Magdeline Laba

SAV Mapping

Since 1995, Cornell researchers have worked in collaboration with the Hudson River National Estuarine Research Reserve and the Hudson River Estuary Program to inventory and map submerged aquatic vegetation (SAV) as part of a long-term effort to monitor SAV in the Hudson River. The first comprehensive inventory, conducted in 1995, documented SAV and Trapa natans (water chestnut) along what is now referred to as the river’s main stem. Subsequent inventories in 2007, 2014, 2016, 2018, and 2022 expanded the study area to include coves and major tributaries and utilized advanced aerial remote sensing techniques to map SAV distribution and extent.

The SAV mapping area extends from Troy to Hastings-on-Hudson and includes nine major tributaries: Rondout Creek, Catskill Creek, Esopus Creek, Annsville Creek, Croton River, Stockport Creek, Moodna Creek, Fishkill Creek, and Wappinger Creek. Each inventory has mapped the presence and extent of SAV and Trapa natans. In past reports and associated documentation, the term SAV mainly represents Vallisneria americana (water celery) and Myriophyllum spicatum (water milfoil), which comprise approximately 90 percent of the SAV community.

The objectives of the SAV mapping program are to: (1) document the presence and spatial extent of SAV and Trapa natans using digital aerial imagery; (2) identify spatial and temporal changes in SAV distribution among inventory years; and (3) conduct river-wide accuracy assessments to evaluate mapping performance. Long-term monitoring has demonstrated that SAV beds may disappear and reestablish over time, likely in response to a combination of environmental and anthropogenic factors. Documented SAV habitat therefore warrants stringent protection by resource managers and regulatory agencies.

• Data products and associated documentation are available through the New York State Clearinghouse.

Ecosystem Services

The effects of Hurricane Sandy storm surge on wetland degradation and consequent loss of ecosystem services were estimated for coastal wetlands in New Jersey. Research in this field has qualitatively determined the effects of hurricanes on wetlands; however, there has been little quantification of wetland degradation and absolutely no assessment of impact to ecosystem services following a hurricane. Wetland degradation was mapped and quantified by comparing pre- and post-Sandy aerial photography from 2012. Loss of ecosystem services was estimated based on the degree of wetland degradation. Our wetland degradation analysis found that the main mechanisms behind degradation were erosion, deposition and marsh salinization. Moderate flooding and marsh dieback were the most prevalent types of damage, and saline marshes and herbaceous wetlands were the most degraded wetland types. Severe degradation was most prevalent, occurring in 41.38% of the wetlands. In addition, we found that 51.05% of the degradation was long-term damage. In our ecosystem service loss analysis, we created a range of monetary values to show the distribution of damage. Monetary loss within New Jersey ranged up to $4.4 billion of the total $9.4 billion provided by wetlands (47%). Our wetland degradation quantification and ecosystem service loss analysis provide insight into the impacts from storm surge damage and offers a novel methodology for remediation and restoration efforts.

• Hauser, S., M. Meixler, M. Laba. 2015. Quantification of impacts and ecosystem service loss in New Jersey coastal wetlands due to Hurricane Sandy storm surge. Wetlands 25:1137-1148.

Soil Science

Soil Taxonomy and Pedology

As part of our lab group’s work on agricultural soil data, I contribute to the creation of datasets that support both agricultural assessment and renewable energy planning in New York State. One of these datasets aligns with the New York State Department of Agriculture and Markets (AGM) in implementing agricultural assessment values under Chapter 69, Article 25-AA, §304-a of the Agriculture & Markets Law. This law requires that agricultural assessment values be calculated and certified annually based on soil productivity and capability. The AGM maintains a detailed agricultural land classification system, distinguishing between mineral and organic soils, with ten primary mineral soil groups (and subgroups reflecting high-lime and low-lime content) and four organic soil groups. My work involves compiling and structuring soils information from multiple sources into a comprehensive, GIS-compatible dataset that enables the commissioner of taxation and finance to calculate agricultural assessment values accurately. This dataset provides transparency for landowners and local officials and supports informed decision-making regarding land use, conservation, and agricultural management.

Building on this expertise, our lab group also contributed to the creation of the NYSERDA 2024 Soils Dataset, which currently supports New York State’s Large-Scale Renewable Energy and NY-Sun programs. This dataset organizes soils classified by AGM and links each soil type to the Natural Resources Conservation Service (NRCS) SSURGO soils database, allowing geographic mapping and integration with GIS tools. While it does not represent in situ soil conditions, the dataset serves as a critical planning tool for solar developers to minimize impacts on highly productive agricultural soils, specifically Mineral Soil Groups 1–4 (MSG 1–4). 

Both datasets integrate information from multiple sources to create standardized, usable tools for policy, planning, and land management. The AGM dataset ensures accurate calculation of agricultural assessment values statewide, while the NYSERDA soils dataset informs renewable energy siting decisions and encourages the preservation of New York’s agricultural productivity. Through these projects, our lab group has helped provide critical data infrastructure that bridges environmental science, agriculture, and renewable energy development.

Proximal Sensing of Soils

In recent years, advances in spectral sensing technology have generated growing interest among soil scientists. These systems offer new opportunities to measure soil properties using proximal sensors for precision agriculture, as well as through remote sensing approaches. A key challenge, however, is that soils in the field differ significantly from the prepared samples typically analyzed in laboratories. Field soils are often moist and have uneven surfaces, particularly after tillage, which can affect how they reflect electromagnetic radiation. We are interestedin examining how surface roughness, soil moisture, particle size, and pore structure influence the relationship between soil properties and their spectral responses.

Publications

• Baveye, P. and M. Laba. 2016. Comment on “Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: A prospective review” by Horta et al. Geoderma 271: 254-255.
• Baveye, P. and M. Laba. 2015. Visible and near-infrared reflectance spectroscopy is of limited practical use to monitor soil contamination by heavy metals. Journal of Hazardous Materials 285: 137-139.
• Wu, C.-Y., A. Jacobson, M. Laba, B. Kim, P. Baveye. 2010. Surrogate correlations and near-infrared diffuse reflectance sensing of trace metal content in soils. Water, Air & Soil Pollution 209(1-4): 337-390.
• Wu, C.-Y., A. Jacobson, M. Laba, P. Baveye. 2009. Accounting for surface roughness effects in the near-infrared reflectance sensing of soils. Geoderma 152(1/2): 171-180.
• Wu, C.-Y., A. Jacobson, M. Laba, P. Baveye. 2009. Alleviating moisture content effects on the near-infrared diffuse-reflectance sensing of soils. Soil Science 174(8): 456-465.

Wetlands Mapping

Wetlands are critical components of river and coastal systems, providing flood attenuation, water quality improvement, carbon storage, and habitat for a wide range of species. Our research has examined both the institutional frameworks that guide wetland protection in the United States and the ways tidal marsh communities along the Hudson River are responding to sea-level rise. Together, these studies emphasize the importance of informed policy, sound science, and adaptive management in sustaining wetland ecosystems under changing environmental conditions.

• Chen, X., M. Laba, M. Robertson, B Cosens, W. Ziyan, C. Xue, J. Anderson, M. Otte, C. Craft, D. Feldman, L. Jianguo, L. Yangfan, P. Sullivan, L. Xianguo. 2016. Study on US wetland protection institution change. Resources Science 38(4): 777-789.
• Tabak, N., M. Laba, S. Spector. 2016. Simulating the effects of sea level rise on the resilience and migration of tidal wetlands along the Hudson River. PLOS ONE, http://dx.doi.org/10.1371/journal.pone.0152437.

New York State Wetland Mapping

Because of their ecological and economic importance, wetlands in New York State have long been protected through a combination of federal, state, and local regulations. Prior to 2025, however, a wetland could only be regulated if it both met conservation criteria and appeared in the NYS Department of Environmental Conservation’s official wetland maps, meaning some wetlands that met protection standards could still go unrecognized. To address this gap, we collaborated with the NYSDEC to develop a new, statewide educational wetlands database. Using a novel three-part geospatial modeling approach that combines soils, hydrology, climate, land cover, and topography, the project identifies potential wetlands across New York’s diverse landscapes, from the Adirondacks to Long Island. Published in December 2024, this high-resolution dataset supports more informed conservation planning, education, and future regulatory decision-making.

Mapping Plant Communities in the Hudson River National Estuarine Research Reserve

In 2007 and 2018, in collaboration with the Hudson River National Estuarine Research Reserve and the Hudson River Estuary Program, we inventoried and mapped tidal wetlands along the Hudson River corridor from Troy to Hastings-on-Hudson, including major tributaries and coves. This reach of the river encompasses both estuarine wetlands and tidal freshwater wetlands. In the southern and middle reaches, estuarine wetlands consist of varying degrees of brackish-water environments, while tidal freshwater wetlands, characterized by predominantly freshwater conditions, occur primarily in the northern reach and within tributaries.

To support effective environmental management and protection, we developed comprehensive classification schemes that captured the diversity of tidal wetland plant communities at an appropriate spatial scale. The objectives of this mapping effort were to: (1) document the extent and vegetation community types of existing tidal wetlands, and (2) develop an index of potential impact areas to assist in the review of river development proposals.

• Laba, M., B. Blair, R. Downs, B. Monger, W Philpot, S. Smith, P. Sullivan, P. Baveye. 2010. Use of textural measurements to map invasive wetland plants in the Hudson River National Estuarine Research Reserve with Ikonos satellite imagery. Remote Sensing of the Environment 114(4): 876-886.
• Laba, M., R. Downs, S. Smith, S. Welsh, C. Neider, S. White, M. Richmond, W. Philpot, P. Baveye. 2010. Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using QuickBird satellite imagery. Remote Sensing of the Environment 112(1): 286-300.
• Laba, M., S. Smith, P. Sullivan, W. Philpot, P. Baveye. 2007. Influence of wavelet type on the classification of marsh vegetation from satellite imagery using a combination of wavelet texture and statistical component analyses. Canadian Journal of Remote Sensing 33(4): 260-265.
• Laba, M., F. Tsai, D. Ogurcak, S. Smith, M. Richmond. 2005. Field determination of optimal dates for the discrimination of invasive wetland plant species using derivative spectral analysis. Photogrammetric Engineering and Remote Sensing 71(5): 603-611.

Long Island Commission for Aquifer Protection

Long Island’s sole-source aquifer system, which serves over three million residents, is recharged primarily through local precipitation, making groundwater quality highly susceptible to surface land use. In coordination with the Long Island Commission on Aquifer Protection (LICAP) and the Suffolk County Water Authority (SCWA), this project modernized a landmark 1990 Cornell inventory by employing high-resolution remote sensing to identify contemporary threats to the water supply. By utilizing aerial imagery, the team developed a comprehensive GIS geodatabase to map 3,270 groundwater-relevant features, including unlined recharge basins vulnerable to PFAS and road salts, agricultural wells, and illegal disposal sites in sensitive areas such as the Pine Barrens. This systematic analysis, guided by monthly LICAP working group meetings and validated by a rigorous QA/QC protocol, achieved a 99% classification accuracy. The final findings, originally presented at the annual LICAP State of the Aquifer meeting, now provide a robust scientific foundation for regional agencies to prioritize monitoring, enforcement, and long-term resource management across the county.