Ibrahima sall

Dr. Ibrahima sall

The University of Arizona
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2014 in Ecology and Society
Verified
Journal Article
Open access
SHStefanie Herrmann
Stefanie Herrmann
ISIbrahima sall
Ibrahima sall
OSOumar Sy
Oumar Sy
Herrmann, S. M., I. Sall, and O. Sy. 2014. People and pixels in the Sahel: a study linking coarse-resolution remote sensing observations to land users? perceptions of their changing environment in Senegal. Ecology and Society 19(3): 29.http://dx.doi.org/10.5751/ES-06710-190329

1 February 2020 in Journal of Arid Environments
Verified
Journal Article
Closed access
SHStefanie Herrmann
Stefanie Herrmann
ADAbdoul Aziz Diouf
Abdoul Aziz Diouf
ISIbrahima sall
Ibrahima sall

10 July 2020 in Remote Sensing in Ecology and Conservation
Verified
Journal Article
Open access
PDF file
ISIbrahima sall
Ibrahima sall
CJChristopher J. Jarchow
Christopher J. Jarchow
BSBrent H. Sigafus
Brent H. Sigafus
LELisa A. Eby
Lisa A. Eby
MFMichael J. Forzley
Michael J. Forzley
BHBlake R. Hossack
Blake R. Hossack
Small waterbodies are numerically dominant in many landscapes and provide several important ecosystem services, but automated measurement of waterbodies smaller than a standard Landsat pixel (0.09 ha) remains challenging. To further evaluate sub‐Landsat pixel techniques for estimating inundation extent of small waterbodies (basin area: 0.06–1.79 ha), we used a partial spectral unmixing method with matched filtering applied to September 1985–2018 Landsat 5 and eight imagery from southern Arizona, USA. We estimated trends in modeled surface water area each September and evaluated the ability of several common drought indices to explain variation in mean water area. Our methods accurately classified waterbodies as dry or inundated (Landsat 5: 91.3%; Landsat 8: 98.9%) and modeled and digitized surface water areas were strongly correlated (R2 = 0.70–0.92; bias = −0.024 to −0.015 ha). Estimated surface water area was best explained by the 3‐month seasonal standardized precipitation index (SPI03; July‒September). We found a wide range of estimated relationships between drought indices (e.g. SPI vs. Palmer Drought Severity Index) and estimated water area, even for different durations of the same drought index (e.g. SPI01 vs. SPI12). Mean waterbody surface area decreased by ~14% from September 1985 to September 2018, which matches declines in local annual precipitation and regional trends of reduced inundation extent of larger waterbodies. These results emphasize the importance of understanding local systems when relying on drought indices to infer variation in past or future surface water dynamics. Several challenges remain before widespread application of sub‐pixel methods is feasible, but our results provide further evidence that partial spectral unmixing with matched filtering provides reliable measures of inundation extent of small waterbodies.

22 December 2022 in Remote Sensing
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Journal Article
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Pamela NaglerPamela Nagler
Pamela Nagler
ABArmando Barreto-Muñoz
Armando Barreto-Muñoz
ISIbrahima sall
Ibrahima sall
MLMatthew Lurtz
Matthew Lurtz
KDKamel Didan
Kamel Didan
Estimates of riparian vegetation water use are important for hydromorphological assessment, partitioning within human and natural environments, and informing environmental policy decisions. The objectives of this study were to calculate the actual evapotranspiration (ETa) (mm/day and mm/year) and derive riparian vegetation annual consumptive use (CU) in acre-feet (AF) for select riparian areas of the Little Colorado River watershed within the Navajo Nation, in northeastern Arizona, USA. This was accomplished by first estimating the riparian land cover area for trees and shrubs using a 2019 summer scene from National Agricultural Imagery Program (NAIP) (1 m resolution), and then fusing the riparian delineation with Landsat-8 OLI (30-m) to estimate ETa for 2014–2020. We used indirect remote sensing methods based on gridded weather data, Daymet (1 km) and PRISM (4 km), and Landsat measurements of vegetation activity using the two-band Enhanced Vegetation Index (EVI2). Estimates of potential ET were calculated using Blaney-Criddle. Riparian ETa was quantified using the Nagler ET(EVI2) approach. Using both vector and raster estimates of tree, shrub, and total riparian area, we produced the first CU measurements for this region. Our best estimate of annual CU is 36,983 AF with a range between 31,648–41,585 AF and refines earlier projections of 25,387–46,397 AF.

Verified
Journal Article
Open access
PDF file
ISIbrahima sall
Ibrahima sall
RTRussell Tronstad
Russell Tronstad
US crop insurance is subsidized to encourage producers to participate and reduce their risk exposure. However, what has been the impact of these subsidies on insurance demand and crop acres planted? Using a simultaneous system of two equations, we quantify both insurance participation and acreage response to subsidized crop insurance for cotton-producing counties across the US at the national and regional levels. We also quantify the impact of both the realized rate of return and the expected subsidy per pound, plus the combined effects of expected yield and price while accounting for the adoption of Bacillus thuringiensis (Bt) technology and other factors. Results show that both the rate of return and the expected subsidy per unit of production have a statistically significant and positive effect on the percentage of arable acres planted. Furthermore, the marginal effect of expected price on insurance participation is much more significant for low- than high-yield counties. Results indicate that not all regions respond the same to subsidized crop insurance and that subsidies should be based on dollars per expected unit of production rather than expected production to be less distorting. Overall, US cotton acreage response is estimated to be inelastic (0.58) to insurance participation.

18 May 2024 in Remote Sensing
Verified
Journal Article
Open access
PDF file
Pamela NaglerPamela Nagler
Pamela Nagler
ISIbrahima sall
Ibrahima sall
MGMartha Gomez-Sapiens
Martha Gomez-Sapiens
ABArmando Barreto-Muñoz
Armando Barreto-Muñoz
CJChristopher J. Jarchow
Christopher J. Jarchow
KDKamel Didan
Kamel Didan
Natural resource managers may utilize remotely sensed data to monitor vegetation within their decision-making frameworks for improving habitats. Under binational agreements between the United States and Mexico, seven reaches were targeted for riparian habitat enhancement. Monitoring was carried out using Landsat 8 16-day intervals of the two-band enhanced vegetation index 2 (EVI2) for greenness and actual evapotranspiration (ETa). In-channel water was delivered in 2021 and 2022 at four places in Reach 4. Three reaches (Reaches 4, 5 and 7) showed no discernable difference in EVI2 from reaches that did not receive in-channel water (Reaches 1, 2, 3 and 6). EVI2 in 2021 was higher than 2020 in all reaches except Reach 3, and EVI2 in 2022 was lower than 2021 in all reaches except Reach 7. ET(EVI2) was higher in 2020 than in 2021 and 2022 in all seven reaches; it was highest in Reach 4 (containing restoration sites) in all years. Excluding restoration sites, compared with 2020, unrestored reaches showed that EVI2 minimally increased in 2021 and 2022, while ET(EVI2) minimally decreased despite added water in 2021–2022. Difference maps comparing 2020 (no-flow year) to 2021 and 2022 (in-channel flows) reveal areas in Reaches 5 and 7 where the in-channel flows increased greenness and ET(EVI2).