AIMC Topic: Forests
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Physical evolution of the Three Gorges Reservoir using advanced SVM on Landsat images and SRTM DEM data.
Environmental science and pollution research international
Mar 15, 2018
The Three Gorges Reservoir (TGR) is one of the largest hydropower reservoirs in the world. However, changes of the important physical characteristics of the reservoir covering pre-, during-, and post- dam have not been well studied. This study analyz...
An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India.
Environmental monitoring and assessment
Oct 20, 2017
Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology...
High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models.
PloS one
Jan 23, 2017
Accurate and detailed spatial soil information is essential for environmental modelling, risk assessment and decision making. The use of Remote Sensing data as secondary sources of information in digital soil mapping has been found to be cost effecti...
Modeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks.
Anais da Academia Brasileira de Ciencias
Aug 15, 2016
The study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the ...
Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.
PloS one
May 17, 2016
Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approa...
Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.
Sensors (Basel, Switzerland)
Jan 14, 2016
Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as...
GIS Fuzzy Expert System for the assessment of ecosystems vulnerability to fire in managing Mediterranean natural protected areas.
Journal of environmental management
Dec 14, 2015
A significant threat to the natural and cultural heritage of Mediterranean natural protected areas (NPAs) is related to uncontrolled fires that can cause potential damages related to the loss or a reduction of ecosystems. The assessment and mapping o...
Landscape ethnoecological knowledge base and management of ecosystem services in a Székely-Hungarian pre-capitalistic village system (Transylvania, Romania).
Journal of ethnobiology and ethnomedicine
Jan 7, 2015
BACKGROUND: Previous studies showed an in-depth ecological understanding by traditional people of managing natural resources. We studied the landscape ethnoecological knowledge (LEEK) of Székelys on the basis of 16-19(th) century village laws. We ana...
Profiling of mangrove forest dynamics in the Fly River delta, Papua New Guinea.
Marine pollution bulletin
Aug 1, 2025
Mangrove forests (MFs), as vital ecosystems in tropical and subtropical coastal regions, play a significant role in the global carbon cycle. However, MFs are currently facing unprecedented risks of degradation due to both natural and anthropogenic fa...
Process-Informed Neural Networks: A Hybrid Modelling Approach to Improve Predictive Performance and Inference of Neural Networks in Ecology and Beyond.
Ecology letters
Nov 1, 2024
Despite deep learning being state of the art for data-driven model predictions, its application in ecology is currently subject to two important constraints: (i) deep-learning methods are powerful in data-rich regimes, but in ecology data are typical...
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