Terrestrial research will be enabled by the Instrument's capability to acquire, manage, and analyze super-resolution aerial imagery and sensor data. The Instrument's no-propulsion no-fuel super-resolution multi-sensor balloons are ideal for ecology research within endangered areas. Absence of noise will lessen the impact on the fauna. The Instrument' capability to analyze data and mash up data of multiple sources will enable new discoveries.

The team of Daniel Gann [http://gis.fiu.edu/?p=362] at FIU and the FIU GIS-RS Center will use the Instrument for their research on scaling and detection of wetland plant community dynamics. The team is developing mapping and monitoring methods that can bridging the gap between

(1) plot level acquired abundance data of vegetation to larger spatial extents surrounding a plot and

(2) the use of field data when training classifiers to detect those communities utilizing remote sensing methodologies (i.e., high spatial and spectral resolution satellite data).

Limitations of existing map applications that provide aerial photography is the spatial (sub-meter) and temporal resolution of the data (years). A combination of nadir view with oblique very high resolution aerial photography acquired by an unmanned aerial system (UAS) can provide a valuable source of high resolution plant community reference information that links ground reference plot data to spatial extensive vegetation mapping using remote sensing (RS) methods [Pauly, K.; Adams, S.; Tommaselli, A.; Perko, R.].

The GIS-RC Center is specifically interested in monitoring of wetland plant community and vegetation dynamics, where mobility for intensive sampling is difficult and invasive to the ecosystem - access to oblique and nadir view aerial photography can aid in the identification and estimation of species abundances without extensive invasive ground surveys [Gilmore, M.S.; Korpela, I.; Fassnacht, F.]. Timing of data acquisition - phenological cycles - are important and the recognition of species from photography requires a ground resolution of ~ 2cm or higher [Kaimaris, D.; Key, T.].

The team has experience working with fixed wing UAS photography and see potential benefits of non- or slow moving platform such as the ones within the proposed Instrument would provide

(1) higher and variable resolution with more precise and consistent altitude and spatial position estimates,

(2) better data quality due to slow motion or stationary platform, and

(3) no flight restrictions apply, which makes its application temporally more flexible.

Very high-resolution photography covering the spectral wavelength from blue to near infrared is of great interest in this project. This type of photography can provide valuable reference data when processing and analyzing airborne or terrestrial LiDAR or other high resolution remotely sensed satellite data.

The development of algorithms that would allow for integration of different remotely sensed data sources with extensive field data surveys collected over the years is the second aspect of their monitoring system that would benefit from the proposed Instrument.

References Cited

[PC11] K. Pauly and O. Clerck. "Low-cost very high resolution intertidal vegetation monitoring enabled by near-infrared kite aerial photography." (2011).

[Per+13] R. Perko, et al. "Counting people from above: Airborne video based crowd analysis." arXiv preprint arXiv:1304.6213 (2013).

[ALF13] S.M. Adams, M.L. Levitan, and C.J. Friedland. "High Resolution Imagery Collection Utilizing Unmanned Aerial Vehicles (UAVs) for Post-Disaster Studies." Advances in Hurricane Engineering@ sLearning from Our Past. ASCE, 2013.

[TA+13] A. Tommaselli, et al. "Generating Virtual Images from Oblique Frames." Remote Sensing 5.4 (2013): 1875-1893.

[GM+08] M.S. Gilmore, et al. "Integrating multi-temporal spectral and structural information to map wetland vegetation in a lower Connecticut River tidal marsh." Remote sensing of environment 112.11 (2008): 4048-4060.

[KOR04] I. Korpela. Individual tree measurements by means of digital aerial photogrammetry. Vol. 3. Helsinki, Finland: Finnish Society of Forest Science, 2004.

[FK12] F. Fassnacht, and B. Koch. "Review of forestry oriented multi-angular remote sensing techniques." International Forestry Review 14, no. 3 (2012): 285-298.

[KPT12] D. Kaimaris, P. Patias, and M. Tsakiri. "Best period for high spatial resolution satellite images for the detection of marks of buried structures." The Egyptian Journal of Remote Sensing and Space Science 15.1 (2012): 9-18.

[KEY+01] T. Key, et al. "A comparison of multispectral and multitemporal information in high spatial resolution imagery for classification of individual tree species in a temperate hardwood forest." Remote Sensing of Environment 75.1 (2001): 100-112.