Results for “vegetable conservation” — Page 2

NASA NTRS2020

Africa Food Security & Agriculture: Predicting the Likelihood of Human-elephant Conflict and Assessing Elephant Habitat Conditions During Extreme Drought and Crop Deficit in the Kavango-Zambezi Area

Human-wildlife conflict is increasingly more common due to human population growth, habitat fragmentation, and changing climatic conditions. This conflict is particularly evident in the Kavango-Zambezi area, where over three million people share the landscape with an abundant megafauna population. As the changing climate continues to exacerbate drought severity and subsequent food availability, conflict between humans and wildlife has become more prevalent. In the Kavango-Zambezi area, conflict between elephants and humans has resulted in crop loss, property damage, and threats to public safety. In order to manage current and future conflict, The Ecoexist Project and Connected Conservation have been working to empower farmers and conserve the natural habitat. This DEVELOP project employed Earth observations to conduct a time series analysis of vegetation health change, elephant movement, and climate conditions, from 2017 to 2020. Data were aggregated into the wet (November through April) and dry (May through October) seasons. The resulting analysis demonstrated the potential to use Landsat 8 Operational Land Imager (OLI), Global Precipitation Measurement’s Integrated Multi-satellite Retrievals for GPM (GPM IMERG), and TerraClimate data to identify potential areas of conflict under increased seasonal variability. An improved understanding of conflict drivers will help support sustainable wildlife conservation and food security in the future.

DEVELOP Project Summary↗

NASA NTRS2020

Africa Food Security & Agriculture: Predicting the Likelihood of Human-elephant Conflict and Assessing Elephant Habitat Conditions During Extreme Drought and Crop Deficit in the Kavango-Zambezi Area

Human-wildlife conflict is increasingly more common due to human population growth, habitat fragmentation, and changing climatic conditions. This conflict is particularly evident in the Kavango-Zambezi area, where over three million people share the landscape with an abundant megafauna population. As the changing climate continues to exacerbate drought severity and subsequent food availability, conflict between humans and wildlife has become more prevalent. In the Kavango-Zambezi area, conflict between elephants and humans has resulted in crop loss, property damage, and threats to public safety. In order to manage current and future conflict, The Ecoexist Project and Connected Conservation have been working to empower farmers and conserve the natural habitat. This DEVELOP project employed Earth observations to conduct a time series analysis of vegetation health change, elephant movement, and climate conditions, from 2017 to 2020. Data were aggregated into the wet (November through April) and dry (May through October) seasons. The resulting analysis demonstrated the potential to use Landsat 8 Operational Land Imager (OLI), Global Precipitation Measurement’s Integrated Multi-satellite Retrievals for GPM (GPM IMERG), and TerraClimate data to identify potential areas of conflict under increased seasonal variability. An improved understanding of conflict drivers will help support sustainable wildlife conservation and food security in the future.

DEVELOP Tech Paper↗

NASA NTRS2022

Changes in Land Use Enhance the Sensitivity of Tropical Ecosystems to Fire-Climate Extremes

The Pantanal, the largest contiguous wetland in the world with a high diversity of ecosystems and habitat for several endangered species, was impacted by record-breaking wildfires in 2020. In this study, we integrate satellite and modeling data that enable exploration of natural and human contributing factors to the unprecedented 2020 fires. We demonstrate that the fires were fueled by an exceptional multi-year drought, but dry conditions solely could not explain the spatial patterns of burning. Our analysis reveals how human-caused fires exacerbated drought effects on natural ecosystem within the Pantanal, with large burned fractions primarily over natural (52%), and low cattle density areas (44%) in 2020. The post-fire ecosystem and hydrology changes also had strong ecological effects, with vegetation productivity less than − 1.5 σ over more than 30% of the natural and conservation areas. In contrast to more managed areas, there was a clear decrease in evaporation (by ~ 9%) and an increase in runoff (by ~ 5%) over the natural areas, with long-term impacts on ecosystem recovery and fire risk. This study provides the first tropical evidence outside rainforests of the synergy between climate, land management and fires, and the associated impacts on the ecosystem and hydrology over the largest contiguous wetlands in the world.

Sujay Kumar↗

NASA NTRSDate not supplied

Relating Land Cover Change to Runoff Distribution Using NASA Earth Observations in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for CN values specific to various land and crop cover types and account for various farming best practices but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and it captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geologic Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

Ella Griffith↗

NASA NTRS1992

Soil conservation applications with C-band SAR

Soil conservation programs are becoming more important as the growing human population exerts greater pressure on this non-renewable resource. Indeed, soil degradation affects approximately 10 percent of Canada's agricultural land with an estimated loss of 6,000 hectares of topsoil annually from Ontario farmland alone. Soil loss not only affects agricultural productivity but also decreases water quality and can lead to siltation problems. Thus, there is a growing demand for soil conservation programs and a need to develop an effective monitoring system. Topography and soil type information can easily be handled within a geographic information system (GIS). Information about vegetative cover type and surface roughness, which both experience considerable temporal change, can be obtained from remote sensing techniques. For further development of the technology to produce an operational soil conservation monitoring system, an experiment was conducted in Oxford County, Ontario which investigated the separability of fall surface cover type using C-band Synthetic Aperture Radar (SAR) data.

Brisco, B.↗

NASA NTRS2020

Lower Omo Food Security & Agriculture: Mapping Land Cover Change in Unprotected and Protected Areas in the Lower Omo River Valley, Ethiopia

Ethiopia is home to unique wildlife, biodiversity, and ecosystem services and, like much of the world, is undergoing population growth, development, and land use change. As a result, some biodiverse regions may be at risk of being urbanized, cultivated as agricultural plots, or losing access to water bodies that are essential for maintaining both terrestrial and aquatic life. The DEVELOP team partnered with the Ethiopian Wildlife Conservation Authority to quantify the land cover change between the years 1994, 2010, and 2018. The team utilized Ethiopia’s dry season (January to May) for training point development which was crucial in differentiating the level of greenness between the four land cover classes: water, natural vegetation, cultivated land, and bare ground. The study area covered 62,000 sq.km of the Lower Omo River Valley and includes eight protected areas. We used Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Shuttle Radar Topography Mission imagery within Google Earth Engine to employ a Random Forest Classifier and identify these four distinct classes. For each of our supervised classifications, overall model accuracy was between 83% (2018) and 89% (1994). Between 1994 and 2018, the Lower Omo Valley experienced an overall increase of 258.57% in water bodies and 291.23% in cultivated areas, while experiencing an 8.91% decrease in natural vegetation and 18.76% bare ground. There was an increase in water bodies and cultivated land and a decrease in natural vegetation and bare ground in unprotected areas and all protected areas. However, protected areas disproportionately experienced an increase in land cover change, including Tama Community Conservation Area which saw a 17,272.33% increase between 1994 and 2018.

Food Security & Agriculture↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila National Forest (Gila NF), wildfire events have occurred with increasing frequency and severity over recent years. These disturbances, such as the historic Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), have raised concerns over post-fire flooding, debris flows, and vegetation recovery. Understanding connections between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure conservation of the watershed. The Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project provided insight into the influence of wildfires on increased flooding events and determined if restoration efforts in the Gila NF are having a beneficial impact on vegetation regeneration. To understand recovery trends and hydrologic impact in the Gila NF between 2000-2019, this project used Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Global Precipitation Measurement Integrated Multi-satellite Retrievals for GPM precipitation, along with ancillary data from USGS stream gauges and data provided by USDA USFS’s Gila National Forest and Region 3. Based on these data, the team identified burn areas that received restorative treatments and compared Normalized Burn Ratio for different land cover types to better inform land management decisions. Additionally, the team analyzed the relationship between precipitation and streamflow from stream gauges to investigate the impact wildfires have on hydrology within the watershed.

Water Resources↗

NASA NTRS2022

Bryce Canyon Water Resources: Monitoring Vegetation Health and Water Availability in Bryce Canyon National Park for Drought Stress Mitigation Planning

Bryce Canyon National Park is home to groundwater-dependent ecosystems (GDEs) that are threatened by a multidecadal drought and increased groundwater extraction due to a spike in tourism. These ecosystems contain unique species that are only found in areas where near-surface groundwater is present, such as aspen groves and fens. These species contribute to the high biodiversity found in Bryce Canyon, which boosts an ecosystem’s productivity and the services it provides to the park. Unfortunately, many of these GDEs are too small to identify with traditional Earth observation platforms and are difficult to physically reach for monitoring purposes. This project partnered with the National Park Service to identify springs and seeps as a proxy for GDEs within Bryce Canyon from 2013–2022. Furthermore, this project tested the feasibility of various methods to detect and monitor springs and seeps and therefore facilitate the partner’s efforts to conserve these ecologically valuable GDEs in Bryce Canyon. The team mapped groundwater discharge with high resolution National Agriculture Imagery Program (NAIP) and assessed park vegetation trends with Landsat 8 Operational Land Imager (OLI) and PlanetScope imagery. In-situ precipitation data and the Western Land Data Assimilation System (WLDAS) were used to produce time series of climatic variables. Seeps and spring locations were predicted using random forest classification and maximum entropy machine learning models.

Groundwater dependent ecosystems↗

NASA NTRSDate not supplied

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves Response To Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Samuel Perrello↗

NASA NTRS2022

Florida Water Resources: Assessing Coastal Resiliency Across Florida's Aquatic Preserves in Response to Hurricane Forces

Intensifying weather events, sea level rise, and extensive coastal development in Southwestern Florida are escalating the need for Florida’s mangrove conservation. These mangroves are imperative for coastline stabilization, habitat provision for native species, and water quality management. Our partner, the Florida Department of Environmental Protection (FDEP), Office of Resilience and Coastal Protection is tasked with monitoring and conserving the Charlotte Harbor, Estero Bay, Rookery Bay, and Pinellas County Aquatic Preserves. We developed the Growth, Resilience, and Optical Vegetation Evaluator (GROVE) Google Earth Engine toolset for partners to determine mangrove forest extent through time, analyze mangrove forest health, and collect several water quality parameters within the preserves from January 2002–August 2022. The toolset provides easily accessible data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 Operational Land Imager 2 (OLI-2), and the Shuttle Radar Topography Mission (SRTM). Using training datasets of known mangrove forest locations, we also established a machine learning approach to create mangrove extent maps. Maps from all four preserves indicated migration of mangrove forests inland as the greatest areas of change were transitional zones. Additionally, normalized difference vegetation index (NDVI), normalized difference turbidity index (NDTI), and chlorophyll-a maps were generated for the partners. This project provides decision makers with a useful tool for understanding temporal changes in Florida’s aquatic preserves, identifying areas of ecological stress, and providing actionable data to make informed plans for mangrove preservation.

Remote sensing↗

NASA NTRS2023

Southern Idaho Ecological Conservation: Investigating the Impact of Targeted Grazing to Improve Wetland Habitat in the Sterling Wildlife Management Area

Wetland ecosystems are vital for biodiversity conservation and ecosystem services. The Sterling Wildlife Management Area in Bingham County, Idaho, has management concerns about decadent and accumulated vegetation growth encroaching on wetland habitat, which presents challenges for wildlife, decreases biodiversity, and limits public access. Targeted grazing has been proposed as a sustainable alternative to chemical herbicides or burning. Land managers introduced targeted cattle grazing in January 2021 to reduce biomass. NASA DEVELOP partnered with the Idaho Department of Fish and Game to determine the impact of grazing using NASA Earth observations from Landsat 8 Operational Land Imager (OLI) in Google Earth Engine (GEE). Images were processed with TerrSet’s Land Change Modeler and ArcGIS Pro’s Change Detection Wizard to understand land changes following grazing. A Normalized Difference Vegetation Index (NDVI) analysis was performed to assess impacts on vegetation productivity and compare variance in biomass before and after grazing. A Normalized Difference Water Index (NDWI) was used to compare changes in the wetland and its vegetation content to evaluate the suitability of the area for migratory birds post-grazing. Results showed a decrease in the vegetation index and an increase in the water index postgrazing. The DEVELOP team’s analysis suggests that grazing helps break down thick, senesced vegetation and increase soil moisture. Providing a workflow model will aid partners in continuing to monitor this management area and other management areas across the state.

change detection↗

NASA NTRS1990

Investigation of biogeophysical feedback on the African climate using a two-dimensional model

A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.

Xue, Yongkang↗

NASA NTRS1990

Waterbird use of coastal impoundments and management implications in east-central Florida

Monthly surveys were conducted on Kennedy Space Center for one year to determine densities of waterbirds within impounded salt marshes that were predominantly open water with little emergent vegetation. The objective was to assess the importance of these impoundments to waterbirds, particularly wading birds, which are species of special conservation concern. Water-level management for mosquito control and waterfowl provided habitat for an abundance of ducks, shorebirds, coots, and wading birds. Average densities throughout the year for these groups were 5.26, 412, 2.80, and 2.20 birds/ha, respectively. The majority of waterfowl were present during the winter. Shorebirds were most common during spring migration. Wading bird densities increased with declining water level. Due to the extensive alteration and development of coastal wetlands in central Florida, properly managed impoundments may provide important feeding areas for maintaining certain waterbird populations.

Breininger, David R.↗

NASA NTRSDate not supplied

Utilizing Earth Observations to Understand Landscape Patterns and Assist in Wildlife Management in Iona National Park, Angola

Following the end of the Angolan Civil War (1975-2002), human habitation in Iona National Park has grown exponentially, as has the livestock population. An ongoing drought beginning in 2017 has brought people, livestock, and wildlife into increasing competition for resources within the park. This study used Earth observation data, primarily Landsat and Sentinel imagery, to examine landscape trends to improve wildlife preservation approaches in Iona National Park, Angola. In collaboration with the NGO African Parks, we developed a robust land use and land cover (LULC) classification model using remote sensing data to augment sparse ground-based data in this arid land region. We used Google Earth Engine and a random forest classifier to map vegetation types, water bodies, and potential wildlife habitats. This analysis resulted in a high spatial resolution LULC time-series between 1984-2023, highlighting critical periods of socioecological change over the past 40 years. These results increased the partner’s ability to make scientifically grounded decisions about resource allocation and conservation priorities. This analysis supports the feasibility of applying remote sensing techniques coupled with machine learning models in dry regions, where standard survey methods are frequently limited by accessibility and resource availability. However, we identified limitations in ground-truth data and the difficulty of recognizing certain vegetation types in arid areas. Despite these limitations, the study demonstrated Earth observations' ability to transform wildlife management techniques in distant and data-scarce locations, providing a reproducible foundation for similar ecosystems around the world.

Emmanuel Aklie↗

NASA NTRS1974

ERTS-1 flood hazard studies in the Mississippi River Basin

The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicate that ERTS-1 is extremely useful as a regional tool for flood and floodplain management. The maximum error of such flood area measurements is conservatively estimated to be less than five percent. Change detection analysis indicates that the flood had major impacts on soil moisture, land pattern stability, and vegetation stress. Flood hazard identification was conducted using photointerpretation techniques in three study areas along the Mississippi River using pre-flood ERTS-1 imagery down to 1:100,000 scale. Flood prone area boundaries obtained from ERTS-1 were generally in agreement with flood hazard maps produced by the U.S. Army Corps of Engineers and the U.S. Geological Survey although the latter are somewhat more detailed because of their larger scale. Initial results indicate that ERTS-1 digital mapping of the flood-prone areas can be performed at least 1:62,500 which is comparable to conventional flood hazard map scales.

Rango, A.↗

NASA NTRS1982

Influence of land-surface evapotranspiration on the earth's climate

Land-surface evapotranspiration is shown to strongly influence global fields of rainfall, temperature and motion by calculations using a numerical model of the atmosphere, confirming the general belief in the importance of evapotranspiration-producing surface vegetation for the earth's climate. The current version of the Goddard Laboratory atmospheric general circulation model is used in the present experiment, in which conservation equations for mass, momentum, moisture and energy are expressed in finite-difference form for a spherical grid to calculate (1) surface pressure field evolution, and (2) the wind, temperature, and water vapor fields at nine levels between the surface and a 20 km height.

Shukla, J.↗

NASA NTRS2020

Gila Water Resources II: Using Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires have the potential to cause devastating and long-lasting impacts on ecological systems. In the Gila NF, wildfire events have occurred with increasing frequency and severity over recent years. These disturbances such as the historic Whitewater-Baldy Complex Fire (2012) and Silver Fire (2013) have raised concerns over post-fire soil erosion, flooding, debris flows, and vegetation recovery. Understanding the connection between burn events and ecological functions is crucial for developing effective land management practices within the Gila NF that ensure the conservation of the watershed. Our Gila Water Resources II team worked in partnership with the US Department of Agriculture (USDA) US Forest Service’s (USFS) Gila National Forest and Region 3. This project was designed to provide insight into the influence of wildfires on increased flooding events and to determine if restoration efforts in the Gila NF are having a beneficial and noticeable impact on recovery. The goals of this project included generating data-supported end products to inform land management decisions, including the prioritization of specific regions and time scales for post-fire restoration efforts. To understand recovery trends and hydrologic impact in the Gila NF between 2000 and 2020, this project used NASA EO and ancillary data, including, but not limited to, Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), USGS stream gauge data, and data provided by USDA USFS’s Gila National Forest and Region 3.

Water Resources↗

NASA NTRS2025

Nevada Wildland Fires: Mapping Historical Burned Areas and Identifying Drivers of Fuel Load Growth to Inform Desert Tortoise Habitat Management in Southern Nevada

Wildfire frequency and intensity in the Mojave desert are increasing, driven by invasive grasses that outcompete native vegetation not well-adapted to wildfire. These grasses, primarily cheatgrass (Bromus tectorum) and red brome (Bromus rubens), and the wildfires that occur when the grasses ignite, are a serious threat to the critically endangered Mojave desert tortoise (Gopherus agassizii). Declining Mojave desert tortoise populations are of great concern to project partners, the Bureau of Land Management Southern Nevada District Office, the US Forest Service’s Rocky Mountain Research Station, and the US Department of Agriculture Agricultural Research Service’s Arid Lands Ecology Lab, who currently lack the resources for fire recovery studies essential for informed fire and invasive grass management. To address this gap, the team utilized NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI), to analyze trends in burned areas over the past 20 years through historic burn maps and to examine fuel load growth drivers, with a focus on invasive vegetation. These historical burn maps revealed a pattern of precipitation anomalies that strongly correlate with higher Normalized Difference Vegetation Index (NDVI) values. Years with significant precipitation and NDVI spikes led to greater fuel load in the dry season and larger burns. Additionally, El Niño years correlated significantly with precipitation anomalies which may provide our partners with insights into burn trends and enable better allocation of fuel load treatment practices. However, while identifying drivers of fuel load growth proved feasible, a lack of in situ data hindered attempts to analyze pre-fire growth of invasive grasses compared with native grasses. Despite this limitation, the project demonstrated the feasibility of using Earth observations for wildfire and habitat management, ultimately benefiting conservation efforts for the Mojave desert tortoise.

fuel load↗