Progress 09/01/16 to 05/31/19
Outputs
Target Audience:
Nothing Reported
Changes/Problems:Our contractor (ArgenTech) had technical trouble with their main UAS; Vapor Pulse, which reduced our field sampling scheme. To augment we integrated additional plots from colleagues at USFS and UNH and shifted our sampling period. What opportunities for training and professional development has the project provided? Open access software released ongithubfor Forest Stand Heighthttps://github.com/leiyangleon/FSHThis software can be used for training. How have the results been disseminated to communities of interest?We had discussions with White Mountain National Forest and University of New Hampshire. We presented our work at the NESAF Annual Winter Meeting New England Forest Stories: the People, the Management, the Technical Knowledge, March, 2018. Additional outreach efforts: Project development with Winrock on MRV tools Member of science team on NASA's NISAR mission Project development with Conservation International on radar MRV tools Promotion at NASA and USDA science team meetings and programs such as SERVIR, GOFC-GOLD, SilvaCarbon, LEAF, IWMI Promotion with TNC on forest monitoring tools Discussions with Prime on Remote Sensing and Geospatial Technology Support Services" contract (Solicitation Number: 1284JC18R0001) under USFS solicitation What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Open access software released on github for Forest Stand Height https://github.com/leiyangleon/FSH Tested ALOS-2 currently for updated baselines and working with NASA JPL and ISCE Executed two main field campaigns focused on assessing Gypsy Moth infestation and another for fused algorithm development with measurements of Above Ground Biomass (AGB), species, TLS, crown canopy cover, DBH, Lorey's Height, and related metrics. Worked with WMNF and USFS community to assess management plans, harvest activities, and disturbances (infestation, ice damage, fire) across WMNF and regional hot spots; 3b. conduct tech transfer to transition tools to WMNF as part of Public Private Partnership. A multitemporal analysis routine (MT) was developed. The MT routine is modular, allowing time series operations to be chained together in potentially complex arrangements, starting with one or more data sources, followed by processing steps, each step having one or more inputs, and an output that can take several different structural forms. MT includes modules for smoothing, recompositing, statistical summaries, trend calculation (e.g., decreasing biomass), seasonal phenological metrics calculation (e.g., Start Of Season), anomaly detection, gap filling, correlation analysis between two time series, and fusion of two time series based on correlation. Taken together, these infrastructure developments have enabled and improved our ability to create fully automated agricultural metrics derived from SAR. During this period we continued to utilize and extend our Geospatial Information Processing System (GIPS) data infrastructure for retrieval, management, and analysis of data from Sentinel-1 and PALAR-2 ScanSAR. GIPS is a modular open source framework that is based on "driver" technology, which enables extension to include data from essentially any source, abstracting away the details of data formats, projections, source, retrieval mechanisms, structure, or units. GIPS drivers include the definition of processing blocks, so we can create custom products on the fly. We've built around the ESA S1Toolbox v5.3 to generate despeckled and terrain corrected gamma and / or sigma naught stacks along with ancillary information such as layover shadow masks and incidence angle maps depending on custom options via XML. This allows for automated data feeds into DSTs or further ingestion into work flows. Annotated data sets hold metadata on the main characteristics including acquisition, image properties, polarization, Doppler information, swath merging, calibration, and geographic location. Our driver is designed to operate with any combination of specifications (e.g., Single Look Complex (SLC), Ground Range Detected (GRD), etc...) depending on application objectives. Worked with ISCE and WINSAR on SW development but determined ISCE is not optimal for commercial applications Deployed GIPS on cloud computing environment
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Huang et al., 2018, Assessment of Forest above Ground Biomass Estimation Using Multi-Temporal C-band Sentinel-1and Polarimetric L-band PALSAR-2 Data, Remote Sens.2018,10, 1424; doi:10.3390/rs10091424
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2017
Citation:
Y. Lei, P. Siqueira, N. Torbick, D. Chowdhury, W. Salas and R. Treuhaft, "Large-scale product of forest height using a new approach from spacborne repeat-pass sar interferometry and lidar," 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, 2017, pp. 2875-2878.
doi: 10.1109/IGARSS.2017.8127598;
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Progress 09/01/17 to 08/31/18
Outputs
Target Audience:Worked with WMNF and USFS community to assess management plans, harvest activities, and disturbances (infestation, ice damage, fire) across WMNF and regional hot spots; conducted tech transfer to transition tools to WMNF as part of Public Private Partnership. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided? We released an open access software released on github for Forest Stand Heigh Working with NASA JPL and ISCE Staff training at Small Business in radar procesing and forest carbon modeling How have the results been disseminated to communities of interest? Presentation at the NESAF Annual Winter Meeting New England Forest Stories: the People, the Management, the Technical Knowledge, March, 2018 Open access software released on github for Forest Stand Height and SAR drivers, ie. https://github.com/leiyangleon/FSH and https://github.com/Applied-GeoSolutions more coming soon Discussions with end users in WMNF and UNH Discussion of project interest and development with Forwarn Project development with Winrock on MRV tools Member of science team on NASA's NISAR mission Project development with Conservation International on radar MRV tools Promotion at NASA and USDA science team meetings and programs such as SERVIR, GOFC-GOLD, SilvaCarbon, LEAF, IWMI Promotion with TNC on forest monitoring tools Discussions with Prime on Remote Sensing and Geospatial Technology Support Services" contract (Solicitation Number: 1284JC18R0001) under USFS solicitation Publication in IEEE, Y. Lei, P. Siqueira, N. Torbick, D. Chowdhury, W. Salas and R. Treuhaft, "Large-scale product of forest height using a new approach from spacborne repeat-pass sar interferometry and lidar," 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, 2017, pp. 2875-2878. doi: 10.1109/IGARSS.2017.8127598; http://ieeexplore.ieee.org/document/8127598/?anchor=authors What do you plan to do during the next reporting period to accomplish the goals? Execute commercialization plan.
Impacts
What was accomplished under these goals?
Mapped Above Ground Biomass (AGB) and Crown Canopy Cover (CCC) across White Mountain National Forest and entire northeast USA for ~2008 and ~2016. Example structural mapping of Kingman Farm (NH) using UAS lidar and time series Sentinel-1. "C1" is the control site vs the "T1" is the treatment site. Treatment site contains a more shorter scrubby/shrubby vegetation (regrowth or understory) as compared with the control site. Evaluated ABG modeling. Theassessment scatterplot illustrated random forest model of AGB with strong outcome (R2 0.8), middle highlights variable importance within model, and right shows AGB for development site. Coefficient of variation for cell intensity above 2m had the strong importance in model runs. Initial mapping of gypsy moth disturbance mapping. Results shown below. Operationalized Interferometric Synthetic Aperture Radar (InSAR) Forest Stand Height (FSH) maps across northeast USA using PALSAR-2 (2015-2017 data); 4a. work with USFS, NASA JPL, and EPA on using FSH to improve carbon models
Publications
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Progress 09/01/16 to 08/31/17
Outputs
Target Audience:United States Department of Agriculture (USDA) United States Forest Service (USFS)- Forest lands comprise 304million hectares of the total land area in the US with 44% controlled by Federal, State, and local governments. Characterizing forest structure, quantifying forest disturbance, and monitoring forest utilization on these lands is a primary and continuous need by multiple end user communities, including the USDA USFS (see letters). Both natural and anthropogenic stressors are influencing forest disturbance processes and patterns. Climate change, extreme weather, renewable energy demands, timber, land conversion, and invasive species are several key actors influencing forest function and services. These can range in frequency, intensity, and magnitude. Timely and accurate assessment of disturbance events and condition are critical to respond effectively and appropriately at local, regional, and national scales. In addition, assessing the severity and understanding the scales of disturbance are critical for broad-scale management, policy, and economic decision-making. While optical-based mapping techniques have made significant contributions toward assessment, they are limited by cloud coverage and only provided limited information on stand structure. The wide adaptation of operational SAR derived metrics into USFS programs and disturbance protocol has remained elusive due to the technical barriers. In this SBIR we intend to bridge this gap and provide enhanced products and services (metrics, maps, techniques, and expertise) that are easy to apply and integrate into decision support tools. Monitoring, Reporting, and Verification (MRV) community- The rapid growth of carbon science and characterization of ecosystem services has created a huge market for tools, products, and services. International monitoring frameworks, such as Reducing Emissions from Deforestation and Degradation (REDD), have created the need for robust Monitoring, Reporting, and Verification (MRV) platforms that can serve programs and initiatives aimed at carbon cycle science, conservation, and conventions. Maps of deforestation and degradation at multiple scales have taken on increased importance with the recognition of the value of forests and the rates of forest loss. International programs, like REDD, are being constructed to help preserve the world's forests, improve livelihoods, and promote sustainable practices. Under REDD, emissions and removals of carbon due to changes in forests are estimated from two components: activity data (e.g. deforestation, degradation) and forest carbon stock data (e.g. carbon in biomass, soil c). As systems are built in which some people pay others to slow the rate of carbon emissions from forest loss, the need for accurate, spatially explicit, and timely information on forests and forest change becomes critical. Satellite observations have been used to map forests since the 1970s. While optical reflectance data are the most abundant and common type of observations available, radar and Lidar data can be used to effectively map forest characteristics and changes. Optical reflectance observations passively measure the sun's radiation off of the land surface. Trees, forested areas, and changes in these areas are identified based on the amount and change in reflectance. SAR and Lidar are active systems that send out energy to the Earth's surface and measure the subsequent energy return. These active systems often provide more information regarding forest structure and, therefore, are useful for biomass and carbon content. Additionally, SAR systems are much less sensitive to cloud and haze cover than are optical systems, making them useful for forest monitoring in cloudy areas. However, many MRV/REDD platforms do not have the capacity to integrate SAR forest metrics. In this SBIR, we have strategically aligned the goals to serve this community (see letters). Our small business (AGS) has several high profile example MRV or "Decision Support Tools" (DST) currently operating that blend satellite maps, geospatial information, graphing and tabular data, mobile Apps, and end user options within web-GIS. Changes/Problems:Lidar contractor had technical problems. Workign with UNH partners on work around and leveraging GRANIT lidar as solution. What opportunities for training and professional development has the project provided?Conducted workshops and training at NASA Science team meetings (LCLUC) and at academic partbner institutions Serving on PhD commitee at partner institution (UNH) How have the results been disseminated to communities of interest?In part, working on final products now. What do you plan to do during the next reporting period to accomplish the goals?Extensive marketign and promotional campaign with strategic partners
Impacts
What was accomplished under these goals?
Working with regional USFS in White Mountian National Forest & New England Society of American Foresters http://www.nesaf.org/society-american-foresters-annual-winter-meeting.asp
Publications
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