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Robert Griffin

Publications and source records attributed to Robert Griffin.

Perspectives on flood forecast-based early action and opportunities for Earth observations

This paper seeks to identify opportunities to integrate Earth observations (EO) into flood forecast-based early action and propose future directions for research and collaboration between EO and humanitarian communities. Forecast-based early action (FbA) is an approach to shift disaster response toward anticipation to mitigate impacts to at-risk communities; however, timely and accurate information is needed in the development of data-based triggers and thresholds for action. Therefore, this paper considers the readiness of a wide range of EO for flood monitoring and forecasting in the design, operations, and evaluation phases of FbA. The most significant opportunities for EO to inform FbA efforts lie in the design and evaluation phases, as EO can aid in the development of impact-based triggers. The EO products most readily applicable include precipitation, streamflow estimates, and exposure mapping, and those requiring the greatest amount of further research include vulnerability and impact assessments. This paper identifies collaboration opportunities for the EO and humanitarian communities to create tailored products, such as overlays combining flood extents with exposure maps. Such collaboration opportunities can be fostered by open data sharing, data verification efforts, and incentives for supporting boundary organizations capable of enabling the use of EO for FbA.

disasters↗

Identifying Optimal Site Location for Wind Energy Farms Considering Ecological and Social Impacts

With the increasing cost and declining availability of fossil fuels, renewable energy, specifically wind power, has become one of the fastest growing sources of energy in New Mexico. To assist with the goals set by the state’s Renewables Standard Portfolio established in 2004, the NASA DEVELOP team created three Optimal Wind Farm Suitability maps that consider social impact, ecological impact, and power production efficiency. The team utilized datasets from February 2013 – May 2018 that show vulnerable species, average wind patterns, and US Air Force Base locations. These three maps were combined into a final suitability map for optimal wind farm placement.

Joy Marich↗

Developing a Customized Composite Drought Index for Pakistan

This study aims to identify historical agricultural droughts between 2004-2019 using 10 geophysical variables (Table 1) and determine what variables have little importance in this identification. Satellite data products or model outputs are used for all input variables. Understanding the interactions between the data will provide information on temporal and spatial patterns of how drought is presented in irrigated and rainfed areas (Fig. 2). This knowledge will assist in creating a Customized Composite Drought Index in future work

Drought↗

Assessing the Feasibility of using PlanetScope Data for Air Quality Applications

Planet is a commercial company known for having one of the largest operational smallsat satellite constellations. This constellation comprises over 120 3U CubeSats called Doves (equipped with a sensor called PlanetScope), which combined, are able to image the entire Earth’s surface daily at a high 3-meter spatial resolution. With Planet data becoming more readily available to scientists due to NASA’s Commercial Smallsat Data Acquisition Program (CSDAP), this study investigates the feasibility of utilizing Planet data to conduct scientific analyses with an emphasis on air quality research. This study offers a comparison of PlanetScope data with MODIS over a variety of land cover types, as well as in response to varying PM2.5 conditions. It also investigates the feasibility of utilizing PlanetScope data for estimating PM2.5 concentrations using deep learning

Jeanne Le Roux↗

Developing a Customizable Composite Drought Index for Pakistan

Pakistan has experienced intense agricultural droughts in recent years, with the southern provinces experiencing the most severe drought conditions. These prolonged dry conditions often result in failed crop production, impacting families and communities. To reduce the impacts a drought may have on a community by identifying dry conditions, drought indices are used. A customizable composite drought index (CDI) is developed to improve the spatial and temporal understanding of historical agricultural droughts that have affected Pakistan. An in depth analysis using 9 input variables will provide information regarding the most important variables for differing locations. This framework can enhance drought monitoring and forecasting systems. The performance of the CDI will be evaluated by using production data from different crops that have significant economic value in Pakistan. These crops include wheat, rice, maize, cotton and barley. The expected relationship between the CDI and crop production would be to see production decrease when the CDI decreases, an indication that crops failed due to drought. The CDI is made more precise by evaluating only agricultural areas using the months of the growing season for each specific crop. This will allow for a custom drought index to be developed based on crop type and geographic location that only uses the most important variables, while still capturing the full extent of historical drought.

Caily Schwartz↗

Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above ground biomass for greenhouse gas emissions reporting, and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) are applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

remote sensing↗

An Analysis of Fire Dynamics Inside and Outside Indigenous Territories and Protected Areas in a Brazilian Agricultural Frontier

Sustainable land management, including protected areas, is integral to conserving tropical ecosystems and reducing carbon emissions in the Brazilian Amazon. In disturbed Amazon landscapes fire is commonly used to clear land or old fields for agriculture or pastureland. Human-set fires are the most common driver of deforestation and carbon emissions in Amazonia. Evidence suggests that indigenous groups have also used fire for land management since Pre-Columbian times. However, when used unsustainably, fires in this biome can result in degradation of forest ecosystems, decreased ability to store carbon, and health impacts resulting from smoke and particulate matter. Due to the uptick in fire occurrences in 2019, more restrictions on fire use were implemented in 2019 and 2020. Presidential decrees 9.992/2019 and 10.424/2020 banned fire use completely for periods of 60 and 120 days respectively, except by indigenous communities or authorities. Despite these bans, fire use remained high in both years. In the state of Mato Grosso, agricultural activity and expansion influences the anthropogenic fire regime. Indigenous and protected areas cover approximately 25% of its land area.

remote sensing↗

Modeled Impacts of LULC and Climate Change Predictions on Water Quality in Belize

Land use and land cover (LULC) change can have detrimental effects on water quality. In Belize, agricultural expansion creates the risk of increased sediment load and excess nutrients in runoff water, while deforestation removes potential infiltration sites for this outflow. Climate change and evolving precipitation rates can intensify the quantity of runoff, further enabling the flow of sediments and excess nutrients out to the lagoon surrounding the Belize Barrier Reef Reserve System (BBRRS). This study estimated future water quality in Belize by projecting LULC change through 2090 across Belize’s major watersheds based on observed trends from 2008-2018. Those LULC projections were subsequently combined with soil type data, elevation, and precipitation rates into a hydrologic model to produce runoff estimates as a proxy for water quality. The two Coupled Model Intercomparison Project phase 6 (CMIP-6) scenarios employed in the study represented bookend climate change scenarios, and both predicted lower precipitation rates in Belize over the next century due to climate change. When holding LULC change constant, these climate scenarios projected a decrease in runoff, suggesting a positive relationship between precipitation and runoff. The southern watersheds in particular are projected to experience greater decreases in annual rainfall and runoff by 2090. When holding climate constant, runoff increased by approximately 2.8% in the Conservation-focused LULC scenario by 2090, which was 28% lower than the Business as Usual scenario and 42% lower than the Development scenario.

water resources↗

Co-developing a SAR for Disasters Reference Guide for the International Applications Community

Synthetic Aperture Radar (SAR) data are widely applicable for disaster monitoring, especially in Central and South America where atmospheric effects are a frequent obstacle for disaster monitoring. There is a growing interest in the application of SAR data to diverse disasters, ranging from landslides to volcanic eruptions and floods. With this interest comes a growing need for user-friendly guides that facilitate the integration of SAR into existing workflows. A joint effort between AmeriGEO, university networks in the Americas, NASA SERVIR’s Science Coordination Office (SCO), and the NASA Earth Science Disasters Program, culminated in the “SAR for Disasters” Guide. The guide is modeled after the one-page informational sheets created for SERVIR’s SAR Handbook, with the aim to succinctly communicate the key considerations needed to apply relevant analyses using SAR. Developed with contributors from diverse backgrounds, this guide is designed to be a useful reference for experienced technical users and beginners alike.

SAR↗

Implications of the Golden Age of Remote Sensing on Earth Observation Applications in Central America

Appraising the period spanning the launch of the first Landsat satellite in 1972 to the present, the common consensus within the Earth observation (EO) community is that we are currently living in a “Golden Age of Remote Sensing,” with access to datasets, tools, and capacity building opportunities hitherto unavailable (e.g. data from Landsat, the Copernicus program, Planet / NICFI, platforms such as Google Earth Engine and SEPAL, and trainings via NASA’s ARSET and Europe's EO College). With the inter-governmental Group on Earth Observations (GEO) focusing its efforts on helping regions across the world to develop their EO capacities, Central America serves as a useful case study on the development of such capacity, with important implications for other emerging regions. A significant chapter of the region’s development of its EO capacity can be traced to 1998 when a regional body - the Central American Commission for the Environment and Development (CCAD, in Spanish) - signed a Memorandum of Understanding with NASA, which eventually led to the development of the SERVIR-Mesoamerica program, also with the support of the U.S. Agency for International Development, in 2004. The establishment of the Reducing Emissions from Deforestation and forest Degradation (REDD+) initiative in 2007 in the context of the United Nations Framework Convention on Climate Change provided additional impetus for strengthening the region’s environmental monitoring capacities. REDD+ paved the way, over the past decade, for the region’s countries to benefit from cooperation with the Germany development agency, GIZ, and the United States’ SilvaCarbon initiative. By 2021, the CCAD’s parent body - the Central American Integration System (SICA, in Spanish) - had also entered into collaborations with not only NASA, but other entities, including the Copernicus program, the Japanese Aerospace Exploration Agency, and the United Nations Office for Outer Space Affairs, and the region is also engaging with GEO’s AmeriGEO regional initiative. Nevertheless, the aforementioned collaborative efforts only convey part of the case study regarding Central America’s EO capacity. This presentation will also examine applications aspects, as well as implications for the development of EO capacity in other regions, including via regional GEO initiatives.

Earth observation↗

SERVIR: Cross-Comparison of Carbon Emission Estimates Based on Variable Land Use Land Cover Changes within SERVIR Focus Regions

Deforestation in the tropics contributes approximately one-fifth of the annual global greenhouse gas (GHG) emissions. In an effort to reduce GHG emissions, SERVIR - a joint USAID and NASA initiative - is currently implementing the SERVIR CArbon Pilot (S-CAP) activity. By developing a comprehensive CO2 tracking system in Google Earth Engine based on both remotely sensed data and in situ observations, S-CAP aims to build capacity within the SERVIR regional hubs to improve decision making and local monitoring efforts surrounding GHG emissions. The S-CAP estimations are being completed throughout 11 pilot countries within the SERVIR regions of Asia, Africa, and the Americas to integrate partner contributions and local input into the development process. These emission estimate calculations use country-level REDD+ FREL reported values, global remotely sensed data (e.g. Global Forest Watch) and regional datasets and are completed using the IPCC Guidelines for National Greenhouse Gas Inventories. From the S-CAP activity thus far, country CO2 estimations had varied differences, ranging from 56% to 197% between their lowest and highest estimates. The results from this study show that CO2 emission estimates can differ greatly depending on the land cover data sets used as well as the biomass values, and how a comprehensive database is essential in understanding the full range of impacts that land cover change has in these regions. Using this ensemble approach, SERVIR hubs can better select the most appropriate datasets available for estimating emissions.

Carbon Emission↗