Machine learning in landscape ecological analysis: a review of recent approaches
Abstract Context Artificial Intelligence (AI) has rapidly developed over the past several
decades. Several related AI approaches, such as Machine Learning (ML), have been …
decades. Several related AI approaches, such as Machine Learning (ML), have been …
Spatio-temporal simulation and prediction of land-use change using conventional and machine learning models: a review
Spatio-temporal land-use change modeling, simulation, and prediction have become one of
the critical issues in the last three decades due to uncertainty, structure, flexibility, accuracy …
the critical issues in the last three decades due to uncertainty, structure, flexibility, accuracy …
Improving land-use change modeling by integrating ANN with Cellular Automata-Markov Chain model
A Gharaibeh, A Shaamala, R Obeidat, S Al-Kofahi - Heliyon, 2020 - cell.com
Urban growth and land-use change are a few of many puzzling factors affecting our future
cities. Creating a precise simulation for future land change is a challenging process that …
cities. Creating a precise simulation for future land change is a challenging process that …
Flood susceptibility assessment using integration of adaptive network-based fuzzy inference system (ANFIS) and biogeography-based optimization (BBO) and BAT …
This paper couples an adaptive neuro-fuzzy inference system (ANFIS), with two heuristic-
based computation methods namely biogeography-based optimization (BBO) and BAT …
based computation methods namely biogeography-based optimization (BBO) and BAT …
Wetland conversion risk assessment of East Kolkata Wetland: A Ramsar site using random forest and support vector machine model
Abstract East Kolkata Wetland (EKW) is a Ramsar site located adjacent to the Kolkata
megacity. EKW is one of the resourceful wetland ecosystems of the world which offers a …
megacity. EKW is one of the resourceful wetland ecosystems of the world which offers a …
Spatial mapping of groundwater springs potentiality using grid search-based and genetic algorithm-based support vector regression
In this study, groundwater springs potentiality maps were prepared using a novel integrated
model, support vector regression (SVR) with genetic algorithm (GA), for the Jerash and …
model, support vector regression (SVR) with genetic algorithm (GA), for the Jerash and …
Field-scale estimation of sugarcane leaf nitrogen content using vegetation indices and spectral bands of Sentinel-2: Application of random forest and support vector …
M Soltanikazemi, S Minaei… - … and Electronics in …, 2022 - Elsevier
Nitrogen is an essential factor for assessing the quality of sugarcane during the growing
season, as deficiency of this component significantly reduces crop yield. The Kjeldahl …
season, as deficiency of this component significantly reduces crop yield. The Kjeldahl …
A neural network and landscape metrics to propose a flexible urban growth boundary: A case study
Urban sprawl is a major barrier for the precise demarcation of administrative boundary in the
world. In India, medium and small towns have so far developed outside the envisaged …
world. In India, medium and small towns have so far developed outside the envisaged …
Urban expansion simulation towards low-carbon development: A case study of Wuhan, China
Rapid urbanization causes great changes of carbon metabolism. Current research mainly
focuses on carbon consequences of urban expansion projections, but rarely explores how …
focuses on carbon consequences of urban expansion projections, but rarely explores how …
Patch-based cellular automata model of urban growth simulation: Integrating feedback between quantitative composition and spatial configuration
Urban land use change modeling can enhance our understanding of processes and
patterns of urban growth that emerge from human-environment interactions. Cellular …
patterns of urban growth that emerge from human-environment interactions. Cellular …