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Item type:Publication, Improved SMAP soil moisture retrieval using a deep neural network-based replacement of radiative transfer and roughness model(Institute of Electrical and Electronics Engineers Inc., 2024-01-01)The L-band (1.4 GHz) brightness temperature (TB) is interpreted by the zeroth-order approximation of the radiation transfer model, known as the τ-ω model. The soil moisture active passive (SMAP) mission facilitates the operational retrieval of global soil moisture (SM) through the τ-ω model. The operational SMAP SM retrieval algorithms demonstrate favorable alignment with the International SM Network (ISMN) and the SMAP core validation sites (CVSs). Nevertheless, the performance of these retrieval algorithms is reduced in densely vegetated areas or on rough surfaces, due to the smaller sensitivity of L-band TB to SM and less optimized parameterization. Therefore, this study proposed a deep neural network (DNN) model that can replace the currently used algorithms. The complex dielectric constant was simulated using ISMN data with the dielectric model to directly train DNN and determine the relationship between measured TB and retrieved dielectric constant. This involved establishing a correlation between the measured V- and H-polarized TB and the parameters from the SMAP SCA, i.e., surface temperature, vegetation water content (VWC), b, ω, and h. The challenge posed by the scale mismatch between point-based and SM data was effectively managed using the triple collocation analysis (TCA). The accuracy of the proposed model was evaluated using the ISMN and SMAP CVS and compared with the existing SM retrievals such as SCA-V, DCA, SMAP-IB, and the recently developed MCCA. The developed SM in this study demonstrated enhanced agreement with ISMN, SMAP CVS in situ SM data, and the Tambopata site located in the Amazon compared with existing SM retrievals. Moreover, by inversely tracking the developed DNN, we propose a novel method for parameterizing the τ-ω model that potentially improves the parameterization of the existing SMAP-based SM retrieval algorithms. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Peru’s zoning amendment endangers forests(American Association for the Advancement of Science, 2024-03-01)Article MetricsDownloadsCitationsNo data available.02040608003 Mar 202410 Mar 202417 Mar 202424 Mar 20246520TotalFirst 30 Days6 Months12 MonthsTotal number of downloads for the first 30 days after content publication - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing Peru’s land monitoring system contributions towards fulfilment of its international environmental commitments(Multidisciplinary Digital Publishing Institute (MDPI), 2024-02-01)Land use change (LUC) is recognized as one of the major drivers of the global loss of biodiversity and represents a major threat to ecosystems. Deforestation through LUC is mainly driven by fire regimes, logging, farming (cropping and ranching), and illegal mining, which are closely linked with environmental management policies. Efficient land management strategies, however, require reliable and robust information. Land monitoring is one such approach that can provide critical information to coordinate policymaking at the global, regional, and local scales, and enable a programmed implementation of shared commitments under the Rio Conventions: the United Nations Convention on Biological Diversity (CBD), Convention to Combat Desertification (UNCCD), and Framework Convention on Climate Change (UNFCCC). Here we use Peru as a case study to evaluate how a land monitoring system enables environmental policy decisions which appear in the country’s international commitment reports. Specifically, we synthesize how effective the ongoing land monitoring system has been in responding to current and future environmental challenges; and how improvements in land monitoring can assist in the achievement of national commitments under the Rio Conventions. We find that Peruvian policies and commitments need to be improved to be consistent with the 1.5 °C temperature limit of the Paris agreement. Regarding the Aichi targets, Peru has achieved 17% land area with sustainable management; however, the funding deficit is a great challenge. Even though Peru commits to reducing GHG emissions by reducing LUC and improving agricultural and land use forestry practices, it needs policy improvements in relation to land tenure, governance, and equity. Potential explanations for the observed shortcomings include the fragmentation and duplication of government roles across sectors at both a national and regional scale. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evapotranspiration, carbon dynamics and water use efficiency in a drip-irrigated olive orchard in arid coastal western South America(Elsevier B.V., 2024-05-31)The primary climatic characteristic of olive cultivation in Peru is the coastal desert environment with moderate temperatures, minimal precipitation, and high atmospheric water content during the winter season. This report presents a comprehensive study on water and carbon fluxes in a drip-irrigated olive orchard in Pisco Province, Peru, addressing the current lack of information on olive physiology and water management under these environmental conditions. The eddy covariance system installed in September 2019 showed an average ET of 2.18 ± 0.38 mm d−1, with seasonal variation. Drip irrigation was set at 60 m3 ha−1 d−1 during the growing season and reduced to half that amount in the winter. The study suggests that using deficit irrigation based on affordable dendrometry sensors could reduce water use by close to 30% while potentially preserving biomass gain and fruit yields. This could help improve water management in olive cultivation in coastal Peru. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Calibration of the SMAP soil moisture retrieval algorithm to reduce bias over the Amazon rainforest(Institute of Electrical and Electronics Engineers Inc., 2024-01-01)Soil moisture (SM) is crucial for the Earth's ecosystem, impacting climate and vegetation health. Obtaining in situ observations of SM is labor-intensive and complex, particularly in remote and densely vegetated regions like the Amazon rainforest. NASA's soil moisture active and passive (SMAP) mission, utilizing an L-band radiometer, aims to monitor global SM. While it has been validated in areas with low vegetation water content (VWC) (< 5 {text{kgm}}{ - 2}), its efficiency in the Amazon, with dense canopies and high VWC (> 10 {text{kgm}}{ - 2}), is limitedly investigated due to scarce in situ measurements. This study assessed and analyzed the SMAP SM retrievals in the Amazon, employing the single-channel algorithm and adjusting vegetation optical depth (τ) and single scattering albedo (ω), two key vegetation parameters. It incorporated in situ SM observations from three old-growth rainforest locations: Tambopata (Southwest Amazon), Manaus (Central Amazon), and Caxiuana (Eastern Amazon). The SMAP SM deviated substantially from the in situ SM. However, calibrating τ and ω values, characterized by a lower τ, resulted in better agreement with the in situ measurements. This study emphasizes the pressing need for innovative methodologies to accurately retrieve SM in high-VWC regions like the Amazon rainforest using SMAP data.1