A Systematic Review of the Application of Remote Sensing Technologies in Mapping Forest Insect Pests and Diseases at a Tree-Level.
An increase in the frequency and severity of forest insect pest and disease (FIPD) outbreaks
has drastically affected the health and functioning of many forest stands worldwide. This has …
has drastically affected the health and functioning of many forest stands worldwide. This has …
[HTML][HTML] The utility of Planetscope spectral data in quantifying above-ground carbon stock in an urban reforested landscape
Urbanization, deforestation, and forest degradation significantly contribute to atmospheric
carbon emissions and heightened climate change risks. Reforestation, a sustainable long …
carbon emissions and heightened climate change risks. Reforestation, a sustainable long …
Estimating aboveground biomass of two different forest types in myanmar from sentinel-2 data with machine learning and geostatistical algorithms
P Wai, H Su, M Li - Remote Sensing, 2022 - mdpi.com
The accurate estimation of spatially explicit forest aboveground biomass (AGB) provides an
essential basis for sustainable forest management and carbon sequestration accounting …
essential basis for sustainable forest management and carbon sequestration accounting …
Estimating aboveground carbon stocks of urban trees by synergizing ICESat-2 LiDAR with GF-2 data
H Qin, W Zhou, Y Qian, H Zhang, Y Yao - Urban Forestry & Urban Greening, 2022 - Elsevier
Accurately mapping carbon stocks of urban trees is necessary for urban managers to design
strategies to mitigate climate change. However, the aboveground carbon stocks of urban …
strategies to mitigate climate change. However, the aboveground carbon stocks of urban …
Two-step carbon storage estimation in urban human settlements using airborne LiDAR and Sentinel-2 data based on machine learning
The quantification of carbon storage (CS) within urban areas has become increasingly
crucial for achieving global carbon neutrality. This study proposed a new approach to …
crucial for achieving global carbon neutrality. This study proposed a new approach to …
[HTML][HTML] Quantifying the relationship between urban blue-green landscape spatial pattern and carbon sequestration: a case study of Nanjing's central city
Y Yuan, S Tang, J Zhang, W Guo - Ecological Indicators, 2023 - Elsevier
Against the background of global warming, urban blue–green spaces (UBGS) are important
carbon sequestration (CS) carriers that can reduce carbon emissions. However, previous …
carbon sequestration (CS) carriers that can reduce carbon emissions. However, previous …
Urban Above-Ground Biomass Estimation Using GEDI Laser Data and Optical Remote Sensing Images
X Zhao, W Hu, H Jiang, W Wei, J Xu - Remote Sensing, 2024 - search.proquest.com
Accurate estimating of above-ground biomass (AGB) of vegetation in urbanized areas is
essential for urban ecosystem services. NASA's Global Ecosystem Dynamics Investigation …
essential for urban ecosystem services. NASA's Global Ecosystem Dynamics Investigation …
Quantitative remote sensing of forest ecosystem services in sub-Saharan Africa's urban landscapes: A review
A dearth of information on urban ecosystem services in the past decades has led to little
consolidation of such information for informed planning, decision-making and policy …
consolidation of such information for informed planning, decision-making and policy …
Identifying Spatial Variation of Carbon Stock in a Warm Temperate Forest in Central Japan Using Sentinel-2 and Digital Elevation Model Data
The accurate estimation of carbon stocks in natural and plantation forests is a prerequisite
for the realization of carbon peaking and neutrality. In this study, the potential of optical …
for the realization of carbon peaking and neutrality. In this study, the potential of optical …
Machine learning applied to tree crop yield prediction using field data and satellite imagery: A case study in a citrus orchard
The overall goal of this study is to define an intelligent system for predicting citrus fruit yield
before the harvest period. This system uses a machine learning algorithm trained on …
before the harvest period. This system uses a machine learning algorithm trained on …