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Abstract
The land area covered by freely available very high-resolution (VHR) imagery has grown dramatically over recent years, which has considerable relevance for forest observation and monitoring. For example, it is possible to recognize and extract a number of features related to forest type, forest management, degradation and disturbance using VHR imagery. Moreover, time series of medium-to-high-resolution imagery such as MODIS, Landsat or Sentinel has allowed for monitoring of parameters related to forest cover change. Although automatic classification is used regularly to monitor forests using medium-resolution imagery, VHR imagery and changes in web-based technology have opened up new possibilities for the role of visual interpretation in forest observation. Visual interpretation of VHR is typically employed to provide training and/or validation data for other remote sensing-based techniques or to derive statistics directly on forest cover/forest cover change over large regions. Hence, this paper reviews the state of the art in tools designed for visual interpretation of VHR, including Geo-Wiki, LACO-Wiki and Collect Earth as well as issues related to interpretation of VHR imagery and approaches to quality assurance. We have also listed a number of success stories where visual interpretation plays a crucial role, including a global forest mask harmonized with FAO FRA country statistics; estimation of dryland forest area; quantification of deforestation; national reporting to the UNFCCC; and drivers of forest change.
Highlights
Remote sensing plays a critical role in the estimation of forest parameters, and in the monitoring of disturbances and changes in forest cover
We focus on the state of the art in visual interpretation of satellite imagery, recognizing the continuing role of HR imagery but focusing on advances that are possible from very high-resolution (VHR) imagery, and highlight their unique and complementary role in remote sensing and in situ data collection for the observation and monitoring of forests
Since the legend for visual interpretation is determined by the land cover map uploaded to the system, LACO-Wiki can be used for collecting data on forest cover, expressed as either forest cover classes or percentage forest cover, or any other features defined by the users, which are visible from VHR satellite imagery
Summary
Remote sensing plays a critical role in the estimation of forest parameters, and in the monitoring of disturbances and changes in forest cover. Different types of satellite sensors (i.e., optical, hyperspectral, LiDAR and radar at varying spatial and temporal resolutions) play different and complementary roles in forest monitoring. The land area covered by VHR imagery has grown dramatically over recent years (Lesiv et al 2018b) This opens up the possibility to visually identify land cover and land use features, as well as the structure of forests. We focus on the state of the art in visual interpretation of satellite imagery, recognizing the continuing role of HR imagery but focusing on advances that are possible from VHR imagery, and highlight their unique and complementary role in remote sensing and in situ data collection for the observation and monitoring of forests. We highlight some successful case studies that have employed satellite imagery for forest observation
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