146
6.7 Management Applications: Limitations
and Opportunities
Thanks to continuing advances in computing and software technologies, we are
poised to bring near-real-time RS products to more stakeholders. Applications like
Google Earth Engine (https://earthengine.google.com/) now have the ability to
automate image acquisition, preprocessing, and more complex modeling algorithms
to provide critical forest health information across large landscapes at regular time
intervals. Similarly, the ESA’s Grid Processing on Demand (G-POD) provides an
online environment where scientists can build and automate RS applications (https://
gpod.eo.esa.int/). While several organizations (see ForWarn, FDM, and eDaRT
above) are making final products from this type of rapid analysis and assessment
operational for coarse forest health assessments and disturbance mapping efforts,
higher-level products (higher spatial resolution, low-level stress detection) are not
yet publicly available for use by broad stakeholder groups.
Currently, most RS efforts to detect incipient stress factors or detailed vegetation
condition are conducted by the research community with scientific journals as their
primary outputs. The more widespread use of more advanced RS techniques in forest management is primarily limited by:
• The cost of image acquisition and expertise required to accurately calibrate sensors and validate products. This is particularly true for hyperspectral efforts,
which generate large amounts of data and require specialized expertise for preprocessing corrections, calibration, and data management. Computing advances
and the growing commercial sector promise improved access, but for many land
managers, cost is still a strong deterrent. Some organizations are hoping to make
cutting-edge imagery more accessible. For example, NASA’s Goddard’s LiDAR,
Hyperspectral, and Thermal Imager (G-LiHT) (https://gliht.gsfc.nasa.gov/) is a
portable, airborne imaging system that simultaneously maps composition, structure, and function of terrestrial ecosystems using multispectral LiDARs (3-D
information about the vertical and horizontal distribution of foliage and other
canopy elements), hyperspectral imaging spectrometer to discern species composition and variations in biophysical variables (photosynthetic pigments and
nutrient and water content), and a thermal camera to measure surface temperatures to detect heat and moisture stress (Cook et al. 2013). Owned and operated
by NASA Goddard, this instrument has proven to be more affordable and accessible than comparable commercial vendors and may greatly expand access to
cutting-edge sensor technologies for a variety of applications (Fig. 6.13).
• The turnaround time required to deliver final mapping products. Typically, the
more irruptive forest health issues require immediate attention in the current
growing season (e.g., pest outbreaks, extreme climate events, wildfires), while
turnaround from RS projects doesn’t always occur in the same year. This disparity between product delivery and product need is especially evident in studies
J. Pontius et al.
6.7 Management Applications: Limitations
and Opportunities
Thanks to continuing advances in computing and software technologies, we are
poised to bring near-real-time RS products to more stakeholders. Applications like
Google Earth Engine (https://earthengine.google.com/) now have the ability to
automate image acquisition, preprocessing, and more complex modeling algorithms
to provide critical forest health information across large landscapes at regular time
intervals. Similarly, the ESA’s Grid Processing on Demand (G-POD) provides an
online environment where scientists can build and automate RS applications (https://
gpod.eo.esa.int/). While several organizations (see ForWarn, FDM, and eDaRT
above) are making final products from this type of rapid analysis and assessment
operational for coarse forest health assessments and disturbance mapping efforts,
higher-level products (higher spatial resolution, low-level stress detection) are not
yet publicly available for use by broad stakeholder groups.
Currently, most RS efforts to detect incipient stress factors or detailed vegetation
condition are conducted by the research community with scientific journals as their
primary outputs. The more widespread use of more advanced RS techniques in forest management is primarily limited by:
• The cost of image acquisition and expertise required to accurately calibrate sensors and validate products. This is particularly true for hyperspectral efforts,
which generate large amounts of data and require specialized expertise for preprocessing corrections, calibration, and data management. Computing advances
and the growing commercial sector promise improved access, but for many land
managers, cost is still a strong deterrent. Some organizations are hoping to make
cutting-edge imagery more accessible. For example, NASA’s Goddard’s LiDAR,
Hyperspectral, and Thermal Imager (G-LiHT) (https://gliht.gsfc.nasa.gov/) is a
portable, airborne imaging system that simultaneously maps composition, structure, and function of terrestrial ecosystems using multispectral LiDARs (3-D
information about the vertical and horizontal distribution of foliage and other
canopy elements), hyperspectral imaging spectrometer to discern species composition and variations in biophysical variables (photosynthetic pigments and
nutrient and water content), and a thermal camera to measure surface temperatures to detect heat and moisture stress (Cook et al. 2013). Owned and operated
by NASA Goddard, this instrument has proven to be more affordable and accessible than comparable commercial vendors and may greatly expand access to
cutting-edge sensor technologies for a variety of applications (Fig. 6.13).
• The turnaround time required to deliver final mapping products. Typically, the
more irruptive forest health issues require immediate attention in the current
growing season (e.g., pest outbreaks, extreme climate events, wildfires), while
turnaround from RS projects doesn’t always occur in the same year. This disparity between product delivery and product need is especially evident in studies
J. Pontius et al.