AI-ForestWatch: semantic segmentation based end-to-end framework for forest estimation and change detection using multi-spectral remote sensing imagery

Spatio-Temporal Response of Vegetation Indices to Rainfall and Temperature in A Semiarid Region

(2020) Edith Olmos-Trujillo et al.   Sustainability

Rapid generation of global forest cover map using Landsat based on the forest ecological zones

(2020) Xiaomei Zhang et al.   Journal of Applied Remote Sensing

Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks

(2020) Pablo de Bem et al.   Remote Sensing

A Patch-Based Light Convolutional Neural Network for Land-Cover Mapping Using Landsat-8 Images

(2019) Hunsoo Song et al.   Remote Sensing

Predictive Modeling of Future Forest Cover Change Patterns in Southern Belize

(2019) Carly Voight et al.   Remote Sensing

Socioeconomic Impacts of the Billion Trees Afforestation Program in Khyber Pakhtunkhwa Province (KPK), Pakistan

(2019) Khan et al.   Forests

Classification of tree species and stock volume estimation in ground forest images using Deep Learning

(2019) Jiazheng Liu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A system dynamics model for billion trees tsunami afforestation project of Khyber Pakhtunkhwa in Pakistan: Model application to afforestation activities

(2019) Naila Nazir et al.   Journal of Mountain Science

Forest height estimation and change monitoring based on artificial neural network using Geoscience Laser Altimeter System and Landsat data

(2019) Xiliang Ni et al.   Journal of Applied Remote Sensing

Comparison of machine learning algorithms for forest parameter estimations and application for forest quality assessments

(2018) Qingxia Zhao et al.   FOREST ECOLOGY AND MANAGEMENT

Forest Change Detection in Incomplete Satellite Images With Deep Neural Networks

(2017) Salman H. Khan et al.   IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING

Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications

(2017) Jinru Xue et al.   Journal of Sensors

Mapping tree height distributions in Sub-Saharan Africa using Landsat 7 and 8 data

(2016) Matthew C. Hansen et al.   REMOTE SENSING OF ENVIRONMENT

Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan

(2016) Faisal Qamer et al.   Remote Sensing

Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil

(2015) Dan-Xia Song et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

(2014) Masanobu Shimada et al.   REMOTE SENSING OF ENVIRONMENT

Global, Landsat-based forest-cover change from 1990 to 2000

(2014) Do-Hyung Kim et al.   REMOTE SENSING OF ENVIRONMENT

Change detection from remotely sensed images: From pixel-based to object-based approaches

(2013) Masroor Hussain et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

High-Resolution Global Maps of 21st-Century Forest Cover Change

(2013) M. C. Hansen et al.   SCIENCE

Ten-Year Landsat Classification of Deforestation and Forest Degradation in the Brazilian Amazon

(2013) Carlos Souza et al.   Remote Sensing

Forest cover trends from time series Landsat data for the Australian continent

(2012) Eric A. Lehmann et al.   International Journal of Applied Earth Observation and Geoinformation

Quantifying forest cover loss in Democratic Republic of the Congo, 2000–2010, with Landsat ETM+ data

(2012) Peter V. Potapov et al.   REMOTE SENSING OF ENVIRONMENT

A New Approach to Change Vector Analysis Using Distance and Similarity Measures

(2011) Osmar A. Carvalho Júnior et al.   Remote Sensing

Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods

(2010) George Xian et al.   REMOTE SENSING OF ENVIRONMENT

Object based image analysis for remote sensing

(2009) T. Blaschke   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks

(2009) Chengquan Huang et al.   REMOTE SENSING OF ENVIRONMENT