Satellite Imagery to Map Topsoil Organic Carbon Content over Cultivated Areas: An Overview

There is a need to update soil maps and monitor soil organic carbon (SOC) in the upper horizons or plough layer for enabling decision support and land management, while complying with several policies, especially those favoring soil carbon storage. This review paper is dedicated to the satellite-based spectral approaches for SOC assessment that have been achieved from several satellite sensors, study scales and geographical contexts in the past decade. Most approaches relying on pure spectral models have been carried out since 2019 and have dealt with temperate croplands in Europe, China and North America at the scale of small regions, of some hundreds of km(2): dry combustion and wet oxidation were the analytical determination methods used for 50% and 35% of the satellite-derived SOC studies, for which measured topsoil SOC contents mainly referred to mineral soils, typically cambisols and luvisols and to a lesser extent, regosols, leptosols, stagnosols and chernozems, with annual cropping systems with a SOC value of similar to 15 g.kg(-1) and a range of 30 g.kg(-1) in median. Most satellite-derived SOC spectral prediction models used limited preprocessing and were based on bare soil pixel retrieval after Normalized Difference Vegetation Index (NDVI) thresholding. About one third of these models used partial least squares regression (PLSR), while another third used random forest (RF), and the remaining included machine learning methods such as support vector machine (SVM). We did not find any studies either on deep learning methods or on all-performance evaluations and uncertainty analysis of spatial model predictions. Nevertheless, the literature examined here identifies satellite-based spectral information, especially derived under bare soil conditions, as an interesting approach that deserves further investigations. Future research includes considering the simultaneous analysis of imagery acquired at several dates i.e., temporal mosaicking, testing the influence of possible disturbing factors and mitigating their effects fusing mixed models incorporating non-spectral ancillary information

Linking Multi-Year and Multi-Sensor Land Cover Data to Water Yield in the Nueces Headwaters Watershed of Texas

The stress on water resources is more critical in drylands due to ecological and climatological changes. Because upscaling the findings of paired-catchment studies to larger watersheds is difficult, hydrological models like the Soil and Water Assessment Tool (SWAT) were oftentimes used to investigate the impact of land use and land cover changes (LULC) on water yield. Such modeling studies first require the accurate estimates of LULC change using remote sensing images, which has been hindered by the presence of shadows in these images. Also, the data used in many previous modeling studies didn’t have the extent of variations in LULC and other variables including climatic conditions comparable to the simulation scenarios. The objectives of this study are to classify LULC types in the shadow areas of aerial images; to evaluate the complement between LULC data and ancillary data; to estimate LULC change; and to assess the impact of the LULC change on the water yield of the Nueces River Headwaters watershed using multi-year and multi-sensor LULC data and the SWAT model. More than 99% of the shadow area was identified with a 92.68% average accuracy. This outcome indicates that LULC types of shadow area on higher-resolution images can be classified successfully with a straightforward method incorporating the multi-sensor LULC classification schemes. The high accuracy of multi-year and multi-sensor LULC maps revealed the benefits of ancillary data use in remote sensing image classification. LULC change detection analysis was conducted using higher-resolution maps for precise quantification. There was at least an 8% reduction in juniper cover from 2008 to 2014 in the watershed. To account for variations in LULC, 2008, 2012 and 2016 maps were used to set up multiple SWAT models. Although satisfactory model performance statistics obtained from calibration, model performance was degraded for the validation period. This indicated that the model couldn’t sufficiently assess the variation in LULC and weather for a relatively brief period in the specific karst watershed. This study may be the first study conducted in a large karst watershed in the Edwards Plateau which accounted for the watershed-wide LULC changes for the entire modeling period

Geo-Spatial Analysis in Hydrology

Geo-spatial analysis has become an essential component of hydrological studies to process and examine geo-spatial data such as hydrological variables (e.g., precipitation and discharge) and basin characteristics (e.g., DEM and land use land cover). The advancement of the data acquisition technique helps accumulate geo-spatial data with more extensive spatial coverage than traditional in-situ observations. The development of geo-spatial analytic methods is beneficial for the processing and analysis of multi-source data in a more efficient and reliable way for a variety of research and practical issues in hydrology. This book is a collection of the articles of a published Special Issue Geo-Spatial Analysis in Hydrology in the journal ISPRS International Journal of Geo-Information. The topics of the articles range from the improvement of geo-spatial analytic methods to the applications of geo-spatial analysis in emerging hydrological issues. The results of these articles show that traditional hydrological/hydraulic models coupled with geo-spatial techniques are a way to make streamflow simulations more efficient and reliable for flood-related decision making. Geo-spatial analysis based on more advanced methods and data is a reliable resolution to obtain high-resolution information for hydrological studies at fine spatial scale

Teledetección. Nuevas plataformas y sensores aplicados a la gestión del agua, la agricultura y el medio ambiente

Este libro recoge las comunicaciones presentadas al XVII Congreso de la Asociación Española de Teledetección (AET), celebrado del 3 al 7 de octubre de 2017 en el auditorio y palacio de congresos de Murcia y organizado por el Grupo de Sistemas de Información Geográfica y Teledetección del Instituto Murciano de Investigación y Desarrollo Agrario y Alimentario (IMIDA),con el soporte de la AET,el Instituto Geográfico Nacional (IGN), las universidades politécnicas de Cartagena y Valencia, la Confederación Hidrográfica del Segura, el ayuntamiento de Murcia,las empresas Gade Eventos y Geodim y la Universidad Católica de San Antonio El lema elegido para el Congreso ha sido "Nuevas plataformas y sensores de teledetección" aplicados a la gestión del agua,la agricultura y el medio ambiente, con la intención de promover el encuentro entre las comunidades académicas, científicas e industriales en el área de la teledetección, destacando las nuevas plataformas de bajo coste y los logros conseguidos en la generación y difusión de productos útiles para la sociedadRuiz Fernández, LÁ.; Estornell Cremades, J.; Erena Arrabal, M. (2017). Teledetección. Nuevas plataformas y sensores aplicados a la gestión del agua, la agricultura y el medio ambiente. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/90688EDITORIA

A Statewide Evaluation of Fuel Treatment Effectiveness in Altering Wildfire Outcomes on Public Lands in Utah

Fuel treatments are land management activities that reduce living and dead flammable materials on the landscape to mitigate undesirable wildfire behavior and effects. Common treatments in the western United States include mechanical methods such as thinning and mastication, prescribed burns, and chemical methods, such as herbicide application. Treatments usually have multiple objectives, including reducing fire intensity, protecting natural and cultural resources, slowing or disrupting a potential future fire’s path, supporting ecosystem health, and reestablishing low to mid severity fire cycles in ecosystems. Although treatments can potentially modify fire behavior and ecological health, they generally cannot prevent fires from igniting, eliminate fires from occurring, or consistently stop active fires from spreading. The majority of fuel treatments are never encountered by wildfire, which limits our understanding of effectiveness. In Utah, treatments are primarily implemented by the U.S. Department of the Interior Bureau of Land Management (BLM) and U.S. Department of Agriculture Forest Service (USFS). In order to increase understanding of fuel treatment effectiveness, I conducted a statewide study, including 3,208 fuel treatments and 1,558 wildfires on BLM and USFS managed lands across Utah from 1997 to 2019. The objective of my study was to evaluate treatment effectiveness using four metrics: 1.) Encounter rates, 2.) Burn severity, 3.) Manager reports and 4.) Ecological health. In Chapter 2, I summarized treatment and wildfire distributions and calculated a treatment encounter rate of 8.7%. I also analyzed burn severity in 48 treatments in forested vegetation, finding that treatments significantly reduced burn severity, especially in areas that had been treated repeatedly. Finally, manager observations from treatments encountered by fire were summarized, with findings that managers reported fuel treatments to be effective in the majority of encounters. Chapter 3 evaluated ecological health in juniper mastication treatments, using field measurements, and found no treatment effect on cheatgrass, bare ground, or sagebrush density post-fire. In conclusion, fuel treatments were effective in their primary goals of altering fire behavior and effects, based on the metrics of burn severity and manager reports. However, fuel treatments were seldom encountered by wildfire, and juniper mastication treatments were ineffective at improving the measured ecological health metrics. These findings suggest that expanding treated areas to improve encounter rates will increase the circumstances in which treatments are effective