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Forests

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Modeling land use and land cover dynamics of Bale Mountains National Park using Google Earth Engine and cellular automata-artificial neural network (CA-ANN) model.

PloS one
This research aimed to assess the observed land use and land cover (LULC) changes of Bale Mountains National Park (BMNP) from 1993 to 2023 and its future projections for the years (2033 and 2053). The study utilized multi-date Landsat imagery from 19...

U3UNet: An accurate and reliable segmentation model for forest fire monitoring based on UAV vision.

Neural networks : the official journal of the International Neural Network Society
Forest fires pose a serious threat to the global ecological environment, and the critical steps in reducing the impact of fires are fire warning and real-time monitoring. Traditional monitoring methods, like ground observation and satellite sensing, ...

The intuitionistic fuzzy linguistic assessment of forest soil quality with multi-granularity qualitative information.

Environmental monitoring and assessment
The soil quality of forest land is directly related to the growth of forest trees and the local ecological environment. This paper proposes an intuitionistic fuzzy linguistic aggregation method for heterogeneous linguistic assessment information, to ...

Remote sensing estimation of aboveground biomass of different forest types in Xinjiang based on machine learning.

Scientific reports
Forest aboveground biomass (AGB) is a key indicator reflecting the function and quality of forest ecosystems, and accurate large-scale estimations of forest AGB are essential for effective forest ecosystem management. However, owing to limitations in...

Capsule neural network and adapted golden search optimizer based forest fire and smoke detection.

Scientific reports
Forest fires represent a major risk to both ecosystems and human health that rising frequency of it exacerbates global warming. This study introduces an innovative methodology for detecting forest fires and smoke using an enhanced capsule neural netw...

Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems.

Environmental science and pollution research international
Forest fires pose a significant ecological and environmental threat globally, and India has seen a marked increase in both the frequency and severity of these events in recent years. This has led to extensive damage to natural resources, including fo...

Forest fire susceptibility mapping using multi-criteria decision making and machine learning models in the Western Ghats of India.

Journal of environmental management
Forest fires have significantly increased over the last decade due to shifts in rainfall patterns, warmer summers, and long spells of dry weather events in the coastal regions. Assessment of susceptibility to forest fires has become an important mana...

Forecasting deforestation and carbon loss across New Guinea using machine learning and cellular automata.

The Science of the total environment
The island of New Guinea harbors some of the world's most biologically diverse and highly endemic tropical ecosystems. Nevertheless, progressing land-use change in the region threatens their integrity, which will adversely affect their biodiversity a...

Spatial and temporal classification and prediction of aspen probability in boreal forests using machine learning algorithms.

Environmental monitoring and assessment
Mapping and classifying the probability of occurrence of Populus tremula L. (aspen) in boreal forests is a complex task for sustainable forest management and biodiversity conservation. As a key broadleaved species in the taiga region, aspen supports ...

Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning.

Environmental monitoring and assessment
The Mount Kenya forest ecosystem (MKFE), a crucial biodiversity hotspot and one of Kenya's key water towers, is increasingly threatened by climate change, putting its ecological integrity and vital ecosystem services at risk. Understanding the intera...