The data set is the result of the Drivers of Tropical Forest Loss crowdsourcing campaign. The campaign took place in December 2020. A total of 58 participants contributed validations of almost 120k locations worldwide. The locations were selected randomly from the Global Forest Watch tree loss layer (Hansen et al 2013), version 1.7. At each location the participants were asked to look at satellite imagery time series using a customized Geo-Wiki user interface and identify drivers of tropical forest loss during the years 2008 to 2019 following 3 steps: Step 1) Select the predominant driver of forest loss visible on a 1 km square (delimited by a blue bounding box); Step 2) Select any additional driver(s) of forest loss and; Step 3) Select if ...
Tropical forests harbour the highest biodiversity on the planet and are essential to human livelihoo...
Digital and scalable technologies are increasingly important for rapid and large-scale assessment an...
Tropical forests are disappearing at unprecedented rates, but the drivers behind this transformation...
The data set is the result of the Drivers of Tropical Forest Loss crowdsourcing campaign. The campai...
During December 2020, a crowdsourcing campaign to understand what has been driving tropical forest l...
The zip file contains a map to support the publication 'A Continental Assessment of the Drivers of T...
The zip file contains the map used for the statistics calculated in the publication 'A Continental A...
Every year, deforestation results in the loss of wide stretches of forest which is worsening the sta...
Spatially explicit information on forest management at a global scale is critical for understanding ...
Deforestation contributes to global greenhouse gas emissions and must be reduced if the 1.5° C limit...
The data set, in a form of table, contains information on Human Impact on Forests that was collected...
This data repository contains the data results used to analyse how deforestation dynamics relate to ...
These datasets provide maps of deforestation frontier classsification into three themed typologies (...
Both datasets are available on the Global Forest Watch website on their Dashboard. The Datasets on t...
In spite of the high importance of forests, global forest loss has remained alarmingly high during t...
Tropical forests harbour the highest biodiversity on the planet and are essential to human livelihoo...
Digital and scalable technologies are increasingly important for rapid and large-scale assessment an...
Tropical forests are disappearing at unprecedented rates, but the drivers behind this transformation...
The data set is the result of the Drivers of Tropical Forest Loss crowdsourcing campaign. The campai...
During December 2020, a crowdsourcing campaign to understand what has been driving tropical forest l...
The zip file contains a map to support the publication 'A Continental Assessment of the Drivers of T...
The zip file contains the map used for the statistics calculated in the publication 'A Continental A...
Every year, deforestation results in the loss of wide stretches of forest which is worsening the sta...
Spatially explicit information on forest management at a global scale is critical for understanding ...
Deforestation contributes to global greenhouse gas emissions and must be reduced if the 1.5° C limit...
The data set, in a form of table, contains information on Human Impact on Forests that was collected...
This data repository contains the data results used to analyse how deforestation dynamics relate to ...
These datasets provide maps of deforestation frontier classsification into three themed typologies (...
Both datasets are available on the Global Forest Watch website on their Dashboard. The Datasets on t...
In spite of the high importance of forests, global forest loss has remained alarmingly high during t...
Tropical forests harbour the highest biodiversity on the planet and are essential to human livelihoo...
Digital and scalable technologies are increasingly important for rapid and large-scale assessment an...
Tropical forests are disappearing at unprecedented rates, but the drivers behind this transformation...