Frank H. Koch

Principles of Applied Remote Sensing

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Data, data everywhere: detecting spatial patterns in fine-scale ecological information collected across a continent

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Remote Sensing: Past and Present

ContextFine-scale ecological data collected across broad regions are becoming increasingly available. Appropriate geographic analyses of these data can help identify locations of ecological concern.ObjectivesWe present one such approach, spatial association of scalable hexagons (SASH), which identifies locations where ecological phenomena occur at greater or lower frequencies than expected by chance. This approach is based on a sampling frame optimized for spatial neighborhood analysis, adjustable to the appropriate spatial resolution, and applicable to multiple data types.MethodsWe divided portions of the United States into scalable equal-area hexagonal cells and, using three types of data (field surveys, aerial surveys, satellite imagery), identified geographic clusters of forested areas having high and low values for (1) invasive plant diversity and cover, (2) mountain pine beetle-induced tree mortality, and (3) wildland forest fire occurrences.ResultsUsing the SASH approach, we detected statistically significant patterns of plant invasion, bark beetle-induced tree mortality, and fire occurrence density that will be useful for understanding macroscale patterns and processes associated with each forest health threat, for assessing its ecological and economic impacts, and for identifying areas where specific management activities may be needed.ConclusionsThe presented method is a “big data” analysis tool with potential application for macrosystems ecology studies that require rigorous testing of hypotheses within a spatial framework. This method is a standard component of annual national reports on forest health status and trends across the United States and can be applied easily to other regions and datasets.

Future Trends in Remote Sensing

The use of remote sensing perhaps goes all the way back to prehistoric times when the early man stood on a platform in front of his cave and glanced at the surrounding landscape (late Robert N. Colwell, UC Berkeley). These humans were remotely sensing the features in the landscape to determine the best places to gather food and water and how to avoid becoming a food for the other inhabitants of the landscape. The term “photography” is derived from two Greek words meaning “light” (phos) and “writing” (graphein) (late John E. Estes, UC Santa Barbara). All cameras and sensors utilize the same concept of light entering a camera or a sensor and being recorded on a film or on a digital media.

Atmospheric Applications of Remote Sensing

In the previous chapters, we have discussed how the scientific community, government agencies, nongovernmental organizations (NGOs), private industry, and the general public use the wealth of information provided by airborne and satellite remote sensing data. We have presented specific examples of its cost-effective and timely use in a wide range of disciplines including engineering, forestry, geology, public health, archaeology, humanitarian aid, natural resources, and geography. Finally, we explored the linkages between remote sensing, geographical information systems, and spatial modeling. It is this continued fusion of remote sensing and big data science where the future of remote sensing lies.

International Laws, Charters, and Policies

The discovery that the stratospheric ozone layer can be eroded by human activities along with the existence of a larger-than-expected hole over Antarctica more than 30 years ago propelled the use of remote sensing of Earth’s atmospheric structure for more than weather forecasting; it became central to observation research and a tool for the development of environmental policy such as the Montreal Protocol on Substances that Deplete the Ozone Layer.

Observing Coastal and Ocean Ecosystems

Remote sensing has been identified as one of the most significant technological achievements of the twentieth century. Earth observation satellites transcend national boundaries and geophysical space, creating transparency into activities and places that were once concealed from foreign states. This raises many issues—the ideals of cooperation, societal openness, and information sharing juxtaposed with the very real fears that spatial information could be used for sparking military conflicts and other malevolent purposes.

The Final Frontier: Building New Knowledge Through Planetary and Extrasolar Observation

Marine environments contain substantial biological diversity, deliver vital ecosystem services, supply valuable natural resources, and are a core component of our weather and climate system. However, the ocean environment is complex and ever-changing. Examining how our oceans, atmosphere, and landmasses interact would be virtually impossible without the use of a wide variety of sensors and platforms. Satellite observation sensors work in concert with in situ sensors (e.g., buoys and high-frequency radars), research vessels and ships of opportunity, aircraft, gliders (unmanned underwater robots), autonomous undersea vehicles (AUVs), drifters, animal telemetry, and tripod LiDAR to provide cohesive information regarding deep ocean, coastal, and shelf areas in order to understand the complexity, function, and structure of these systems.

Terrestrial Applications of Remote Sensing

Many technological developments in remote sensing are at least partially rooted in space exploration efforts; for instance, imaging spectroscopy—hyperspectral imaging—was developed in parallel for terrestrial and planetary applications. Of course, what are perhaps the best-known space exploration efforts have actually involved direct (i.e., non-remote-sensing) measurements: the Apollo missions, which landed astronauts on the Earth’s Moon during the late 1960s and early 1970s, and more recently, the unmanned Mars Exploration Rovers Spirit and Opportunity, which began collecting data from the Martian surface in 2004, as well as the rover Curiosity, which has been collecting data since 2012 as part of NASA’s Mars Science Laboratory mission. Notably, all of these surface investigation missions have coincided with remote sensing by orbiting spacecraft. For example, the Apollo Command and Service Modules, which orbited the Moon while their corresponding Lunar Modules were on the surface, were equipped with a variety of remote sensing instruments, and there are currently five different spacecraft orbiting Mars. Ultimately, oriting or fly-by spacecraft have collected remotely sensed data, in varying amounts, for all of the planets in our solar system and some of their moons (Hanel et al. 2003), as well as asteroids and the Sun (e.g., NASA’s Solar Dynamics Observatory). Furthermore, the number of satellite-based instruments targeted at deep space continues to increase. In this chapter, we highlight some prominent historical missions as well as some active efforts.

Data Processing Tools

Each day, millions of individual images and observations collect an enormous variety of information about the Earth’s surface and subsurface. This routine surveillance enables the monitoring and modeling of ecosystem health, detecting seismic activity, identifying surface vegetation, promoting sustainable agriculture, and characterizing the physical and social vulnerability of human settlements.