Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine …

L Parente, V Mesquita, F Miziara, L Baumann… - Remote Sensing of …, 2019 - Elsevier
The livestock activity accounts for a large part of the transformations in land cover in the
world, with pasture areas being the main land use in Brazil and the main livelihood of the …

Accuracy improvements to pixel-based and object-based lulc classification with auxiliary datasets from Google Earth engine

L Qu, Z Chen, M Li, J Zhi, H Wang - Remote Sensing, 2021 - mdpi.com
The monitoring and assessment of land use/land cover (LULC) change over large areas are
significantly important in numerous research areas, such as natural resource protection …

Using Landsat observations (1988–2017) and Google Earth Engine to detect vegetation cover changes in rangelands-A first step towards identifying degraded lands …

Z Xie, SR Phinn, ET Game, DJ Pannell… - Remote Sensing of …, 2019 - Elsevier
Globally, the area of agricultural land is shrinking in part due to environmental degradation.
Acquisition and restoration of degraded lands no longer used for agriculture may present a …

A geographical direction-based approach for capturing the local variation of urban expansion in the application of CA-Markov model

MK Firozjaei, A Sedighi, M Argany, M Jelokhani-Niaraki… - Cities, 2019 - Elsevier
Predictive modelling and its application in land change science has been considerably
advanced, however, further performance improvement of the existing models is undergoing …

Developing a random forest algorithm for MODIS global burned area classification

R Ramo, E Chuvieco - Remote Sensing, 2017 - mdpi.com
This paper aims to develop a global burned area (BA) algorithm for MODIS BRDF-corrected
images based on the Random Forest (RF) classifier. Two RF models were generated …

Urban expansion occurred at the expense of agricultural lands in the Tarai region of Nepal from 1989 to 2016

B Rimal, L Zhang, N Stork, S Sloan, S Rijal - Sustainability, 2018 - mdpi.com
Recent rapid urbanization in developing countries presents challenges for sustainable
environmental planning and peri-urban cropland management. An improved understanding …

Predicting landslide susceptibility and risks using GIS-based machine learning simulations, case of upper Nyabarongo catchment

JB Nsengiyumva, R Valentino - Geomatics, Natural Hazards and …, 2020 - Taylor & Francis
Sustainable landslide mitigation requires appropriate approaches to predict susceptible
zones. This study compared the performance of Logistic Model Tree (LMT), Random Forest …

Improving the remote estimation of soil organic carbon in complex ecosystems with Sentinel-2 and GIS using Gaussian processes regression

JE Ayala Izurieta, CA Jara Santillán, CO Márquez… - Plant and soil, 2022 - Springer
Background and aims The quantitative retrieval of soil organic carbon (SOC) storage,
particularly for soils with a large potential for carbon sequestration, is of global interest due …

Improvement in satellite image-based land cover classification with landscape metrics

A Gudmann, N Csikós, P Szilassi, L Mucsi - Remote Sensing, 2020 - mdpi.com
The use of an object-based image analysis (OBIA) method has recently become quite
common for classifying high-resolution remote-sensed images. However, despite OBIA's …

Post-typhoon forest damage estimation using multiple vegetation indices and machine learning models

X Chen, R Avtar, DA Umarhadi, AS Louw… - Weather and Climate …, 2022 - Elsevier
The frequency and intensity of typhoons have increased due to climate change. These
climate change-induced disasters have caused widespread damage to forests. Evaluation of …