote sensing data: A case study of Hangzhou city, China
Y Kang, Z Chen, L Li, Q Zhang - Ecological Informatics, 2023 - Elsevier
China is the world's largest tea producer and trader. From 1995 to 2020, the plantation area
and tea production increased by approximately 200 and 400%, respectively. Therefore, we …
and tea production increased by approximately 200 and 400%, respectively. Therefore, we …
Influences of climatic variability and human activities on terrestrial water storage variations across the Yellow River basin in the recent decade
J Xie, YP Xu, Y Wang, H Gu, F Wang, S Pan - Journal of Hydrology, 2019 - Elsevier
Terrestrial water storage (TWS) variations can be influenced by both climatic variability and
human activities. In this study, we made an integrated use of GRACE data and …
human activities. In this study, we made an integrated use of GRACE data and …
Tracking small-scale tropical forest disturbances: Fusing the Landsat and Sentinel-2 data record
Abstract Information on forest disturbance is crucial for tropical forest management and
global carbon cycle analysis. The long-term collection of data from the Landsat missions …
global carbon cycle analysis. The long-term collection of data from the Landsat missions …